Development and Validation in Air Traffic Control by Means of Real-Time Simulations

Directory of Open Access Journals (Sweden)

Stephan Herr

2009-02-01

Full Text Available The airspace in Central Europe is already one of the busiest airspaces in the world and the forecasts predict further traffic increases. The current air transport system is reaching its capacity limits, not only at airports but also in parts of the en-route area. This is mainly due to the workload constraints of air traffic controllers. In the past, many technical system functionalities were developed with the aim of reducing controller workload and thus enabling the safe handling of the predicted traffic growth. But these new functionalities alone will not provide adequate relief to air traffic controllers. Their working procedures and the airspace structure will have to be adapted accordingly. In order to obtain real operational benefits, these technical innovations must be integrated into an overall concept which – in addition to the above-mentioned factors – also takes account of ergonomic aspects and human-machine interfaces. When developing such an overall concept, additional evaluation and validation measures are indispensable to ensure that the desired operational benefits are achieved. This is why DFS has for many years used fast- and real-time simulations to assess and optimise any changes to be made to the air traffic control system. The working methods of DFS in this context are in keeping with the European Operational Concept Validation Methodology of 2007, in short E-OCVM. This paper outlines the development and validation activities of DFS using the MSP D/L project as an example. The project deals with the introduction of the new role of air traffic controllers as multi-sector planners (MSP and new system functionalities, such as air/ground data link (D/L. The project included the development of an operational concept for using the new functionalities as well as for defining working procedures and the airspace structure. This concept was subsequently evaluated by means of a fast-time simulation and two real-time simulations

3D Markov Process for Traffic Flow Prediction in Real-Time

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Eunjeong Ko

2016-01-01

Full Text Available Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1 a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2 the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.

Simulating Photon Mapping for Real-time Applications

DEFF Research Database (Denmark)

Larsen, Bent Dalgaard; Christensen, Niels Jørgen

2004-01-01

This paper introduces a novel method for simulating photon mapping for real-time applications. First we introduce a new method for selectively redistributing photons. Then we describe a method for selectively updating the indirect illumination. The indirect illumination is calculated using a new...... GPU accelerated final gathering method and the illumination is then stored in light maps. Caustic photons are traced on the CPU and then drawn using points in the framebuffer, and finally filtered using the GPU. Both diffuse and non-diffuse surfaces can be handled by calculating the direct...... illumination on the GPU and the photon tracing on the CPU. We achieve real-time frame rates for dynamic scenes....

An Anomalous Noise Events Detector for Dynamic Road Traffic Noise Mapping in Real-Life Urban and Suburban Environments

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Joan Claudi Socoró

2017-10-01

Full Text Available One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM. The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement.

A real-time radiation mapping system

International Nuclear Information System (INIS)

Scoggins, W.A.; VanEtten, D.M.

1988-01-01

A prototype of a real-time radiation mapping system, Ranger, was developed to respond to an accident involving the release of plutonium for the Department of Energy's Accident Response Group. In 1987 Ranger demonstrated that it can provide an efficient method of monitoring large areas of land for radioactive contamination. With the experience gained from the operation of the prototype, the external computer and software are being upgraded in order to obtain a fully operational system. The new system uses the prototype's commercially available line-of-sight microwave system for determining position and the same radiation detection instruments. The data obtained from the radiation detection instrument(s) are linked back to the external computer along with the relative position of the measurement through the ranging system. The data are displayed on a gridded map as colored circles and permanently stored in real-time. The different colors represent different contamination levels. Contours can be drawn using the permanently stored data. 4 figs

A revealed-preference study of behavioural impacts of real-time traffic information

NARCIS (Netherlands)

Knockaert, J.S.A.; Tseng, Y.; Verhoef, E.T.

2013-01-01

In the present study, we investigate the impact of real-time traffic information on traveller behaviour by using repeated day-to-day revealed-preference (RP) observations from a reward experiment. We estimate a trip scheduling model of morning peak behaviour that allows us to determine the impact of

Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation.

Science.gov (United States)

Son, Sanghyun; Baek, Yunju

2015-08-18

As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

Directory of Open Access Journals (Sweden)

Sanghyun Son

2015-08-01

Full Text Available As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

The impact of real-time and predictive traffic information on travelers' behavior on the I-4 corridor. Final report.

Science.gov (United States)

2003-07-01

Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transport...

Crash risk analysis during fog conditions using real-time traffic data.

Science.gov (United States)

Wu, Yina; Abdel-Aty, Mohamed; Lee, Jaeyoung

2018-05-01

This research investigates the changes of traffic characteristics and crash risks during fog conditions. Using real-time traffic flow and weather data at two regions in Florida, the traffic patterns at the fog duration were compared to the traffic patterns at the clear duration. It was found that the average 5-min speed and the average 5-min volume were prone to decreasing during fog. Based on previous studies, a "Crash Risk Increase Indicator (CRII)" was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the increase of crash risks with traffic flow characteristics. The results suggested that the proposed indicator worked well in evaluating the increase of crash risk under fog condition. It was indicated that the crash risk was prone to increase at ramp vicinities in fog conditions. Also, the average 5-min volume during fog and the lane position are important factors for crash risk increase. The differences between the regions were also explored in this study. The results indicated that the locations with heavier traffic or locations at the lanes that were closest to the median in Region 2 were more likely to observe an increase in crash risks in fog conditions. It is expected that the proposed indicator can help identify the dangerous traffic status under fog conditions and then proper ITS technologies can be implemented to enhance traffic safety when the visibility declines. Copyright © 2017 Elsevier Ltd. All rights reserved.

Large-scale machine learning and evaluation platform for real-time traffic surveillance

Science.gov (United States)

Eichel, Justin A.; Mishra, Akshaya; Miller, Nicholas; Jankovic, Nicholas; Thomas, Mohan A.; Abbott, Tyler; Swanson, Douglas; Keller, Joel

2016-09-01

In traffic engineering, vehicle detectors are trained on limited datasets, resulting in poor accuracy when deployed in real-world surveillance applications. Annotating large-scale high-quality datasets is challenging. Typically, these datasets have limited diversity; they do not reflect the real-world operating environment. There is a need for a large-scale, cloud-based positive and negative mining process and a large-scale learning and evaluation system for the application of automatic traffic measurements and classification. The proposed positive and negative mining process addresses the quality of crowd sourced ground truth data through machine learning review and human feedback mechanisms. The proposed learning and evaluation system uses a distributed cloud computing framework to handle data-scaling issues associated with large numbers of samples and a high-dimensional feature space. The system is trained using AdaBoost on 1,000,000 Haar-like features extracted from 70,000 annotated video frames. The trained real-time vehicle detector achieves an accuracy of at least 95% for 1/2 and about 78% for 19/20 of the time when tested on ˜7,500,000 video frames. At the end of 2016, the dataset is expected to have over 1 billion annotated video frames.

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

Science.gov (United States)

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing

Discrete events simulation of a route with traffic lights through automated control in real time

Directory of Open Access Journals (Sweden)

Rodrigo César Teixeira Baptista

2013-03-01

Full Text Available This paper presents the integration and communication in real-time of a discrete event simulation model with an automatic control system. The simulation model of an intersection with roads having traffic lights was built in the Arena environment. The integration and communication have been made via network, and the control system was operated by a programmable logic controller. Scenarios were simulated for the free, regular and congested traffic situations. The results showed the average number of vehicles that entered in the system and that were retained and also the total average time of the crossing of the vehicles on the road. In general, the model allowed evaluating the behavior of the traffic in each of the ways and the commands from the controller to activation and deactivation of the traffic lights.

Real time curriculum map for internal medicine residency

Directory of Open Access Journals (Sweden)

Roberts J Mark

2007-11-01

Full Text Available Abstract Background To manage the voluminous formal curriculum content in a limited amount of structured teaching time, we describe the development and evaluation of a curriculum map for academic half days (AHD in a core internal medicine residency program. Methods We created a 3-year cyclical curriculum map (an educational tool combining the content, methodology and timetabling of structured teaching, comprising a matrix of topics under various specialties/themes and corresponding AHD hours. All topics were cross-matched against the ACP-ASIM in-training examination, and all hours were colour coded based on the categories of core competencies. Residents regularly updated the map on a real time basis. Results There were 208 topics covered in 283 AHD hours. All topics represented core competencies with minimal duplication (78% covered once in 3 years. Only 42 hours (15% involved non-didactic teaching, which increased after implementation of the map (18–19 hours/year versus baseline 5 hours/year. Most AHD hours (78% focused on medical expert competencies. Resident satisfaction (90% response was high throughout (range 3.64 ± 0.21, 3.84 ± 0.14 out of 4, which improved after 1 year but returned to baseline after 2 years. Conclusion We developed and implemented an internal medicine curriculum map based on real time resident input, with minimal topic duplication and high resident satisfaction. The map provided an opportunity to balance didactic versus non-didactic teaching, and teaching on medical versus non medical expert topics.

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials.

Science.gov (United States)

Theofilatos, Athanasios

2017-06-01

The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Description of Anomalous Noise Events for Reliable Dynamic Traffic Noise Mapping in Real-Life Urban and Suburban Soundscapes

Directory of Open Access Journals (Sweden)

Francesc Alías

2017-02-01

Full Text Available Traffic noise is one of the main pollutants in urban and suburban areas. European authorities have driven several initiatives to study, prevent and reduce the effects of exposure of population to traffic. Recent technological advances have allowed the dynamic computation of noise levels by means of Wireless Acoustic Sensor Networks (WASN such as that developed within the European LIFE DYNAMAP project. Those WASN should be capable of detecting and discarding non-desired sound sources from road traffic noise, denoted as anomalous noise events (ANE, in order to generate reliable noise level maps. Due to the local, occasional and diverse nature of ANE, some works have opted to artificially build ANE databases at the cost of misrepresentation. This work presents the production and analysis of a real-life environmental audio database in two urban and suburban areas specifically conceived for anomalous noise events’ collection. A total of 9 h 8 min of labelled audio data is obtained differentiating among road traffic noise, background city noise and ANE. After delimiting their boundaries manually, the acoustic salience of the ANE samples is automatically computed as a contextual signal-to-noise ratio (SNR. The analysis of the real-life environmental database shows high diversity of ANEs in terms of occurrences, durations and SNRs, as well as confirming both the expected differences between the urban and suburban soundscapes in terms of occurrences and SNRs, and the rare nature of ANE.

Real Time Mapping and Dynamic Navigation for Mobile Robots

Directory of Open Access Journals (Sweden)

Maki K. Habib

2008-11-01

Full Text Available This paper discusses the importance, the complexity and the challenges of mapping mobile robot?s unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobile robots navigating within unknown environment, and then introduces a solution for the complex problem of autonomous map building and maintenance method with focus on developing an incremental grid based mapping technique that is suitable for real-time obstacle detection and avoidance. In this case, the navigation of mobile robots can be treated as a problem of tracking geometric features that occur naturally in the environment of the robot. The robot maps its environment incrementally using the concept of occupancy grids and the fusion of multiple ultrasonic sensory information while wandering in it and stay away from all obstacles. To ensure real-time operation with limited resources, as well as to promote extensibility, the mapping and obstacle avoidance modules are deployed in parallel and distributed framework. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach.

[Dynamic road vehicle emission inventory simulation study based on real time traffic information].

Science.gov (United States)

Huang, Cheng; Liu, Juan; Chen, Chang-Hong; Zhang, Jian; Liu, Deng-Guo; Zhu, Jing-Yu; Huang, Wei-Ming; Chao, Yuan

2012-11-01

The vehicle activity survey, including traffic flow distribution, driving condition, and vehicle technologies, were conducted in Shanghai. The databases of vehicle flow, VSP distribution and vehicle categories were established according to the surveyed data. Based on this, a dynamic vehicle emission inventory simulation method was designed by using the real time traffic information data, such as traffic flow and average speed. Some roads in Shanghai city were selected to conduct the hourly vehicle emission simulation as a case study. The survey results show that light duty passenger car and taxi are major vehicles on the roads of Shanghai city, accounting for 48% - 72% and 15% - 43% of the total flow in each hour, respectively. VSP distribution has a good relationship with the average speed. The peak of VSP distribution tends to move to high load section and become lower with the increase of average speed. Vehicles achieved Euro 2 and Euro 3 standards are majorities of current vehicle population in Shanghai. Based on the calibration of vehicle travel mileage data, the proportions of Euro 2 and Euro 3 standard vehicles take up 11% - 70% and 17% - 51% in the real-world situation, respectively. The emission simulation results indicate that the ratios of emission peak and valley for the pollutants of CO, VOC, NO(x) and PM are 3.7, 4.6, 9.6 and 19.8, respectively. CO and VOC emissions mainly come from light-duty passenger car and taxi, which has a good relationship with the traffic flow. NO(x) and PM emissions are mainly from heavy-duty bus and public buses and mainly concentrate in the morning and evening peak hours. The established dynamic vehicle emission simulation method can reflect the change of actual road emission and output high emission road sectors and hours in real time. The method can provide an important technical means and decision-making basis for transportation environment management.

Adaptive Kalman filtering for real-time mapping of the visual field

Science.gov (United States)

Ward, B. Douglas; Janik, John; Mazaheri, Yousef; Ma, Yan; DeYoe, Edgar A.

2013-01-01

This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results. Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field. Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications. The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume. PMID:22100663

Real-time frequency-to-time mapping based on spectrally-discrete chromatic dispersion.

Science.gov (United States)

Dai, Yitang; Li, Jilong; Zhang, Ziping; Yin, Feifei; Li, Wangzhe; Xu, Kun

2017-07-10

Traditional photonics-assisted real-time Fourier transform (RTFT) usually suffers from limited chromatic dispersion, huge volume, or large time delay and attendant loss. In this paper we propose frequency-to-time mapping (FTM) by spectrally-discrete dispersion to increase frequency sensitivity greatly. The novel media has periodic ON/OFF intensity frequency response while quadratic phase distribution along disconnected channels, which de-chirps matched optical input to repeated Fourier-transform-limited output. Real-time FTM is then obtained within each period. Since only discrete phase retardation rather than continuously-changed true time delay is required, huge equivalent dispersion is then available by compact device. Such FTM is theoretically analyzed, and implementation by cascaded optical ring resonators is proposed. After a numerical example, our theory is demonstrated by a proof-of-concept experiment, where a single loop containing 0.5-meters-long fiber is used. FTM under 400-MHz unambiguous bandwidth and 25-MHz resolution is reported. Highly-sensitive and linear mapping is achieved with 6.25 ps/MHz, equivalent to ~4.6 × 10 4 -km standard single mode fiber. Extended instantaneous bandwidth is expected by ring cascading. Our proposal may provide a promising method for real-time, low-latency Fourier transform.

Novel techniques of real-time blood flow and functional mapping: technical note.

Science.gov (United States)

Kamada, Kyousuke; Ogawa, Hiroshi; Saito, Masato; Tamura, Yukie; Anei, Ryogo; Kapeller, Christoph; Hayashi, Hideaki; Prueckl, Robert; Guger, Christoph

2014-01-01

There are two main approaches to intraoperative monitoring in neurosurgery. One approach is related to fluorescent phenomena and the other is related to oscillatory neuronal activity. We developed novel techniques to visualize blood flow (BF) conditions in real time, based on indocyanine green videography (ICG-VG) and the electrophysiological phenomenon of high gamma activity (HGA). We investigated the use of ICG-VG in four patients with moyamoya disease and two with arteriovenous malformation (AVM), and we investigated the use of real-time HGA mapping in four patients with brain tumors who underwent lesion resection with awake craniotomy. Real-time data processing of ICG-VG was based on perfusion imaging, which generated parameters including arrival time (AT), mean transit time (MTT), and BF of brain surface vessels. During awake craniotomy, we analyzed the frequency components of brain oscillation and performed real-time HGA mapping to identify functional areas. Processed results were projected on a wireless monitor linked to the operating microscope. After revascularization for moyamoya disease, AT and BF were significantly shortened and increased, respectively, suggesting hyperperfusion. Real-time fusion images on the wireless monitor provided anatomical, BF, and functional information simultaneously, and allowed the resection of AVMs under the microscope. Real-time HGA mapping during awake craniotomy rapidly indicated the eloquent areas of motor and language function and significantly shortened the operation time. These novel techniques, which we introduced might improve the reliability of intraoperative monitoring and enable the development of rational and objective surgical strategies.

Dynamic Subcarrier Allocation for Real-Time Traffic over Multiuser OFDM Systems

Directory of Open Access Journals (Sweden)

Li VictorOK

2009-01-01

Full Text Available A dynamic resource allocation algorithm to satisfy the packet delay requirements for real-time services, while maximizing the system capacity in multiuser orthogonal frequency division multiplexing (OFDM systems is introduced. Our proposed cross-layer algorithm, called Dynamic Subcarrier Allocation algorithm for Real-time Traffic (DSA-RT, consists of two interactive components. In the medium access control (MAC layer, the users' expected transmission rates in terms of the number of subcarriers per symbol and their corresponding transmission priorities are evaluated. With the above MAC-layer information and the detected subcarriers' channel gains, in the physical (PHY layer, a modified Kuhn-Munkres algorithm is developed to minimize the system power for a certain subcarrier allocation, then a PHY-layer resource allocation scheme is proposed to optimally allocate the subcarriers under the system signal-to-noise ratio (SNR and power constraints. In a system where the number of mobile users changes dynamically, our developed MAC-layer access control and removal schemes can guarantee the quality of service (QoS of the existing users in the system and fully utilize the bandwidth resource. The numerical results show that DSA-RT significantly improves the system performance in terms of the bandwidth efficiency and delay performance for real-time services.

Combining Kohonen maps with Arima time series models to forecast traffic flow

NARCIS (Netherlands)

van der Voort, Mascha C.; Dougherty, Mark; Dougherty, M.S.; Watson, Susan

1996-01-01

A hybrid method of short-term traffic forecasting is introduced; the KARIMA method. The technique uses a Kohonen self-organizing map as an initial classifier; each class has an individually tuned ARIMA model associated with it. Using a Kohonen map which is hexagonal in layout eases the problem of

An Efficient MapReduce-Based Parallel Clustering Algorithm for Distributed Traffic Subarea Division

Directory of Open Access Journals (Sweden)

Dawen Xia

2015-01-01

Full Text Available Traffic subarea division is vital for traffic system management and traffic network analysis in intelligent transportation systems (ITSs. Since existing methods may not be suitable for big traffic data processing, this paper presents a MapReduce-based Parallel Three-Phase K-Means (Par3PKM algorithm for solving traffic subarea division problem on a widely adopted Hadoop distributed computing platform. Specifically, we first modify the distance metric and initialization strategy of K-Means and then employ a MapReduce paradigm to redesign the optimized K-Means algorithm for parallel clustering of large-scale taxi trajectories. Moreover, we propose a boundary identifying method to connect the borders of clustering results for each cluster. Finally, we divide traffic subarea of Beijing based on real-world trajectory data sets generated by 12,000 taxis in a period of one month using the proposed approach. Experimental evaluation results indicate that when compared with K-Means, Par2PK-Means, and ParCLARA, Par3PKM achieves higher efficiency, more accuracy, and better scalability and can effectively divide traffic subarea with big taxi trajectory data.

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

Science.gov (United States)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

Robot Mapping With Real-Time Incremental Localization Using Expectation Maximization

National Research Council Canada - National Science Library

Owens, Kevin L

2005-01-01

This research effort explores and develops a real-time sonar-based robot mapping and localization algorithm that provides pose correction within the context of a singe room, to be combined with pre...

Parallel pipeline algorithm of real time star map preprocessing

Science.gov (United States)

Wang, Hai-yong; Qin, Tian-mu; Liu, Jia-qi; Li, Zhi-feng; Li, Jian-hua

2016-03-01

To improve the preprocessing speed of star map and reduce the resource consumption of embedded system of star tracker, a parallel pipeline real-time preprocessing algorithm is presented. The two characteristics, the mean and the noise standard deviation of the background gray of a star map, are firstly obtained dynamically by the means that the intervene of the star image itself to the background is removed in advance. The criterion on whether or not the following noise filtering is needed is established, then the extraction threshold value is assigned according to the level of background noise, so that the centroiding accuracy is guaranteed. In the processing algorithm, as low as two lines of pixel data are buffered, and only 100 shift registers are used to record the connected domain label, by which the problems of resources wasting and connected domain overflow are solved. The simulating results show that the necessary data of the selected bright stars could be immediately accessed in a delay time as short as 10us after the pipeline processing of a 496×496 star map in 50Mb/s is finished, and the needed memory and registers resource total less than 80kb. To verify the accuracy performance of the algorithm proposed, different levels of background noise are added to the processed ideal star map, and the statistic centroiding error is smaller than 1/23 pixel under the condition that the signal to noise ratio is greater than 1. The parallel pipeline algorithm of real time star map preprocessing helps to increase the data output speed and the anti-dynamic performance of star tracker.

Performances and recent evolutions of EMSC Real Time Information services

Science.gov (United States)

Mazet-Roux, G.; Godey, S.; Bossu, R.

2009-04-01

The EMSC (http://www.emsc-csem.org) operates Real Time Earthquake Information services for the public and the scientific community which aim at providing rapid and reliable information on the seismic-ity of the Euro-Mediterranean region and on significant earthquakes worldwide. These services are based on parametric data rapidly provided by 66 seismological networks which are automatically merged and processed at EMSC. A web page which is updated every minute displays a list and a map of the latest earthquakes as well as additional information like location maps, moment tensors solutions or past regional seismicity. Since 2004, the performances and the popularity of these services have dramatically increased. The number of messages received from the contributors and the number of published events have been multiplied by 2 since 2004 and by 1.6 since 2005 respectively. The web traffic and the numbers of users of the Earthquake Notification Service (ENS) have been multiplied by 15 and 7 respectively. In terms of performances of the ENS, the median dissemination time for Euro-Med events is minutes in 2008. In order to further improve its performances and especially the speed and robustness of the reception of real time data, EMSC has recently implemented a software named QWIDS (Quake Watch Information Distribution System) which provides a quick and robust data exchange system through permanent TCP connections. At the difference with emails that can sometimes be delayed or lost, QWIDS is an actual real time communication system that ensures the data delivery. In terms of hardware, EMSC imple-mented a high availability, dynamic load balancing, redundant and scalable web servers infrastructure, composed of two SUN T2000 and one F5 BIG-IP switch. This will allow coping with constantly increas-ing web traffic and the occurrence of huge peaks of traffic after widely felt earthquakes.

Real-Time Mapping Spectroscopy on the Ground, in the Air, and in Space

Science.gov (United States)

Thompson, D. R.; Allwood, A.; Chien, S.; Green, R. O.; Wettergreen, D. S.

2016-12-01

Real-time data interpretation can benefit both remote in situ exploration and remote sensing. Basic analyses at the sensor can monitor instrument performance and reveal invisible science phenomena in real time. This promotes situational awareness for remote robotic explorers or campaign decision makers, enabling adaptive data collection, reduced downlink requirements, and coordinated multi-instrument observations. Fast analysis is ideal for mapping spectrometers providing unambiguous, quantitative geophysical measurements. This presentation surveys recent computational advances in real-time spectroscopic analysis for Earth science and planetary exploration. Spectral analysis at the sensor enables new operations concepts that significantly improve science yield. Applications include real-time detection of fugitive greenhouse emissions by airborne monitoring, real-time cloud screening and mineralogical mapping by orbital spectrometers, and adaptive measurement by the PIXL instrument on the Mars 2020 rover. Copyright 2016 California Institute of Technology. All Rights Reserved. We acknowledge support of the US Government, NASA, the Earth Science Division and Terrestrial Ecology program.

Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study.

Science.gov (United States)

Cole, Justin; Beare, Richard; Phan, Thanh G; Srikanth, Velandai; MacIsaac, Andrew; Tan, Christianne; Tong, David; Yee, Susan; Ho, Jesslyn; Layland, Jamie

2017-01-01

Recent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI) for a proportion of ST elevation myocardial infarction (STEMI) presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI. Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times. Inner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. ( p  travel time can predict optimal residence of staff when on-call for PCI.

Analysis of vehicular traffic flow in the major areas of Kuala Lumpur utilizing open-traffic

Science.gov (United States)

Manogaran, Saargunawathy; Ali, Muhammad; Yusof, Kamaludin Mohamad; Suhaili, Ramdhan

2017-09-01

Vehicular traffic congestion occurs when a large number of drivers are overcrowded on the road and the traffic flow does not run smoothly. Traffic congestion causes chaos on the road and interruption to daily activities of users. Time consumed on road give lots of negative effects on productivity, social behavior, environmental and cost to economy. Congestion is worsens and leads to havoc during the emergency such as flood, accidents, road maintenance and etc., where behavior of traffic flow is always unpredictable and uncontrollable. Real-time and historical traffic data are critical inputs for most traffic flow analysis applications. Researcher attempt to predict traffic using simulations as there is no exact model of traffic flow exists due to its high complexity. Open Traffic is an open source platform available for traffic data analysis linked to Open Street Map (OSM). This research is aimed to study and understand the Open Traffic platform. The real-time traffic flow pattern in Kuala Lumpur area was successfully been extracted and analyzed using Open Traffic. It was observed that the congestion occurs on every major road in Kuala Lumpur and most of it owes to the offices and the economic and commercial centers during rush hours. At some roads the congestion occurs at night due to the tourism activities.

Application of Real-Time Automated Traffic Incident Response Plan Management System: A Web Structure for the Regional Highway Network in China

Directory of Open Access Journals (Sweden)

Yongfeng Ma

2014-01-01

Full Text Available Traffic incidents, caused by various factors, may lead to heavy traffic delay and be harmful to traffic capacity of downstream sections. Traffic incident management (TIM systems have been developed widely to respond to traffic incidents intelligently and reduce the losses. Traffic incident response plans, as an important component of TIM, can effectively guide responders as to what and how to do in traffic incidents. In the paper, a real-time automated traffic incident response plan management system was developed, which could generate and manage traffic incident response plans timely and automatically. A web application structure and a physical structure were designed to implement and show these functions. A standard framework of data storage was also developed to save information about traffic incidents and generated response plans. Furthermore, a conformation survey and case-based reasoning (CBR were introduced to identify traffic incident and generate traffic incident response plans automatically, respectively. Twenty-three traffic crash-related incidents were selected and three indicators were used to measure the system performance. Results showed that 20 of 23 cases could be retrieved effectively and accurately. The system is practicable to generate traffic incident response plans and has been implemented in China.

The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) field study methodology.

Science.gov (United States)

Richmond-Bryant, Jennifer; Hahn, Intaek; Fortune, Christopher R; Rodes, Charles E; Portzer, Jeffrey W; Lee, Sangdon; Wiener, Russell W; Smith, Luther A; Wheeler, Michael; Seagraves, Jeremy; Stein, Mark; Eisner, Alfred D; Brixey, Laurie A; Drake-Richman, Zora E; Brouwer, Lydia H; Ellenson, William D; Baldauf, Richard

2009-12-01

The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) field study examined indoor and outdoor exposure to traffic-generated air pollution by studying the individual processes of generation of traffic emissions, transport and dispersion of air contaminants along a roadway, and infiltration of the contaminants into a residence. Real-time instrumentation was used to obtain highly resolved time-series concentration profiles for a number of air pollutants. The B-TRAPPED field study was conducted in the residential Sunset Park neighborhood of Brooklyn, NY, USA, in May 2005. The neighborhood contained the Gowanus Expressway (Interstate 278), a major arterial road (4(th) Avenue), and residential side streets running perpendicular to the Gowanus Expressway and 4(th) Avenue. Synchronized measurements were obtained inside a test house, just outside the test house façade, and along the urban residential street canyon on which the house was located. A trailer containing Federal Reference Method (FRM) and real-time monitors was located next to the Gowanus Expressway to assess the source. Ultrafine particulate matter (PM), PM(2.5), nitrogen oxides (NO(x)), sulfur dioxide (SO(2)), carbon monoxide (CO), carbon dioxide (CO(2)), temperature, relative humidity, and wind speed and direction were monitored. Different sampling schemes were devised to focus on dispersion along the street canyon or infiltration into the test house. Results were obtained for ultrafine PM, PM(2.5), criteria gases, and wind conditions from sampling schemes focused on street canyon dispersion and infiltration. For comparison, the ultrafine PM and PM(2.5) results were compared with an existing data set from the Los Angeles area, and the criteria gas data were compared with measurements from a Vancouver epidemiologic study. Measured ultrafine PM and PM(2.5) concentration levels along the residential urban street canyon and at the test house façade in Sunset Park

Fast Drawing of Traffic Sign Using Mobile Mapping System

Science.gov (United States)

Yao, Q.; Tan, B.; Huang, Y.

2016-06-01

Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a

Flexibility Driven Scheduling and Mapping for Distributed Real-Time Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2002-01-01

In this paper we present an approach to mapping and scheduling of distributed hard real-time systems, aiming at improving the flexibility of the design process. We consider an incremental design process that starts from an already existing system running a set of applications, with preemptive...

System And Method For Monitoring Traffic While Preserving Personal Privacy

KAUST Repository

Canepa, Edward

2015-08-06

A traffic monitoring system and method for mapping traffic speed and density while preserving privacy. The system can include fixed stations that make up a network and mobile probes that are associated with vehicles. The system and method do not gather, store, or transmit any unique or identifying information, and thereby preserves the privacy of members of traffic. The system and method provide real-time traffic density and speed mapping. The system and method can further be integrated with a complementary flood monitoring system and method.

Generation of real-time global ionospheric map based on the global GNSS stations with only a sparse distribution

Science.gov (United States)

Li, Zishen; Wang, Ningbo; Li, Min; Zhou, Kai; Yuan, Yunbin; Yuan, Hong

2017-04-01

The Earth's ionosphere is part of the atmosphere stretching from an altitude of about 50 km to more than 1000 km. When the Global Navigation Satellite System (GNSS) signal emitted from a satellite travels through the ionosphere before reaches a receiver on or near the Earth surface, the GNSS signal is significantly delayed by the ionosphere and this delay bas been considered as one of the major errors in the GNSS measurement. The real-time global ionospheric map calculated from the real-time data obtained by global stations is an essential method for mitigating the ionospheric delay for real-time positioning. The generation of an accurate global ionospheric map generally depends on the global stations with dense distribution; however, the number of global stations that can produce the real-time data is very limited at present, which results that the generation of global ionospheric map with a high accuracy is very different when only using the current stations with real-time data. In view of this, a new approach is proposed for calculating the real-time global ionospheric map only based on the current stations with real-time data. This new approach is developed on the basis of the post-processing and the one-day predicted global ionospheric map from our research group. The performance of the proposed approach is tested by the current global stations with the real-time data and the test results are also compared with the IGS-released final global ionospheric map products.

System And Method For Monitoring Traffic While Preserving Personal Privacy

KAUST Repository

Canepa, Edward; Claudel, Christian G.; Shamim, Atif; Dehwah, Ahmad H.; Mousa, Mustafa; Jiang, Jiming

2015-01-01

not gather, store, or transmit any unique or identifying information, and thereby preserves the privacy of members of traffic. The system and method provide real-time traffic density and speed mapping. The system and method can further be integrated with a

FAST DRAWING OF TRAFFIC SIGN USING MOBILE MAPPING SYSTEM

Directory of Open Access Journals (Sweden)

Q. Yao

2016-06-01

Full Text Available Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare

Task Mapping and Partition Allocation for Mixed-Criticality Real-Time Systems

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2012-01-01

In this paper we address the mapping of mixedcriticality hard real-time applications on distributed embedded architectures. We assume that the architecture provides both spatial and temporal partitioning, thus enforcing enough separation between applications. With temporal partitioning, each...

A real time QRS detection using delay-coordinate mapping for the microcontroller implementation.

Science.gov (United States)

Lee, Jeong-Whan; Kim, Kyeong-Seop; Lee, Bongsoo; Lee, Byungchae; Lee, Myoung-Ho

2002-01-01

In this article, we propose a new algorithm using the characteristics of reconstructed phase portraits by delay-coordinate mapping utilizing lag rotundity for a real-time detection of QRS complexes in ECG signals. In reconstructing phase portrait the mapping parameters, time delay, and mapping dimension play important roles in shaping of portraits drawn in a new dimensional space. Experimentally, the optimal mapping time delay for detection of QRS complexes turned out to be 20 ms. To explore the meaning of this time delay and the proper mapping dimension, we applied a fill factor, mutual information, and autocorrelation function algorithm that were generally used to analyze the chaotic characteristics of sampled signals. From these results, we could find the fact that the performance of our proposed algorithms relied mainly on the geometrical property such as an area of the reconstructed phase portrait. For the real application, we applied our algorithm for designing a small cardiac event recorder. This system was to record patients' ECG and R-R intervals for 1 h to investigate HRV characteristics of the patients who had vasovagal syncope symptom and for the evaluation, we implemented our algorithm in C language and applied to MIT/BIH arrhythmia database of 48 subjects. Our proposed algorithm achieved a 99.58% detection rate of QRS complexes.

Scheduling and Mapping in an Incremental Design Methodology for Distributed Real-Time Embedded Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2004-01-01

In this paper we present an approach to mapping and scheduling of distributed embedded systems for hard real-time applications, aiming at a minimization of the system modification cost. We consider an incremental design process that starts from an already existing system running a set of applicat......In this paper we present an approach to mapping and scheduling of distributed embedded systems for hard real-time applications, aiming at a minimization of the system modification cost. We consider an incremental design process that starts from an already existing system running a set...... be added to the resulted system. Thus, we propose a heuristic which finds the set of already running applications which have to be remapped and rescheduled at the same time with mapping and scheduling the new application, such that the disturbance on the running system (expressed as the total cost implied...... by the modifications) is minimized. Once this set of applications has been determined, we outline a mapping and scheduling algorithm aimed at fulfilling the requirements stated above. The approaches have been evaluated based on extensive experiments using a large number of generated benchmarks as well as a real...

Real-time flood extent maps based on social media

Science.gov (United States)

Eilander, Dirk; van Loenen, Arnejan; Roskam, Ruud; Wagemaker, Jurjen

2015-04-01

During a flood event it is often difficult to get accurate information about the flood extent and the people affected. This information is very important for disaster risk reduction management and crisis relief organizations. In the post flood phase, information about the flood extent is needed for damage estimation and calibrating hydrodynamic models. Currently, flood extent maps are derived from a few sources such as satellite images, areal images and post-flooding flood marks. However, getting accurate real-time or maximum flood extent maps remains difficult. With the rise of social media, we now have a new source of information with large numbers of observations. In the city of Jakarta, Indonesia, the intensity of unique flood related tweets during a flood event, peaked at 8 tweets per second during floods in early 2014. A fair amount of these tweets also contains observations of water depth and location. Our hypothesis is that based on the large numbers of tweets it is possible to generate real-time flood extent maps. In this study we use tweets from the city of Jakarta, Indonesia, to generate these flood extent maps. The data-mining procedure looks for tweets with a mention of 'banjir', the Bahasa Indonesia word for flood. It then removes modified and retweeted messages in order to keep unique tweets only. Since tweets are not always sent directly from the location of observation, the geotag in the tweets is unreliable. We therefore extract location information using mentions of names of neighborhoods and points of interest. Finally, where encountered, a mention of a length measure is extracted as water depth. These tweets containing a location reference and a water level are considered to be flood observations. The strength of this method is that it can easily be extended to other regions and languages. Based on the intensity of tweets in Jakarta during a flood event we can provide a rough estimate of the flood extent. To provide more accurate flood extend

Real-Time Vision-Based Stiffness Mapping †.

Science.gov (United States)

Faragasso, Angela; Bimbo, João; Stilli, Agostino; Wurdemann, Helge Arne; Althoefer, Kaspar; Asama, Hajime

2018-04-26

This paper presents new findings concerning a hand-held stiffness probe for the medical diagnosis of abnormalities during palpation of soft-tissue. Palpation is recognized by the medical community as an essential and low-cost method to detect and diagnose disease in soft-tissue. However, differences are often subtle and clinicians need to train for many years before they can conduct a reliable diagnosis. The probe presented here fills this gap providing a means to easily obtain stiffness values of soft tissue during a palpation procedure. Our stiffness sensor is equipped with a multi degree of freedom (DoF) Aurora magnetic tracker, allowing us to track and record the 3D position of the probe whilst examining a tissue area, and generate a 3D stiffness map in real-time. The stiffness probe was integrated in a robotic arm and tested in an artificial environment representing a good model of soft tissue organs; the results show that the sensor can accurately measure and map the stiffness of a silicon phantom embedded with areas of varying stiffness.

Real-Time Vision-Based Stiffness Mapping †

Directory of Open Access Journals (Sweden)

Angela Faragasso

2018-04-01

Full Text Available This paper presents new findings concerning a hand-held stiffness probe for the medical diagnosis of abnormalities during palpation of soft-tissue. Palpation is recognized by the medical community as an essential and low-cost method to detect and diagnose disease in soft-tissue. However, differences are often subtle and clinicians need to train for many years before they can conduct a reliable diagnosis. The probe presented here fills this gap providing a means to easily obtain stiffness values of soft tissue during a palpation procedure. Our stiffness sensor is equipped with a multi degree of freedom (DoF Aurora magnetic tracker, allowing us to track and record the 3D position of the probe whilst examining a tissue area, and generate a 3D stiffness map in real-time. The stiffness probe was integrated in a robotic arm and tested in an artificial environment representing a good model of soft tissue organs; the results show that the sensor can accurately measure and map the stiffness of a silicon phantom embedded with areas of varying stiffness.

Vessel thermal map real-time system for the JET tokamak

Directory of Open Access Journals (Sweden)

D. Alves

2012-05-01

Full Text Available The installation of international thermonuclear experimental reactor-relevant materials for the plasma facing components (PFCs in the Joint European Torus (JET is expected to have a strong impact on the operation and protection of the experiment. In particular, the use of all-beryllium tiles, which deteriorate at a substantially lower temperature than the formerly installed carbon fiber composite tiles, imposes strict thermal restrictions on the PFCs during operation. Prompt and precise responses are therefore required whenever anomalous temperatures are detected. The new vessel thermal map real-time application collects the temperature measurements provided by dedicated pyrometers and infrared cameras, groups them according to spatial location and probable offending heat source, and raises alarms that will trigger appropriate protective responses. In the context of the JET global scheme for the protection of the new wall, the system is required to run on a 10 ms cycle communicating with other systems through the real-time data network. In order to meet these requirements a commercial off-the-shelf solution has been adopted based on standard x86 multicore technology. Linux and the multithreaded application real-time executor (MARTe software framework were respectively the operating system of choice and the real-time framework used to build the application. This paper presents an overview of the system with particular technical focus on the configuration of its real-time capability and the benefits of the modular development approach and advanced tools provided by the MARTe framework.

Personal attitudes toward time: The relationship between temporal focus, space-time mappings and real life experiences.

Science.gov (United States)

Li, Heng; Cao, Yu

2017-06-01

What influences how people implicitly associate "past" and "future" with "front" and "back?" Whereas previous research has shown that cultural attitudes toward time play a role in modulating space-time mappings in people's mental models (de la Fuente, Santiago, Román, Dumitrache & Casasanto, 2014), we investigated real life experiences as potential additional influences on these implicit associations. Participants within the same single culture, who are engaged in different intermediate-term educational experiences (Study 1), long-term living experiences (Study 2), and short-term visiting experiences (Study 3), showed their distinct differences in temporal focus, thereby influencing their implicit spatializations of time. Results across samples suggest that personal attitudes toward time related to real life experiences may influence people's space-time mappings. The findings we report on shed further light on the high flexibility of human conceptualization system. While culture may exert an important influence on temporal focus, a person's conceptualization of time may be attributed to a culmination of factors. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Interactive Mapping on Virtual Terrain Models Using RIMS (Real-time, Interactive Mapping System)

Science.gov (United States)

Bernardin, T.; Cowgill, E.; Gold, R. D.; Hamann, B.; Kreylos, O.; Schmitt, A.

2006-12-01

Recent and ongoing space missions are yielding new multispectral data for the surfaces of Earth and other planets at unprecedented rates and spatial resolution. With their high spatial resolution and widespread coverage, these data have opened new frontiers in observational Earth and planetary science. But they have also precipitated an acute need for new analytical techniques. To address this problem, we have developed RIMS, a Real-time, Interactive Mapping System that allows scientists to visualize, interact with, and map directly on, three-dimensional (3D) displays of georeferenced texture data, such as multispectral satellite imagery, that is draped over a surface representation derived from digital elevation data. The system uses a quadtree-based multiresolution method to render in real time high-resolution (3 to 10 m/pixel) data over large (800 km by 800 km) spatial areas. It allows users to map inside this interactive environment by generating georeferenced and attributed vector-based elements that are draped over the topography. We explain the technique using 15 m ASTER stereo-data from Iraq, P.R. China, and other remote locations because our particular motivation is to develop a technique that permits the detailed (10 m to 1000 m) neotectonic mapping over large (100 km to 1000 km long) active fault systems that is needed to better understand active continental deformation on Earth. RIMS also includes a virtual geologic compass that allows users to fit a plane to geologic surfaces and thereby measure their orientations. It also includes tools that allow 3D surface reconstruction of deformed and partially eroded surfaces such as folded bedding planes. These georeferenced map and measurement data can be exported to, or imported from, a standard GIS (geographic information systems) file format. Our interactive, 3D visualization and analysis system is designed for those who study planetary surfaces, including neotectonic geologists, geomorphologists, marine

Towards a Cloud Based Smart Traffic Management Framework

Science.gov (United States)

Rahimi, M. M.; Hakimpour, F.

2017-09-01

Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

Real time expert systems

International Nuclear Information System (INIS)

Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

1992-01-01

Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

Freeway Driving Cycle Construction Based on Real-Time Traffic Information and Global Optimal Energy Management for Plug-In Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Hongwen He

2017-11-01

Full Text Available This paper presents a freeway driving cycle (FDC construction method based on traffic information. A float car collected different type of roads in California and we built a velocity fragment database. We selected a real freeway driving cycle (RFDC and established the corresponding time traffic information tensor model by using the data in California Department of Transportation performance measure system (PeMS. The correlation of road velocity in the time dimension and spatial dimension are analyzed. According to the average velocity of road sections at different times, the kinematic fragments are stochastically selected in the velocity fragment database to construct a real-time FDC of each section. The comparison between construction freeway driving cycle (CFDC and real freeway driving cycle (RFDC show that the CFDC well reflects the RFDC characteristic parameters. Compared to its application in plug-in electric hybrid vehicle (PHEV optimal energy management based on a dynamic programming (DP algorithm, CFDC and RFDC fuel consumption are similar within approximately 5.09% error, and non-rush hour fuel economy is better than rush hour 3.51 (L/100 km at non-rush hour, 4.29 (L/km at rush hour. Moreover, the fuel consumption ratio can be up to 13.17% in the same CFDC at non-rush hour.

TOWARDS A CLOUD BASED SMART TRAFFIC MANAGEMENT FRAMEWORK

Directory of Open Access Journals (Sweden)

M. M. Rahimi

2017-09-01

Full Text Available Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING

Data.gov (United States)

National Aeronautics and Space Administration — DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING SUBHASISH MOHANTY*, ADITI CHATTOPADHYAY, JOHN N. RAJADAS, AND CLYDE...

Project of Near-Real-Time Generation of ShakeMaps and a New Hazard Map in Austria

Science.gov (United States)

Jia, Yan; Weginger, Stefan; Horn, Nikolaus; Hausmann, Helmut; Lenhardt, Wolfgang

2016-04-01

Target-orientated prevention and effective crisis management can reduce or avoid damage and save lives in case of a strong earthquake. To achieve this goal, a project for automatic generated ShakeMaps (maps of ground motion and shaking intensity) and updating the Austrian hazard map was started at ZAMG (Zentralanstalt für Meteorologie und Geodynamik) in 2015. The first goal of the project is set for a near-real-time generation of ShakeMaps following strong earthquakes in Austria to provide rapid, accurate and official information to support the governmental crisis management. Using newly developed methods and software by SHARE (Seismic Hazard Harmonization in Europe) and GEM (Global Earthquake Model), which allows a transnational analysis at European level, a new generation of Austrian hazard maps will be ultimately calculated. More information and a status of our project will be given by this presentation.

Real time freeway incident detection.

Science.gov (United States)

2014-04-01

The US Department of Transportation (US-DOT) estimates that over half of all congestion : events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time : incident detection on freeways is an important part of any mo...

GSM based real time remote radiation monitoring and mapping system

International Nuclear Information System (INIS)

Dodiya, Kamal; Gupta, Ashutosh; Padmanabhan, N.; Chaudhury, Probal; Pradeepkumar, K.S.

2014-01-01

Mobile Radiological Impact Assessment Laboratory (M-RIAL) has been developed in Radiation Safety Systems Division, Bhabha Atomic Research Centre for carrying out assessment of radioactive contamination following a nuclear or radiological emergency in a nuclear facility or in public domain. During such situations a large area is to be monitored for radiological impact assessment and availability of the monitored data in real-time to a control centre is a great advantage for the decision makers. Development and application of such a system has been described in this paper. The system can transmit real-time radiological data, acquired by the universal counting system of M-RIAL and tagged with positional information, wirelessly to an Emergency Response Centre (ERC) using Global System for Mobile (GSM) communication. The radiological profile of the affected area is then superimposed on Geographical Information System (GIS) at the ERC and which can be used for the generation of radiological impact maps for use as decision support

Switching performance of OBS network model under prefetched real traffic

Science.gov (United States)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

Real-Time Mapping: Contemporary Challenges and the Internet of Things as the Way Forward

Science.gov (United States)

Bęcek, Kazimierz

2016-12-01

The Internet of Things (IoT) is an emerging technology that was conceived in 1999. The key components of the IoT are intelligent sensors, which represent objects of interest. The adjective `intelligent' is used here in the information gathering sense, not the psychological sense. Some 30 billion sensors that `know' the current status of objects they represent are already connected to the Internet. Various studies indicate that the number of installed sensors will reach 212 billion by 2020. Various scenarios of IoT projects show sensors being able to exchange data with the network as well as between themselves. In this contribution, we discuss the possibility of deploying the IoT in cartography for real-time mapping. A real-time map is prepared using data harvested through querying sensors representing geographical objects, and the concept of a virtual sensor for abstract objects, such as a land parcel, is presented. A virtual sensor may exist as a data record in the cloud. Sensors are identified by an Internet Protocol address (IP address), which implies that geographical objects through their sensors would also have an IP address. This contribution is an updated version of a conference paper presented by the author during the International Federation of Surveyors 2014 Congress in Kuala Lumpur. The author hopes that the use of the IoT for real-time mapping will be considered by the mapmaking community.

Real-Time Mapping: Contemporary Challenges and the Internet of Things as the Way Forward

Directory of Open Access Journals (Sweden)

Bęcek Kazimierz

2016-12-01

Full Text Available The Internet of Things (IoT is an emerging technology that was conceived in 1999. The key components of the IoT are intelligent sensors, which represent objects of interest. The adjective ‘intelligent’ is used here in the information gathering sense, not the psychological sense. Some 30 billion sensors that ‘know’ the current status of objects they represent are already connected to the Internet. Various studies indicate that the number of installed sensors will reach 212 billion by 2020. Various scenarios of IoT projects show sensors being able to exchange data with the network as well as between themselves. In this contribution, we discuss the possibility of deploying the IoT in cartography for real-time mapping. A real-time map is prepared using data harvested through querying sensors representing geographical objects, and the concept of a virtual sensor for abstract objects, such as a land parcel, is presented. A virtual sensor may exist as a data record in the cloud. Sensors are identified by an Internet Protocol address (IP address, which implies that geographical objects through their sensors would also have an IP address. This contribution is an updated version of a conference paper presented by the author during the International Federation of Surveyors 2014 Congress in Kuala Lumpur. The author hopes that the use of the IoT for real-time mapping will be considered by the mapmaking community.

Rapid and minimum invasive functional brain mapping by real-time visualization of high gamma activity during awake craniotomy.

Science.gov (United States)

Ogawa, Hiroshi; Kamada, Kyousuke; Kapeller, Christoph; Hiroshima, Satoru; Prueckl, Robert; Guger, Christoph

2014-11-01

Electrocortical stimulation (ECS) is the gold standard for functional brain mapping during an awake craniotomy. The critical issue is to set aside enough time to identify eloquent cortices by ECS. High gamma activity (HGA) ranging between 80 and 120 Hz on electrocorticogram is assumed to reflect localized cortical processing. In this report, we used real-time HGA mapping and functional neuronavigation integrated with functional magnetic resonance imaging (fMRI) for rapid and reliable identification of motor and language functions. Four patients with intra-axial tumors in their dominant hemisphere underwent preoperative fMRI and lesion resection with an awake craniotomy. All patients showed significant fMRI activation evoked by motor and language tasks. During the craniotomy, we recorded electrocorticogram activity by placing subdural grids directly on the exposed brain surface. Each patient performed motor and language tasks and demonstrated real-time HGA dynamics in hand motor areas and parts of the inferior frontal gyrus. Sensitivity and specificity of HGA mapping were 100% compared with ECS mapping in the frontal lobe, which suggested HGA mapping precisely indicated eloquent cortices. We found different HGA dynamics of language tasks in frontal and temporal regions. Specificities of the motor and language-fMRI did not reach 85%. The results of HGA mapping was mostly consistent with those of ECS mapping, although fMRI tended to overestimate functional areas. This novel technique enables rapid and accurate identification of motor and frontal language areas. Furthermore, real-time HGA mapping sheds light on underlying physiological mechanisms related to human brain functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Two dimensional microcirculation mapping with real time spatial frequency domain imaging

Science.gov (United States)

Zheng, Yang; Chen, Xinlin; Lin, Weihao; Cao, Zili; Zhu, Xiuwei; Zeng, Bixin; Xu, M.

2018-02-01

We present a spatial frequency domain imaging (SFDI) study of local hemodynamics in the human finger cuticle of healthy volunteers performing paced breathing and the forearm of healthy young adults performing normal breathing with our recently developed Real Time Single Snapshot Multiple Frequency Demodulation - Spatial Frequency Domain Imaging (SSMD-SFDI) system. A two-layer model was used to map the concentrations of deoxy-, oxy-hemoglobin, melanin, epidermal thickness and scattering properties at the subsurface of the forearm and the finger cuticle. The oscillations of the concentrations of deoxy- and oxy-hemoglobin at the subsurface of the finger cuticle and forearm induced by paced breathing and normal breathing, respectively, were found to be close to out-of-phase, attributed to the dominance of the blood flow modulation by paced breathing or heartbeat. Our results suggest that the real time SFDI platform may serve as one effective imaging modality for microcirculation monitoring.

Evaluation of noise pollution in urban traffic hubs—Noise maps and measurements

International Nuclear Information System (INIS)

Fiedler, Paulo Eduardo Kirrian; Zannin, Paulo Henrique Trombetta

2015-01-01

A study was made of some of the main traffic hubs in a Latin American metropolis, in order to determine the presence or absence of noise by means of noise measurements and acoustic mapping. To characterize noise in the evaluated road stretches, 232 measurements were taken at different points. The Predictor software package was used for the noise mapping calculations. Noise sensitive areas, e.g., hospitals, were identified in the evaluated road stretches. Noise maps were calculated for two hospitals, showing the current levels of noise that reach their facades. Hypothetical scenarios were simulated by making changes in the composition of traffic and total number of vehicles, and an assessment was made of the potential influence of these modifications in reducing the noise levels reaching the facades of the buildings in question. The simulations indicated that a 50% reduction in total traffic flow, or a 50% reduction in heavy vehicle traffic flow, would reduce the noise levels by about 3 dB(A). - Highlights: • Evaluation of noise pollution in urban traffic hubs • Street systems • Environmental noise impacts • Noise mapping

Evaluation of noise pollution in urban traffic hubs—Noise maps and measurements

Energy Technology Data Exchange (ETDEWEB)

Fiedler, Paulo Eduardo Kirrian; Zannin, Paulo Henrique Trombetta, E-mail: paulo.zannin@pesquisador.cnpq.br

2015-02-15

A study was made of some of the main traffic hubs in a Latin American metropolis, in order to determine the presence or absence of noise by means of noise measurements and acoustic mapping. To characterize noise in the evaluated road stretches, 232 measurements were taken at different points. The Predictor software package was used for the noise mapping calculations. Noise sensitive areas, e.g., hospitals, were identified in the evaluated road stretches. Noise maps were calculated for two hospitals, showing the current levels of noise that reach their facades. Hypothetical scenarios were simulated by making changes in the composition of traffic and total number of vehicles, and an assessment was made of the potential influence of these modifications in reducing the noise levels reaching the facades of the buildings in question. The simulations indicated that a 50% reduction in total traffic flow, or a 50% reduction in heavy vehicle traffic flow, would reduce the noise levels by about 3 dB(A). - Highlights: • Evaluation of noise pollution in urban traffic hubs • Street systems • Environmental noise impacts • Noise mapping.

A real-time traffic control method for the intersection with pre-signals under the phase swap sorting strategy.

Directory of Open Access Journals (Sweden)

Yiming Bie

Full Text Available To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios.

A real-time traffic control method for the intersection with pre-signals under the phase swap sorting strategy.

Science.gov (United States)

Bie, Yiming; Liu, Zhiyuan; Wang, Yinhai

2017-01-01

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios.

Optimizing Travel Time to Outpatient Interventional Radiology Procedures in a Multi-Site Hospital System Using a Google Maps Application.

Science.gov (United States)

Mandel, Jacob E; Morel-Ovalle, Louis; Boas, Franz E; Ziv, Etay; Yarmohammadi, Hooman; Deipolyi, Amy; Mohabir, Heeralall R; Erinjeri, Joseph P

2018-02-20

The purpose of this study is to determine whether a custom Google Maps application can optimize site selection when scheduling outpatient interventional radiology (IR) procedures within a multi-site hospital system. The Google Maps for Business Application Programming Interface (API) was used to develop an internal web application that uses real-time traffic data to determine estimated travel time (ETT; minutes) and estimated travel distance (ETD; miles) from a patient's home to each a nearby IR facility in our hospital system. Hypothetical patient home addresses based on the 33 cities comprising our institution's catchment area were used to determine the optimal IR site for hypothetical patients traveling from each city based on real-time traffic conditions. For 10/33 (30%) cities, there was discordance between the optimal IR site based on ETT and the optimal IR site based on ETD at non-rush hour time or rush hour time. By choosing to travel to an IR site based on ETT rather than ETD, patients from discordant cities were predicted to save an average of 7.29 min during non-rush hour (p = 0.03), and 28.80 min during rush hour (p travel time when more than one location providing IR procedures is available within the same hospital system.

Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

Science.gov (United States)

Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

2014-12-01

Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active

Estimation of Bimodal Urban Link Travel Time Distribution and Its Applications in Traffic Analysis

Directory of Open Access Journals (Sweden)

Yuxiong Ji

2015-01-01

Full Text Available Vehicles travelling on urban streets are heavily influenced by traffic signal controls, pedestrian crossings, and conflicting traffic from cross streets, which would result in bimodal travel time distributions, with one mode corresponding to travels without delays and the other travels with delays. A hierarchical Bayesian bimodal travel time model is proposed to capture the interrupted nature of urban traffic flows. The travel time distributions obtained from the proposed model are then considered to analyze traffic operations and estimate travel time distribution in real time. The advantage of the proposed bimodal model is demonstrated using empirical data, and the results are encouraging.

Climate Signals: An On-Line Digital Platform for Mapping Climate Change Impacts in Real Time

Science.gov (United States)

Cutting, H.

2016-12-01

Climate Signals is an on-line digital platform for cataloging and mapping the impacts of climate change. The CS platform specifies and details the chains of connections between greenhouse gas emissions and individual climate events. Currently in open-beta release, the platform is designed to to engage and serve the general public, news media, and policy-makers, particularly in real-time during extreme climate events. Climate Signals consists of a curated relational database of events and their links to climate change, a mapping engine, and a gallery of climate change monitors offering real-time data. For each event in the database, an infographic engine provides a custom attribution "tree" that illustrates the connections to climate change. In addition, links to key contextual resources are aggregated and curated for each event. All event records are fully annotated with detailed source citations and corresponding hyper links. The system of attribution used to link events to climate change in real-time is detailed here. This open-beta release is offered for public user testing and engagement. Launched in May 2016, the operation of this platform offers lessons for public engagement in climate change impacts.

Integration of MDSplus in real-time systems

International Nuclear Information System (INIS)

Luchetta, A.; Manduchi, G.; Taliercio, C.

2006-01-01

RFX-mod makes extensive usage of real-time systems for feedback control and uses MDSplus to interface them to the main Data Acquisition system. For this purpose, the core of MDSplus has been ported to VxWorks, the operating system used for real-time control in RFX. Using this approach, it is possible to integrate real-time systems, but MDSplus is used only for non-real-time tasks, i.e. those tasks which are executed before and after the pulse and whose performance does not affect the system time constraints. More extensive use of MDSplus in real-time systems is foreseen, and a real-time layer for MDSplus is under development, which will provide access to memory-mapped pulse files, shared by the tasks running on the same CPU. Real-time communication will also be integrated in the MDSplus core to provide support for distributed memory-mapped pulse files

TRAFFIC SIMULATION FOR MIXED TRAFFIC SYSTEMS

African Journals Online (AJOL)

EGETE

2012-05-04

May 4, 2012 ... Traffic problem is classified into single and mixed, especially in most developing countries, where motorbikes are ..... The traffic light control system presented by its location on ... multi-destination dynamic routing and real-time.

Visual simultaneous localization and mapping (VSLAM) methods applied to indoor 3D topographical and radiological mapping in real-time

International Nuclear Information System (INIS)

Hautot, F.; Dubart, P.; Chagneau, B.; Bacri, C.O.; Abou-Khalil, R.

2017-01-01

New developments in the field of robotics and computer vision enable to merge sensors to allow fast real-time localization of radiological measurements in the space/volume with near real-time radioactive sources identification and characterization. These capabilities lead nuclear investigations to a more efficient way for operators' dosimetry evaluation, intervention scenarios and risks mitigation and simulations, such as accidents in unknown potentially contaminated areas or during dismantling operations. This paper will present new progresses in merging RGB-D camera based on SLAM (Simultaneous Localization and Mapping) systems and nuclear measurement in motion methods in order to detect, locate, and evaluate the activity of radioactive sources in 3-dimensions

Optimal task mapping in safety-critical real-time parallel systems

International Nuclear Information System (INIS)

Aussagues, Ch.

1998-01-01

This PhD thesis is dealing with the correct design of safety-critical real-time parallel systems. Such systems constitutes a fundamental part of high-performance systems for command and control that can be found in the nuclear domain or more generally in parallel embedded systems. The verification of their temporal correctness is the core of this thesis. our contribution is mainly in the following three points: the analysis and extension of a programming model for such real-time parallel systems; the proposal of an original method based on a new operator of synchronized product of state machines task-graphs; the validation of the approach by its implementation and evaluation. The work addresses particularly the main problem of optimal task mapping on a parallel architecture, such that the temporal constraints are globally guaranteed, i.e. the timeliness property is valid. The results incorporate also optimally criteria for the sizing and correct dimensioning of a parallel system, for instance in the number of processing elements. These criteria are connected with operational constraints of the application domain. Our approach is based on the off-line analysis of the feasibility of the deadline-driven dynamic scheduling that is used to schedule tasks inside one processor. This leads us to define the synchronized-product, a system of linear, constraints is automatically generated and then allows to calculate a maximum load of a group of tasks and then to verify their timeliness constraints. The communications, their timeliness verification and incorporation to the mapping problem is the second main contribution of this thesis. FInally, the global solving technique dealing with both task and communication aspects has been implemented and evaluated in the framework of the OASIS project in the LETI research center at the CEA/Saclay. (author)

Explaining How to Play Real-Time Strategy Games

Science.gov (United States)

Metoyer, Ronald; Stumpf, Simone; Neumann, Christoph; Dodge, Jonathan; Cao, Jill; Schnabel, Aaron

Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.

A real-time multichannel memory controller and optimal mapping of memory clients to memory channels

NARCIS (Netherlands)

Gomony, M.D.; Akesson, K.B.; Goossens, K.G.W.

2015-01-01

Ever-increasing demands for main memory bandwidth and memory speed/power tradeoff led to the introduction of memories with multiple memory channels, such as Wide IO DRAM. Efficient utilization of a multichannel memory as a shared resource in multiprocessor real-time systems depends on mapping of the

The near real-time solar irradiance mapping in California based on satellite data and economic and emission benefits analysis

OpenAIRE

Liu, Honglei

2008-01-01

As the most abundant, sustainable, and green energy source on the earth, solar energy has the potential to resolve environmental problems such as climate change and air pollution caused by fossil energy. Real-time solar irradiance mapping, which gives the real-time data on local solar energy distribution, would provide valuable information and lead to more efficient use of solar energy. State of California (CA) is abundant in solar energy. However, the data of real-time direct ...

Application and API for Real-time Visualization of Ground-motions and Tsunami

Science.gov (United States)

Aoi, S.; Kunugi, T.; Suzuki, W.; Kubo, T.; Nakamura, H.; Azuma, H.; Fujiwara, H.

2015-12-01

Due to the recent progress of seismograph and communication environment, real-time and continuous ground-motion observation becomes technically and economically feasible. K-NET and KiK-net, which are nationwide strong motion networks operated by NIED, cover all Japan by about 1750 stations in total. More than half of the stations transmit the ground-motion indexes and/or waveform data in every second. Traditionally, strong-motion data were recorded by event-triggering based instruments with non-continues telephone line which is connected only after an earthquake. Though the data from such networks mainly contribute to preparations for future earthquakes, huge amount of real-time data from dense network are expected to directly contribute to the mitigation of ongoing earthquake disasters through, e.g., automatic shutdown plants and helping decision-making for initial response. By generating the distribution map of these indexes and uploading them to the website, we implemented the real-time ground motion monitoring system, Kyoshin (strong-motion in Japanese) monitor. This web service (www.kyoshin.bosai.go.jp) started in 2008 and anyone can grasp the current ground motions of Japan. Though this service provides only ground-motion map in GIF format, to take full advantage of real-time strong-motion data to mitigate the ongoing disasters, digital data are important. We have developed a WebAPI to provide real-time data and related information such as ground motions (5 km-mesh) and arrival times estimated from EEW (earthquake early warning). All response data from this WebAPI are in JSON format and are easy to parse. We also developed Kyoshin monitor application for smartphone, 'Kmoni view' using the API. In this application, ground motions estimated from EEW are overlapped on the map with the observed one-second-interval indexes. The application can playback previous earthquakes for demonstration or disaster drill. In mobile environment, data traffic and battery are

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN

Directory of Open Access Journals (Sweden)

Rosa Ma Alsina-Pagès

2018-04-01

Full Text Available One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE unrelated to road traffic (sirens, horns, people, etc. should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED. In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap and low-capacity (Lo-Cap sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 1 6 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%. However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN.

Science.gov (United States)

Alsina-Pagès, Rosa Ma; Alías, Francesc; Socoró, Joan Claudi; Orga, Ferran

2018-04-20

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 1 6 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.

Timed bisimulation and open maps

DEFF Research Database (Denmark)

Hune, Thomas; Nielsen, Mogens

1998-01-01

of timed bisimulation. Thus the abstract results from the theory of open maps apply, e.g. the existence of canonical models and characteristic logics. Here, we provide an alternative proof of decidability of bisimulation for finite timed transition systems in terms of open maps, and illustrate the use......Open maps have been used for defining bisimulations for a range of models, but none of these have modelled real-time. We define a category of timed transition systems, and use the general framework of open maps to obtain a notion of bisimulation. We show this to be equivalent to the standard notion...... of open maps in presenting bisimulations....

Traffic flow model at fixed control signals with discrete service time distribution

Directory of Open Access Journals (Sweden)

Lucky I. Igbinosun

2016-04-01

Full Text Available Most of the models of road traffic flow at fixed-cycle controlled intersection assume stationary distributions and provide steady state results. The assumption that a constant number of vehicles can leave the system during the green phase is unrealistic in real life situations. A discrete time queuing model was developed to describe the operation of traffic flow at a road intersection with fixed-cycle signalized control and to account for the randomness in the number of vehicles that can leave the system. The results show the expected queue size in the system when the traffic is light and for a busy period, respectively. For the light period, when the traffic intensity is less than one, it takes a shorter green cycle time for vehicles to clear up than during high traffic intensity (the road junction is saturated. Increasing the number of cars that can leave the junction at the turn of the green phase reduces the number of cycle times before the queue is cleared.

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

Science.gov (United States)

Adams, Matthew D; Kanaroglou, Pavlos S

2016-03-01

Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved

Using Self-Adaptive Evolutionary Algorithms to Evolve Dynamism-Oriented Maps for a Real Time Strategy Game

OpenAIRE

Lara-Cabrera, Raúl; Cotta, Carlos; Fernández Leiva, Antonio J.

2013-01-01

This work presents a procedural content generation system that uses an evolutionary algorithm in order to generate interesting maps for a real-time strategy game, called Planet Wars. Interestingness is here captured by the dynamism of games (i.e., the extent to which they are action-packed). We consider two different approaches to measure the dynamism of the games resulting from these generated maps, one based on fluctuations in the resources controlled by either player and another one based ...

On the feasibility of real-time mapping of the geoelectric field across North America

Science.gov (United States)

Love, Jeffrey J.; Rigler, E. Joshua; Kelbert, Anna; Finn, Carol A.; Bedrosian, Paul A.; Balch, Christopher C.

2018-06-08

A review is given of the present feasibility for accurately mapping geoelectric fields across North America in near-realtime by modeling geomagnetic monitoring and magnetotelluric survey data. Should this capability be successfully developed, it could inform utility companies of magnetic-storm interference on electric-power-grid systems. That real-time mapping of geoelectric fields is a challenge is reflective of (1) the spatiotemporal complexity of geomagnetic variation, especially during magnetic storms, (2) the sparse distribution of ground-based geomagnetic monitoring stations that report data in realtime, (3) the spatial complexity of three-dimensional solid-Earth impedance, and (4) the geographically incomplete state of continental-scale magnetotelluric surveys.

Real-time tsunami inundation forecasting and damage mapping towards enhancing tsunami disaster resiliency

Science.gov (United States)

Koshimura, S.; Hino, R.; Ohta, Y.; Kobayashi, H.; Musa, A.; Murashima, Y.

2014-12-01

With use of modern computing power and advanced sensor networks, a project is underway to establish a new system of real-time tsunami inundation forecasting, damage estimation and mapping to enhance society's resilience in the aftermath of major tsunami disaster. The system consists of fusion of real-time crustal deformation monitoring/fault model estimation by Ohta et al. (2012), high-performance real-time tsunami propagation/inundation modeling with NEC's vector supercomputer SX-ACE, damage/loss estimation models (Koshimura et al., 2013), and geo-informatics. After a major (near field) earthquake is triggered, the first response of the system is to identify the tsunami source model by applying RAPiD Algorithm (Ohta et al., 2012) to observed RTK-GPS time series at GEONET sites in Japan. As performed in the data obtained during the 2011 Tohoku event, we assume less than 10 minutes as the acquisition time of the source model. Given the tsunami source, the system moves on to running tsunami propagation and inundation model which was optimized on the vector supercomputer SX-ACE to acquire the estimation of time series of tsunami at offshore/coastal tide gauges to determine tsunami travel and arrival time, extent of inundation zone, maximum flow depth distribution. The implemented tsunami numerical model is based on the non-linear shallow-water equations discretized by finite difference method. The merged bathymetry and topography grids are prepared with 10 m resolution to better estimate the tsunami inland penetration. Given the maximum flow depth distribution, the system performs GIS analysis to determine the numbers of exposed population and structures using census data, then estimates the numbers of potential death and damaged structures by applying tsunami fragility curve (Koshimura et al., 2013). Since the tsunami source model is determined, the model is supposed to complete the estimation within 10 minutes. The results are disseminated as mapping products to

Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai

Directory of Open Access Journals (Sweden)

Young-Ji Byon

2017-09-01

Full Text Available Traditionally, departments of transportation (DOTs have dispatched probe vehicles with dedicated vehicles and drivers for monitoring traffic conditions. Emerging assisted GPS (AGPS and accelerometer-equipped smartphones offer new sources of raw data that arise from voluntarily-traveling smartphone users provided that their modes of transportation can correctly be identified. By introducing additional raster map layers that indicate the availability of each mode, it is possible to enhance the accuracy of mode detection results. Even in its simplest form, an artificial neural network (ANN excels at pattern recognition with a relatively short processing timeframe once it is properly trained, which is suitable for real-time mode identification purposes. Dubai is one of the major cities in the Middle East and offers unique environments, such as a high density of extremely high-rise buildings that may introduce multi-path errors with GPS signals. This paper develops real-time mode identification ANNs enhanced with proposed mode availability geographic information system (GIS layers, firstly for a universal mode detection and, secondly for an auto mode detection for the particular intelligent transportation system (ITS application of traffic monitoring, and compares the results with existing approaches. It is found that ANN-based real-time mode identification, enhanced by mode availability GIS layers, significantly outperforms the existing methods.

Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

Directory of Open Access Journals (Sweden)

Tan-Hsu Tan

2017-01-01

Full Text Available This study presents a new ubiquitous emergency medical service system (UEMS that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients’ biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient’s biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.

Data forwarding mechanism for supporting real-time services during relocations in UMTS systems

Science.gov (United States)

Cai, Wei; Liao, Xianglong; Zheng, Liang; Liu, Zehong

2004-04-01

To minimize the interruption during the handovers or relocations invoked by subscribers moving is a very critical factor to enhance the performance of the UMTS systems. We know that the 2G systems have been optimized to minimize the interruption of speech during handovers by two main technologies: one is the bi-casting for the DL traffic and the other is the fast radio resynchronization by the UE for the UL traffic. In the UMTS systems, we have also implemented lossless relocations for non real-time services with high reliability by data buffering in the source RNC and target RNC for the UE. However, the UMTS systems support four QoS classes traffic flow: conversational class, streaming class, interactive class and background class. The main distinguishing factor between these QoS classes is how delay sensitive the traffic is: Conversational and Streaming classes are mainly used to carry real-time traffic flows, like video telephony, interactive and background classes are mainly used by traditional Internet applications like WWW, E-mail and FTP. It"s essential to provide the solutions for supporting real-time services to meet the requirement for QoS in UMTS systems. Apparently, the Data buffering mechanism is not adapted to real-time services because of it"s delay may exceed the basic requirement for real-time services. Under this background, the paper discussed two data forwarding solutions for real-time services from the PS domain in the UMTS systems: packet duplication and Core Network bi-casting. The former mechanism does not require any new procedures, messages nor information elements. The later mechanism requires that the GGSN or SGSN is able to bi-cast the DL traffic to the target RNC according to the relocations involving two SGSNs or just involving one SGSN. It also implicitly shows that we need change procedures at the nodes SGSN, GGSN and RNC which are involved in the relocation procedure based on existing procedures that we have already designed if

Robust and flexible mapping for real-time distributed applications during the early design phases

DEFF Research Database (Denmark)

Gan, Junhe; Pop, Paul; Gruian, Flavius

2012-01-01

has a high chance of being schedulable, considering the wcet uncertainties, whereas a flexible mapping has a high chance to successfully accommodate the future scenarios. We propose a Genetic Algorithm-based approach to solve this optimization problem. Extensive experiments show the importance......We are interested in mapping hard real-time applications on distributed heterogeneous architectures. An application is modeled as a set of tasks, and we consider a fixed-priority preemptive scheduling policy. We target the early design phases, when decisions have a high impact on the subsequent...... in the functionality requirements are captured using “future scenarios”, which are task sets that model functionality likely to be added in the future. In this context, we derive a mapping of tasks in the application, such that the resulted implementation is both robust and flexible. Robust means that the application...

Traffic Flow Visualization and Control

National Research Council Canada - National Science Library

Larson, Robert

1999-01-01

.... Air Force Research Laboratory. It is a video-camera-based, wide-area, traffic surveillance and detection system that provides real-time traffic information to traffic management center operators...

On the Impact of Anomalous Noise Events on Road Traffic Noise Mapping in Urban and Suburban Environments.

Science.gov (United States)

Orga, Ferran; Alías, Francesc; Alsina-Pagès, Rosa Ma

2017-12-23

Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate.

Transforming GIS data into functional road models for large-scale traffic simulation.

Science.gov (United States)

Wilkie, David; Sewall, Jason; Lin, Ming C

2012-06-01

There exists a vast amount of geographic information system (GIS) data that model road networks around the world as polylines with attributes. In this form, the data are insufficient for applications such as simulation and 3D visualization-tools which will grow in power and demand as sensor data become more pervasive and as governments try to optimize their existing physical infrastructure. In this paper, we propose an efficient method for enhancing a road map from a GIS database to create a geometrically and topologically consistent 3D model to be used in real-time traffic simulation, interactive visualization of virtual worlds, and autonomous vehicle navigation. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, legal merge zones, and intersections with arbitrary states, and it is independent of the simulation methodologies. We test the 3D models of road networks generated by our algorithm on real-time traffic simulation using both macroscopic and microscopic techniques.

Investigation Model for DDoS Attack Detection in Real-Time

Directory of Open Access Journals (Sweden)

Abdulghani Ali Ahmed

2015-02-01

Full Text Available Investigating traffic of distributed denial of services (DDoS attack requires extra overhead which mostly results in network performance degradation. This study proposes an investigation model for detecting DDoS attack in real-time without causing negative degradation against network performance. The model investigates network traffic in a scalable way to detect user violations on quality of service regulations. Traffic investigation is triggered only when the network is congested; at that exact moment, burst gateways actually generate a congestion notification to misbehaving users. The misbehaving users are thus further investigated by measuring their consumption ratios of bandwidth. By exceeding the service level agreement bandwidth ratio, user traffic is filtered as DDoS traffic. Simulation results demonstrate that the proposed model efficiently monitors intrusive traffic and precisely detects DDoS attack.

The feasibility of an infrared system for real-time visualization and mapping of ultrasound fields

Energy Technology Data Exchange (ETDEWEB)

Shaw, Adam; Nunn, John, E-mail: adam.shaw@npl.co.u [National Physical Laboratory, Teddington, Middlesex, TW11 0LW (United Kingdom)

2010-06-07

In treatment planning for ultrasound therapy, it is desirable to know the 3D structure of the ultrasound field. However, mapping an ultrasound field in 3D is very slow, with even a single planar raster scan taking typically several hours. Additionally, hydrophones that are used for field mapping are expensive and can be damaged in some therapy fields. So there is value in rapid methods which enable visualization and mapping of the ultrasound field in about 1 min. In this note we explore the feasibility of mapping the intensity distribution by measuring the temperature distribution produced in a thin sheet of absorbing material. A 0.2 mm thick acetate sheet forms a window in the wall of a water tank containing the transducer. The window is oriented at 45{sup 0} to the beam axis, and the distance from the transducer to the window can be varied. The temperature distribution is measured with an infrared camera; thermal images of the inclined plane could be viewed in real time or images could be captured for later analysis and 3D field reconstruction. We conclude that infrared thermography can be used to gain qualitative information about ultrasound fields. Thermal images are easily visualized with good spatial and thermal resolutions (0.044 mm and 0.05 {sup 0}C in our system). The focus and field structure such as side lobes can be identified in real time from the direct video output. 3D maps and image planes at arbitrary orientations to the beam axis can be obtained and reconstructed within a few minutes. In this note we are primarily interested in the technique for characterization of high intensity focused ultrasound (HIFU) fields, but other applications such as physiotherapy fields are also possible. (note)

The feasibility of an infrared system for real-time visualization and mapping of ultrasound fields

International Nuclear Information System (INIS)

Shaw, Adam; Nunn, John

2010-01-01

In treatment planning for ultrasound therapy, it is desirable to know the 3D structure of the ultrasound field. However, mapping an ultrasound field in 3D is very slow, with even a single planar raster scan taking typically several hours. Additionally, hydrophones that are used for field mapping are expensive and can be damaged in some therapy fields. So there is value in rapid methods which enable visualization and mapping of the ultrasound field in about 1 min. In this note we explore the feasibility of mapping the intensity distribution by measuring the temperature distribution produced in a thin sheet of absorbing material. A 0.2 mm thick acetate sheet forms a window in the wall of a water tank containing the transducer. The window is oriented at 45 0 to the beam axis, and the distance from the transducer to the window can be varied. The temperature distribution is measured with an infrared camera; thermal images of the inclined plane could be viewed in real time or images could be captured for later analysis and 3D field reconstruction. We conclude that infrared thermography can be used to gain qualitative information about ultrasound fields. Thermal images are easily visualized with good spatial and thermal resolutions (0.044 mm and 0.05 0 C in our system). The focus and field structure such as side lobes can be identified in real time from the direct video output. 3D maps and image planes at arbitrary orientations to the beam axis can be obtained and reconstructed within a few minutes. In this note we are primarily interested in the technique for characterization of high intensity focused ultrasound (HIFU) fields, but other applications such as physiotherapy fields are also possible. (note)

Real-time flood inundation forecasting and mapping for key railway infrastructure: a UK case study

Directory of Open Access Journals (Sweden)

Murphy Alexandra T.

2016-01-01

Full Text Available Flooding events that impede railway infrastructure can cause severe travel delays for the general public and large fines in delayed minutes for the rail industry. Early warnings of flood inundation can give more time to implement mitigation measures which help reduce cancellations, delays and fines. Initial work is reported on the development of a real-time flood inundation forecasting and mapping system for the Cowley Bridge track area near Exeter, UK. This location is on one of the main access routes to South West England and has suffered major floods in the past resulting in significant transport impacts. Flood forecasting systems in the UK mainly forecast river level/flow rather than extent and depth of flood inundation. Here, the development of a chain of coupled models is discussed that link rainfall to river flow, river level and flood extent for the rail track area relating to Cowley Bridge. Historical events are identified to test model performance in predicting inundation of railway infrastructure. The modelling system will operate alongside a series of in-situ sensors chosen to enhance the flood mapping forecasting system. Sensor data will support offline model calibration/verification and real-time data assimilation as well as monitoring flood conditions to inform track closure decisions.

Geomagnetic Observatory Data for Real-Time Applications

Science.gov (United States)

Love, J. J.; Finn, C. A.; Rigler, E. J.; Kelbert, A.; Bedrosian, P.

2015-12-01

The global network of magnetic observatories represents a unique collective asset for the scientific community. Historically, magnetic observatories have supported global magnetic-field mapping projects and fundamental research of the Earth's interior and surrounding space environment. More recently, real-time data streams from magnetic observatories have become an important contributor to multi-sensor, operational monitoring of evolving space weather conditions, especially during magnetic storms. In this context, the U.S. Geological Survey (1) provides real-time observatory data to allied space weather monitoring projects, including those of NOAA, the U.S. Air Force, NASA, several international agencies, and private industry, (2) collaborates with Schlumberger to provide real-time geomagnetic data needed for directional drilling for oil and gas in Alaska, (3) develops products for real-time evaluation of hazards for the electric-power grid industry that are associated with the storm-time induction of geoelectric fields in the Earth's conducting lithosphere. In order to implement strategic priorities established by the USGS Natural Hazards Mission Area and the National Science and Technology Council, and with a focus on developing new real-time products, the USGS is (1) leveraging data management protocols already developed by the USGS Earthquake Program, (2) developing algorithms for mapping geomagnetic activity, a collaboration with NASA and NOAA, (3) supporting magnetotelluric surveys and developing Earth conductivity models, a collaboration with Oregon State University and the NSF's EarthScope Program, (4) studying the use of geomagnetic activity maps and Earth conductivity models for real-time estimation of geoelectric fields, (5) initiating geoelectric monitoring at several observatories, (6) validating real-time estimation algorithms against historical geomagnetic and geoelectric data. The success of these long-term projects is subject to funding constraints

Video-based real-time on-street parking occupancy detection system

Science.gov (United States)

Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

2013-10-01

Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA

Directory of Open Access Journals (Sweden)

N. Zarrinpanjeh

2015-12-01

Full Text Available One of the most practical tools for urban traffic monitoring is CCTV imaging which is widely used for traffic map generation and updating through human surveillance. But due to the expansion of urban road network and the use of huge number of CCTV cameras, visual inspection and updating of traffic sometimes seems to be ineffective and time consuming and therefore not providing real-time robust update. In this paper a method for vehicle detection accounting and speed estimation is proposed to give a more automated solution for traffic assessment. Through removing violating objects and detection of vehicles via morphological filtering and also classification of moving objects at the scene vehicles are counted and traffic speed is estimated. The proposed method is developed and tested using two datasets and evaluation values are computed. The results show that the successfulness of the algorithm decreases by about 12 % due to decrease in illumination quality of imagery.

Traffic Flow Optimization Using a Quantum Annealer

Directory of Open Access Journals (Sweden)

Florian Neukart

2017-12-01

Full Text Available Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum processing units (QPUs produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology’s usefulness for optimization and sampling tasks. In this paper, we present a real-world application that uses quantum technologies. Specifically, we show how to map certain parts of a real-world traffic flow optimization problem to be suitable for quantum annealing. We show that time-critical optimization tasks, such as continuous redistribution of position data for cars in dense road networks, are suitable candidates for quantum computing. Due to the limited size and connectivity of current-generation D-Wave QPUs, we use a hybrid quantum and classical approach to solve the traffic flow problem.

Real-Time Integrated Re-scheduling for Tramway Operations

NARCIS (Netherlands)

Cheung, Kam-Fung; Kuo, Yong-Hong; Lai, S.W.; Leung, Janny M.Y.

2018-01-01

Our work aims to develop practical solution approaches for real-time dispatch of crews and vehicles for disruption management. The practical motivation for our research arose from the operations of a public tramway system in Hong Kong. The tram system shares the road with other vehicular traffic in

Sonification of network traffic flow for monitoring and situational awareness

Science.gov (United States)

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

Science.gov (United States)

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

Intensity Maps Production Using Real-Time Joint Streaming Data Processing From Social and Physical Sensors

Science.gov (United States)

Kropivnitskaya, Y. Y.; Tiampo, K. F.; Qin, J.; Bauer, M.

2015-12-01

Intensity is one of the most useful measures of earthquake hazard, as it quantifies the strength of shaking produced at a given distance from the epicenter. Today, there are several data sources that could be used to determine intensity level which can be divided into two main categories. The first category is represented by social data sources, in which the intensity values are collected by interviewing people who experienced the earthquake-induced shaking. In this case, specially developed questionnaires can be used in addition to personal observations published on social networks such as Twitter. These observations are assigned to the appropriate intensity level by correlating specific details and descriptions to the Modified Mercalli Scale. The second category of data sources is represented by observations from different physical sensors installed with the specific purpose of obtaining an instrumentally-derived intensity level. These are usually based on a regression of recorded peak acceleration and/or velocity amplitudes. This approach relates the recorded ground motions to the expected felt and damage distribution through empirical relationships. The goal of this work is to implement and evaluate streaming data processing separately and jointly from both social and physical sensors in order to produce near real-time intensity maps and compare and analyze their quality and evolution through 10-minute time intervals immediately following an earthquake. Results are shown for the case study of the M6.0 2014 South Napa, CA earthquake that occurred on August 24, 2014. The using of innovative streaming and pipelining computing paradigms through IBM InfoSphere Streams platform made it possible to read input data in real-time for low-latency computing of combined intensity level and production of combined intensity maps in near-real time. The results compare three types of intensity maps created based on physical, social and combined data sources. Here we correlate

Data assimilation of citizen collected information for real-time flood hazard mapping

Science.gov (United States)

Sayama, T.; Takara, K. T.

2017-12-01

Many studies in data assimilation in hydrology have focused on the integration of satellite remote sensing and in-situ monitoring data into hydrologic or land surface models. For flood predictions also, recent studies have demonstrated to assimilate remotely sensed inundation information with flood inundation models. In actual flood disaster situations, citizen collected information including local reports by residents and rescue teams and more recently tweets via social media also contain valuable information. The main interest of this study is how to effectively use such citizen collected information for real-time flood hazard mapping. Here we propose a new data assimilation technique based on pre-conducted ensemble inundation simulations and update inundation depth distributions sequentially when local data becomes available. The propose method is composed by the following two-steps. The first step is based on weighting average of preliminary ensemble simulations, whose weights are updated by Bayesian approach. The second step is based on an optimal interpolation, where the covariance matrix is calculated from the ensemble simulations. The proposed method was applied to case studies including an actual flood event occurred. It considers two situations with more idealized one by assuming continuous flood inundation depth information is available at multiple locations. The other one, which is more realistic case during such a severe flood disaster, assumes uncertain and non-continuous information is available to be assimilated. The results show that, in the first idealized situation, the large scale inundation during the flooding was estimated reasonably with RMSE effective. Nevertheless, the applications of the proposed data assimilation method demonstrated a high potential of this method for assimilating citizen collected information for real-time flood hazard mapping in the future.

Multiprocessor scheduling for real-time systems

CERN Document Server

Baruah, Sanjoy; Buttazzo, Giorgio

2015-01-01

This book provides a comprehensive overview of both theoretical and pragmatic aspects of resource-allocation and scheduling in multiprocessor and multicore hard-real-time systems.  The authors derive new, abstract models of real-time tasks that capture accurately the salient features of real application systems that are to be implemented on multiprocessor platforms, and identify rules for mapping application systems onto the most appropriate models.  New run-time multiprocessor scheduling algorithms are presented, which are demonstrably better than those currently used, both in terms of run-time efficiency and tractability of off-line analysis.  Readers will benefit from a new design and analysis framework for multiprocessor real-time systems, which will translate into a significantly enhanced ability to provide formally verified, safety-critical real-time systems at a significantly lower cost.

High-level traffic-violation detection for embedded traffic analysis

NARCIS (Netherlands)

Vijverberg, J.A.; de Koning, A.H.M.; Han, Jungong; de With, P.H.N.; Cornelissen, D.

2007-01-01

This paper presents the design of a robust and real-time traffic-violation detection system for cameras on intersections. We use background segmentation and a novel road-model to obtain the candidate traffic participants. A region-based tracking system, equipped with static occlusion-reasoning,

Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

Directory of Open Access Journals (Sweden)

Carlos T. Calafate

2015-01-01

Full Text Available Intelligent Transportation System (ITS technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

Pedestrian Friendly Traffic Signal Control.

Science.gov (United States)

2016-01-01

This project continues research aimed at real-time detection and use of pedestrian : traffic flow information to enhance adaptive traffic signal control in urban areas : where pedestrian traffic is substantial and must be given appropriate attention ...

Automating Flood Hazard Mapping Methods for Near Real-time Storm Surge Inundation and Vulnerability Assessment

Science.gov (United States)

Weigel, A. M.; Griffin, R.; Gallagher, D.

2015-12-01

Storm surge has enough destructive power to damage buildings and infrastructure, erode beaches, and threaten human life across large geographic areas, hence posing the greatest threat of all the hurricane hazards. The United States Gulf of Mexico has proven vulnerable to hurricanes as it has been hit by some of the most destructive hurricanes on record. With projected rises in sea level and increases in hurricane activity, there is a need to better understand the associated risks for disaster mitigation, preparedness, and response. GIS has become a critical tool in enhancing disaster planning, risk assessment, and emergency response by communicating spatial information through a multi-layer approach. However, there is a need for a near real-time method of identifying areas with a high risk of being impacted by storm surge. Research was conducted alongside Baron, a private industry weather enterprise, to facilitate automated modeling and visualization of storm surge inundation and vulnerability on a near real-time basis. This research successfully automated current flood hazard mapping techniques using a GIS framework written in a Python programming environment, and displayed resulting data through an Application Program Interface (API). Data used for this methodology included high resolution topography, NOAA Probabilistic Surge model outputs parsed from Rich Site Summary (RSS) feeds, and the NOAA Census tract level Social Vulnerability Index (SoVI). The development process required extensive data processing and management to provide high resolution visualizations of potential flooding and population vulnerability in a timely manner. The accuracy of the developed methodology was assessed using Hurricane Isaac as a case study, which through a USGS and NOAA partnership, contained ample data for statistical analysis. This research successfully created a fully automated, near real-time method for mapping high resolution storm surge inundation and vulnerability for the

Traffic Accidents Involving Cyclists Identifying Causal Factors Using Questionnaire Survey, Traffic Accident Data, and Real-World Observation.

Science.gov (United States)

Oikawa, Shoko; Hirose, Toshiya; Aomura, Shigeru; Matsui, Yasuhiro

2016-11-01

The purpose of this study is to clarify the mechanism of traffic accidents involving cyclists. The focus is on the characteristics of cyclist accidents and scenarios, because the number of traffic accidents involving cyclists in Tokyo is the highest in Japan. First, dangerous situations in traffic incidents were investigated by collecting data from 304 cyclists in one city in Tokyo using a questionnaire survey. The survey indicated that cyclists used their bicycles generally while commuting to work or school in the morning. Second, the study investigated the characteristics of 250 accident situations involving cyclists that happened in the city using real-world bicycle accident data. The results revealed that the traffic accidents occurred at intersections of local streets, where cyclists collided most often with vehicles during commute time in the morning. Third, cyclists' behavior was observed at a local street intersection in the morning in the city using video pictures. In one hour during the morning commute period, 250 bicycles passed through the intersection. The results indicated that one of the reasons for traffic accidents involving cyclists might be the combined effect of low visibility, caused by the presence of box-like building structures close to the intersections, and the cyclists' behavior in terms of their velocity and no confirming safety. It was observed that, on average, bicycle velocity was 3.1 m/s at the initial line of an intersection. The findings from this study could be useful in developing new technologies to improve cyclist safety, such as alert devices for cyclists and vehicle drivers, wireless communication systems between cyclists and vehicle drivers, or advanced vehicles with bicycle detection and collision mitigation systems.

Real-time video analysis for retail stores

Science.gov (United States)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Leveraging GIS in a real-time data environment

Energy Technology Data Exchange (ETDEWEB)

Nemeth, D.B. [Panhandle Energy, Houston, TX, (United States); Spangler, J. [Global Information Systems, Kearney, MO (United States)

2010-07-01

This presentation discussed a project to integrate Gas Control (GC) with a Geographic Information System (GIS) for meeting asset, schematic, and mapping needs. The new system allows maps to be updated accurately and in real time, thereby avoiding first-flow delays. This is a substantial improvement over the previous system, in which maps were updated annually. GC users required a greater depth of data, the authority of update data and send commands, and viewing capability for real-time values for flow and pressure, with multiple concurrent views of the system and near constant availability of views and data. GC users needed to be able to see asset attributes with real-time values; send commands to facilities/equipment to control product flow; coordinate with asset management teams to control product flow; and have strict data/quality control processes. The project team defined and refined the system requirements, reviewed technologies that could be leveraged into a solution, provided data clean-up/migration services to supplement the GIS database with additional data needed for Supervisory Control and Data Acquisition (SCADA), and created overlays of pipe information for map viewing annotated with real-time data readings/asset information. Detailed schematics were presented for the data flow migration. The project resulted in the completed data capture process to supplement GIS asset data for the 5,000-mile Florida Gas Transmission (FGT) system, the completed clean-up of network and schematic diagrams, and the linking of real-time operations data for FGT. The presentation concluded with a discussion regarding opportunities for improvement to the user interface. 24 figs.

Traffic Analysis for Real-Time Communication Networks onboard Ships

DEFF Research Database (Denmark)

Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Jørgensen, N.

1998-01-01

The paper presents a novel method for establishing worst case estimates of queue lenghts and transmission delays in networks of interconnected segments each of ring topology as defined by the ATOMOS project for marine automation. A non probalistic model for describing traffic is introduced as well...

Traffic Analysis for Real-Time Communication Networks onboard Ships

DEFF Research Database (Denmark)

Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Jørgensen, N.

The paper presents a novel method for establishing worst case estimates of queue lenghts and transmission delays in networks of interconnected segments each of ring topology as defined by the ATOMOS project for marine automation. A non probalistic model for describing traffic is introduced as well...

Real-time three-dimensional temperature mapping in photothermal therapy with optoacoustic tomography

Science.gov (United States)

Oyaga Landa, Francisco Javier; Deán-Ben, Xosé Luís.; Sroka, Ronald; Razansky, Daniel

2017-07-01

Ablation and photothermal therapy are widely employed medical protocols where the selective destruction of tissue is a necessity as in cancerous tissue removal or vascular and brain abnormalities. Tissue denaturation takes place when the temperature reaches a threshold value while the time of exposure determines the lesion size. Therefore, the spatio-temporal distribution of temperature plays a crucial role in the outcome of these clinical interventions. We demonstrate fast volumetric temperature mapping with optoacoustic tomography based on real-time optoacoustic readings from the treated region. The performance of the method was investigated in tissue-mimicking phantom experiments. The new ability to non-invasively measure temperature volumetrically in an entire treated region with high spatial and temporal resolutions holds potential for improving safety and efficacy of thermal ablation and to advance the general applicability of laser-based therapy.

U27 : real-time commercial vehicle safety & security monitoring final report.

Science.gov (United States)

2012-12-01

Accurate real-time vehicle tracking has a wide range of applications including fleet management, drug/speed/law enforcement, transportation planning, traffic safety, air quality, electronic tolling, and national security. While many alternative track...

Real-time services in IP network architectures

Science.gov (United States)

Gilardi, Antonella

1996-12-01

The worldwide internet system seems to be the success key for the provision of real time multimedia services to both residential and business users and someone says that in such a way broadband networks will have a reason to exist. This new class of applications that use multiple media (voice, video and data) impose constraints to the global network nowadays consisting of subnets with various data links. The attention will be focused on the interconnection of IP non ATM and ATM networks. IETF and ATM forum are currently involved in the developing specifications suited to adapt the connectionless IP protocol to the connection oriented ATM protocol. First of all the link between the ATM and the IP service model has to be set in order to match the QoS and traffic requirements defined in the relative environment. A further significant topic is represented by the mapping of IP resource reservation model onto the ATM signalling and in the end it is necessary to define how the routing works when there are QoS parameters associated. This paper, considering only unicast applications, will examine the above issues taking as a starting point the situation where an host launches as call set up request with the relevant QoS and traffic descriptor and at some point a router at the edge of the ATM network has to decide how forwarding and request in order to establish an end to end link with the right capabilities. The aim is to compare the proposals emerging from different standard bodies to point out convergency or incompatibility.

Comparison of Microscopic Drivers' Probabilistic Lane-changing Models With Real Traffic Microscopic Data

Directory of Open Access Journals (Sweden)

Seyyed Mohammad Sadat Hoseini

2011-07-01

Full Text Available The difficulties of microscopic-level simulation models to accurately reproduce real traffic phenomena stem not only from the complexity of calibration and validation operations, but also from the structural inadequacies of the sub-models themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty in gathering accurate field data. This paper studies the traffic behaviour of individual drivers utilizing vehicle trajectory data extracted from digital images collected from freeways in Iran. These data are used to evaluate the four proposed microscopic traffic models. One of the models is based on the traffic regulations in Iran and the three others are probabilistic models that use a decision factor for calculating the probability of choosing a position on the freeway by a driver. The decision factors for three probabilistic models are increasing speed, decreasing risk of collision, and increasing speed combined with decreasing risk of collision. The models are simulated by a cellular automata simulator and compared with the real data. It is shown that the model based on driving regulations is not valid, but that other models appear useful for predicting the driver’s behaviour on freeway segments in Iran during noncongested conditions.

Color reproduction and processing algorithm based on real-time mapping for endoscopic images.

Science.gov (United States)

Khan, Tareq H; Mohammed, Shahed K; Imtiaz, Mohammad S; Wahid, Khan A

2016-01-01

In this paper, we present a real-time preprocessing algorithm for image enhancement for endoscopic images. A novel dictionary based color mapping algorithm is used for reproducing the color information from a theme image. The theme image is selected from a nearby anatomical location. A database of color endoscopy image for different location is prepared for this purpose. The color map is dynamic as its contents change with the change of the theme image. This method is used on low contrast grayscale white light images and raw narrow band images to highlight the vascular and mucosa structures and to colorize the images. It can also be applied to enhance the tone of color images. The statistic visual representation and universal image quality measures show that the proposed method can highlight the mucosa structure compared to other methods. The color similarity has been verified using Delta E color difference, structure similarity index, mean structure similarity index and structure and hue similarity. The color enhancement was measured using color enhancement factor that shows considerable improvements. The proposed algorithm has low and linear time complexity, which results in higher execution speed than other related works.

Proactive Traffic Information Control in Emergency Evacuation Network

Directory of Open Access Journals (Sweden)

Zhengfeng Huang

2015-01-01

Full Text Available Traffic demand in emergency evacuation is usually too large to be effectively managed with reactive traffic information control methods. These methods adapt to the road traffic passively by publishing real-time information without consideration of the routing behavior feedback produced by evacuees. Other remedy measures have to be prepared in case of nonrecurring congestion under these methods. To use the network capacity fully to mitigate near-future evacuation traffic congestion, we propose proactive traffic information control (PTIC model. Based on the mechanism between information and routing behavior feedback, this model can change the route choice of evacuees in advance by dissipating strategic traffic information. Generally, the near-future traffic condition is difficult to accurately predict because it is uncertain in evacuation. Assume that the value of traffic information obeys certain distribution within a range, and then real-time traffic information may reflect the most-likely near-future traffic condition. Unlike the real-time information, the proactive traffic information is a selection within the range to achieve a desired level of the road network performance index (total system travel time. In the aspect of the solution algorithm, differential equilibrium decomposed optimization (D-EDO is proposed to compare with other heuristic methods. A field study on a road network around a large stadium is used to validate the PTIC.

D Model Visualization Enhancements in Real-Time Game Engines

Science.gov (United States)

Merlo, A.; Sánchez Belenguer, C.; Vendrell Vidal, E.; Fantini, F.; Aliperta, A.

2013-02-01

This paper describes two procedures used to disseminate tangible cultural heritage through real-time 3D simulations providing accurate-scientific representations. The main idea is to create simple geometries (with low-poly count) and apply two different texture maps to them: a normal map and a displacement map. There are two ways to achieve models that fit with normal or displacement maps: with the former (normal maps), the number of polygons in the reality-based model may be dramatically reduced by decimation algorithms and then normals may be calculated by rendering them to texture solutions (baking). With the latter, a LOD model is needed; its topology has to be quad-dominant for it to be converted to a good quality subdivision surface (with consistent tangency and curvature all over). The subdivision surface is constructed using methodologies for the construction of assets borrowed from character animation: these techniques have been recently implemented in many entertainment applications known as "retopology". The normal map is used as usual, in order to shade the surface of the model in a realistic way. The displacement map is used to finish, in real-time, the flat faces of the object, by adding the geometric detail missing in the low-poly models. The accuracy of the resulting geometry is progressively refined based on the distance from the viewing point, so the result is like a continuous level of detail, the only difference being that there is no need to create different 3D models for one and the same object. All geometric detail is calculated in real-time according to the displacement map. This approach can be used in Unity, a real-time 3D engine originally designed for developing computer games. It provides a powerful rendering engine, fully integrated with a complete set of intuitive tools and rapid workflows that allow users to easily create interactive 3D contents. With the release of Unity 4.0, new rendering features have been added, including Direct

A Dynamic Traffic Signal Timing Model and its Algorithm for Junction of Urban Road

DEFF Research Database (Denmark)

Cai, Yanguang; Cai, Hao

2012-01-01

As an important part of Intelligent Transportation System, the scientific traffic signal timing of junction can improve the efficiency of urban transport. This paper presents a novel dynamic traffic signal timing model. According to the characteristics of the model, hybrid chaotic quantum...... evolutionary algorithm is employed to solve it. The proposed model has simple structure, and only requires traffic inflow speed and outflow speed are bounded functions with at most finite number of discontinuity points. The condition is very loose and better meets the requirements of the practical real......-time and dynamic signal control of junction. To obtain the optimal solution of the model by hybrid chaotic quantum evolutionary algorithm, the model is converted to an easily solvable form. To simplify calculation, we give the expression of the partial derivative and change rate of the objective function...

MonoSLAM: real-time single camera SLAM.

Science.gov (United States)

Davison, Andrew J; Reid, Ian D; Molton, Nicholas D; Stasse, Olivier

2007-06-01

We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to Structure from Motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera.

Scene data fusion: Real-time standoff volumetric gamma-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Barnowski, Ross [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720, United States of America (United States); Haefner, Andrew; Mihailescu, Lucian [Lawrence Berkeley National Lab - Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720, United States of America (United States); Vetter, Kai [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720, United States of America (United States); Lawrence Berkeley National Lab - Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720, United States of America (United States)

2015-11-11

An approach to gamma-ray imaging has been developed that enables near real-time volumetric (3D) imaging of unknown environments thus improving the utility of gamma-ray imaging for source-search and radiation mapping applications. The approach, herein dubbed scene data fusion (SDF), is based on integrating mobile radiation imagers with real-time tracking and scene reconstruction algorithms to enable a mobile mode of operation and 3D localization of gamma-ray sources. A 3D model of the scene, provided in real-time by a simultaneous localization and mapping (SLAM) algorithm, is incorporated into the image reconstruction reducing the reconstruction time and improving imaging performance. The SDF concept is demonstrated in this work with a Microsoft Kinect RGB-D sensor, a real-time SLAM solver, and a cart-based Compton imaging platform comprised of two 3D position-sensitive high purity germanium (HPGe) detectors. An iterative algorithm based on Compton kinematics is used to reconstruct the gamma-ray source distribution in all three spatial dimensions. SDF advances the real-world applicability of gamma-ray imaging for many search, mapping, and verification scenarios by improving the tractiblity of the gamma-ray image reconstruction and providing context for the 3D localization of gamma-ray sources within the environment in real-time.

Mapping the Recent US Hurricanes Triggered Flood Events in Near Real Time

Science.gov (United States)

Shen, X.; Lazin, R.; Anagnostou, E. N.; Wanik, D. W.; Brakenridge, G. R.

2017-12-01

Synthetic Aperture Radar (SAR) observations is the only reliable remote sensing data source to map flood inundation during severe weather events. Unfortunately, since state-of-art data processing algorithms cannot meet the automation and quality standard of a near-real-time (NRT) system, quality controlled inundation mapping by SAR currently depends heavily on manual processing, which limits our capability to quickly issue flood inundation maps at global scale. Specifically, most SAR-based inundation mapping algorithms are not fully automated, while those that are automated exhibit severe over- and/or under-detection errors that limit their potential. These detection errors are primarily caused by the strong overlap among the SAR backscattering probability density functions (PDF) of different land cover types. In this study, we tested a newly developed NRT SAR-based inundation mapping system, named Radar Produced Inundation Diary (RAPID), using Sentinel-1 dual polarized SAR data over recent flood events caused by Hurricanes Harvey, Irma, and Maria (2017). The system consists of 1) self-optimized multi-threshold classification, 2) over-detection removal using land-cover information and change detection, 3) under-detection compensation, and 4) machine-learning based correction. Algorithm details are introduced in another poster, H53J-1603. Good agreements were obtained by comparing the result from RAPID with visual interpretation of SAR images and manual processing from Dartmouth Flood Observatory (DFO) (See Figure 1). Specifically, the over- and under-detections that is typically noted in automated methods is significantly reduced to negligible levels. This performance indicates that RAPID can address the automation and accuracy issues of current state-of-art algorithms and has the potential to apply operationally on a number of satellite SAR missions, such as SWOT, ALOS, Sentinel etc. RAPID data can support many applications such as rapid assessment of damage

The software and hardware architectural design of the vessel thermal map real-time system in JET

International Nuclear Information System (INIS)

Alves, D.; Neto, A.; Valcarcel, D.F.; Jachmich, S.; Arnoux, G.; Card, P.; Devaux, S.; Felton, R.; Goodyear, A.; Kinna, D.; Lomas, P; McCullen, P.; Stephen, A.; Zastrow, K.D.

2012-01-01

The installation of ITER-relevant materials for the Plasma Facing Components (PFCs) in the Joint European Torus (JET) is expected to have a strong impact on the operation and protection of the experiment. In particular, the use of all-beryllium tiles, which deteriorate at a substantially lower temperature than the formerly installed Carbon Fibre Composite (CFC) tiles, imposes strict thermal restrictions on the PFCs during operation. Prompt and precise responses are therefore required whenever anomalous temperatures are detected. The new Vessel Thermal Map (VTM) real-time application collects the temperature measurements provided by dedicated pyrometers and Infra-Red (IR) cameras, groups them according to spatial location and probable offending heat source and raises alarms that will trigger appropriate protective responses. In the context of JETs global scheme for the protection of the new wall, the system is required to run on a 10 millisecond cycle communicating with other systems through the Real-Time Data Network (RTDN). In order to meet these requirements a Commercial Off- The-Shelf (COTS) solution has been adopted based on standard *86 multi-core technology, Linux and the Multi-threaded Application Real-Time executor (MARTe) software framework. This paper presents an overview of the system with particular technical focus on the configuration of its real-time capability and the benefits of the modular development approach and advanced tools provided by the MARTe framework. (authors)

Frontal theta EEG dynamics in a real-world air traffic control task.

Science.gov (United States)

Shou, Guofa; Ding, Lei

2013-01-01

Mental workload and time-on-task effect are two major factors expediting fatigue progress, which leads to performance decline and/or failure in real-world tasks. In the present study, electroencephalography (EEG) is applied to study mental fatigue development during an air traffic control (ATC) task. Specifically, the frontal theta EEG dynamics are firstly dissolved into a unique frontal independent component (IC) through a novel time-frequency independent component analysis (tfICA) method. Then the temporal fluctuations of the identified frontal ICs every minute are compared to workload (reflected by number of clicks per minute) and time-on-task effect by correlational analysis and linear regression analysis. It is observed that the frontal theta activity significantly increase with workload augment and time-on-task. The present study demonstrates that the frontal theta EEG activity identified by tfICA method is a sensitive and reliable metric to assess mental workload and time-on-task effect in a real-world task, i.e., ATC task, at the resolution of minute(s).

Real Time Speed Measure while Automobile Braking on Soft Sensing Technique

Energy Technology Data Exchange (ETDEWEB)

Zhu, W B; Li, D S; Lu, Y [China Jiliang University, Hangzhou, Zhejiang province, 310018 (China)

2006-10-15

Because the braking performance of automobile has close relationship to traffic safety, it is important to detect that. Focusing on the problem that the real time speed is difficult to obtain in detection process, soft sensing technique is introduced in this paper. According to analyzing the relationship of the dynamics equation of a moving automobile, a module of real time speed of braking is set up. By using imitation method with experiment data to get the pressure function of cylinder and analyzing the relationship between the trigging moment of a wheel and the pressure function of brake cylinder, the real time speed is confirmed in good precision. The maximal measurement error of real time speed is 8.7% and the precision can satisfy engineering request.

Real Time Speed Measure while Automobile Braking on Soft Sensing Technique

International Nuclear Information System (INIS)

Zhu, W B; Li, D S; Lu, Y

2006-01-01

Because the braking performance of automobile has close relationship to traffic safety, it is important to detect that. Focusing on the problem that the real time speed is difficult to obtain in detection process, soft sensing technique is introduced in this paper. According to analyzing the relationship of the dynamics equation of a moving automobile, a module of real time speed of braking is set up. By using imitation method with experiment data to get the pressure function of cylinder and analyzing the relationship between the trigging moment of a wheel and the pressure function of brake cylinder, the real time speed is confirmed in good precision. The maximal measurement error of real time speed is 8.7% and the precision can satisfy engineering request

System and method for traffic signal timing estimation

KAUST Repository

Dumazert, Julien; Claudel, Christian G.

2015-01-01

A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

System and method for traffic signal timing estimation

KAUST Repository

Dumazert, Julien

2015-12-30

A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

An Algorithm of Traffic Perception of DDoS Attacks against SOA Based on Time United Conditional Entropy

Directory of Open Access Journals (Sweden)

Yuntao Zhao

2016-01-01

Full Text Available DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destination IP addresses of DDoS attacks, traffic characteristics of services are analyzed based on conditional entropy. The algorithm is provided with perception ability of DDoS attacks on SOA services by introducing time dimension. Simulation results show that the novel method can realize DDoS traffic perception with analyzing abrupt variation of conditional entropy in time dimension.

AND MAPPING OF THE ENVIRONMENT IN REAL TIME

Directory of Open Access Journals (Sweden)

ANDRÉS DÍAZ

2014-01-01

Full Text Available En este trabajo se presenta el desarrollo de un sistema de SLAM Visual (Simultaneous Localization and Mapping que se desempeña en tiempo real, construyendo mapas basados en puntos característicos y estimando la trayectoria de la cámara. La cámara es transportada por una persona que la mueve suavemente con seis grados de libertad en entornos interiores. Los puntos característicos corresponden a esquinas de alta calidad parametrizados con el inverso de su profundidad. Estos son detectados dentro de regiones de interés y se aplica un criterio de ocupación con el fin de evitar aglomeración de características. El proceso de asociación se desarrolla usando búsqueda activa. La representación final se realiza en un entorno tridimensional.

Increase the Safety of Road Traffic Accidents by Applying Clustering

Directory of Open Access Journals (Sweden)

Kos Goran

2013-12-01

Full Text Available In terms of continual increase of number of traffic accidents and alarming trend of increasing number of traffic accidents with catastrophic consequences for human life and health, it is necessary to actively research and develop methods to combat these trends. One of the measures is the implementation of advanced information systems in existing traffic environment. Accidents clusters, as databases of traffic accidents, introduce a new dimension in traffic systems in the form of experience, providing information on current accidents and the ones that have previously occurred in a given period. This paper proposes a new approach to predictive management of traffic processes, based on the collection of data in real time and is based on accidents clusters. The modern traffic information services collects road traffic status data from a wide variety of traffic sensing systems using modern ICT technologies, creating the most accurate road traffic situation awareness achieved so far. Road traffic situation awareness enhanced by accident clusters' data can be visualized and distributed in various ways (including the forms of dynamic heat maps and on various information platforms, suiting the requirements of the end-users. Accent is placed on their significant features that are based on additional knowledge about existing traffic processes and distribution of important traffic information in order to prevent and reduce traffic accidents.

Traffic analysis and control using image processing

Science.gov (United States)

Senthilkumar, K.; Ellappan, Vijayan; Arun, A. R.

2017-11-01

This paper shows the work on traffic analysis and control till date. It shows an approach to regulate traffic the use of image processing and MATLAB systems. This concept uses computational images that are to be compared with original images of the street taken in order to determine the traffic level percentage and set the timing for the traffic signal accordingly which are used to reduce the traffic stoppage on traffic lights. They concept proposes to solve real life scenarios in the streets, thus enriching the traffic lights by adding image receivers like HD cameras and image processors. The input is then imported into MATLAB to be used. as a method for calculating the traffic on roads. Their results would be computed in order to adjust the traffic light timings on a particular street, and also with respect to other similar proposals but with the added value of solving a real, big instance.

Grid Mapping for Spatial Pattern Analyses of Recurrent Urban Traffic Congestion Based on Taxi GPS Sensing Data

Directory of Open Access Journals (Sweden)

Yang Liu

2017-03-01

Full Text Available Traffic congestion is one of the most serious problems that impact urban transportation efficiency, especially in big cities. Identifying traffic congestion locations and occurring patterns is a prerequisite for urban transportation managers in order to take proper countermeasures for mitigating traffic congestion. In this study, the historical GPS sensing data of about 12,000 taxi floating cars in Beijing were used for pattern analyses of recurrent traffic congestion based on the grid mapping method. Through the use of ArcGIS software, 2D and 3D maps of the road network congestion were generated for traffic congestion pattern visualization. The study results showed that three types of traffic congestion patterns were identified, namely: point type, stemming from insufficient capacities at the nodes of the road network; line type, caused by high traffic demand or bottleneck issues in the road segments; and region type, resulting from multiple high-demand expressways merging and connecting to each other. The study illustrated that the proposed method would be effective for discovering traffic congestion locations and patterns and helpful for decision makers to take corresponding traffic engineering countermeasures in order to relieve the urban traffic congestion issues.

A real-time crash prediction model for the ramp vicinities of urban expressways

Directory of Open Access Journals (Sweden)

Moinul Hossain

2013-07-01

Full Text Available Ramp vicinities are arguably the known black-spots on urban expressways. There, while maintaining high speed, drivers need to respond to several complex events such as maneuvering, reading road signs, route planning and maintaining safe distance from other maneuvering vehicles simultaneously which demand higher level of cognitive response to ensure safety. Therefore, any additional discomfort caused by traffic dynamics may induce driving error resulting in a crash. This manuscript presents a methodology for identifying these dynamically forming hazardous traffic conditions near the ramp vicinities with high resolution real-time traffic flow data. It separates the ramp vicinities into four zones – upstream and downstream of entrance and exit ramps, and builds four separate real-time crash prediction models. Around two year (December 2007 to October 2009 crash data as well as their matching traffic sensor data from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited have been utilized for this research. Random multinomial logit, a forest of multinomial logit models, has been used to identify the most important variables. Finally, a real-time modeling method, Bayesian belief net (BBN, has been employed to build the four models using ramp flow, flow and congestion index in the upstream and flow and speed in the downstream of the ramp location as variables. The newly proposed models could predict 50%, 42%, 43% and 55% of the future crashes with around 10% false alarm for the downstream of entrance, downstream of exit, upstream of entrance and upstream of exit ramps respectively. The models can be utilized in combination with various traffic smoothing measures such as ramp metering, variable speed limit, warning messages through variable message signs, etc. to enhance safety near the ramp vicinities.

A regression-based method for mapping traffic-related air pollution. Application and testing in four contrasting urban environments

International Nuclear Information System (INIS)

Briggs, D.J.; De Hoogh, C.; Elliot, P.; Gulliver, J.; Wills, J.; Kingham, S.; Smallbone, K.

2000-01-01

Accurate, high-resolution maps of traffic-related air pollution are needed both as a basis for assessing exposures as part of epidemiological studies, and to inform urban air-quality policy and traffic management. This paper assesses the use of a GIS-based, regression mapping technique to model spatial patterns of traffic-related air pollution. The model - developed using data from 80 passive sampler sites in Huddersfield, as part of the SAVIAH (Small Area Variations in Air Quality and Health) project - uses data on traffic flows and land cover in the 300-m buffer zone around each site, and altitude of the site, as predictors of NO 2 concentrations. It was tested here by application in four urban areas in the UK: Huddersfield (for the year following that used for initial model development), Sheffield, Northampton, and part of London. In each case, a GIS was built in ArcInfo, integrating relevant data on road traffic, urban land use and topography. Monitoring of NO 2 was undertaken using replicate passive samplers (in London, data were obtained from surveys carried out as part of the London network). In Huddersfield, Sheffield and Northampton, the model was first calibrated by comparing modelled results with monitored NO 2 concentrations at 10 randomly selected sites; the calibrated model was then validated against data from a further 10-28 sites. In London, where data for only 11 sites were available, validation was not undertaken. Results showed that the model performed well in all cases. After local calibration, the model gave estimates of mean annual NO 2 concentrations within a factor of 1.5 of the actual mean (approx. 70-90%) of the time and within a factor of 2 between 70 and 100% of the time. r 2 values between modelled and observed concentrations are in the range of 0.58-0.76. These results are comparable to those achieved by more sophisticated dispersion models. The model also has several advantages over dispersion modelling. It is able, for example, to

Real-time distributed scheduling algorithm for supporting QoS over WDM networks

Science.gov (United States)

Kam, Anthony C.; Siu, Kai-Yeung

1998-10-01

Most existing or proposed WDM networks employ circuit switching, typically with one session having exclusive use of one entire wavelength. Consequently they are not suitable for data applications involving bursty traffic patterns. The MIT AON Consortium has developed an all-optical LAN/MAN testbed which provides time-slotted WDM service and employs fast-tunable transceivers in each optical terminal. In this paper, we explore extensions of this service to achieve fine-grained statistical multiplexing with different virtual circuits time-sharing the wavelengths in a fair manner. In particular, we develop a real-time distributed protocol for best-effort traffic over this time-slotted WDM service with near-optical fairness and throughput characteristics. As an additional design feature, our protocol supports the allocation of guaranteed bandwidths to selected connections. This feature acts as a first step towards supporting integrated services and quality-of-service guarantees over WDM networks. To achieve high throughput, our approach is based on scheduling transmissions, as opposed to collision- based schemes. Our distributed protocol involves one MAN scheduler and several LAN schedulers (one per LAN) in a master-slave arrangement. Because of propagation delays and limits on control channel capacities, all schedulers are designed to work with partial, delayed traffic information. Our distributed protocol is of the `greedy' type to ensure fast execution in real-time in response to dynamic traffic changes. It employs a hybrid form of rate and credit control for resource allocation. We have performed extensive simulations, which show that our protocol allocates resources (transmitters, receivers, wavelengths) fairly with high throughput, and supports bandwidth guarantees.

A Multi-Agent Traffic Control Model Based on Distributed System

Directory of Open Access Journals (Sweden)

Qian WU

2014-06-01

Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

Science.gov (United States)

Islam, Kh Tohidul; Raj, Ram Gopal

2017-01-01

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network.

Science.gov (United States)

Islam, Kh Tohidul; Raj, Ram Gopal

2017-04-13

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.

Real-time photorealistic stereoscopic rendering of fire

Science.gov (United States)

Rose, Benjamin M.; McAllister, David F.

2007-02-01

We propose a method for real-time photorealistic stereo rendering of the natural phenomenon of fire. Applications include the use of virtual reality in fire fighting, military training, and entertainment. Rendering fire in real-time presents a challenge because of the transparency and non-static fluid-like behavior of fire. It is well known that, in general, methods that are effective for monoscopic rendering are not necessarily easily extended to stereo rendering because monoscopic methods often do not provide the depth information necessary to produce the parallax required for binocular disparity in stereoscopic rendering. We investigate the existing techniques used for monoscopic rendering of fire and discuss their suitability for extension to real-time stereo rendering. Methods include the use of precomputed textures, dynamic generation of textures, and rendering models resulting from the approximation of solutions of fluid dynamics equations through the use of ray-tracing algorithms. We have found that in order to attain real-time frame rates, our method based on billboarding is effective. Slicing is used to simulate depth. Texture mapping or 2D images are mapped onto polygons and alpha blending is used to treat transparency. We can use video recordings or prerendered high-quality images of fire as textures to attain photorealistic stereo.

LIDAR-INCORPORATED TRAFFIC SIGN DETECTION FROM VIDEO LOG IMAGES OF MOBILE MAPPING SYSTEM

Directory of Open Access Journals (Sweden)

Y. Li

2016-06-01

Full Text Available Mobile Mapping System (MMS simultaneously collects the Lidar points and video log images in a scenario with the laser profiler and digital camera. Besides the textural details of video log images, it also captures the 3D geometric shape of point cloud. It is widely used to survey the street view and roadside transportation infrastructure, such as traffic sign, guardrail, etc., in many transportation agencies. Although many literature on traffic sign detection are available, they only focus on either Lidar or imagery data of traffic sign. Based on the well-calibrated extrinsic parameters of MMS, 3D Lidar points are, the first time, incorporated into 2D video log images to enhance the detection of traffic sign both physically and visually. Based on the local elevation, the 3D pavement area is first located. Within a certain distance and height of the pavement, points of the overhead and roadside traffic signs can be obtained according to the setup specification of traffic signs in different transportation agencies. The 3D candidate planes of traffic signs are then fitted using the RANSAC plane-fitting of those points. By projecting the candidate planes onto the image, Regions of Interest (ROIs of traffic signs are found physically with the geometric constraints between laser profiling and camera imaging. The Random forest learning of the visual color and shape features of traffic signs is adopted to validate the sign ROIs from the video log images. The sequential occurrence of a traffic sign among consecutive video log images are defined by the geometric constraint of the imaging geometry and GPS movement. Candidate ROIs are predicted in this temporal context to double-check the salient traffic sign among video log images. The proposed algorithm is tested on a diverse set of scenarios on the interstate highway G-4 near Beijing, China under varying lighting conditions and occlusions. Experimental results show the proposed algorithm enhances the

DIRADTM - a system for real time detection and identification of radioactive objects

International Nuclear Information System (INIS)

Guillot, L.; Reboli, A.

2009-01-01

The authors present the DIRAD system (DIRAD stands for Detection and Identification of Radionuclides), an automatic system for real time identification of a radioactive anomaly and its interpretation in terms of risk level. It can be adapted to different contexts: pedestrian control, parcel or luggage control, road traffic control, and so on. In case of risk detection, an alert is transmitted in real time to a supervision station along with the whole set of spectral data

THE DEVELOPMENT OF THE REAL TIME INTEGRATED TRAFFIC INFORMATION SYSTEM (RITIS FOR INDONESIA

Directory of Open Access Journals (Sweden)

Ofyar Z. TAMIN

2001-01-01

One of the most important information is the best routes from each origin zone to each destination zone which have already considered the effect of congestion. This information will be the main data for the development of the Route Guidance System (RGS so that each driver can choose his best route through the road network. The best route information will be changed in a short-time-interval basis depending on the traffic condition. Moreover, this approach can also be extended to provide the short-time-interval environmental information. The system has been tested and validated in Bandung and it showed remarkably good results for Bandung condition.

Robust dynamical effects in traffic and chaotic maps on trees

Indian Academy of Sciences (India)

Here we study two types of well-defined diffusive dynamics on scale-free trees: traffic of packets as navigated random walks, and chaotic standard maps coupled along the network links. We show that in both cases robust collective dynamic effects appear, which can be measured statistically and related to non-ergodicity of ...

Real Driving Emissions in Congested Traffic: A Comparison of Cold and Hot Start

OpenAIRE

Khalfan, A; Andrews, GE; Li, H

2016-01-01

Air quality NO₂ and PM exceedances in cities are common, where congested traffic occurs and the monitoring station is at the roadside. This work investigated real world emissions for a Euro 4 SI vehicle on a congested road by a roadside air quality monitoring station that exceeds European air quality standards for NOx and PM. The PEMS used was the Temet FTIR with Horiba OBS pitot tube exhaust mass flow sensor and gas sampler. Twenty nine hot start repeat journeys were made at different times ...

Real-time optoacoustic monitoring of temperature in tissues

International Nuclear Information System (INIS)

Larina, Irina V; Larin, Kirill V; Esenaliev, Rinat O

2005-01-01

To improve the safety and efficacy of thermal therapy, it is necessary to map tissue temperature in real time with submillimetre spatial resolution. Accurate temperature maps may provide the necessary control of the boundaries of the heated regions and minimize thermal damage to surrounding normal tissues. Current imaging modalities fail to monitor tissue temperature in real time with high resolution and accuracy. We investigated a non-invasive optoacoustic method for accurate, real-time monitoring of tissue temperature during thermotherapy. In this study, we induced temperature gradients in tissue and tissue-like samples and monitored the temperature distribution using the optoacoustic technique. The fundamental harmonic of a Q-switched Nd : YAG laser (λ = 1064 nm) was used for optoacoustic wave generation and probing of tissue temperature. The tissue temperature was also monitored with a multi-sensor temperature probe inserted in the samples. Good agreement between optoacoustically measured and actual tissue temperatures was obtained. The accuracy of temperature monitoring was better than 1 0 C, while the spatial resolution was about 1 mm. These data suggest that the optoacoustic technique has the potential to be used for non-invasive, real-time temperature monitoring during thermotherapy

Estimation of urban traffic density from street camera images

OpenAIRE

Chandrakaladharan, Shreyas

2017-01-01

Traffic is a very real problem in today’s world. Elon Musk, CEO of SpaceX and Tesla, has created a start-up which aims to bore tunnels to better manage traffic. While we do not dare to challenge him, we propose to better manage traffic on roads by leveraging currently available technologies in a novel way. Our project aims to give accurate real-time predictions of traffic, so that prospective commuters can choose routes that are free of traffic, thereby automatically balanci...

An Overview on Base Real-Time Hard Shadow Techniques in Virtual Environments

Directory of Open Access Journals (Sweden)

Mohd Shahrizal Sunar

2012-03-01

Full Text Available Shadows are elegant to create a realistic scene in virtual environments variety type of shadow techniques encourage us to prepare an overview on all base shadow techniques. Non real-time and real-time techniques are big subdivision of shadow generation. In non real-time techniques ray tracing, ray casting and radiosity are well known and are described deeply. Radiosity is implemented to create very realistic shadow on non real-time scene. Although traditional radiosity algorithm is difficult to implement, we have proposed a simple one. The proposed pseudo code is easier to understand and implement. Ray tracing is used to prevent of collision of movement objects. Projection shadow, shadow volume and shadow mapping are used to create real-time shadow in virtual environments. We have used projection shadow for some objects are static and have shadow on flat surface. Shadow volume is used to create accurate shadow with sharp outline. Shadow mapping that is the base of most recently techniques is reconstructed. The reconstruct algorithm gives some new idea to propose another algorithm based on shadow mapping.

Handheld real-time volumetric 3-D gamma-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Haefner, Andrew, E-mail: ahaefner@lbl.gov [Lawrence Berkeley National Lab – Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720 (United States); Barnowski, Ross [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720 (United States); Luke, Paul; Amman, Mark [Lawrence Berkeley National Lab – Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720 (United States); Vetter, Kai [Department of Nuclear Engineering, UC Berkeley, 4155 Etcheverry Hall, MC 1730, Berkeley, CA 94720 (United States); Lawrence Berkeley National Lab – Applied Nuclear Physics, 1 Cyclotron Road, Berkeley, CA 94720 (United States)

2017-06-11

This paper presents the concept of real-time fusion of gamma-ray imaging and visual scene data for a hand-held mobile Compton imaging system in 3-D. The ability to obtain and integrate both gamma-ray and scene data from a mobile platform enables improved capabilities in the localization and mapping of radioactive materials. This not only enhances the ability to localize these materials, but it also provides important contextual information of the scene which once acquired can be reviewed and further analyzed subsequently. To demonstrate these concepts, the high-efficiency multimode imager (HEMI) is used in a hand-portable implementation in combination with a Microsoft Kinect sensor. This sensor, in conjunction with open-source software, provides the ability to create a 3-D model of the scene and to track the position and orientation of HEMI in real-time. By combining the gamma-ray data and visual data, accurate 3-D maps of gamma-ray sources are produced in real-time. This approach is extended to map the location of radioactive materials within objects with unknown geometry.

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

Science.gov (United States)

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Traffic Noise as a Factor Influencing Apartment Prices in Large Cities

Directory of Open Access Journals (Sweden)

Szczepańska Agnieszka

2014-10-01

Full Text Available Environmental factors are among the key determinants of real estate prices. They include landscape attractiveness, land relief, exposure to sunlight and proximity to natural features. In large urban centers, traffic noise emissions significantly affect decision-making on the real estate market. Weakly developed road networks and the absence of ring roads that shift road traffic outside residential districts are a widespread problem in the cities of Central-Eastern Europe. The prevention of traffic noise pollution, one of the key environmental problems in Europe, is an important goal of European Union policy. This paper analyzes the correlations between apartment prices and traffic noise levels in Olsztyn, the capital city of the Warminsko-Mazurskie Voivodeship (province in north-eastern Poland. A linear correlation analysis was performed, and the distribution of unit prices of apartments was mapped by ordinary kriging.

A prototype system for real time computer animation of slow traffic in a driving simulator

NARCIS (Netherlands)

Roerdink, JBTM; van Delden, MJB; Hin, AJS; van Wolffelaar, PC; Thalmann, NM; Skala,

1997-01-01

The Traffic Research Centre (TRC) of the University of Groningen in the Netherlands has developed a driving simulator with 'intelligent' computer-controlled traffic, consisting at the moment only of saloon cars. The range of possible applications would be greatly enhanced if other traffic

Passive language mapping combining real-time oscillation analysis with cortico-cortical evoked potentials for awake craniotomy.

Science.gov (United States)

Tamura, Yukie; Ogawa, Hiroshi; Kapeller, Christoph; Prueckl, Robert; Takeuchi, Fumiya; Anei, Ryogo; Ritaccio, Anthony; Guger, Christoph; Kamada, Kyousuke

2016-12-01

OBJECTIVE Electrocortical stimulation (ECS) is the gold standard for functional brain mapping; however, precise functional mapping is still difficult in patients with language deficits. High gamma activity (HGA) between 80 and 140 Hz on electrocorticography is assumed to reflect localized cortical processing, whereas the cortico-cortical evoked potential (CCEP) can reflect bidirectional responses evoked by monophasic pulse stimuli to the language cortices when there is no patient cooperation. The authors propose the use of "passive" mapping by combining HGA mapping and CCEP recording without active tasks during conscious resections of brain tumors. METHODS Five patients, each with an intraaxial tumor in their dominant hemisphere, underwent conscious resection of their lesion with passive mapping. The authors performed functional localization for the receptive language area, using real-time HGA mapping, by listening passively to linguistic sounds. Furthermore, single electrical pulses were delivered to the identified receptive temporal language area to detect CCEPs in the frontal lobe. All mapping results were validated by ECS, and the sensitivity and specificity were evaluated. RESULTS Linguistic HGA mapping quickly identified the language area in the temporal lobe. Electrical stimulation by linguistic HGA mapping to the identified temporal receptive language area evoked CCEPs on the frontal lobe. The combination of linguistic HGA and frontal CCEPs needed no patient cooperation or effort. In this small case series, the sensitivity and specificity were 93.8% and 89%, respectively. CONCLUSIONS The described technique allows for simple and quick functional brain mapping with higher sensitivity and specificity than ECS mapping. The authors believe that this could improve the reliability of functional brain mapping and facilitate rational and objective operations. Passive mapping also sheds light on the underlying physiological mechanisms of language in the human brain.

Value of Information for Optimal Adaptive Routing in Stochastic Time-Dependent Traffic Networks: Algorithms and Computational Tools

Science.gov (United States)

2010-10-25

Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...

Delay Bound: Fractal Traffic Passes through Network Servers

Directory of Open Access Journals (Sweden)

Ming Li

2013-01-01

Full Text Available Delay analysis plays a role in real-time systems in computer communication networks. This paper gives our results in the aspect of delay analysis of fractal traffic passing through servers. There are three contributions presented in this paper. First, we will explain the reasons why conventional theory of queuing systems ceases in the general sense when arrival traffic is fractal. Then, we will propose a concise method of delay computation for hard real-time systems as shown in this paper. Finally, the delay computation of fractal traffic passing through severs is presented.

A Prototype System for Real Time Computer Animation of Slow Traffic in a Driving Simulator

NARCIS (Netherlands)

Roerdink, Jos B.T.M.; Delden, Mattijs J.B. van; Hin, Andrea J.S.; Wolffelaar, Peter C. van

1997-01-01

The Traffic Research Centre (TRC) of the University of Groningen in the Netherlands has developed a driving simulator with ‘intelligent’ computer-controlled traffic, consisting at the moment only of saloon cars. The range of possible applications would be greatly enhanced if other traffic

Trajectory Based Traffic Analysis

DEFF Research Database (Denmark)

Krogh, Benjamin Bjerre; Andersen, Ove; Lewis-Kelham, Edwin

2013-01-01

We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point-and-click a......We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point......-and-click analysis, due to a novel and efficient indexing structure. With the web-site daisy.aau.dk/its/spqdemo/we will demonstrate several analyses, using a very large real-world data set consisting of 1.9 billion GPS records (1.5 million trajectories) recorded from more than 13000 vehicles, and touching most...

Measurements and modelling of base station power consumption under real traffic loads.

Science.gov (United States)

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads

Directory of Open Access Journals (Sweden)

Goran Petrovic

2012-03-01

Full Text Available Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications and UMTS (Universal Mobile Telecommunications System base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

OMPS Near Real-time Products Available Through NASA LANCE (Land Atmosphere Near Real-time Capability for EOS)

Science.gov (United States)

Warnock, A.; Durbin, P. B.; Cechini, M. F.; Masuoka, E.

2017-12-01

Near real-time (NRT) images from the NASA Ozone Mapping and Profiler Suite (OMPS) for sulfur dioxide, total column ozone and aerosol index products are now available through NASA's online Land Atmosphere Near real-time Capability for EOS (LANCE) system. Color palettes, image dimensions and data ranges have been aligned with the corresponding OMI products, allowing for direct comparison of OMPS NRT images with OMI NRT images already available in NASA Worldview. The images are delivered to LANCE within hours of satellite observation. LANCE NRT imagery can be interactively viewed through Worldview and the Global Imagery Browse Services (GIBS).

Traveler oriented traffic performance metrics using real time traffic data from the Midtown-in-Motion (MIM) project in Manhattan, NY.

Science.gov (United States)

2013-10-01

In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...

Improving method of real-time offset tuning for arterial signal coordination using probe trajectory data

Directory of Open Access Journals (Sweden)

Jian Zhang

2016-12-01

Full Text Available In the environment of intelligent transportation systems, traffic condition data would have higher resolution in time and space, which is especially valuable for managing the interrupted traffic at signalized intersections. There exist a lot of algorithms for offset tuning, but few of them take the advantage of modern traffic detection methods such as probe vehicle data. This study proposes a method using probe trajectory data to optimize and adjust offsets in real time. The critical point, representing the changing vehicle dynamics, is first defined as the basis of this approach. Using the critical points related to different states of traffic conditions, such as free flow, queue formation, and dissipation, various traffic status parameters can be estimated, including actual travel speed, queue dissipation rate, and standing queue length. The offset can then be adjusted on a cycle-by-cycle basis. The performance of this approach is evaluated using a simulation network. The results show that the trajectory-based approach can reduce travel time of the coordinated traffic flow when compared with using well-defined offline offset.

Strongly stable real infinitesimally symplectic mappings

NARCIS (Netherlands)

Cushman, R.; Kelley, A.

We prove that a mapA εsp(σ,R), the set of infinitesimally symplectic maps, is strongly stable if and only if its centralizerC(A) insp(σ,R) contains only semisimple elements. Using the theorem that everyB insp(σ,R) close toA is conjugate by a real symplectic map to an element ofC(A), we give a new

Scene independent real-time indirect illumination

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall; Christensen, Niels Jørgen; Falster, Peter

2005-01-01

A novel method for real-time simulation of indirect illumination is presented in this paper. The method, which we call Direct Radiance Mapping (DRM), is based on basal radiance calculations and does not impose any restrictions on scene geometry or dynamics. This makes the method tractable for rea...

Real-time stress monitoring of highway bridges with a secured wireless sensor network.

Science.gov (United States)

2011-12-01

"This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...

Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior

Science.gov (United States)

Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.

Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.

Survey of real-time processing systems for big data

DEFF Research Database (Denmark)

Liu, Xiufeng; Lftikhar, Nadeem; Xie, Xike

2014-01-01

In recent years, real-time processing and analytics systems for big data–in the context of Business Intelligence (BI)–have received a growing attention. The traditional BI platforms that perform regular updates on daily, weekly or monthly basis are no longer adequate to satisfy the fast......-changing business environments. However, due to the nature of big data, it has become a challenge to achieve the real-time capability using the traditional technologies. The recent distributed computing technology, MapReduce, provides off-the-shelf high scalability that can significantly shorten the processing time...... for big data; Its open-source implementation such as Hadoop has become the de-facto standard for processing big data, however, Hadoop has the limitation of supporting real-time updates. The improvements in Hadoop for the real-time capability, and the other alternative real-time frameworks have been...

Automatic traveltime picking using local time-frequency maps

KAUST Repository

Saragiotis, Christos; Alkhalifah, Tariq Ali; Fomel, Sergey B.

2011-01-01

The arrival times of distinct and sufficiently concentrated signals can be computed using Fourier transforms. In real seis- mograms, however, signals are far from distinct. We use local time-frequency maps of the seismograms and its frequency

Realistic Real-Time Outdoor Rendering in Augmented Reality

Science.gov (United States)

Kolivand, Hoshang; Sunar, Mohd Shahrizal

2014-01-01

Realistic rendering techniques of outdoor Augmented Reality (AR) has been an attractive topic since the last two decades considering the sizeable amount of publications in computer graphics. Realistic virtual objects in outdoor rendering AR systems require sophisticated effects such as: shadows, daylight and interactions between sky colours and virtual as well as real objects. A few realistic rendering techniques have been designed to overcome this obstacle, most of which are related to non real-time rendering. However, the problem still remains, especially in outdoor rendering. This paper proposed a much newer, unique technique to achieve realistic real-time outdoor rendering, while taking into account the interaction between sky colours and objects in AR systems with respect to shadows in any specific location, date and time. This approach involves three main phases, which cover different outdoor AR rendering requirements. Firstly, sky colour was generated with respect to the position of the sun. Second step involves the shadow generation algorithm, Z-Partitioning: Gaussian and Fog Shadow Maps (Z-GaF Shadow Maps). Lastly, a technique to integrate sky colours and shadows through its effects on virtual objects in the AR system, is introduced. The experimental results reveal that the proposed technique has significantly improved the realism of real-time outdoor AR rendering, thus solving the problem of realistic AR systems. PMID:25268480

Realistic real-time outdoor rendering in augmented reality.

Directory of Open Access Journals (Sweden)

Hoshang Kolivand

Full Text Available Realistic rendering techniques of outdoor Augmented Reality (AR has been an attractive topic since the last two decades considering the sizeable amount of publications in computer graphics. Realistic virtual objects in outdoor rendering AR systems require sophisticated effects such as: shadows, daylight and interactions between sky colours and virtual as well as real objects. A few realistic rendering techniques have been designed to overcome this obstacle, most of which are related to non real-time rendering. However, the problem still remains, especially in outdoor rendering. This paper proposed a much newer, unique technique to achieve realistic real-time outdoor rendering, while taking into account the interaction between sky colours and objects in AR systems with respect to shadows in any specific location, date and time. This approach involves three main phases, which cover different outdoor AR rendering requirements. Firstly, sky colour was generated with respect to the position of the sun. Second step involves the shadow generation algorithm, Z-Partitioning: Gaussian and Fog Shadow Maps (Z-GaF Shadow Maps. Lastly, a technique to integrate sky colours and shadows through its effects on virtual objects in the AR system, is introduced. The experimental results reveal that the proposed technique has significantly improved the realism of real-time outdoor AR rendering, thus solving the problem of realistic AR systems.

Mapping and characterizing N6-methyladenine in eukaryotic genomes using single molecule real-time sequencing.

Science.gov (United States)

Zhu, Shijia; Beaulaurier, John; Deikus, Gintaras; Wu, Tao; Strahl, Maya; Hao, Ziyang; Luo, Guanzheng; Gregory, James A; Chess, Andrew; He, Chuan; Xiao, Andrew; Sebra, Robert; Schadt, Eric E; Fang, Gang

2018-05-15

N6-methyladenine (m6dA) has been discovered as a novel form of DNA methylation prevalent in eukaryotes, however, methods for high resolution mapping of m6dA events are still lacking. Single-molecule real-time (SMRT) sequencing has enabled the detection of m6dA events at single-nucleotide resolution in prokaryotic genomes, but its application to detecting m6dA in eukaryotic genomes has not been rigorously examined. Herein, we identified unique characteristics of eukaryotic m6dA methylomes that fundamentally differ from those of prokaryotes. Based on these differences, we describe the first approach for mapping m6dA events using SMRT sequencing specifically designed for the study of eukaryotic genomes, and provide appropriate strategies for designing experiments and carrying out sequencing in future studies. We apply the novel approach to study two eukaryotic genomes. For green algae, we construct the first complete genome-wide map of m6dA at single nucleotide and single molecule resolution. For human lymphoblastoid cells (hLCLs), joint analyses of SMRT sequencing and independent sequencing data suggest that putative m6dA events are enriched in the promoters of young, full length LINE-1 elements (L1s). These analyses demonstrate a general method for rigorous mapping and characterization of m6dA events in eukaryotic genomes. Published by Cold Spring Harbor Laboratory Press.

Characterization of the Virginia earthquake effects and source parameters from website traffic analysis

Science.gov (United States)

Bossu, R.; Lefebvre, S.; Mazet-Roux, G.; Roussel, F.

2012-12-01

This paper presents an after the fact study of the Virginia earthquake of 2011 August 23 using only the traffic observed on the EMSC website within minutes of its occurrence. Although the EMSC real time information services remain poorly identified in the US, a traffic surge was observed immediately after the earthquake's occurrence. Such surges, known as flashcrowd and commonly observed on our website after felt events within the Euro-Med region are caused by eyewitnesses looking for information about the shaking they have just felt. EMSC developed an approach named flashsourcing to map the felt area, and in some circumstances, the regions affected by severe damage or network disruption. The felt area is mapped simply by locating the Internet Protocol (IP) addresses of the visitors to the website during these surges while the existence of network disruption is detected by the instantaneous loss at the time of earthquake's occurrence of existing Internet sessions originating from the impacted area. For the Virginia earthquake, which was felt at large distances, the effects of the waves propagation are clearly observed. We show that the visits to our website are triggered by the P waves arrival: the first visitors from a given locality reach our website 90s after their location was shaken by the P waves. From a processing point of view, eyewitnesses can then be considered as ground motion detectors. By doing so, the epicentral location is determined through a simple dedicated location algorithm within 2 min of the earthquake's occurrence and 30 km accuracy. The magnitude can be estimated in similar time frame by using existing empirical relationships between the surface of the felt area and the magnitude. Concerning the effects of the earthquake, we check whether one can discriminate localities affected by strong shaking from web traffic analysis. This is actually the case. Localities affected by strong level of shaking exhibit higher ratio of visitors to the number

Real-time pedestrian detection with the videos of car camera

Directory of Open Access Journals (Sweden)

Yunling Zhang

2015-12-01

Full Text Available Pedestrians in the vehicle path are in danger of being hit, thus causing severe injury to pedestrians and vehicle occupants. Therefore, real-time pedestrian detection with the video of vehicle-mounted camera is of great significance to vehicle–pedestrian collision warning and traffic safety of self-driving car. In this article, a real-time scheme was proposed based on integral channel features and graphics processing unit. The proposed method does not need to resize the input image. Moreover, the computationally expensive convolution of the detectors and the input image was converted into the dot product of two larger matrixes, which can be computed effectively using a graphics processing unit. The experiments showed that the proposed method could be employed to detect pedestrians in the video of car camera at 20+ frames per second with acceptable error rates. Thus, it can be applied in real-time detection tasks with the videos of car camera.

Optimization of Time-Partitions for Mixed-Criticality Real-Time Distributed Embedded Systems

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2011-01-01

In this paper we are interested in mixed-criticality embedded real-time applications mapped on distributed heterogeneous architectures. The architecture provides both spatial and temporal partitioning, thus enforcing enough separation for the critical applications. With temporal partitioning, each...

A RED modified weighted moving average for soft real-time application

Directory of Open Access Journals (Sweden)

Domanśka Joanna

2014-09-01

Full Text Available The popularity of TCP/IP has resulted in an increase in usage of best-effort networks for real-time communication. Much effort has been spent to ensure quality of service for soft real-time traffic over IP networks. The Internet Engineering Task Force has proposed some architecture components, such as Active Queue Management (AQM. The paper investigates the influence of the weighted moving average on packet waiting time reduction for an AQM mechanism: the RED algorithm. The proposed method for computing the average queue length is based on a difference equation (a recursive equation. Depending on a particular optimality criterion, proper parameters of the modified weighted moving average function can be chosen. This change will allow reducing the number of violations of timing constraints and better use of this mechanism for soft real-time transmissions. The optimization problem is solved through simulations performed in OMNeT++ and later verified experimentally on a Linux implementation

Novel real-time 3D radiological mapping solution for ALARA maximization, D and D assessments and radiological management

Energy Technology Data Exchange (ETDEWEB)

Dubart, Philippe; Hautot, Felix [AREVA Group, 1 route de la Noue, Gif sur Yvette (France); Morichi, Massimo; Abou-Khalil, Roger [AREVA Group, Tour AREVA-1, place Jean Millier, Paris (France)

2015-07-01

Good management of dismantling and decontamination (D and D) operations and activities is requiring safety, time saving and perfect radiological knowledge of the contaminated environment as well as optimization for personnel dose and minimization of waste volume. In the same time, Fukushima accident has imposed a stretch to the nuclear measurement operational approach requiring in such emergency situation: fast deployment and intervention, quick analysis and fast scenario definition. AREVA, as return of experience from his activities carried out at Fukushima and D and D sites has developed a novel multi-sensor solution as part of his D and D research, approach and method, a system with real-time 3D photo-realistic spatial radiation distribution cartography of contaminated premises. The system may be hand-held or mounted on a mobile device (robot, drone, e.g). In this paper, we will present our current development based on a SLAM technology (Simultaneous Localization And Mapping) and integrated sensors and detectors allowing simultaneous topographic and radiological (dose rate and/or spectroscopy) data acquisitions. This enabling technology permits 3D gamma activity cartography in real-time. (authors)

Novel real-time 3D radiological mapping solution for ALARA maximization, D and D assessments and radiological management

International Nuclear Information System (INIS)

Dubart, Philippe; Hautot, Felix; Morichi, Massimo; Abou-Khalil, Roger

2015-01-01

Good management of dismantling and decontamination (D and D) operations and activities is requiring safety, time saving and perfect radiological knowledge of the contaminated environment as well as optimization for personnel dose and minimization of waste volume. In the same time, Fukushima accident has imposed a stretch to the nuclear measurement operational approach requiring in such emergency situation: fast deployment and intervention, quick analysis and fast scenario definition. AREVA, as return of experience from his activities carried out at Fukushima and D and D sites has developed a novel multi-sensor solution as part of his D and D research, approach and method, a system with real-time 3D photo-realistic spatial radiation distribution cartography of contaminated premises. The system may be hand-held or mounted on a mobile device (robot, drone, e.g). In this paper, we will present our current development based on a SLAM technology (Simultaneous Localization And Mapping) and integrated sensors and detectors allowing simultaneous topographic and radiological (dose rate and/or spectroscopy) data acquisitions. This enabling technology permits 3D gamma activity cartography in real-time. (authors)

Proportional green time scheduling for traffic lights

NARCIS (Netherlands)

P. Kovacs; Le, T. (Tung); R. Núñez Queija (Rudesindo); Vu, H. (Hai); N. Walton

2016-01-01

textabstractWe consider the decentralized scheduling of a large number of urban traffic lights. We investigate factors determining system performance, in particular, the length of the traffic light cycle and the proportion of green time allocated to each junction. We study the effect of the length

Optimization of traffic light control system of an intersection using ...

African Journals Online (AJOL)

This paper considers an automated static road traffic control system of an intersection for the purpose of minimizing the effects of traffic jam and hence its attendant consequences such as prolonged waiting time, emission of toxic hydrocarbons from automobiles, etc. Using real-time road traffic data, a dynamic round-robin ...

Real-Time Support on IEEE 802.11 Wireless Ad-Hoc Networks: Reality vs. Theory

Science.gov (United States)

Kang, Mikyung; Kang, Dong-In; Suh, Jinwoo

The usable throughput of an IEEE 802.11 system for an application is much less than the raw bandwidth. Although 802.11b has a theoretical maximum of 11Mbps, more than half of the bandwidth is consumed by overhead leaving at most 5Mbps of usable bandwidth. Considering this characteristic, this paper proposes and analyzes a real-time distributed scheduling scheme based on the existing IEEE 802.11 wireless ad-hoc networks, using USC/ISI's Power Aware Sensing Tracking and Analysis (PASTA) hardware platform. We compared the distributed real-time scheduling scheme with the real-time polling scheme to meet deadline, and compared a measured real bandwidth with a theoretical result. The theoretical and experimental results show that the distributed scheduling scheme can guarantee real-time traffic and enhances the performance up to 74% compared with polling scheme.

Real-time systems

OpenAIRE

Badr, Salah M.; Bruztman, Donald P.; Nelson, Michael L.; Byrnes, Ronald Benton

1992-01-01

This paper presents an introduction to the basic issues involved in real-time systems. Both real-time operating sys and real-time programming languages are explored. Concurrent programming and process synchronization and communication are also discussed. The real-time requirements of the Naval Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real-time operating system, real-time programming language, real-time sy...

Traffic dispersion through a series of signals with irregular split

Science.gov (United States)

Nagatani, Takashi

2016-01-01

We study the traffic behavior of a group of vehicles moving through a sequence of signals with irregular splits on a roadway. We present the stochastic model of vehicular traffic controlled by signals. The dynamic behavior of vehicular traffic is clarified by analyzing traffic pattern and travel time numerically. The group of vehicles breaks up more and more by the irregularity of signal's split. The traffic dispersion is induced by the irregular split. We show that the traffic dispersion depends highly on the cycle time and the strength of split's irregularity. Also, we study the traffic behavior through the series of signals at the green-wave strategy. The dependence of the travel time on offset time is derived for various values of cycle time. The region map of the traffic dispersion is shown in (cycle time, offset time)-space.

RCNF: Real-time Collaborative Network Forensic Scheme for Evidence Analysis

OpenAIRE

Moustafa, Nour; Slay, Jill

2017-01-01

Network forensic techniques help in tracking different types of cyber attack by monitoring and inspecting network traffic. However, with the high speed and large sizes of current networks, and the sophisticated philosophy of attackers, in particular mimicking normal behaviour and/or erasing traces to avoid detection, investigating such crimes demands intelligent network forensic techniques. This paper suggests a real-time collaborative network Forensic scheme (RCNF) that can monitor and inves...

Web application and database modeling of traffic impact analysis using Google Maps

Science.gov (United States)

Yulianto, Budi; Setiono

2017-06-01

Traffic impact analysis (TIA) is a traffic study that aims at identifying the impact of traffic generated by development or change in land use. In addition to identifying the traffic impact, TIA is also equipped with mitigation measurement to minimize the arising traffic impact. TIA has been increasingly important since it was defined in the act as one of the requirements in the proposal of Building Permit. The act encourages a number of TIA studies in various cities in Indonesia, including Surakarta. For that reason, it is necessary to study the development of TIA by adopting the concept Transportation Impact Control (TIC) in the implementation of the TIA standard document and multimodal modeling. It includes TIA's standardization for technical guidelines, database and inspection by providing TIA checklists, monitoring and evaluation. The research was undertaken by collecting the historical data of junctions, modeling of the data in the form of relational database, building a user interface for CRUD (Create, Read, Update and Delete) the TIA data in the form of web programming with Google Maps libraries. The result research is a system that provides information that helps the improvement and repairment of TIA documents that exist today which is more transparent, reliable and credible.

Intraoperative mapping of expressive language cortex using passive real-time electrocorticography

Directory of Open Access Journals (Sweden)

AmiLyn M. Taplin

2016-01-01

Full Text Available In this case report, we investigated the utility and practicality of passive intraoperative functional mapping of expressive language cortex using high-resolution electrocorticography (ECoG. The patient presented here experienced new-onset seizures caused by a medium-grade tumor in very close proximity to expressive language regions. In preparation of tumor resection, the patient underwent multiple functional language mapping procedures. We examined the relationship of results obtained with intraoperative high-resolution ECoG, extraoperative ECoG utilizing a conventional subdural grid, extraoperative electrical cortical stimulation (ECS mapping, and functional magnetic resonance imaging (fMRI. Our results demonstrate that intraoperative mapping using high-resolution ECoG is feasible and, within minutes, produces results that are qualitatively concordant to those achieved by extraoperative mapping modalities. They also suggest that functional language mapping of expressive language areas with ECoG may prove useful in many intraoperative conditions given its time efficiency and safety. Finally, they demonstrate that integration of results from multiple functional mapping techniques, both intraoperative and extraoperative, may serve to improve the confidence in or precision of functional localization when pathology encroaches upon eloquent language cortex.

Assistance System for Traffic Signs Inventory

Directory of Open Access Journals (Sweden)

Karel Zídek

2015-01-01

Full Text Available We can see arising trend in the automotive industry in last years – autonomous cars that are driven just by on-board computers. The traffic signs tracking system must deal with real conditions with data that are frequently obtained in poor light conditions, fog, heavy rain or are otherwise disturbed. Completely same problem is solved by mapping companies that are producing geospatial data for different information systems, navigations, etc. They are frequently using cars equipped with a wide range of measuring instruments including panoramic cameras. These measurements are frequently done during early morning hours when the traffic conditions are acceptable. However, in this time, the sun position is usually not optimal for the photography. Most of the traffic signs and other street objects are heavily underexposed. Hence, it is difficult to find an automatic approach that can identify them reliably. In this article, we focus on methods designed to deal with the described conditions. An overview of the state-of-the-art methods is outlined. Further, where it is possible, we outline an implementation of the described methods using well-known Open Computer Vision library. Finally, emphasis is placed on the methods that can deal with low light conditions, fog or other situations that complicate the detection process.

Near-Real-Time DMSP SSM/I-SSMIS Daily Polar Gridded Sea Ice Concentrations

Data.gov (United States)

National Aeronautics and Space Administration — This data set provides a near-real-time (NRT) map of sea ice concentrations for both the Northern and Southern Hemispheres. The near-real-time passive microwave...

Real-time Global Illumination by Simulating Photon Mapping

DEFF Research Database (Denmark)

Larsen, Bent Dalgaard

2004-01-01

This thesis introduces a new method for simulating photon mapping in realtime. The method uses a variety of both CPU and GPU based algorithms for speeding up the different elements in global illumination. The idea behind the method is to calculate each illumination element individually in a progr......This thesis introduces a new method for simulating photon mapping in realtime. The method uses a variety of both CPU and GPU based algorithms for speeding up the different elements in global illumination. The idea behind the method is to calculate each illumination element individually...... in a progressive and efficient manner. This has been done by analyzing the photon mapping method and by selecting efficient methods, either CPU based or GPU based, which replaces the original photon mapping algorithms. We have chosen to focus on the indirect illumination and the caustics. In our method we first...... divide the photon map into several photon maps in order to make local updates possible. Then indirect illumination is added using light maps that are selectively updated by using selective photon tracing on the CPU. The final gathering step is calculated by using fragment programs and GPU based...

Progress in Near Real-Time Volcanic Cloud Observations Using Satellite UV Instruments

Science.gov (United States)

Krotkov, N. A.; Yang, K.; Vicente, G.; Hughes, E. J.; Carn, S. A.; Krueger, A. J.

2011-12-01

Volcanic clouds from explosive eruptions can wreak havoc in many parts of the world, as exemplified by the 2010 eruption at the Eyjafjöll volcano in Iceland, which caused widespread disruption to air traffic and resulted in economic impacts across the globe. A suite of satellite-based systems offer the most effective means to monitor active volcanoes and to track the movement of volcanic clouds globally, providing critical information for aviation hazard mitigation. Satellite UV sensors, as part of this suite, have a long history of making unique near-real time (NRT) measurements of sulfur dioxide (SO2) and ash (aerosol Index) in volcanic clouds to supplement operational volcanic ash monitoring. Recently a NASA application project has shown that the use of near real-time (NRT,i.e., not older than 3 h) Aura/OMI satellite data produces a marked improvement in volcanic cloud detection using SO2 combined with Aerosol Index (AI) as a marker for ash. An operational online NRT OMI AI and SO2 image and data product distribution system was developed in collaboration with the NOAA Office of Satellite Data Processing and Distribution. Automated volcanic eruption alarms, and the production of volcanic cloud subsets for multiple regions are provided through the NOAA website. The data provide valuable information in support of the U.S. Federal Aviation Administration goal of a safe and efficient National Air Space. In this presentation, we will highlight the advantages of UV techniques and describe the advances in volcanic SO2 plume height estimation and enhanced volcanic ash detection using hyper-spectral UV measurements, illustrated with Aura/OMI observations of recent eruptions. We will share our plan to provide near-real-time volcanic cloud monitoring service using the Ozone Mapping and Profiler Suite (OMPS) on the Joint Polar Satellite System (JPSS).

Early Model of Traffic Sign Reminder Based on Neural Network

Directory of Open Access Journals (Sweden)

Budi Rahmani

2012-12-01

Full Text Available Recognizing the traffic signs installed on the streets is one of the requirements of driving on the road. Laxity in driving may result in traffic accident. This paper describes a real-time reminder model, by utilizing a camera that can be installed in a car to capture image of traffic signs, and is processed and later to inform the driver. The extracting feature harnessing the morphological elements (strel is used in this paper. Artificial Neural Networks is used to train the system and to produce a final decision. The result shows that the accuracy in detecting and recognizing the ten types of traffic signs in real-time is 80%.

Real-time travel time prediction framework for departure time and route advice

NARCIS (Netherlands)

Calvert, S.C.; Snelder, M.; Bakri, T.; Heijligers, B.; Knoop, V.L.

2015-01-01

Heavily used urban networks remain a challenge for travel time prediction because traffic flow is rarely homogeneous and is also subject to a wide variety of disturbances. Various models, some of which use traffic flow theory and some of which are data driven, have been developed to predict traffic

Analysis of the LTE Access Reservation Protocol for Real-Time Traffic

DEFF Research Database (Denmark)

Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

2013-01-01

LTE is increasingly seen as a system for serving real-time Machine-to-Machine (M2M) communication needs. The asynchronous M2M user access in LTE is obtained through a two-phase access reservation protocol (contention and data phase). Existing analysis related to these protocols is based...... of the two-phase LTE reservation protocol and asses its performance, when assumptions (1) and (2) do not hold....

The Traffic Signal Acquisition System Based on GPS and SD Card Storage

Directory of Open Access Journals (Sweden)

LIU Chang-yuan

2017-06-01

Full Text Available In terms of the issues where traffic lights’ positions and traffic status information cannot be managed automatically，in this system，STC12C5A60S2 microcontroller can be used as the master chip in conjunction with the GPS position module，Neo-5Q. The wireless transceiver module，PT2262 /2272 and the portable installing SD card are used to design a new type of real-time information acquisition solution for positions of traffic lights and signal status. And the system can determine the traffic lights’ positions and the process of lighting in a real time. Then the data will be stored in SD card by the SD card module. Furthermore，the equipment can be implemented on existing facilities with a simple circuit. According to the result of experiments，the system contains a convenient storage，works in a real time and it is also advisable to help with the data reading and analysis. Thus， implementation of the system is of great significance to acquire and analyze the traffic status information in recent times.

Intelligent Traffic Light Based on PLC Control

Science.gov (United States)

Mei, Lin; Zhang, Lijian; Wang, Lingling

2017-11-01

The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

New Near-Real Time Monitoring of the Ionosphere over Europe Available On-line

Science.gov (United States)

Chevalier, J. M.; Bergeot, N.; Bruyninx, C.; Pottiaux, E.; Aerts, W.; Baire, Q.; Legrand, J.; Defraigne, P.

2012-04-01

With the beginning of the 24th Solar cycle, the increased Solar activity requires having a close eye on the ionosphere for better understanding Space Weather physics and its effects on radio communications. In that frame, near-real time ionospheric models over Europe are now routinely generated at the Royal Observatory of Belgium (ROB). These models are made available to the public through new interactive web pages at the web site of the GNSS team (www.gnss.be) and the Solar Influences Data Analysis Center (www.sidc.be) of ROB. The models are ionospheric Vertical Total Electron Content (VTEC) maps estimated every 15 minutes on a 0.5°x0.5° grid. They use the high-rate GPS observations of the real-time stations in the EUREF Permanent Network (EPN) provided by the ROB NTRIP broadcaster. The maps are published on the ROB web site with a latency of 7-15 minutes with respect to the last GPS measurement included in the 15-minute observation files. In a first step, this paper presents the processing strategy used to generate the VTEC maps: input data, parameter estimation, data cleaning and interpolation method. In addition, the tools developed to further exploit the product are introduced, e.g. on-demand animated VTEC maps. In a second step, the VTEC maps are compared with external ionospheric products and models such as Global Ionospheric Maps and IRI 2011. These new near-real time VTEC maps will allow any user within the geographical scope of the maps to estimate in near-real time the ionospheric delay induced along the signal of any observed satellite. In the future, the web site will continuously be updated in response to evolving user needs. This paper opens doors to discussions with the user community to target their needs.

A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks.

Science.gov (United States)

Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il

2017-11-09

Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new ( m , k )-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the ( m , k )-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured ( m , k )-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.

Time series modeling in traffic safety research.

Science.gov (United States)

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

AVL and Monitoring for Massive Traffic Control System over DDS

Directory of Open Access Journals (Sweden)

Basem Almadani

2015-01-01

Full Text Available This paper proposes a real-time Automatic Vehicle Location (AVL and monitoring system for traffic control of pilgrims coming towards the city of Makkah in Saudi Arabia based on Data Distribution Service (DDS specified by the Object Management Group (OMG. DDS based middleware employs Real-Time Publish/Subscribe (RTPS protocol that implements many-to-many communication paradigm suitable in massive traffic control applications. Using this middleware approach, we are able to locate and track huge number of mobile vehicles and identify all passengers in real-time who are coming to perform annual Hajj. For validation of our proposed framework, various performance matrices are examined over WLAN using DDS. Results show that DDS based middleware can meet real-time requirements in large-scale AVL environment.

Controlling traffic jams by time modulating the safety distance

DEFF Research Database (Denmark)

Gaididei, Yu B.; Gorria, C.; Berkemer, R.

2013-01-01

The possibility of controlling traffic dynamics by applying high-frequency time modulation of traffic flow parameters is studied. It is shown that the region of the car density where the uniform (free) flow is unstable changes in the presence of time modulation compared with the unmodulated case....

Wave dynamics in an extended macroscopic traffic flow model with periodic boundaries

Science.gov (United States)

Wang, Yu-Qing; Chu, Xing-Jian; Zhou, Chao-Fan; Yan, Bo-Wen; Jia, Bin; Fang, Chen-Hao

2018-06-01

Motivated by the previous traffic flow model considering the real-time traffic state, a modified macroscopic traffic flow model is established. The periodic boundary condition is applied to the car-following model. Besides, the traffic state factor R is defined in order to correct the real traffic conditions in a more reasonable way. It is a key step that we introduce the relaxation time as a density-dependent function and provide corresponding evolvement of traffic flow. Three different typical initial densities, namely the high density, the medium one and the low one, are intensively investigated. It can be found that the hysteresis loop exists in the proposed periodic-boundary system. Furthermore, the linear and nonlinear stability analyses are performed in order to test the robustness of the system.

Automated Big Traffic Analytics for Cyber Security

OpenAIRE

Miao, Yuantian; Ruan, Zichan; Pan, Lei; Wang, Yu; Zhang, Jun; Xiang, Yang

2018-01-01

Network traffic analytics technology is a cornerstone for cyber security systems. We demonstrate its use through three popular and contemporary cyber security applications in intrusion detection, malware analysis and botnet detection. However, automated traffic analytics faces the challenges raised by big traffic data. In terms of big data's three characteristics --- volume, variety and velocity, we review three state of the art techniques to mitigate the key challenges including real-time tr...

Adaptive Traffic Signal Control: Deep Reinforcement Learning Algorithm with Experience Replay and Target Network

OpenAIRE

Gao, Juntao; Shen, Yulong; Liu, Jia; Ito, Minoru; Shiratori, Norio

2017-01-01

Adaptive traffic signal control, which adjusts traffic signal timing according to real-time traffic, has been shown to be an effective method to reduce traffic congestion. Available works on adaptive traffic signal control make responsive traffic signal control decisions based on human-crafted features (e.g. vehicle queue length). However, human-crafted features are abstractions of raw traffic data (e.g., position and speed of vehicles), which ignore some useful traffic information and lead t...

Active traffic management case study: phase 1 : final report.

Science.gov (United States)

2016-03-01

This study developed a systematic approach for using data from multiple sources to provide active traffic management : solutions. The feasibility of two active traffic management solutions is analyzed in this report: ramp-metering and real-time : cra...

Suitability of Synthetic Driving Profiles from Traffic Micro-Simulation for Real-World Energy Analysis: Preprint

Energy Technology Data Exchange (ETDEWEB)

Hou, Yunfei; Wood, Eric; Burton, Evan; Gonder, Jeffrey

2015-10-14

A shift towards increased levels of driving automation is generally expected to result in improved safety and traffic congestion outcomes. However, little empirical data exists to estimate the impact that automated driving could have on energy consumption and greenhouse gas emissions. In the absence of empirical data on differences between drive cycles from present day vehicles (primarily operated by humans) and future vehicles (partially or fully operated by computers) one approach is to model both situations over identical traffic conditions. Such an exercise requires traffic micro-simulation to not only accurately model vehicle operation under high levels of automation, but also (and potentially more challenging) vehicle operation under present day human drivers. This work seeks to quantify the ability of a commercial traffic micro-simulation program to accurately model real-world drive cycles in vehicles operated primarily by humans in terms of driving speed, acceleration, and simulated fuel economy. Synthetic profiles from models of freeway and arterial facilities near Atlanta, Georgia, are compared to empirical data collected from real-world drivers on the same facilities. Empirical and synthetic drive cycles are then simulated in a powertrain efficiency model to enable comparison on the basis of fuel economy. Synthetic profiles from traffic micro-simulation were found to exhibit low levels of transient behavior relative to the empirical data. Even with these differences, the synthetic and empirical data in this study agree well in terms of driving speed and simulated fuel economy. The differences in transient behavior between simulated and empirical data suggest that larger stochastic contributions in traffic micro-simulation (relative to those present in the traffic micro-simulation tool used in this study) are required to fully capture the arbitrary elements of human driving. Interestingly, the lack of stochastic contributions from models of human drivers

Integrated deployment architecture for predictive real-time traffic routing incorporating human factors considerations.

Science.gov (United States)

2014-05-01

As Advanced Traveler Information Systems (ATIS) are being more widely accessed by drivers, understanding drivers behavioral responses to real-time travel information through ATIS and its consequential benefits are important to the widespread deplo...

Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor

Science.gov (United States)

Landry, Steven J.; Farley, Todd; Hoang, Ty

2005-01-01

Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.

Road Artery Traffic Light Optimization with Use of the Reinforcement Learning

Directory of Open Access Journals (Sweden)

Rok Marsetič

2014-04-01

Full Text Available The basic principle of optimal traffic control is the appropriate real-time response to dynamic traffic flow changes. Signal plan efficiency depends on a large number of input parameters. An actuated signal system can adjust very well to traffic conditions, but cannot fully adjust to stochastic traffic volume oscillation. Due to the complexity of the problem analytical methods are not applicable for use in real time, therefore the purpose of this paper is to introduce heuristic method suitable for traffic light optimization in real time. With the evolution of artificial intelligence new possibilities for solving complex problems have been introduced. The goal of this paper is to demonstrate that the use of the Q learning algorithm for traffic lights optimization is suitable. The Q learning algorithm was verified on a road artery with three intersections. For estimation of the effectiveness and efficiency of the proposed algorithm comparison with an actuated signal plan was carried out. The results (average delay per vehicle and the number of vehicles that left road network show that Q learning algorithm outperforms the actuated signal controllers. The proposed algorithm converges to the minimal delay per vehicle regardless of the stochastic nature of traffic. In this research the impact of the model parameters (learning rate, exploration rate, influence of communication between agents and reward type on algorithm effectiveness were analysed as well.

Design of real-time voice over internet protocol system under bandwidth network

Science.gov (United States)

Zhang, Li; Gong, Lina

2017-04-01

With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

The Use of OMPS Near Real Time Products in Volcanic Cloud Risk Mitigation and Smoke/Dust Air Quality Assessments

Science.gov (United States)

Seftor, C. J.; Krotkov, N. A.; McPeters, R. D.; Li, J. Y.; Durbin, P. B.

2015-12-01

Near real time (NRT) SO2 and aerosol index (AI) imagery from Aura's Ozone Monitoring Instrument (OMI) has proven invaluable in mitigating the risk posed to air traffic by SO2 and ash clouds from volcanic eruptions. The OMI products, generated as part of NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) NRT system and available through LANCE and both NOAA's NESDIS and ESA's Support to Aviation Control Service (SACS) portals, are used to monitor the current location of volcanic clouds and to provide input into Volcanic Ash (VA) advisory forecasts. NRT products have recently been developed using data from the Ozone Mapping and Profiler Suite onboard the Suomi NPP platform; they are currently being made available through the SACS portal and will shortly be incorporated into the LANCE NRT system. We will show examples of the use of OMPS NRT SO2 and AI imagery to monitor recent volcanic eruption events. We will also demonstrate the usefulness of OMPS AI imagery to detect and track dust storms and smoke from fires, and how this information can be used to forecast their impact on air quality in areas far removed from their source. Finally, we will show SO2 and AI imagery generated from our OMPS Direct Broadcast data to highlight the capability of our real time system.

Real-time information and processing system for radiation protection

International Nuclear Information System (INIS)

Oprea, I.; Oprea, M.; Stoica, M.; Badea, E.; Guta, V.

1999-01-01

The real-time information and processing system has as main task to record, collect, process and transmit the radiation level and weather data, being proposed for radiation protection, environmental monitoring around nuclear facilities and for civil defence. Such a system can offer information in order to provide mapping, data base, modelling and communication and to assess the consequences of nuclear accidents. The system incorporates a number of stationary or mobile radiation monitoring equipment, weather parameter measuring station, a GIS-based information processing center and the communication network, all running on a real-time operating system. It provides the automatic data collection on-line and off-line, remote diagnostic, advanced presentation techniques, including a graphically oriented executive support, which has the ability to respond to an emergency by geographical representation of the hazard zones on the map.The system can be integrated into national or international environmental monitoring systems, being based on local intelligent measuring and transmission units, simultaneous processing and data presentation using a real-time operating system for PC and geographical information system (GIS). Such an integrated system is composed of independent applications operating under the same computer, which is capable to improve the protection of the population and decision makers efforts, updating the remote GIS data base. All information can be managed directly from the map by multilevel data retrieving and presentation by using on-line dynamic evolution of the events, environment information, evacuation optimization, image and voice processing

Real-Time Smart Tools for Processing Spectroscopy Data, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose novel and real-time smart software tools to process spectroscopy data. Material abundance or compositional maps will be generated for rover guidance,...

Methodological Approach Into Researching Traffic Under Extraordinary Security Circumstances

Directory of Open Access Journals (Sweden)

Peter-Anthony Ercegovac

2008-09-01

Full Text Available The complexity of researching traffic under extraordinaryconditions in order to implement a more efficient and functionaltraffic management strategy under both normal and irregularconditions- as well as the grey zone of when the changefrom normal into extraordinary traffic conditions actually occur-provides the researcher with numerous methodologicalproblems.Starting from the viewpoint that the field of traffic scienceneeds an increase into the capacity of research into traffic underextraordinary conditions we have chosen to define withinthis article a specific methodological approach that undertakesa study into the exposure, menace, threat and risk faced by trafficsystems under extraordinary conditions through utilisingmethods utilised by the military that allow for the possible resolutionof such problems through compatible testing of both simulatedand real life conditions that such systems may face.In searching for possible applicable solutions to such demandingparametres we believe that the use of concrete informationin real time and real space in order to bring about amore efficient functioning of traffic under extraordinary conditionscan be achieved through the use of the analytical capacityof traffic systems information gathering attained through theusage of Uninhabited Flying Vehicles (UFVs in monitoringroad, rail and maritime traffic and transport.

Hardware Approach for Real Time Machine Stereo Vision

Directory of Open Access Journals (Sweden)

Michael Tornow

2006-02-01

Full Text Available Image processing is an effective tool for the analysis of optical sensor information for driver assistance systems and controlling of autonomous robots. Algorithms for image processing are often very complex and costly in terms of computation. In robotics and driver assistance systems, real-time processing is necessary. Signal processing algorithms must often be drastically modified so they can be implemented in the hardware. This task is especially difficult for continuous real-time processing at high speeds. This article describes a hardware-software co-design for a multi-object position sensor based on a stereophotogrammetric measuring method. In order to cover a large measuring area, an optimized algorithm based on an image pyramid is implemented in an FPGA as a parallel hardware solution for depth map calculation. Object recognition and tracking are then executed in real-time in a processor with help of software. For this task a statistical cluster method is used. Stabilization of the tracking is realized through use of a Kalman filter. Keywords: stereophotogrammetry, hardware-software co-design, FPGA, 3-d image analysis, real-time, clustering and tracking.

Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

Science.gov (United States)

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2018-06-01

Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

Long-range correlation analysis of urban traffic data

International Nuclear Information System (INIS)

Peng, Sheng; Jun-Feng, Wang; Shu-Long, Zhao; Tie-Qiao, Tang

2010-01-01

This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discusses the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by the obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions (vehicles with special numbered plates only run in a special workday) enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation. (general)

Simulation of three lanes one-way freeway in low visibility weather by possible traffic accidents

Science.gov (United States)

Pang, Ming-bao; Zheng, Sha-sha; Cai, Zhang-hui

2015-09-01

The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume's enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.

A Tree Based Broadcast Scheme for (m, k-firm Real-Time Stream in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

HoSung Park

2017-11-01

Full Text Available Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new (m, k-firm-based Real-time Broadcast Protocol (FRBP by constructing a broadcast tree to satisfy the (m, k-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured (m, k-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.

Data-Link and Surface Map Traffic Intent Displays for NextGen 4DT and Equivalent Visual Surface Operations

Science.gov (United States)

Shelton, Kevin J.; Prinzel, Lawrence J., III; Arthur, Jarvis J., III; Jones, Deise R.; Allamandola, Angela S.; Bailey, Randall E.

2009-01-01

By 2025, U.S. air traffic is predicted to increase 3-fold and may strain the current air traffic management system, which may not be able to accommodate this growth. In response to this challenge, a consortium of industry, academia and government agencies have proposed a revolutionary new concept for U.S. aviation operations, termed the Next Generation Air Transportation System or "NextGen". Many key capabilities are being identified to enable NextGen, including the concept of "net-centric" operations whereby each aircraft and air services provider shares information to allow real-time adaptability to ever-changing factors such as weather, traffic, flight trajectories, and security. Data-link is likely to be the primary source of communication in NextGen. Because NextGen represents a radically different approach to air traffic management and requires a dramatic shift in the tasks, roles, and responsibilities for the flight deck, there are numerous research issues and challenges that must be overcome to ensure a safe, sustainable air transportation system. Flight deck display and crew-vehicle interaction concepts are being developed that proactively investigate and overcome potential technology and safety barriers that might otherwise constrain the full realization of NextGen.

Rerouting algorithms solving the air traffic congestion

Science.gov (United States)

Adacher, Ludovica; Flamini, Marta; Romano, Elpidio

2017-06-01

Congestion in the air traffic network is a problem with an increasing relevance for airlines costs as well as airspace safety. One of the major issue is the limited operative capacity of the air network. In this work an Autonomous Agent approach is proposed to solve in real time the problem of air traffic congestion. The air traffic infrastructures are modeled with a graph and are considered partitioned in different sectors. Each sector has its own decision agent dealing with the air traffic control involved in it. Each agent sector imposes a real time aircraft scheduling to respect both delay and capacity constrains. When a congestion is predicted, a new aircraft scheduling is computed. Congestion is solved when the capacity constrains are satisfied once again. This can be done by delaying on ground aircraft or/and rerouting aircraft and/or postponing the congestion. We have tested two different algorithms that calculate K feasible paths for each aircraft involved in the congestion. Some results are reported on North Italian air space.

Traffic Flow Wide-Area Surveillance system

Energy Technology Data Exchange (ETDEWEB)

Allgood, G.O.; Ferrell, R.K.; Kercel, S.W.; Abston, R.A.

1994-09-01

Traffic management can be thought of as a stochastic queuing process where the serving time at one of its control points is dynamically linked to the global traffic pattern, which is, in turn, dynamically linked to the control point. For this closed-loop system to be effective, the traffic management system must sense and interpret a large spatial projection of data originating from multiple sensor suites. This concept is the basis for the development of a Traffic Flow Wide-Area Surveillance (TFWAS) system. This paper presents the results of a study by Oak Ridge National Laboratory to define the operational specifications and characteristics, to determine the constraints, and to examine the state of technology of a TFWAS system in terms of traffic management and control. In doing so, the functions and attributes of a TFWAS system are mapped into an operational structure consistent with the Intelligent Vehicle Highway System (IVHS) concept and the existing highway infrastructure. This mapping includes identifying candidate sensor suites and establishing criteria, requirements, and performance measures by which these systems can be graded in their ability and practicality to meet the operational requirements of a TFWAS system. In light of this, issues such as system integration, applicable technologies, impact on traffic management and control, and public acceptance are addressed.

Traffic flow wide-area surveillance system

Science.gov (United States)

Allgood, Glenn O.; Ferrell, Regina K.; Kercel, Stephen W.; Abston, Ruth A.

1995-01-01

Traffic management can be thought of as a stochastic queuing process where the serving time at one of its control points is dynamically linked to the global traffic pattern, which is, in turn, dynamically linked to the control point. For this closed-loop system to be effective, the traffic management system must sense and interpret a large spatial projection of data originating from multiple sensor suites. This concept is the basis for the development of a traffic flow wide-area surveillance (TFWAS) system. This paper presents the results of a study by Oak Ridge National Laboratory to define the operational specifications and characteristics, to determine the constraints, and to examine the state of technology of a TFWAS system in terms of traffic management and control. In doing so, the functions and attributes of a TFWAS system are mapped into an operational structure consistent with the Intelligent Vehicle Highway System (IVHS) concept and the existing highway infrastructure. This mapping includes identifying candidate sensor suites and establishing criteria, requirements, and performance measures by which these systems can be graded in their ability and practicality to meet the operational requirements of a TFWAS system. In light of this, issues such as system integration, applicable technologies, impact on traffic management and control, and public acceptance are addressed.

Traffic Command Gesture Recognition for Virtual Urban Scenes Based on a Spatiotemporal Convolution Neural Network

Directory of Open Access Journals (Sweden)

Chunyong Ma

2018-01-01

Full Text Available Intelligent recognition of traffic police command gestures increases authenticity and interactivity in virtual urban scenes. To actualize real-time traffic gesture recognition, a novel spatiotemporal convolution neural network (ST-CNN model is presented. We utilized Kinect 2.0 to construct a traffic police command gesture skeleton (TPCGS dataset collected from 10 volunteers. Subsequently, convolution operations on the locational change of each skeletal point were performed to extract temporal features, analyze the relative positions of skeletal points, and extract spatial features. After temporal and spatial features based on the three-dimensional positional information of traffic police skeleton points were extracted, the ST-CNN model classified positional information into eight types of Chinese traffic police gestures. The test accuracy of the ST-CNN model was 96.67%. In addition, a virtual urban traffic scene in which real-time command tests were carried out was set up, and a real-time test accuracy rate of 93.0% was achieved. The proposed ST-CNN model ensured a high level of accuracy and robustness. The ST-CNN model recognized traffic command gestures, and such recognition was found to control vehicles in virtual traffic environments, which enriches the interactive mode of the virtual city scene. Traffic command gesture recognition contributes to smart city construction.

DRAM selection and configuration for real-time mobile systems

NARCIS (Netherlands)

Gomony, M.D.; Weis, C.; Akesson, K.B.; Wehn, N.; Goossens, K.G.W.

2012-01-01

The performance and power consumption of mobile DRAMs (LPDDRs) depend on the configuration of system-level parameters, such as operating frequency, interface width, request size, and memory map. In mobile systems running both realtime and non-real-time applications, the memory configuration must

Real-time global illumination on mobile device

Science.gov (United States)

Ahn, Minsu; Ha, Inwoo; Lee, Hyong-Euk; Kim, James D. K.

2014-02-01

We propose a novel method for real-time global illumination on mobile devices. Our approach is based on instant radiosity, which uses a sequence of virtual point lights in order to represent the e ect of indirect illumination. Our rendering process consists of three stages. With the primary light, the rst stage generates a local illumination with the shadow map on GPU The second stage of the global illumination uses the re ective shadow map on GPU and generates the sequence of virtual point lights on CPU. Finally, we use the splatting method of Dachsbacher et al 1 and add the indirect illumination to the local illumination on GPU. With the limited computing resources in mobile devices, a small number of virtual point lights are allowed for real-time rendering. Our approach uses the multi-resolution sampling method with 3D geometry and attributes simultaneously and reduce the total number of virtual point lights. We also use the hybrid strategy, which collaboratively combines the CPUs and GPUs available in a mobile SoC due to the limited computing resources in mobile devices. Experimental results demonstrate the global illumination performance of the proposed method.

Real Time Revisited

Science.gov (United States)

Allen, Phillip G.

1985-12-01

The call for abolishing photo reconnaissance in favor of real time is once more being heard. Ten years ago the same cries were being heard with the introduction of the Charge Coupled Device (CCD). The real time system problems that existed then and stopped real time proliferation have not been solved. The lack of an organized program by either DoD or industry has hampered any efforts to solve the problems, and as such, very little has happened in real time in the last ten years. Real time is not a replacement for photo, just as photo is not a replacement for infra-red or radar. Operational real time sensors can be designed only after their role has been defined and improvements made to the weak links in the system. Plodding ahead on a real time reconnaissance suite without benefit of evaluation of utility will allow this same paper to be used ten years from now.

Towards Scalable Distributed Framework for Urban Congestion Traffic Patterns Warehousing

Directory of Open Access Journals (Sweden)

A. Boulmakoul

2015-01-01

Full Text Available We put forward architecture of a framework for integration of data from moving objects related to urban transportation network. Most of this research refers to the GPS outdoor geolocation technology and uses distributed cloud infrastructure with big data NoSQL database. A network of intelligent mobile sensors, distributed on urban network, produces congestion traffic patterns. Congestion predictions are based on extended simulation model. This model provides traffic indicators calculations, which fuse with the GPS data for allowing estimation of traffic states across the whole network. The discovery process of congestion patterns uses semantic trajectories metamodel given in our previous works. The challenge of the proposed solution is to store patterns of traffic, which aims to ensure the surveillance and intelligent real-time control network to reduce congestion and avoid its consequences. The fusion of real-time data from GPS-enabled smartphones integrated with those provided by existing traffic systems improves traffic congestion knowledge, as well as generating new information for a soft operational control and providing intelligent added value for transportation systems deployment.

Transferability and robustness of real-time freeway crash risk assessment.

Science.gov (United States)

Shew, Cameron; Pande, Anurag; Nuworsoo, Cornelius

2013-09-01

This study examines the data from single loop detectors on northbound (NB) US-101 in San Jose, California to estimate real-time crash risk assessment models. The classification tree and neural network based crash risk assessment models developed with data from NB US-101 are applied to data from the same freeway, as well as to the data from nearby segments of the SB US-101, NB I-880, and SB I-880 corridors. The performance of crash risk assessment models on these nearby segments is the focus of this research. The model applications show that it is in fact possible to use the same model for multiple freeways, as the underlying relationships between traffic data and crash risk remain similar. The framework provided here may be helpful to authorities for freeway segments with newly installed traffic surveillance apparatuses, since the real-time crash risk assessment models from nearby freeways with existing infrastructure would be able to provide a reasonable estimate of crash risk. The robustness of the model output is also assessed by location, time of day, and day of week. The analysis shows that on some locations the models may require further learning due to higher than expected false positive (e.g., the I-680/I-280 interchange on US-101 NB) or false negative rates. The approach for post-processing the results from the model provides ideas to refine the model prior to or during the implementation. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Road Traffic Congestion Management Based on a Search-Allocation Approach

Directory of Open Access Journals (Sweden)

Raiyn Jamal

2017-03-01

Full Text Available This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA. An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT technologies.

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

Science.gov (United States)

Leimkuhler, Thomas; Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2018-06-01

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

Estimation of traffic recovery time for different flow regimes on freeways.

Science.gov (United States)

2008-06-01

This study attempts to estimate post-incident traffic recovery time along a freeway using Monte Carlo simulation techniques. It has been found that there is a linear relationship between post-incident traffic recovery time, and incident time and traf...

Real-time bicycle detection at signalized intersections using thermal imaging technology

Science.gov (United States)

Collaert, Robin

2013-02-01

More and more governments and authorities around the world are promoting the use of bicycles in cities, as this is healthy for the bicyclist and improves the quality of life in general. Safety and efficiency of bicyclists has become a major focus. To achieve this, there is a need for a smarter approach towards the control of signalized intersections. Various traditional detection technologies, such as video, microwave radar and electromagnetic loops, can be used to detect vehicles at signalized intersections, but none of these can consistently separate bikes from other traffic, day and night and in various weather conditions. As bikes should get a higher priority and also require longer green time to safely cross the signalized intersection, traffic managers are looking for alternative detection systems that can make the distinction between bicycles and other vehicles near the stop bar. In this paper, the drawbacks of a video-based approach are presented, next to the benefits of a thermal-video-based approach for vehicle presence detection with separation of bicycles. Also, the specific technical challenges are highlighted in developing a system that combines thermal image capturing, image processing and output triggering to the traffic light controller in near real-time and in a single housing.

Hydrometeorological aspects of the Real-Time Ultrafinescale Forecast Support during the Special Observing Period of the MAP*

Directory of Open Access Journals (Sweden)

R. Benoit

2003-01-01

Full Text Available During the Special Observation Period (SOP, 7 September–15 November, 1999 of the Mesoscale Alpine Programme (MAP, the Canadian Mesoscale Compressible Community Model (MC2 was run in real time at a horizontal resolution of 3 km on a computational domain of 350☓300☓50 grid points, covering the whole of the Alpine region. The WATFLOOD model was passively coupled to the MC2; the former is an integrated set of computer programs to forecast flood flows, using all available data, for catchments with response times ranging from one hour to several weeks. The unique aspect of this contribution is the operational application of numerical weather prediction data to forecast flows over a very large, multinational domain. An overview of the system performance from the hydrometeorological aspect is presented, mostly for the real-time results, but also from subsequent analyses. A streamflow validation of the precipitation is included for large basins covering upper parts of the Rhine and the Rhone, and parts of the Po and of the Danube. In general, the MC2/WATFLOOD model underestimated the total runoff because of the under-prediction of precipitation by MC2 during the MAP SOP. After the field experiment, a coding error in the cloud microphysics scheme of MC2 explains this underestimation to a large extent. A sensitivity study revealed that the simulated flows reproduce the major features of the observed flow record for most of the flow stations. The experiment was considered successful because two out of three possible flood events in the Swiss-Italian border region were predicted correctly by data from the numerical weather models linked to the hydrological model and no flow events were missed. This study has demonstrated that a flow forecast from a coupled atmospheric-hydrological model can serve as a useful first alert and quantitative forecast. Keywords: mesoscale atmospheric model, hydrological model, flood forecasting, Alps

Schedulability-Driven Partitioning and Mapping for Multi-Cluster Real-Time Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2004-01-01

We present an approach to partitioning and mapping for multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. We have proposed a schedulability analysis for such systems, including a worst-case queuing delay analysis for the gateways...

Automatic, time-interval traffic counts for recreation area management planning

Science.gov (United States)

D. L. Erickson; C. J. Liu; H. K. Cordell

1980-01-01

Automatic, time-interval recorders were used to count directional vehicular traffic on a multiple entry/exit road network in the Red River Gorge Geological Area, Daniel Boone National Forest. Hourly counts of entering and exiting traffic differed according to recorder location, but an aggregated distribution showed a delayed peak in exiting traffic thought to be...

CytoViz: an artistic mapping of network measurements as living organisms in a VR application

Science.gov (United States)

López Silva, Brenda A.; Renambot, Luc

2007-02-01

CytoViz is an artistic, real-time information visualization driven by statistical information gathered during gigabit network transfers to the Scalable Adaptive Graphical Environment (SAGE) at various events. Data streams are mapped to cellular organisms defining their structure and behavior as autonomous agents. Network bandwidth drives the growth of each entity and the latency defines its physics-based independent movements. The collection of entity is bound within the 3D representation of the local venue. This visual and animated metaphor allows the public to experience the complexity of high-speed network streams that are used in the scientific community. Moreover, CytoViz displays the presence of discoverable Bluetooth devices carried by nearby persons. The concept is to generate an event-specific, real-time visualization that creates informational 3D patterns based on actual local presence. The observed Bluetooth traffic is put in opposition of the wide-area networking traffic by overlaying 2D animations on top of the 3D world. Each device is mapped to an animation fading over time while displaying the name of the detected device and its unique physical address. CytoViz was publicly presented at two major international conferences in 2005 (iGrid2005 in San Diego, CA and SC05 in Seattle, WA).

Synchronized 2D/3D optical mapping for interactive exploration and real-time visualization of multi-function neurological images.

Science.gov (United States)

Zhang, Qi; Alexander, Murray; Ryner, Lawrence

2013-01-01

Efficient software with the ability to display multiple neurological image datasets simultaneously with full real-time interactivity is critical for brain disease diagnosis and image-guided planning. In this paper, we describe the creation and function of a new comprehensive software platform that integrates novel algorithms and functions for multiple medical image visualization, processing, and manipulation. We implement an opacity-adjustment algorithm to build 2D lookup tables for multiple slice image display and fusion, which achieves a better visual result than those of using VTK-based methods. We also develop a new real-time 2D and 3D data synchronization scheme for multi-function MR volume and slice image optical mapping and rendering simultaneously through using the same adjustment operation. All these methodologies are integrated into our software framework to provide users with an efficient tool for flexibly, intuitively, and rapidly exploring and analyzing the functional and anatomical MR neurological data. Finally, we validate our new techniques and software platform with visual analysis and task-specific user studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

Science.gov (United States)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

Improved process control through real-time measurement of mineral content

Energy Technology Data Exchange (ETDEWEB)

Turler, Daniel; Karaca, Murat; Davis, William B.; Giauque, Robert D.; Hopkins, Deborah

2001-11-02

In a highly collaborative research and development project with mining and university partners, sensors and data-analysis tools are being developed for rock-mass characterization and real-time measurement of mineral content. Determining mineralogy prior to mucking in an open-pit mine is important for routing the material to the appropriate processing stream. A possible alternative to lab assay of dust and cuttings obtained from drill holes is continuous on-line sampling and real-time x-ray fluorescence (XRF) spectroscopy. Results presented demonstrate that statistical analyses combined with XRF data can be employed to identify minerals and, possibly, different rock types. The objective is to create a detailed three-dimensional mineralogical map in real time that would improve downstream process efficiency.

Validation of a multi-objective, predictive urban traffic model

NARCIS (Netherlands)

Wilmink, I.R.; Haak, P. van den; Woldeab, Z.; Vreeswijk, J.

2013-01-01

This paper describes the results of the verification and validation of the ecoStrategic Model, which was developed, implemented and tested in the eCoMove project. The model uses real-time and historical traffic information to determine the current, predicted and desired state of traffic in a

VOLUNTARY NOISE MAPPING FOR SMART CITY

Directory of Open Access Journals (Sweden)

V. Poslončec-Petrić

2016-09-01

Full Text Available One of the main concept objectives of smart cities is to create a quality living environment that is long-term sustainable and economically justified. In that context, modern cities are aware of the exposure to various forms of physical and non-physical pollution that needs to be remediated, eliminated or reduced. To achieve that it is necessary to quality determine the sources and reasons of each pollution. The most prominent examples of physical pollution that affects the quality of life of citizens in cities are light and noise pollution. Noise pollution or noise, is mostly the consequence of road and rail traffic in cities and it directly affects the health of citizens. Traffic control, reduction of peak congestion, dispersion and traffic redirection or building protective barriers, are ways that cities use to reduce the amount of noise or its effects. To make these measures efficient it is necessary to obtain the information related to the level of noise in certain areas, streets, cities. To achieve this, smart cities use noise mapping. The city of Zagreb since 2012, participates in the i-SCOPE project (interoperable Smart City services trough Open Platform for urban Ecosystems. i-SCOPE delivers an open platform on top of which it develops, three "smart city" services: optimization of energy consumption through a service for accurate assessment of solar energy potential and energy loss at building level, environmental monitoring through a real-time environmental noise mapping service leveraging citizen's involvement will who act as distributed sensors city-wide measuring noise levels through an application on their mobile phones and improved inclusion and personal mobility of aging and diversely able citizens through an accurate personal routing service. The students of Faculty of Geodesy University of Zagreb, who enrolled in the course Thematic Cartography, were actively involved in the voluntary data acquisition in order to monitor the

Voluntary Noise Mapping for Smart City

Science.gov (United States)

Poslončec-Petrić, V.; Vuković, V.; Frangeš, S.; Bačić, Ž.

2016-09-01

One of the main concept objectives of smart cities is to create a quality living environment that is long-term sustainable and economically justified. In that context, modern cities are aware of the exposure to various forms of physical and non-physical pollution that needs to be remediated, eliminated or reduced. To achieve that it is necessary to quality determine the sources and reasons of each pollution. The most prominent examples of physical pollution that affects the quality of life of citizens in cities are light and noise pollution. Noise pollution or noise, is mostly the consequence of road and rail traffic in cities and it directly affects the health of citizens. Traffic control, reduction of peak congestion, dispersion and traffic redirection or building protective barriers, are ways that cities use to reduce the amount of noise or its effects. To make these measures efficient it is necessary to obtain the information related to the level of noise in certain areas, streets, cities. To achieve this, smart cities use noise mapping. The city of Zagreb since 2012, participates in the i-SCOPE project (interoperable Smart City services trough Open Platform for urban Ecosystems). i-SCOPE delivers an open platform on top of which it develops, three "smart city" services: optimization of energy consumption through a service for accurate assessment of solar energy potential and energy loss at building level, environmental monitoring through a real-time environmental noise mapping service leveraging citizen's involvement will who act as distributed sensors city-wide measuring noise levels through an application on their mobile phones and improved inclusion and personal mobility of aging and diversely able citizens through an accurate personal routing service. The students of Faculty of Geodesy University of Zagreb, who enrolled in the course Thematic Cartography, were actively involved in the voluntary data acquisition in order to monitor the noise in real time

Online Traffic Condition Evaluation Method for Connected Vehicles Based on Multisource Data Fusion

Directory of Open Access Journals (Sweden)

Pang-wei Wang

2017-01-01

Full Text Available With the development of connected vehicle (CV and Vehicle to X (V2X communication, more traffic data is being collected from the road network. In order to predict future traffic condition from connected vehicles’ data in real-time, we present an online traffic condition evaluation model utilizing V2X communication. This model employs the Analytic Hierarchy Process (AHP and the multilevel fuzzy set theory to fuse multiple sources of information for prediction. First, the contemporary vehicle data from the On Board Diagnostic (OBD is fused with the static road data in the Road Side Unit (RSU. Then, the real-time traffic evaluation scores are calculated using the variable membership model. The real data collected by OBU in field test demonstrates the feasibility of the evaluation model. Compared with traditional evaluation systems, the proposed model can handle more types of data but demands less data transfer.

Real-time control strategy to maximize hybrid electric vehicle powertrain efficiency

International Nuclear Information System (INIS)

Shabbir, Wassif; Evangelou, Simos A.

2014-01-01

Highlights: • An off-line local control is proposed for real-time HEV energy management. • Powertrain efficiencies are studied to produce a unified objective function. • Penalty function is designed to ensure charge sustaining operation. • Implementation by storing optimal power share in a two-dimensional control map. • Proposed control improved fuel economy by up to 20% compared to conventional control. - Abstract: The proposed supervisory control system (SCS) uses a control map to maximize the powertrain efficiency of a hybrid electric vehicle (HEV) in real-time. The paper presents the methodology and structure of the control, including a novel, comprehensive and unified expression for the overall powertrain efficiency that considers the engine-generator set and the battery in depth as well as the power electronics. A control map is then produced with instructions for the optimal power share between the engine branch and battery branch of the vehicle such that the powertrain efficiency is maximized. This map is computed off-line and can thereafter be operated in real-time at very low computational cost. A charge sustaining factor is also developed and introduced to ensure the SCS operates the vehicle within desired SOC bounds. This SCS is then tested and benchmarked against two conventional control strategies in a high-fidelity vehicle model, representing a series HEV. Extensive simulation results are presented for repeated cycles of a diverse range of standard driving cycles, showing significant improvements in fuel economy (up to 20%) and less aggressive use of the battery

A Novel Real-Time Reference Key Frame Scan Matching Method

Directory of Open Access Journals (Sweden)

Haytham Mohamed

2017-05-01

Full Text Available Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF. RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Real-time monitoring of emissions with traffic data, simulation and air quality measurements

NARCIS (Netherlands)

Klunder, G.A.; Wilmink, I.R.

2009-01-01

This paper investigates the possibility to decide when to apply a (dynamic) traffic management measure to improve the air quality or reduce CO2 emissions, based on a limited set of (measured) data. It is expected that a combination of monitoring and modeling is needed for reliable air quality

Real-world emission factors of fine and ultrafine aerosol particles for different traffic situations in Switzerland.

Science.gov (United States)

Imhof, David; Weingartner, Ernest; Ordónez, Carlos; Gehrig, Robert; Hill, Matz; Buchmann, Brigitte; Baltensperger, Urs

2005-11-01

Extended field measurements of particle number (size distribution of particle diameters, D, in the range between 18 nm and 10 microm), surface area concentrations, and PM1 and PM10 mass concentrations were performed in Switzerland to determine traffic emissions using a comprehensive set of instruments. Measurements took place at roads with representative traffic regimes: at the kerbside of a motorway (120 km h(-1)), a highway (80-100 km h(-1)), and in an urban area with stop-and-go traffic (0-50 km h(-1)) regulated by light signals. Mean diurnal variations showed that the highest pollutant concentrations were during the morning rush hours, especially of the number density in the nanoparticle size range (D real-life" emission factors were derived using NOx concentrations to calculate dilution factors. Particle number and volume emission factors of different size ranges (18-50 nm, 18-100 nm, and 18-300 nm) were derived for the total vehicle fleet and separated into a light-duty (LDV) and a heavy-duty vehicle (HDV) contribution. The total particle number emissions per vehicle were found to be about 11.7-13.5 x 10(14) particles km(-1) for constant speed (80-120 km h(-1) and 3.9 x 10(14) particles km(-1) for urban driving conditions. LDVs showed higher emission factors at constant high speed than under urban disturbed traffic flow. In contrast, HDVs emitted more air pollutants during deceleration and acceleration processes in stop-and-go traffic than with constant speed of about 80 km h(-1). On average, one HDV emits a 10-30 times higher amount of particulate air pollutants (in terms of both number and volume) than one LDV.

Real-Time Incompressible Fluid Simulation on the GPU

Directory of Open Access Journals (Sweden)

Xiao Nie

2015-01-01

Full Text Available We present a parallel framework for simulating incompressible fluids with predictive-corrective incompressible smoothed particle hydrodynamics (PCISPH on the GPU in real time. To this end, we propose an efficient GPU streaming pipeline to map the entire computational task onto the GPU, fully exploiting the massive computational power of state-of-the-art GPUs. In PCISPH-based simulations, neighbor search is the major performance obstacle because this process is performed several times at each time step. To eliminate this bottleneck, an efficient parallel sorting method for this time-consuming step is introduced. Moreover, we discuss several optimization techniques including using fast on-chip shared memory to avoid global memory bandwidth limitations and thus further improve performance on modern GPU hardware. With our framework, the realism of real-time fluid simulation is significantly improved since our method enforces incompressibility constraint which is typically ignored due to efficiency reason in previous GPU-based SPH methods. The performance results illustrate that our approach can efficiently simulate realistic incompressible fluid in real time and results in a speed-up factor of up to 23 on a high-end NVIDIA GPU in comparison to single-threaded CPU-based implementation.

ALGORITHMS FOR TRAFFIC MANAGEMENT IN THE INTELLIGENT TRANSPORT SYSTEMS

Directory of Open Access Journals (Sweden)

Andrey Borisovich Nikolaev

2017-09-01

Full Text Available Traffic jams interfere with the drivers and cost billions of dollars per year and lead to a substantial increase in fuel consumption. In order to avoid such problems the paper describes the algorithms for traffic management in intelligent transportation system, which collects traffic information in real time and is able to detect and manage congestion on the basis of this information. The results show that the proposed algorithms reduce the average travel time, emissions and fuel consumption. In particular, travel time has decreased by about 23%, the average fuel consumption of 9%, and the average emission of 10%.

Dynamic traffic assignment : genetic algorithms approach

Science.gov (United States)

1997-01-01

Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

Timing Analysis of Mixed-Criticality Hard Real-Time Applications Implemented on Distributed Partitioned Architectures

DEFF Research Database (Denmark)

Marinescu, Sorin Ovidiu; Tamas-Selicean, Domitian; Acretoaie, Vlad

In this paper we are interested in the timing analysis of mixed-criticality embedded real-time applications mapped on distributed heterogeneous architectures. Mixedcriticality tasks can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. We...... in partitions using fixedpriority preemptive scheduling. We have extended the stateof- the-art algorithms for schedulability analysis to take into account the partitions. The proposed algorithm has been evaluated using several synthetic and real-life benchmarks....... consider that the separation is provided by partitioning, such that applications run in separate partitions, and each partition is allocated several time slots on a processor. Each partition can have its own scheduling policy. We are interested to determine the worst-case response times of tasks scheduled...

Spectral Analysis of Traffic Functions in Urban Areas

Directory of Open Access Journals (Sweden)

Florin Nemtanu

2015-12-01

Full Text Available The paper is focused on the Fourier transform application in urban traffic analysis and the use of said transform in traffic decomposition. The traffic function is defined as traffic flow generated by different categories of traffic participants. A Fourier analysis was elaborated in terms of identifying the main traffic function components, called traffic sub-functions. This paper presents the results of the method being applied in a real case situation, that is, an intersection in the city of Bucharest where the effect of a bus line was analysed. The analysis was done using different time scales, while three different traffic functions were defined to demonstrate the theoretical effect of the proposed method of analysis. An extension of the method is proposed to be applied in urban areas, especially in the areas covered by predictive traffic control.

Real-Time Generic Face Tracking in the Wild with CUDA

NARCIS (Netherlands)

Cheng, Shiyang; Asthana, Akshay; Asthana, Ashish; Zafeiriou, Stefanos; Shen, Jie; Pantic, Maja

We present a robust real-time face tracking system based on the Constrained Local Models framework by adopting the novel regression-based Discriminative Response Map Fitting (DRMF) method. By exploiting the algorithm's potential parallelism, we present a hybrid CPU-GPU implementation capable of

Adaptive traffic signal control with actor-critic methods in a real-world traffic network with different traffic disruption events

NARCIS (Netherlands)

Aslani, Mohammad; Mesgari, Mohammad Saadi; Wiering, Marco

2017-01-01

The transportation demand is rapidly growing in metropolises, resulting in chronic traffic con-gestions in dense downtown areas. Adaptive traffic signal control as the principle part of in-telligent transportation systems has a primary role to effectively reduce traffic congestion by making a

Evaluation of Environmental Impact of Biodiesel Vehicles in Real Traffic Conditions

Energy Technology Data Exchange (ETDEWEB)

Sato, Susumu; Mizushima, Norifumi [National Traffic Safety and Environment Laboratory (NTSEL) (Japan); Saito, Akira; Takada, Yutaka [Organization for the Promotion of Low Emission Vehicles (LEVO)(Japan

2012-01-15

This report focuses on the comparison of the real-world emissions between the case of using diesel oil and BDF (biodiesel fuel) for fuel. For this purpose, the on-road driving tests were made, by applying BDF, with the latest diesel vehicles complying with the latest emission regulations while avoiding any particular modification to them. For measurement, a PEMS (Portable Emission Measurement System) was used. Note that the heavy diesel vehicles complying with the latest emission gas regulations of Japan also meet the heavy vehicle fuel economy regulations introduced by Japan ahead of other countries of the world. Since application of BDF presents problems not only for the emission gas, but also has non-negligible influence on the fuel economy, the survey was also made for the real-world fuel economy. This report has been produced as the final version deliverable from the International Energy Agency’s (IEA’s) Advanced Motor Fuels (AMF) Implementing Agreement (Annex XXXVIII - Evaluation of Environmental Impact of Biodiesel Vehicle in Real Traffic Conditions).

Understanding characteristics in multivariate traffic flow time series from complex network structure

Science.gov (United States)

Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei

2017-07-01

Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.

Remotely Accessed Vehicle Traffic Management System

Science.gov (United States)

Al-Alawi, Raida

2010-06-01

The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.

A Novel Real-Time DDoS Attack Detection Mechanism Based on MDRA Algorithm in Big Data

Directory of Open Access Journals (Sweden)

Bin Jia

2016-01-01

Full Text Available In the wake of the rapid development and wide application of information technology and Internet, our society has come into the information explosion era. Meanwhile, it brings in new and severe challenges to the field of network attack behavior detection due to the explosive growth and high complexity of network traffic. Therefore, an effective and efficient detection mechanism that can detect attack behavior from large scale of network traffic plays an important role. In this paper, we focus on how to distinguish the attack traffic from normal data flows in Big Data and propose a novel real-time DDoS attack detection mechanism based on Multivariate Dimensionality Reduction Analysis (MDRA. In this mechanism, we first reduce the dimensionality of multiple characteristic variables in a network traffic record by Principal Component Analysis (PCA. Then, we analyze the correlation of the lower dimensional variables. Finally, the attack traffic can be differentiated from the normal traffic by MDRA and Mahalanobis distance (MD. Compared with previous research methods, our experimental results show that higher precision rate is achieved and it approximates to 100% in True Negative Rate (TNR for detection; CPU computing time is one-eightieth and memory resource consumption is one-third of the previous detection method based on Multivariate Correlation Analysis (MCA; computing complexity is constant.

A distributed scheduling algorithm for heterogeneous real-time systems

Science.gov (United States)

Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi

1991-01-01

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Real-Time Risk Assessment Framework for Unmanned Aircraft System (UAS) Traffic Management (UTM)

Science.gov (United States)

Ancel, Ersin; Capristan, Francisco M.; Foster, John V.; Condotta, Ryan

2017-01-01

The new Federal Aviation Administration (FAA) Small Unmanned Aircraft rule (Part 107) marks the first national regulations for commercial operation of small unmanned aircraft systems (sUAS) under 55 pounds within the National Airspace System (NAS). Although sUAS flights may not be performed beyond visual line-of-sight or over non- participant structures and people, safety of sUAS operations must still be maintained and tracked at all times. Moreover, future safety-critical operation of sUAS (e.g., for package delivery) are already being conceived and tested. NASA's Unmanned Aircraft System Trac Management (UTM) concept aims to facilitate the safe use of low-altitude airspace for sUAS operations. This paper introduces the UTM Risk Assessment Framework (URAF) which was developed to provide real-time safety evaluation and tracking capability within the UTM concept. The URAF uses Bayesian Belief Networks (BBNs) to propagate off -nominal condition probabilities based on real-time component failure indicators. This information is then used to assess the risk to people on the ground by calculating the potential impact area and the effects of the impact. The visual representation of the expected area of impact and the nominal risk level can assist operators and controllers with dynamic trajectory planning and execution. The URAF was applied to a case study to illustrate the concept.

Vehicle Routing with Traffic Congestion and Drivers' Driving and Working Rules

NARCIS (Netherlands)

Kok, A.L.; Hans, Elias W.; Schutten, Johannes M.J.; Zijm, Willem H.M.

2010-01-01

For the intensively studied vehicle routing problem (VRP), two real-life restrictions have received only minor attention in the VRP-literature: traffic congestion and driving hours regulations. Traffic congestion causes late arrivals at customers and long travel times resulting in large transport

The effects of redundancy and information manipulation on traffic networks

OpenAIRE

Özel, Berk; Ozel, Berk

2014-01-01

Traffic congestion is one of the most frequently encountered problems in real life. It is not only a scientific concern of scholars, but also an inevitable issue for most of the individuals living in urban areas. Since every driver in traffic networks tries to minimize own journey length, and volume of the traffic prevents coordination between individuals, a cooperative behavior will not be provided spontaneously in order to decrease the total cost of the network and the time spent on traffic...

Packets with deadlines a framework for real-time wireless networks

CERN Document Server

Hou, I-Hong

2013-01-01

With the explosive increase in the number of mobile devices and applications, it is anticipated that wireless traffic will increase exponentially in the coming years. Moreover, future wireless networks all carry a wide variety of flows, such as video streaming, online gaming, and VoIP, which have various quality of service (QoS) requirements. Therefore, a new mechanism that can provide satisfactory performance to the complete variety of all kinds of flows, in a coherent and unified framework, is needed.In this book, we introduce a framework for real-time wireless networks. This consists of a m

Automatic traveltime picking using local time-frequency maps

KAUST Repository

Saragiotis, Christos

2011-01-01

The arrival times of distinct and sufficiently concentrated signals can be computed using Fourier transforms. In real seis- mograms, however, signals are far from distinct. We use local time-frequency maps of the seismograms and its frequency derivatives to obtain frequency-dependent (instantaneous) traveltimes. A smooth division is utilized to control the resolution of the instantaneous traveltimes to allow for a trade-off between resolution and stability. We average these traveltimes over the frequency band which is data-dependent. The resulting traveltime attribute is used to isolate different signals in seismic traces. We demonstrate the effectiveness of this automatic method for picking arrivals by applying it on synthetic and real data. © 2011 Society of Exploration Geophysicists.

Hybrid Map-Based Navigation Method for Unmanned Ground Vehicle in Urban Scenario

Directory of Open Access Journals (Sweden)

Huiyan Chen

2013-07-01

Full Text Available To reduce the data size of metric map and map matching computational cost in unmanned ground vehicle self-driving navigation in urban scenarios, a metric-topological hybrid map navigation system is proposed in this paper. According to the different positioning accuracy requirements, urban areas are divided into strong constraint (SC areas, such as roads with lanes, and loose constraint (LC areas, such as intersections and open areas. As direction of the self-driving vehicle is provided by traffic lanes and global waypoints in the road network, a simple topological map is fit for the navigation in the SC areas. While in the LC areas, the navigation of the self-driving vehicle mainly relies on the positioning information. Simultaneous localization and mapping technology is used to provide a detailed metric map in the LC areas, and a window constraint Markov localization algorithm is introduced to achieve accurate position using laser scanner. Furthermore, the real-time performance of the Markov algorithm is enhanced by using a constraint window to restrict the size of the state space. By registering the metric maps into the road network, a hybrid map of the urban scenario can be constructed. Real unmanned vehicle mapping and navigation tests demonstrated the capabilities of the proposed method.

Ergodicity of Traffic Flow with Constant Penetration Rate for Traffic Monitoring via Floating Vehicle Technique

Science.gov (United States)

Gunawan, Fergyanto E.; Abbas, Bahtiar S.; Atmadja, Wiedjaja; Yoseph Chandra, Fajar; Agung, Alexander AS; Kusnandar, Erwin

2014-03-01

Traffic congestion in Asian megacities has become extremely worse, and any means to lessen the congestion level is urgently needed. Building an efficient mass transportation system is clearly necessary. However, implementing Intelligent Transportation Systems (ITS) have also been demonstrated effective in various advanced countries. Recently, the floating vehicle technique (FVT), an ITS implementation, has become cost effective to provide real-time traffic information with proliferation of the smartphones. Although many publications have discussed various issues related to the technique, none of them elaborates the discrepancy of a single floating car data (FCD) and the associated fleet data. This work addresses the issue based on an analysis of Sugiyama et al's experimental data. The results indicate that there is an optimum averaging time interval such that the estimated velocity by the FVT reasonably representing the traffic velocity.

Multiobjective Traffic Signal Control Model for Intersection Based on Dynamic Turning Movements Estimation

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2014-01-01

Full Text Available The real-time traffic signal control for intersection requires dynamic turning movements as the basic input data. It is impossible to detect dynamic turning movements directly through current traffic surveillance systems, but dynamic origin-destination (O-D estimation can obtain it. However, the combined models of dynamic O-D estimation and real-time traffic signal control are rare in the literature. A framework for the multiobjective traffic signal control model for intersection based on dynamic O-D estimation (MSC-DODE is presented. A state-space model using Kalman filtering is first formulated to estimate the dynamic turning movements; then a revised sequential Kalman filtering algorithm is designed to solve the model, and the root mean square error and mean percentage error are used to evaluate the accuracy of estimated dynamic turning proportions. Furthermore, a multiobjective traffic signal control model is put forward to achieve real-time signal control parameters and evaluation indices. Finally, based on practical survey data, the evaluation indices from MSC-DODE are compared with those from Webster method. The actual and estimated turning movements are further input into MSC-DODE, respectively, and results are also compared. Case studies show that results of MSC-DODE are better than those of Webster method and are very close to unavailable actual values.

Traffic Predictive Control: Case Study and Evaluation

Science.gov (United States)

2017-06-26

This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...

Probabilistic description of traffic flow

International Nuclear Information System (INIS)

Mahnke, R.; Kaupuzs, J.; Lubashevsky, I.

2005-01-01

A stochastic description of traffic flow, called probabilistic traffic flow theory, is developed. The general master equation is applied to relatively simple models to describe the formation and dissolution of traffic congestions. Our approach is mainly based on spatially homogeneous systems like periodically closed circular rings without on- and off-ramps. We consider a stochastic one-step process of growth or shrinkage of a car cluster (jam). As generalization we discuss the coexistence of several car clusters of different sizes. The basic problem is to find a physically motivated ansatz for the transition rates of the attachment and detachment of individual cars to a car cluster consistent with the empirical observations in real traffic. The emphasis is put on the analogy with first-order phase transitions and nucleation phenomena in physical systems like supersaturated vapour. The results are summarized in the flux-density relation, the so-called fundamental diagram of traffic flow, and compared with empirical data. Different regimes of traffic flow are discussed: free flow, congested mode as stop-and-go regime, and heavy viscous traffic. The traffic breakdown is studied based on the master equation as well as the Fokker-Planck approximation to calculate mean first passage times or escape rates. Generalizations are developed to allow for on-ramp effects. The calculated flux-density relation and characteristic breakdown times coincide with empirical data measured on highways. Finally, a brief summary of the stochastic cellular automata approach is given

In situ real-time x-ray reciprocal space mapping during InGaAs/GaAs growth for understanding strain relaxation mechanisms

International Nuclear Information System (INIS)

Sasaki, Takuo; Suzuki, Hidetoshi; Sai, Akihisa; Lee, Jong-Han; Kamiya, Itaru; Ohshita, Yoshio; Yamaguchi, Masafumi; Takahashi, Masamitsu; Fujikawa, Seiji; Arafune, Koji

2009-01-01

In situ real-time X-ray diffraction measurements during In 0.12 Ga 0.88 As/GaAs(001) epitaxial growth are performed for the first time to understand the strain relaxation mechanisms in a lattice-mismatched system. The high resolution reciprocal space maps of 004 diffraction obtained at interval of 6.2 nm thickness enable transient behavior of residual strain and crystal quality to be observed simultaneously as a function of InGaAs film thickness. From the evolution of these data, five thickness ranges with different relaxation processes and these transition points are determined quantitatively, and the dominant dislocation behavior in each phase is deduced. (author)

A time-based concept for terminal-area traffic management

Science.gov (United States)

Erzberger, Heinz; Tobias, Leonard

1986-01-01

An automated air-traffic-management concept that has the potential for significantly increasing the efficiency of traffic flows in high-density terminal areas is discussed. The concept's implementation depends on techniques for controlling the landing time of all aircraft entering the terminal area, both those that are equipped with on-board four-dimensional (4D) guidance systems as well as those aircraft types that are conventionally equipped. The two major ground-based elements of the system are a scheduler which assigns conflict-free landing times and a profile descent advisor. Landing time provided by the scheduler is uplinked to equipped aircraft and translated into the appropriate 4D trajectory by the-board flight-management system. The controller issues descent advisories to unequipped aircraft to help them achieve the assigned landing times. Air traffic control simulations have established that the concept provides an efficient method for controlling various mixes of 4D-equipped and unequipped, as well as low- and high-performance, aircraft. Piloted simulations of profiles flown with the aid of advisories have verified the ability to meet specified descent times with prescribed accuracy.

Using Probe Vehicle Data for Automatic Extraction of Road Traffic Parameters

Directory of Open Access Journals (Sweden)

Roman Popescu Maria Alexandra

2016-12-01

Full Text Available Through this paper the author aims to study and find solutions for automatic detection of traffic light position and for automatic calculation of the waiting time at traffic light. The first objective serves mainly the road transportation field, mainly because it removes the need for collaboration with local authorities to establish a national network of traffic lights. The second objective is important not only for companies which are providing navigation solutions, but especially for authorities, institutions, companies operating in road traffic management systems. Real-time dynamic determination of traffic queue length and of waiting time at traffic lights allow the creation of dynamic systems, intelligent and flexible, adapted to actual traffic conditions, and not to generic, theoretical models. Thus, cities can approach the Smart City concept by boosting, efficienting and greening the road transport, promoted in Europe through the Horizon 2020, Smart Cities, Urban Mobility initiative.

Presenting a practical model for governmental political mapping on road traffic injuries in Iran in 2008: a qualitative study.

Science.gov (United States)

Ainy, E; Soori, Hamid; Mahfozphoor, S; Movahedinejad, Aa

2011-10-01

This study was conducted to assess political mapping in relation to road traffic injuries (RTIs) management and prevention to present a practical model for RTIs. A phenomenological qualitative study was developed to identify stakeholders on RTI in Iran in 2008. The designed questions were discussed by systematic discussion with the relevant specialists. After receiving written consent from the main responsible stakeholders, the questionnaire was filled in by trained experts. Themes were determined and content was analysed in each part. Main responsible stakeholders. By comparing other countries' political mappings which were found in the library and by Internet searching, political mapping of RTI in Iran was suggested. Subjects were 26 experts from governmental and non-governmental organizations. The main proposed leading agencies were traffic police and presidency (13% each). Findings showed that only 31% of our political mapping was formed according to the World Health Organization (WHO). In 94% of cases, the involved organizations had unspecified roles; the reason was poor monitoring for RTI in 39% of organizations. Lack of adequate authority and suitable legislation, appropriate laws and tasks definition were 94% and 18%, respectively. The most essential policy to overcome problems was defined as appropriate legislation (21%), and the most frequent type of support needed was mentioned as adequate budgeting (25%). Traffic police can play the leading agency role by government support, with strong leadership, appropriate legislation, defined tasks and adequate budget.

Real-Time Control of an Articulatory-Based Speech Synthesizer for Brain Computer Interfaces.

Directory of Open Access Journals (Sweden)

Florent Bocquelet

2016-11-01

Full Text Available Restoring natural speech in paralyzed and aphasic people could be achieved using a Brain-Computer Interface (BCI controlling a speech synthesizer in real-time. To reach this goal, a prerequisite is to develop a speech synthesizer producing intelligible speech in real-time with a reasonable number of control parameters. We present here an articulatory-based speech synthesizer that can be controlled in real-time for future BCI applications. This synthesizer converts movements of the main speech articulators (tongue, jaw, velum, and lips into intelligible speech. The articulatory-to-acoustic mapping is performed using a deep neural network (DNN trained on electromagnetic articulography (EMA data recorded on a reference speaker synchronously with the produced speech signal. This DNN is then used in both offline and online modes to map the position of sensors glued on different speech articulators into acoustic parameters that are further converted into an audio signal using a vocoder. In offline mode, highly intelligible speech could be obtained as assessed by perceptual evaluation performed by 12 listeners. Then, to anticipate future BCI applications, we further assessed the real-time control of the synthesizer by both the reference speaker and new speakers, in a closed-loop paradigm using EMA data recorded in real time. A short calibration period was used to compensate for differences in sensor positions and articulatory differences between new speakers and the reference speaker. We found that real-time synthesis of vowels and consonants was possible with good intelligibility. In conclusion, these results open to future speech BCI applications using such articulatory-based speech synthesizer.

Trip-timing decisions with traffic incidents

DEFF Research Database (Denmark)

Fosgerau, Mogens; Lindsey, Robin

2013-01-01

This paper analyzes traffic bottleneck congestion when drivers randomly cause incidents that temporarily block the bottleneck. Drivers have general scheduling preferences for time spent at home and at work. They independently choose morning departure times from home to maximize expected utility...... without knowing whether an incident has occurred. The resulting departure time pattern may be compressed or dispersed according to whether or not the bottleneck is fully utilized throughout the departure period on days without incidents. For both the user equilibrium (UE) and the social optimum (SO...

A wireless sensor network for urban traffic characterization and trend monitoring.

Science.gov (United States)

Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A

2015-10-15

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.

Prediction of traffic-related nitrogen oxides concentrations using Structural Time-Series models

Science.gov (United States)

Lawson, Anneka Ruth; Ghosh, Bidisha; Broderick, Brian

2011-09-01

Ambient air quality monitoring, modeling and compliance to the standards set by European Union (EU) directives and World Health Organization (WHO) guidelines are required to ensure the protection of human and environmental health. Congested urban areas are most susceptible to traffic-related air pollution which is the most problematic source of air pollution in Ireland. Long-term continuous real-time monitoring of ambient air quality at such urban centers is essential but often not realistic due to financial and operational constraints. Hence, the development of a resource-conservative ambient air quality monitoring technique is essential to ensure compliance with the threshold values set by the standards. As an intelligent and advanced statistical methodology, a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality model. In STS methodology, the different components of a time-series dataset such as the trend, seasonal, cyclical and calendar variations can be modeled separately. To test the effectiveness of the proposed modeling strategy, average hourly concentrations of nitrogen dioxide and nitrogen oxides from a congested urban arterial in Dublin city center were modeled using STS methodology. The prediction error estimates from the developed air quality model indicate that the STS model can be a useful tool in predicting nitrogen dioxide and nitrogen oxides concentrations in urban areas and will be particularly useful in situations where the information on external variables such as meteorology or traffic volume is not available.

Field Evaluation of Two Geophysical Techniques for Real-Time Mapping of Smouldering Remediation (STAR)

Science.gov (United States)

Trento, L. M.; Tsourlos, P.; McMaster, M.; Liefl, D.; Sims, A.; Dominguez, J. L. G.; Vidumsky, J.; Gerhard, J.

2016-12-01

Self-sustaining Treatment for Active Remediation (STAR) technology destroys non-aqueous phase liquid (NAPL) in situ using principles of smouldering combustion. It involves propagating an exothermic (400-1000C) oxidation reaction outwards from an ignition well. A full-scale STAR system is currently being applied at an industrial site contaminated with coal tar below the water table in New Jersey, USA. STAR is typically tracked using multi-level thermocouples, which are discrete and sparse in space and time. This study evaluates two surface-based geophysical methods - Electrical Resistivity Tomography (ERT) and Self-Potential (SP) - for the ability to map the STAR reaction in real time at the New Jersey site. Both techniques involve placing electrode arrays on the surface and monitoring electrical signals over time (i.e., time-lapse). It is hypothesized that ERT should be able to monitor the resistive dry zone that precedes the reaction front and/or the growing NAPL-depleted zone. SP is expected to be able to detect the potential difference associated with thermal gradients generated by the reaction. Approximately 72 ERT electrodes in a "swiss cross" pattern plus 10 SP electrodes will be emplaced over single STAR treatment cell (six ignition wells). This setup will be employed to monitor both a deep (25 feet) and shallow (8 feet) STAR treatments. The geophysics will be complemented by in situ temperature measurements, continuous gas measurements, and pre- and post-treatment coring. The primary goal of this research is to evaluate the effectiveness of using ERT and SP for STAR under field conditions. The tests will be conducted in August 2016.

The "neuro-mapping locator" software. A real-time intraoperative objective paraesthesia mapping tool to evaluate paraesthesia coverage of the painful zone in patients undergoing spinal cord stimulation lead implantation.

Science.gov (United States)

Guetarni, F; Rigoard, P

2015-03-01

Conventional spinal cord stimulation (SCS) generates paraesthesia, as the efficacy of this technique is based on the relationship between the paraesthesia provided by SCS on the painful zone and an analgesic effect on the stimulated zone. Although this basic postulate is based on clinical evidence, it is clear that this relationship has never been formally demonstrated by scientific studies. There is a need for objective evaluation tools ("transducers") to transpose electrical signals to clinical effects and to guide therapeutic choices. We have developed a software at Poitiers University hospital allowing real-time objective mapping of the paraesthesia generated by SCS lead placement and programming during the implantation procedure itself, on a touch screen interface. The purpose of this article is to describe this intraoperative mapping software, in terms of its concept and technical aspects. The Neuro-Mapping Locator (NML) software is dedicated to patients with failed back surgery syndrome, candidates for SCS lead implantation, to actively participate in the implantation procedure. Real-time geographical localization of the paraesthesia generated by percutaneous or multicolumn surgical SCS lead implanted under awake anaesthesia allows intraoperative lead programming and possibly lead positioning to be modified with the patient's cooperation. Software updates should enable us to refine objectives related to the use of this tool and minimize observational biases. The ultimate goals of NML software should not be limited to optimize one specific device implantation in a patient but also allow to compare instantaneously various stimulation strategies, by characterizing new technical parameters as "coverage efficacy" and "device specificity" on selected subgroups of patients. Another longer-term objective would be to organize these predictive factors into computer science ontologies, which could constitute robust and helpful data for device selection and programming

Evaluation of daily time spent in transportation and traffic-influenced microenvironments by urban Canadians.

Science.gov (United States)

Matz, Carlyn J; Stieb, David M; Egyed, Marika; Brion, Orly; Johnson, Markey

2018-01-01

Exposure to traffic and traffic-related air pollution is associated with a wide array of health effects. Time spent in a vehicle, in active transportation, along roadsides, and in close proximity to traffic can substantially contribute to daily exposure to air pollutants. For this study, we evaluated daily time spent in transportation and traffic-influenced microenvironments by urban Canadians using the Canadian Human Activity Pattern Survey (CHAPS) 2 results. Approximately 4-7% of daily time was spent in on- or near-road locations, mainly associated with being in a vehicle and smaller contributions from active transportation. Indoor microenvironments can be impacted by traffic emissions, especially when located near major roadways. Over 60% of the target population reported living within one block of a roadway with moderate to heavy traffic, which was variable with income level and city, and confirmed based on elevated NO 2 exposure estimated using land use regression. Furthermore, over 55% of the target population ≤ 18 years reported attending a school or daycare in close proximity to moderate to heavy traffic, and little variation was observed based on income or city. The results underline the importance of traffic emissions as a major source of exposure in Canadian urban centers, given the time spent in traffic-influenced microenvironments.

Life Times of Simulated Traffic Jams

Science.gov (United States)

Nagel, Kai

We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations when driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from a traffic jam self-organizes into this state of maximum throughput.

High-speed web attack detection through extracting exemplars from HTTP traffic

KAUST Repository

Wang, Wei

2011-01-01

In this work, we propose an effective method for high-speed web attack detection by extracting exemplars from HTTP traffic before the detection model is built. The smaller set of exemplars keeps valuable information of the original traffic while it significantly reduces the size of the traffic so that the detection remains effective and improves the detection efficiency. The Affinity Propagation (AP) is employed to extract the exemplars from the HTTP traffic. K-Nearest Neighbor(K-NN) and one class Support Vector Machine (SVM) are used for anomaly detection. To facilitate comparison, we also employ information gain to select key attributes (a.k.a. features) from the HTTP traffic for web attack detection. Two large real HTTP traffic are used to validate our methods. The extensive test results show that the AP based exemplar extraction significantly improves the real-time performance of the detection compared to using all the HTTP traffic and achieves a more robust detection performance than information gain based attribute selection for web attack detection. © 2011 ACM.

Efficient implementation of real-time programs under the VAX/VMS operating system

Science.gov (United States)

Johnson, S. C.

1985-01-01

Techniques for writing efficient real-time programs under the VAX/VMS oprating system are presented. Basic operations are presented for executing at real-time priority and for avoiding needlless processing delays. A highly efficient technique for accessing physical devices by mapping to the input/output space and accessing the device registrs directly is described. To illustrate the application of the technique, examples are included of different uses of the technique on three devices in the Langley Avionics Integration Research Lab (AIRLAB): the KW11-K dual programmable real-time clock, the Parallel Communications Link (PCL11-B) communication system, and the Datacom Synchronization Network. Timing data are included to demonstrate the performance improvements realized with these applications of the technique.

Time-resolved measurements with intense ultrashort laser pulses: a 'molecular movie' in real time

International Nuclear Information System (INIS)

Rudenko, A; Ergler, Th; Feuerstein, B; Zrost, K; Schroeter, C D; Moshammer, R; Ullrich, J

2007-01-01

We report on the high-resolution multidimensional real-time mapping of H 2 + and D 2 + nuclear wave packets performed employing time-resolved three-dimensional Coulomb explosion imaging with intense laser pulses. Exploiting a combination of a 'reaction microscope' spectrometer and a pump-probe setup with two intense 6-7 fs laser pulses, we simultaneously visualize both vibrational and rotational motion of the molecule, and obtain a sequence of snapshots of the squared ro-vibrational wave function with time-step resolution of ∼ 0.3 fs, allowing us to reconstruct a real-time movie of the ultrafast molecular motion. We observe fast dephasing, or 'collapse' of the vibrational wave packet and its subsequent revival, as well as signatures of rotational excitation. For D 2 + we resolve also the fractional revivals resulting from the interference between the counter-propagating parts of the wave packet

Real Time Monitor of Grid job executions

International Nuclear Information System (INIS)

Colling, D J; Martyniak, J; McGough, A S; Krenek, A; Sitera, J; Mulac, M; Dvorak, F

2010-01-01

In this paper we describe the architecture and operation of the Real Time Monitor (RTM), developed by the Grid team in the HEP group at Imperial College London. This is arguably the most popular dissemination tool within the EGEE [1] Grid. Having been used, on many occasions including GridFest and LHC inauguration events held at CERN in October 2008. The RTM gathers information from EGEE sites hosting Logging and Bookkeeping (LB) services. Information is cached locally at a dedicated server at Imperial College London and made available for clients to use in near real time. The system consists of three main components: the RTM server, enquirer and an apache Web Server which is queried by clients. The RTM server queries the LB servers at fixed time intervals, collecting job related information and storing this in a local database. Job related data includes not only job state (i.e. Scheduled, Waiting, Running or Done) along with timing information but also other attributes such as Virtual Organization and Computing Element (CE) queue - if known. The job data stored in the RTM database is read by the enquirer every minute and converted to an XML format which is stored on a Web Server. This decouples the RTM server database from the client removing the bottleneck problem caused by many clients simultaneously accessing the database. This information can be visualized through either a 2D or 3D Java based client with live job data either being overlaid on to a 2 dimensional map of the world or rendered in 3 dimensions over a globe map using OpenGL.

Daylight Saving Time Transitions and Road Traffic Accidents

Directory of Open Access Journals (Sweden)

Tuuli Lahti

2010-01-01

Full Text Available Circadian rhythm disruptions may have harmful impacts on health. Circadian rhythm disruptions caused by jet lag compromise the quality and amount of sleep and may lead to a variety of symptoms such as fatigue, headache, and loss of attention and alertness. Even a minor change in time schedule may cause considerable stress for the body. Transitions into and out of daylight saving time alter the social and environmental timing twice a year. According to earlier studies, this change in time-schedule leads to sleep disruption and fragmentation of the circadian rhythm. Since sleep deprivation decreases motivation, attention, and alertness, transitions into and out of daylight saving time may increase the amount of accidents during the following days after the transition. We studied the amount of road traffic accidents one week before and one week after transitions into and out of daylight saving time during years from 1981 to 2006. Our results demonstrated that transitions into and out of daylight saving time did not increase the number of traffic road accidents.

Exposure to lateral collision in signalized intersections with protected left turn under different traffic control strategies.

Science.gov (United States)

Midenet, Sophie; Saunier, Nicolas; Boillot, Florence

2011-11-01

This paper proposes an original definition of the exposure to lateral collision in signalized intersections and discusses the results of a real world experiment. This exposure is defined as the duration of situations where the stream that is given the right-of-way goes through the conflict zone while road users are waiting in the cross-traffic approach. This measure, obtained from video sensors, makes it possible to compare different operating conditions such as different traffic signal strategies. The data from a real world experiment is used, where the adaptive real-time strategy CRONOS (ContRol Of Networks by Optimization of Switchovers) and a time-plan strategy with vehicle-actuated ranges alternately controlled an isolated intersection near Paris. Hourly samples with similar traffic volumes are compared and the exposure to lateral collision is different in various areas of the intersection and various traffic conditions for the two strategies. The total exposure under peak hour traffic conditions drops by roughly 5 min/h with the CRONOS strategy compared to the time-plan strategy, which occurs mostly on entry streams. The results are analyzed through the decomposition of cycles in phase sequences and recommendations are made for traffic control strategies. Copyright © 2011 Elsevier Ltd. All rights reserved.

Toward real-time regional earthquake simulation II: Real-time Online earthquake Simulation (ROS) of Taiwan earthquakes

Science.gov (United States)

Lee, Shiann-Jong; Liu, Qinya; Tromp, Jeroen; Komatitsch, Dimitri; Liang, Wen-Tzong; Huang, Bor-Shouh

2014-06-01

We developed a Real-time Online earthquake Simulation system (ROS) to simulate regional earthquakes in Taiwan. The ROS uses a centroid moment tensor solution of seismic events from a Real-time Moment Tensor monitoring system (RMT), which provides all the point source parameters including the event origin time, hypocentral location, moment magnitude and focal mechanism within 2 min after the occurrence of an earthquake. Then, all of the source parameters are automatically forwarded to the ROS to perform an earthquake simulation, which is based on a spectral-element method (SEM). A new island-wide, high resolution SEM mesh model is developed for the whole Taiwan in this study. We have improved SEM mesh quality by introducing a thin high-resolution mesh layer near the surface to accommodate steep and rapidly varying topography. The mesh for the shallow sedimentary basin is adjusted to reflect its complex geometry and sharp lateral velocity contrasts. The grid resolution at the surface is about 545 m, which is sufficient to resolve topography and tomography data for simulations accurate up to 1.0 Hz. The ROS is also an infrastructural service, making online earthquake simulation feasible. Users can conduct their own earthquake simulation by providing a set of source parameters through the ROS webpage. For visualization, a ShakeMovie and ShakeMap are produced during the simulation. The time needed for one event is roughly 3 min for a 70 s ground motion simulation. The ROS is operated online at the Institute of Earth Sciences, Academia Sinica (http://ros.earth.sinica.edu.tw/). Our long-term goal for the ROS system is to contribute to public earth science outreach and to realize seismic ground motion prediction in real-time.

Analysis and comparison of safety models using average daily, average hourly, and microscopic traffic.

Science.gov (United States)

Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie

2018-02-01

There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-Time Prognostics of a Rotary Valve Actuator

Science.gov (United States)

Daigle, Matthew

2015-01-01

Valves are used in many domains and often have system-critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and prediction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remaining useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.

Integrating GPS, GYRO, vehicle speed sensor, and digital map to provide accurate and real-time position in an intelligent navigation system

Science.gov (United States)

Li, Qingquan; Fang, Zhixiang; Li, Hanwu; Xiao, Hui

2005-10-01

The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. The applications of Global Positioning System (GPS) positioning is more and more popular, especially the intelligent navigation system which relies on GPS and Dead Reckoning technology is developing quickly for future huge market in China. In this paper a practical combined positioning model of GPS/DR/MM is put forward, which integrates GPS, Gyro, Vehicle Speed Sensor (VSS) and digital navigation maps to provide accurate and real-time position for intelligent navigation system. This model is designed for automotive navigation system making use of Kalman filter to improve position and map matching veracity by means of filtering raw GPS and DR signals, and then map-matching technology is used to provide map coordinates for map displaying. In practical examples, for illustrating the validity of the model, several experiments and their results of integrated GPS/DR positioning in intelligent navigation system will be shown for the conclusion that Kalman Filter based GPS/DR integrating position approach is necessary, feasible and efficient for intelligent navigation application. Certainly, this combined positioning model, similar to other model, can not resolve all situation issues. Finally, some suggestions are given for further improving integrated GPS/DR/MM application.

Surface Map Traffic Intent Displays and Net-Centric Data-link Communications for NextGen

Science.gov (United States)

Shelton, Kevin J.; Prinzel, Lawrence J., III; Jones, Denise R.; Allamandola, Angela S.; Arthur, Jarvis J., III; Bailey, Randall E.

2009-01-01

By 2025, U.S. air traffic is predicted to increase three fold and may strain the current air traffic management system, which may not be able to accommodate this growth. In response to this challenge, a revolutionary new concept has been proposed for U.S. aviation operations, termed the Next Generation Air Transportation System or "NextGen". Many key capabilities are being identified to enable NextGen, including the use of data-link communications. Because NextGen represents a radically different approach to air traffic management and requires a dramatic shift in the tasks, roles, and responsibilities for the flight deck, there are numerous research issues and challenges that must be overcome to ensure a safe, sustainable air transportation system. Flight deck display and crew-vehicle interaction concepts are being developed that proactively investigate and overcome potential technology and safety barriers that might otherwise constrain the full realization of NextGen. The paper describes simulation research, conducted at National Aeronautics and Space Administration (NASA) Langley Research Center, examining data-link communications and traffic intent data during envisioned four-dimensional trajectory (4DT)-based and equivalent visual (EV) surface operations. Overall, the results suggest that controller pilot data-link communications (CPDLC) with the use of mandatory pilot read-back of all clearances significantly enhanced situation awareness for 4DT and EV surface operations. The depiction of graphical traffic state and intent information on the surface map display further enhanced off-nominal detection and pilot qualitative reports of safety and awareness.

Autonomic urban traffic optimization using data analytics

OpenAIRE

Garriga Porqueras, Albert

2017-01-01

This work focuses on a smart mobility use case where real-time data analytics on traffic measures is used to improve mobility in the event of a perturbation causing congestion in a local urban area. The data monitored is analysed in order to identify patterns that are used to properly reconfigure traffic lights. The monitoring and data analytics infrastructure is based on a hierarchical distributed architecture that allows placing data analytics processes such as machine learning close to the...

Complex motion in nonlinear-map model of elevators in energy-saving traffic

International Nuclear Information System (INIS)

Nagatani, Takashi

2011-01-01

We have studied the dynamic behavior and dynamic transitions of elevators in a system for reducing energy consumption. We present a nonlinear-map model for the dynamics of M elevators. The motion of elevators depends on the loading parameter and their number M. The dependence of the fixed points on the loading parameter is derived. The dynamic transitions occur at 2(M-1) stages with increasing the value of loading parameter. At the dynamic transition point, the motion of elevators changes from a stable state to an unstable state and vice versa. The elevators display periodic motions with various periods in the unstable state. In the unstable state, the number of riding passengers fluctuates in a complex manner over various trips. - Highlights: → We propose the nonlinear-map model in energy-saving traffic of elevators. → We study the dynamical behavior and dynamical transitions in the system of elevators. → We derive the fixed point of the nonlinear map analytically. → We clarify the dependence of the motion on the loading parameter and the number.

Complex motion in nonlinear-map model of elevators in energy-saving traffic

Energy Technology Data Exchange (ETDEWEB)

Nagatani, Takashi, E-mail: tmtnaga@ipc.shizuoka.ac.j [Department of Mechanical Engineering, Division of Thermal Science, Shizuoka University, Hamamatsu 432-8561 (Japan)

2011-05-16

We have studied the dynamic behavior and dynamic transitions of elevators in a system for reducing energy consumption. We present a nonlinear-map model for the dynamics of M elevators. The motion of elevators depends on the loading parameter and their number M. The dependence of the fixed points on the loading parameter is derived. The dynamic transitions occur at 2(M-1) stages with increasing the value of loading parameter. At the dynamic transition point, the motion of elevators changes from a stable state to an unstable state and vice versa. The elevators display periodic motions with various periods in the unstable state. In the unstable state, the number of riding passengers fluctuates in a complex manner over various trips. - Highlights: We propose the nonlinear-map model in energy-saving traffic of elevators. We study the dynamical behavior and dynamical transitions in the system of elevators. We derive the fixed point of the nonlinear map analytically. We clarify the dependence of the motion on the loading parameter and the number.

Residential exposure to traffic noise and leisure-time sports - A population-based study.

Science.gov (United States)

Roswall, Nina; Ammitzbøll, Gunn; Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Jensen, Steen Solvang; Tjønneland, Anne; Sørensen, Mette

2017-08-01

Traffic levels have been found a significant environmental predictor for physical inactivity. A recent study suggested that traffic noise annoyance was associated with lower physical activity. We investigated associations between modelled residential traffic noise and leisure-time sports. In the Diet, Cancer and Health cohort, we performed cross-sectional analyses using data from the baseline questionnaire (1993-97), and longitudinal analyses of change between baseline and follow-up (2000-02). People reported participation (yes/no) and hours of leisure-time sport, from which we calculated MET hrs/week. Present and historical addresses from 1987 to 2002 were found in national registries, and traffic noise was modelled 1 and 5 years before enrolment, and from baseline to follow-up. Analyses were performed using logistic and linear regression. Traffic noise exposure 5 years before baseline was associated with higher prevalence odds ratio of non-participation in leisure-time sports; significantly for road traffic noise (odds ratio (OR): 1.10; 95% confidence interval (CI): 1.07-1.13) and borderline for railway noise (OR: 1.03; 95% CI: 0.99-1.07), per 10dB. In longitudinal analyses, a 10dB higher road traffic noise was associated with a higher prevalence odds ratio of ceasing (OR: 1.12; 95% CI: 1.07-1.18) and a lower prevalence odds ratio of initiating (OR: 0.92; 95% CI: 0.87-0.96) leisure-time sports. Exposure to railway noise was negatively associated with baseline MET hrs/week, whereas no association was found in longitudinal analyses, or for road traffic noise. The study suggests that long-term exposure to residential road traffic noise is negatively associated with leisure-time sports. Results for railway noise were less consistent. Copyright © 2017 Elsevier GmbH. All rights reserved.

Real-time shadows

CERN Document Server

Eisemann, Elmar; Assarsson, Ulf; Wimmer, Michael

2011-01-01

Important elements of games, movies, and other computer-generated content, shadows are crucial for enhancing realism and providing important visual cues. In recent years, there have been notable improvements in visual quality and speed, making high-quality realistic real-time shadows a reachable goal. Real-Time Shadows is a comprehensive guide to the theory and practice of real-time shadow techniques. It covers a large variety of different effects, including hard, soft, volumetric, and semi-transparent shadows.The book explains the basics as well as many advanced aspects related to the domain

Dependable Real-Time Systems

Science.gov (United States)

1991-09-30

0196 or 413 545-0720 PI E-mail Address: krithi@nirvan.cs.umass.edu, stankovic(ocs.umass.edu Grant or Contract Title: Dependable Real - Time Systems Grant...Dependable Real - Time Systems " Grant or Contract Number: N00014-85-k-0398 L " Reporting Period: 1 Oct 87 - 30 Sep 91 , 2. Summary of Accomplishments ’ 2.1 Our...in developing a sound approach to scheduling tasks in complex real - time systems , (2) developed a real-time operating system kernel, a preliminary

Sparse Beamforming for Real-time Resource Management and Energy Trading in Green C-RAN

OpenAIRE

Wan Ariffin, Wan Nur Suryani Firuz; Zhang, Xinruo; Nakhai, Mohammad Reza

2017-01-01

This paper considers cloud radio access network with simultaneous wireless information and power transfer and finite capacity fronthaul, where the remote radio heads are equipped with renewable energy resources and can trade energy with the grid. Due to uneven distribution of mobile radio traffic and inherent intermittent nature of renewable energy resources, the remote radio heads may need real-time energy provisioning to meet the users’ demands. Given the amount of available energy resource...

Feature Selection Criteria for Real Time EKF-SLAM Algorithm

Directory of Open Access Journals (Sweden)

Fernando Auat Cheein

2010-02-01

Full Text Available This paper presents a seletion procedure for environmet features for the correction stage of a SLAM (Simultaneous Localization and Mapping algorithm based on an Extended Kalman Filter (EKF. This approach decreases the computational time of the correction stage which allows for real and constant-time implementations of the SLAM. The selection procedure consists in chosing the features the SLAM system state covariance is more sensible to. The entire system is implemented on a mobile robot equipped with a range sensor laser. The features extracted from the environment correspond to lines and corners. Experimental results of the real time SLAM algorithm and an analysis of the processing-time consumed by the SLAM with the feature selection procedure proposed are shown. A comparison between the feature selection approach proposed and the classical sequential EKF-SLAM along with an entropy feature selection approach is also performed.

LabVIEW Real-Time

CERN Multimedia

CERN. Geneva; Flockhart, Ronald Bruce; Seppey, P

2003-01-01

With LabVIEW Real-Time, you can choose from a variety of RT Series hardware. Add a real-time data acquisition component into a larger measurement and automation system or create a single stand-alone real-time solution with data acquisition, signal conditioning, motion control, RS-232, GPIB instrumentation, and Ethernet connectivity. With the various hardware options, you can create a system to meet your precise needs today, while the modularity of the system means you can add to the solution as your system requirements grow. If you are interested in Reliable and Deterministic systems for Measurement and Automation, you will profit from this seminar. Agenda: Real-Time Overview LabVIEW RT Hardware Platforms - Linux on PXI Programming with LabVIEW RT Real-Time Operating Systems concepts Timing Applications Data Transfer

Adaptation Computing Parameters of Pan-Tilt-Zoom Cameras for Traffic Monitoring

Directory of Open Access Journals (Sweden)

Ya Lin WU

2014-01-01

Full Text Available The Closed- CIRCUIT television (CCTV cameras have been widely used in recent years for traffic monitoring and surveillance applications. We can use CCTV cameras to extract automatically real-time traffic parameters according to the image processing and tracking technologies. Especially, the pan-tilt-zoom (PTZ cameras can provide flexible view selection as well as a wider observation range, and this makes the traffic parameters can be accurately calculated. Therefore, that the parameters of PTZ cameras are calibrated plays an important role in vision-based traffic applications. However, in the specific traffic environment, which is that the license plate number of the illegal parking is located, the parameters of PTZ cameras have to be updated according to the position and distance of illegal parking. In proposed traffic monitoring systems, we use the ordinary webcam and PTZ camera. We get vanishing-point of traffic lane lines in the pixel-based coordinate system by fixed webcam. The parameters of PTZ camera can be initialized by distance of the traffic monitoring and specific objectives and vanishing-point. And then we can use the coordinate position of the illegally parked car to update the parameters of PTZ camera and then get the real word coordinate position of the illegally parked car and use it to compute the distance. The result shows the error of the tested distance and real distance is only 0.2064 meter.

Mobile Phone Based RIMS for Traffic Control a Case Study of Tanzania

OpenAIRE

Angela-Aida Karugila Runyoro; Jesuk Ko

2015-01-01

Vehicles saturation in transportation infrastructure causes traffic congestion, accidents, transportation delays and environment pollution. This problem can be resolved with proper management of traffic flow. Existing traffic management systems are challenged on capturing and processing real-time road data from wide area road networks. The main purpose of this study is to address the gap by implementing a mobile phone based Road Information Management System. The proposed...

Concepts of real time and semi-real time material control

International Nuclear Information System (INIS)

Lovett, J.E.

1975-01-01

After a brief consideration of the traditional material balance accounting on an MBA basis, this paper explores the basic concepts of real time and semi-real time material control, together with some of the major problems to be solved. Three types of short-term material control are discussed: storage, batch processing, and continuous processing. (DLC)

Assessing Road Traffic Expression

Directory of Open Access Journals (Sweden)

Fábio Silva

2014-12-01

Full Text Available Road traffic is a problem which is increasing in cities with large population. Unrelated to this fact the number of portable and wearable devices has also been increasing throughout the population of most countries. With this advent, the capacity to monitor and register data about people habits and locations as well as more complex data such as intensity and strength of movements has created an opportunity to contribute to the general wealth and comfort within these environments. Ambient Intelligence and Intelligent Decision Making processes can benefit from the knowledge gathered by these devices to improve decisions on everyday tasks such as deciding navigation routes by car, bicycle or other means of transportation and avoiding route perils. The concept of computational sustainability may also be applied to this problem. Current applications in this area demonstrate the usefulness of real time system that inform the user of certain conditions in the surrounding area. On the other hand, the approach presented in this work aims to describe models and approaches to automatically identify current states of traffic inside cities and use methods from computer science to improve overall comfort and the sustainability of road traffic both with the user and the environment in mind. Such objective is delivered by analyzing real time contributions from those mobile ubiquitous devices to identifying problematic situations and areas under a defined criteria that have significant influence towards a sustainable use of the road transport infrastructure.

Real Time Systems

DEFF Research Database (Denmark)

Christensen, Knud Smed

2000-01-01

Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems.......Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems....

Co-simulation for real time safety verification of nuclear power plants

International Nuclear Information System (INIS)

Boafo, E.K.; Zhang, L.; Nasimi, E.; Gabbar, H.A.

2015-01-01

Small and major accidents and near misses are still occurring in nuclear power plants (NPPs). Risk level has increased with the degradation of NPP equipment and instrumentations. In order to achieve NPP safety, it is important to continuously evaluate risk for all potential hazard and fault propagation scenarios and map protection layers to fault / failure / hazard propagation scenarios to be able to evaluate and verify safety level during NPP operation. There are major limitations in current real time safety verification tools, as it is mainly offline and with no integration to NPP simulation tools. The main goal of this research is to develop real time safety verification with co-simulation tool to be integrated with plant operation support systems. This includes the development of static and dynamic fault semantic network (FSN) to model all possible fault propagation scenarios and the interrelationships among associated process variables. Safety and protection layers along with their reliability are mapped to FSN so that safety levels can be verified during plant operation. Errors between multiphysics models and real time data are modeled to accurately and dynamically tune FSN for each fault propagation scenario. The detailed methodology will show how to integrate process models, construction of static FSN with fault propagation scenarios, and evaluation and tuning of dynamic FSN with probabilistic and process variable interaction values. Principle Component Analysis method is used reduce dimensionality and reduce process variables associated with each fault scenario. Then map independent protection layers (IPL) to FSN with estimated reliability measures of each protection layer to accurately verify safety for different operational scenarios. Intelligent algorithms is used with multivariate techniques to accurate define the interrelation among process variables, in terms of signal strength and time delay, using Genetic Programming (GP), which will provide basis

Complex motion of elevators in piecewise map model combined with circle map

Science.gov (United States)

Nagatani, Takashi

2013-11-01

We study the dynamic behavior in the elevator traffic controlled by capacity when the inflow rate of passengers into elevators varies periodically with time. The dynamics of elevators is described by the piecewise map model combined with the circle map. The motion of the elevators depends on the inflow rate, its period, and the number of elevators. The motion in the piecewise map model combined with the circle map shows a complex behavior different from the motion in the piecewise map model.

Study of air traffic over KLFIR

Science.gov (United States)

Nusyirwan, I. F.; Rohani, J. Mohd

2017-12-01

This paper shares the overview of the work currently being conducted with the Department of Civil Aviation Malaysia related to the air traffic. The aim is to study air traffic performance over KL and KK FIR, and the area of interest in this paper is the Kuala Lumpur Flight Information Region (KLFIR). The air traffic performance parameters includes general air traffic movement such as level allocation, number of movements, sector load analysis and also more specific parameters such as airborne delays, effects of weather to the air movements as well as ground delays. To achieve this, a huge effort has been undertaken that includes live data collection algorithm development and real time statistical analysis algorithm development. The main outcome from this multi-disciplinary work is the long-term analysis on the air traffic performance in Malaysia, which will put the country at par in the aviation community, namely the International Civil Aviation Organization (ICAO).

STRAW - An Integrated Mobility and Traffic Model for VANETs

National Research Council Canada - National Science Library

Choffnes, David R; Bustamante, Fabian E

2005-01-01

Ad-hoc wireless communication among highly dynamic, mobile nodes in a urban network is a critical capability for a wide range of important applications including automated vehicles, real-time traffic...

Creating real estate maps by using GIS: A case study of Atakum-Samsun/Turkey

Directory of Open Access Journals (Sweden)

Faik Ahmet Sesli

2015-12-01

Full Text Available Determining the real estate evaluations and reflecting them on taxations are among the most important economic resources of the developed countries. In Turkey, the system is not able to ground the real estate evaluations on scientific criteria yet, which causes various problems in applications regarding real estate evaluations (such as estate tax, expropriation, court surveillances and an important economic loss.Thus, it is required to generate tax-base real estate evaluation maps within the scope of the legal legislation in Turkey. This study aimed to generate a fast, up-to-date and dynamic evaluation map that would form a base for the real estate taxation. The closeness of real estates to the technical infrastructure and social equipment areas and their variety affect the real estate evaluations either positively or negatively and form the local benefit for real estates. This study determined the areas (such as main roads, green spaces, trading areas and urban attraction centers affecting the evaluations of real estates depending on their positions. In order to make position-based decisions about the data being stored in the Geographical Information System, the geographical data were questioned and monitored with analyses. The acquired data were exposed to necessary analyses in the relevant modules of the GIS programs, which enabled us to grade the factors affecting the evaluation for each parcel and try to generate real estate evaluation maps depending on the evaluation-effect factors to be selected as dynamics. Parcel-based real estate evaluations were determined by imposing vector-based cadastral maps on these maps being generated. In this study, a raster real estate evaluation map was generated in unstructured parcels of a sample neighborhood via the scoring method and with the help of the Multi-Criteria Decision-Making Analysis and both environmental and social factors. This system could enable us to question and analyze the features of

Real-Time 3D Face Acquisition Using Reconfigurable Hybrid Architecture

Directory of Open Access Journals (Sweden)

Mitéran Johel

2007-01-01

Full Text Available Acquiring 3D data of human face is a general problem which can be applied in face recognition, virtual reality, and many other applications. It can be solved using stereovision. This technique consists in acquiring data in three dimensions from two cameras. The aim is to implement an algorithmic chain which makes it possible to obtain a three-dimensional space from two two-dimensional spaces: two images coming from the two cameras. Several implementations have already been considered. We propose a new simple real-time implementation based on a hybrid architecture (FPGA-DSP, allowing to consider an embedded and reconfigurable processing. Then we show our method which provides depth map of face, dense and reliable, and which can be implemented on an embedded architecture. A various architecture study led us to a judicious choice allowing to obtain the desired result. The real-time data processing is implemented in an embedded architecture. We obtain a dense face disparity map, precise enough for considered applications (multimedia, virtual worlds, biometrics and using a reliable method.

Real-time functional MR imaging (fMRI) for presurgical evaluation of paediatric epilepsy

Energy Technology Data Exchange (ETDEWEB)

Kesavadas, Chandrasekharan; Thomas, Bejoy; Kumar Gupta, Arun [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Imaging Sciences and Interventional Radiology, Trivandrum (India); Sujesh, Sreedharan [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Biomedical Technology Wing, Trivandrum (India); Ashalata, Radhakrishnan; Radhakrishnan, Kurupath [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurology, Trivandrum (India); Abraham, Mathew [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurosurgery, Trivandrum (India)

2007-10-15

The role of fMRI in the presurgical evaluation of children with intractable epilepsy is being increasingly recognized. Real-time fMRI allows the clinician to visualize functional brain activation in real time. Since there is no off-line data analysis as in conventional fMRI, the overall time for the procedure is reduced, making it clinically feasible in a busy clinical sitting. (1) To study the accuracy of real-time fMRI in comparison to conventional fMRI with off-line processing; (2) to determine its effectiveness in mapping the eloquent cortex and language lateralization in comparison to invasive procedures such as intraoperative cortical stimulation and Wada testing; and (3) to evaluate the role of fMRI in presurgical decision making in children with epilepsy. A total of 23 patients (age range 6-18 years) underwent fMRI with sensorimotor, visual and language paradigms. Data processing was done in real time using in-line BOLD. The results of real-time fMRI matched those of off-line processing done using the well-accepted standard technique of statistical parametric mapping (SPM) in all the initial ten patients in whom the two techniques were compared. Coregistration of the fMRI data on a 3-D FLAIR sequence rather than a T1-weighted image gave better information regarding the relationship of the lesion to the area of activation. The results of intraoperative cortical stimulation and fMRI matched in six out of six patients, while the Wada test and fMRI had similar results in four out of five patients in whom these techniques were performed. In the majority of patients in this series the technique influenced patient management. Real-time fMRI is an easily performed and reliable technique in the presurgical workup of children with epilepsy. (orig.)

Real-time functional MR imaging (fMRI) for presurgical evaluation of paediatric epilepsy

International Nuclear Information System (INIS)

Kesavadas, Chandrasekharan; Thomas, Bejoy; Kumar Gupta, Arun; Sujesh, Sreedharan; Ashalata, Radhakrishnan; Radhakrishnan, Kurupath; Abraham, Mathew

2007-01-01

The role of fMRI in the presurgical evaluation of children with intractable epilepsy is being increasingly recognized. Real-time fMRI allows the clinician to visualize functional brain activation in real time. Since there is no off-line data analysis as in conventional fMRI, the overall time for the procedure is reduced, making it clinically feasible in a busy clinical sitting. (1) To study the accuracy of real-time fMRI in comparison to conventional fMRI with off-line processing; (2) to determine its effectiveness in mapping the eloquent cortex and language lateralization in comparison to invasive procedures such as intraoperative cortical stimulation and Wada testing; and (3) to evaluate the role of fMRI in presurgical decision making in children with epilepsy. A total of 23 patients (age range 6-18 years) underwent fMRI with sensorimotor, visual and language paradigms. Data processing was done in real time using in-line BOLD. The results of real-time fMRI matched those of off-line processing done using the well-accepted standard technique of statistical parametric mapping (SPM) in all the initial ten patients in whom the two techniques were compared. Coregistration of the fMRI data on a 3-D FLAIR sequence rather than a T1-weighted image gave better information regarding the relationship of the lesion to the area of activation. The results of intraoperative cortical stimulation and fMRI matched in six out of six patients, while the Wada test and fMRI had similar results in four out of five patients in whom these techniques were performed. In the majority of patients in this series the technique influenced patient management. Real-time fMRI is an easily performed and reliable technique in the presurgical workup of children with epilepsy. (orig.)

ANALYSIS OF SPATIO-TEMPORAL TRAFFIC PATTERNS BASED ON PEDESTRIAN TRAJECTORIES

Directory of Open Access Journals (Sweden)

S. Busch

2016-06-01

Full Text Available For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

Science.gov (United States)

Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

2016-06-01

For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

Realistic 3D Terrain Roaming and Real-Time Flight Simulation

Science.gov (United States)

Que, Xiang; Liu, Gang; He, Zhenwen; Qi, Guang

2014-12-01

This paper presents an integrate method, which can provide access to current status and the dynamic visible scanning topography, to enhance the interactive during the terrain roaming and real-time flight simulation. A digital elevation model and digital ortho-photo map data integrated algorithm is proposed as the base algorithm for our approach to build a realistic 3D terrain scene. A new technique with help of render to texture and head of display for generating the navigation pane is used. In the flight simulating, in order to eliminate flying "jump", we employs the multidimensional linear interpolation method to adjust the camera parameters dynamically and steadily. Meanwhile, based on the principle of scanning laser imaging, we draw pseudo color figures by scanning topography in different directions according to the real-time flying status. Simulation results demonstrate that the proposed algorithm is prospective for applications and the method can improve the effect and enhance dynamic interaction during the real-time flight.

Reliability over time of EEG-based mental workload evaluation during Air Traffic Management (ATM) tasks.

Science.gov (United States)

Arico, Pietro; Borghini, Gianluca; Di Flumeri, Gianluca; Colosimo, Alfredo; Graziani, Ilenia; Imbert, Jean-Paul; Granger, Geraud; Benhacene, Railene; Terenzi, Michela; Pozzi, Simone; Babiloni, Fabio

2015-08-01

Machine-learning approaches for mental workload (MW) estimation by using the user brain activity went through a rapid expansion in the last decades. In fact, these techniques allow now to measure the MW with a high time resolution (e.g. few seconds). Despite such advancements, one of the outstanding problems of these techniques regards their ability to maintain a high reliability over time (e.g. high accuracy of classification even across consecutive days) without performing any recalibration procedure. Such characteristic will be highly desirable in real world applications, in which human operators could use such approach without undergo a daily training of the device. In this work, we reported that if a simple classifier is calibrated by using a low number of brain spectral features, between those ones strictly related to the MW (i.e. Frontal and Occipital Theta and Parietal Alpha rhythms), those features will make the classifier performance stable over time. In other words, the discrimination accuracy achieved by the classifier will not degrade significantly across different days (i.e. until one week). The methodology has been tested on twelve Air Traffic Controls (ATCOs) trainees while performing different Air Traffic Management (ATM) scenarios under three different difficulty levels.

Low-level processing for real-time image analysis

Science.gov (United States)

Eskenazi, R.; Wilf, J. M.

1979-01-01

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Real-time RGB-D image stitching using multiple Kinects for improved field of view

Directory of Open Access Journals (Sweden)

Hengyu Li

2017-03-01

Full Text Available This article concerns the problems of a defective depth map and limited field of view of Kinect-style RGB-D sensors. An anisotropic diffusion based hole-filling method is proposed to recover invalid depth data in the depth map. The field of view of the Kinect-style RGB-D sensor is extended by stitching depth and color images from several RGB-D sensors. By aligning the depth map with the color image, the registration data calculated by registering color images can be used to stitch depth and color images into a depth and color panoramic image concurrently in real time. Experiments show that the proposed stitching method can generate a RGB-D panorama with no invalid depth data and little distortion in real time and can be extended to incorporate more RGB-D sensors to construct even a 360° field of view panoramic RGB-D image.

Application of travel time information for traffic management.

Science.gov (United States)

2012-03-01

This report summarizes findings and implementations of probe vehicle data collection based on Bluetooth MAC address matching : technology. Probe vehicle travel time data are studied in the following field deployment case studies: analysis of traffic ...

A comparison of moving object detection methods for real-time moving object detection

Science.gov (United States)

Roshan, Aditya; Zhang, Yun

2014-06-01

Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

Science.gov (United States)

Hossain, Moinul; Muromachi, Yasunori

2012-03-01

The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evaluating State-of-the-art Object Detector on Challenging Traffic Light Data

DEFF Research Database (Denmark)

Jensen, Morten Bornø; Nasrollahi, Kamal; Moeslund, Thomas B.

2017-01-01

-of-the-art, real-time object detection system You Only Look Once, (YOLO) on the public LISA Traffic Light dataset available through the VIVA-challenge, which contain a high number of annotated traffic lights, captured in varying light and weather conditions. The YOLO object detector achieves an AUC of impres...

Real-time motion-adaptive-optimization (MAO) in TomoTherapy

Energy Technology Data Exchange (ETDEWEB)

Lu Weiguo; Chen Mingli; Ruchala, Kenneth J; Chen Quan; Olivera, Gustavo H [TomoTherapy Inc., 1240 Deming Way, Madison, WI (United States); Langen, Katja M; Kupelian, Patrick A [MD Anderson Cancer Center-Orlando, Orlando, FL (United States)], E-mail: wlu@tomotherapy.com

2009-07-21

IMRT delivery follows a planned leaf sequence, which is optimized before treatment delivery. However, it is hard to model real-time variations, such as respiration, in the planning procedure. In this paper, we propose a negative feedback system of IMRT delivery that incorporates real-time optimization to account for intra-fraction motion. Specifically, we developed a feasible workflow of real-time motion-adaptive-optimization (MAO) for TomoTherapy delivery. TomoTherapy delivery is characterized by thousands of projections with a fast projection rate and ultra-fast binary leaf motion. The technique of MAO-guided delivery calculates (i) the motion-encoded dose that has been delivered up to any given projection during the delivery and (ii) the future dose that will be delivered based on the estimated motion probability and future fluence map. These two pieces of information are then used to optimize the leaf open time of the upcoming projection right before its delivery. It consists of several real-time procedures, including 'motion detection and prediction', 'delivered dose accumulation', 'future dose estimation' and 'projection optimization'. Real-time MAO requires that all procedures are executed in time less than the duration of a projection. We implemented and tested this technique using a TomoTherapy (registered) research system. The MAO calculation took about 100 ms per projection. We calculated and compared MAO-guided delivery with two other types of delivery, motion-without-compensation delivery (MD) and static delivery (SD), using simulated 1D cases, real TomoTherapy plans and the motion traces from clinical lung and prostate patients. The results showed that the proposed technique effectively compensated for motion errors of all test cases. Dose distributions and DVHs of MAO-guided delivery approached those of SD, for regular and irregular respiration with a peak-to-peak amplitude of 3 cm, and for medium and large

Real-time motion-adaptive-optimization (MAO) in TomoTherapy

International Nuclear Information System (INIS)

Lu Weiguo; Chen Mingli; Ruchala, Kenneth J; Chen Quan; Olivera, Gustavo H; Langen, Katja M; Kupelian, Patrick A

2009-01-01

IMRT delivery follows a planned leaf sequence, which is optimized before treatment delivery. However, it is hard to model real-time variations, such as respiration, in the planning procedure. In this paper, we propose a negative feedback system of IMRT delivery that incorporates real-time optimization to account for intra-fraction motion. Specifically, we developed a feasible workflow of real-time motion-adaptive-optimization (MAO) for TomoTherapy delivery. TomoTherapy delivery is characterized by thousands of projections with a fast projection rate and ultra-fast binary leaf motion. The technique of MAO-guided delivery calculates (i) the motion-encoded dose that has been delivered up to any given projection during the delivery and (ii) the future dose that will be delivered based on the estimated motion probability and future fluence map. These two pieces of information are then used to optimize the leaf open time of the upcoming projection right before its delivery. It consists of several real-time procedures, including 'motion detection and prediction', 'delivered dose accumulation', 'future dose estimation' and 'projection optimization'. Real-time MAO requires that all procedures are executed in time less than the duration of a projection. We implemented and tested this technique using a TomoTherapy (registered) research system. The MAO calculation took about 100 ms per projection. We calculated and compared MAO-guided delivery with two other types of delivery, motion-without-compensation delivery (MD) and static delivery (SD), using simulated 1D cases, real TomoTherapy plans and the motion traces from clinical lung and prostate patients. The results showed that the proposed technique effectively compensated for motion errors of all test cases. Dose distributions and DVHs of MAO-guided delivery approached those of SD, for regular and irregular respiration with a peak-to-peak amplitude of 3 cm, and for medium and large prostate motions. The results conceptually

Classification of Automated Search Traffic

Science.gov (United States)

Buehrer, Greg; Stokes, Jack W.; Chellapilla, Kumar; Platt, John C.

As web search providers seek to improve both relevance and response times, they are challenged by the ever-increasing tax of automated search query traffic. Third party systems interact with search engines for a variety of reasons, such as monitoring a web site’s rank, augmenting online games, or possibly to maliciously alter click-through rates. In this paper, we investigate automated traffic (sometimes referred to as bot traffic) in the query stream of a large search engine provider. We define automated traffic as any search query not generated by a human in real time. We first provide examples of different categories of query logs generated by automated means. We then develop many different features that distinguish between queries generated by people searching for information, and those generated by automated processes. We categorize these features into two classes, either an interpretation of the physical model of human interactions, or as behavioral patterns of automated interactions. Using the these detection features, we next classify the query stream using multiple binary classifiers. In addition, a multiclass classifier is then developed to identify subclasses of both normal and automated traffic. An active learning algorithm is used to suggest which user sessions to label to improve the accuracy of the multiclass classifier, while also seeking to discover new classes of automated traffic. Performance analysis are then provided. Finally, the multiclass classifier is used to predict the subclass distribution for the search query stream.

Energy-Aware Synthesis of Fault-Tolerant Schedules for Real-Time Distributed Embedded Systems

DEFF Research Database (Denmark)

Poulsen, Kåre Harbo; Pop, Paul; Izosimov, Viacheslav

2007-01-01

This paper presents a design optimisation tool for distributed embedded real-time systems that 1) decides mapping, fault-tolerance policy and generates a fault-tolerant schedule, 2) is targeted for hard real-time, 3) has hard reliability goal, 4) generates static schedule for processes and messages......, 5) provides fault-tolerance for k transient/soft faults, 6) optimises for minimal energy consumption, while considering impact of lowering voltages on the probability of faults, 7) uses constraint logic programming (CLP) based implementation....

Process algebra with timing : real time and discrete time

NARCIS (Netherlands)

Baeten, J.C.M.; Middelburg, C.A.; Bergstra, J.A.; Ponse, A.J.; Smolka, S.A.

2001-01-01

We present real time and discrete time versions of ACP with absolute timing and relative timing. The starting-point is a new real time version with absolute timing, called ACPsat, featuring urgent actions and a delay operator. The discrete time versions are conservative extensions of the discrete

Process algebra with timing: Real time and discrete time

NARCIS (Netherlands)

Baeten, J.C.M.; Middelburg, C.A.

1999-01-01

We present real time and discrete time versions of ACP with absolute timing and relative timing. The startingpoint is a new real time version with absolute timing, called ACPsat , featuring urgent actions and a delay operator. The discrete time versions are conservative extensions of the discrete

Real-time unmanned aircraft systems surveillance video mosaicking using GPU

Science.gov (United States)

Camargo, Aldo; Anderson, Kyle; Wang, Yi; Schultz, Richard R.; Fevig, Ronald A.

2010-04-01

Digital video mosaicking from Unmanned Aircraft Systems (UAS) is being used for many military and civilian applications, including surveillance, target recognition, border protection, forest fire monitoring, traffic control on highways, monitoring of transmission lines, among others. Additionally, NASA is using digital video mosaicking to explore the moon and planets such as Mars. In order to compute a "good" mosaic from video captured by a UAS, the algorithm must deal with motion blur, frame-to-frame jitter associated with an imperfectly stabilized platform, perspective changes as the camera tilts in flight, as well as a number of other factors. The most suitable algorithms use SIFT (Scale-Invariant Feature Transform) to detect the features consistent between video frames. Utilizing these features, the next step is to estimate the homography between two consecutives video frames, perform warping to properly register the image data, and finally blend the video frames resulting in a seamless video mosaick. All this processing takes a great deal of resources of resources from the CPU, so it is almost impossible to compute a real time video mosaic on a single processor. Modern graphics processing units (GPUs) offer computational performance that far exceeds current CPU technology, allowing for real-time operation. This paper presents the development of a GPU-accelerated digital video mosaicking implementation and compares it with CPU performance. Our tests are based on two sets of real video captured by a small UAS aircraft; one video comes from Infrared (IR) and Electro-Optical (EO) cameras. Our results show that we can obtain a speed-up of more than 50 times using GPU technology, so real-time operation at a video capture of 30 frames per second is feasible.

A real-time 3D scanning system for pavement distortion inspection

International Nuclear Information System (INIS)

Li, Qingguang; Yao, Ming; Yao, Xun; Xu, Bugao

2010-01-01

Pavement distortions, such as rutting and shoving, are the common pavement distress problems that need to be inspected and repaired in a timely manner to ensure ride quality and traffic safety. This paper introduces a real-time, low-cost inspection system devoted to detecting these distress features using high-speed 3D transverse scanning techniques. The detection principle is the dynamic generation and characterization of the 3D pavement profile based on structured light triangulation. To improve the accuracy of the system, a multi-view coplanar scheme is employed in the calibration procedure so that more feature points can be used and distributed across the field of view of the camera. A sub-pixel line extraction method is applied for the laser stripe location, which includes filtering, edge detection and spline interpolation. The pavement transverse profile is then generated from the laser stripe curve and approximated by line segments. The second-order derivatives of the segment endpoints are used to identify the feature points of possible distortions. The system can output the real-time measurements and 3D visualization of rutting and shoving distress in a scanned pavement

Life-Times of Simulated Traffic Jams

OpenAIRE

Nagel, K.

1993-01-01

We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations for driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from...

Extended Traffic Crash Modelling through Precision and Response Time Using Fuzzy Clustering Algorithms Compared with Multi-layer Perceptron

Directory of Open Access Journals (Sweden)

Iman Aghayan

2012-11-01

Full Text Available This paper compares two fuzzy clustering algorithms – fuzzy subtractive clustering and fuzzy C-means clustering – to a multi-layer perceptron neural network for their ability to predict the severity of crash injuries and to estimate the response time on the traffic crash data. Four clustering algorithms – hierarchical, K-means, subtractive clustering, and fuzzy C-means clustering – were used to obtain the optimum number of clusters based on the mean silhouette coefficient and R-value before applying the fuzzy clustering algorithms. The best-fit algorithms were selected according to two criteria: precision (root mean square, R-value, mean absolute errors, and sum of square error and response time (t. The highest R-value was obtained for the multi-layer perceptron (0.89, demonstrating that the multi-layer perceptron had a high precision in traffic crash prediction among the prediction models, and that it was stable even in the presence of outliers and overlapping data. Meanwhile, in comparison with other prediction models, fuzzy subtractive clustering provided the lowest value for response time (0.284 second, 9.28 times faster than the time of multi-layer perceptron, meaning that it could lead to developing an on-line system for processing data from detectors and/or a real-time traffic database. The model can be extended through improvements based on additional data through induction procedure.

A Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment

Directory of Open Access Journals (Sweden)

Rongjie Kuang

2014-03-01

Full Text Available Due to static traffic assignment has poor performance in reflecting actual case and dynamic traffic assignment may incurs excessive compute cost, method of multi-time dynamic traffic assignment combining static and dynamic traffic assignment balances factors of precision and cost effectively. A method based on Dial's logit algorithm is proposed in the article to solve the dynamic stochastic user equilibrium problem in dynamic traffic assignment. Before that, a fitting function that can proximately reflect overloaded traffic condition of link is proposed and used to give corresponding model. Numerical example is given to illustrate heuristic procedure of method and to compare results with one of same example solved by other literature's algorithm. Results show that method based on Dial's algorithm is preferable to algorithm from others.

Do alcohol excise taxes affect traffic accidents? Evidence from Estonia.

Science.gov (United States)

Saar, Indrek

2015-01-01

This article examines the association between alcohol excise tax rates and alcohol-related traffic accidents in Estonia. Monthly time series of traffic accidents involving drunken motor vehicle drivers from 1998 through 2013 were regressed on real average alcohol excise tax rates while controlling for changes in economic conditions and the traffic environment. Specifically, regression models with autoregressive integrated moving average (ARIMA) errors were estimated in order to deal with serial correlation in residuals. Counterfactual models were also estimated in order to check the robustness of the results, using the level of non-alcohol-related traffic accidents as a dependent variable. A statistically significant (P traffic accidents was disclosed under alternative model specifications. For instance, the regression model with ARIMA (0, 1, 1)(0, 1, 1) errors revealed that a 1-unit increase in the tax rate is associated with a 1.6% decrease in the level of accidents per 100,000 population involving drunk motor vehicle drivers. No similar association was found in the cases of counterfactual models for non-alcohol-related traffic accidents. This article indicates that the level of alcohol-related traffic accidents in Estonia has been affected by changes in real average alcohol excise taxes during the period 1998-2013. Therefore, in addition to other measures, the use of alcohol taxation is warranted as a policy instrument in tackling alcohol-related traffic accidents.

Real-time radiography

International Nuclear Information System (INIS)

Bossi, R.H.; Oien, C.T.

1981-01-01

Real-time radiography is used for imaging both dynamic events and static objects. Fluorescent screens play an important role in converting radiation to light, which is then observed directly or intensified and detected. The radiographic parameters for real-time radiography are similar to conventional film radiography with special emphasis on statistics and magnification. Direct-viewing fluoroscopy uses the human eye as a detector of fluorescent screen light or the light from an intensifier. Remote-viewing systems replace the human observer with a television camera. The remote-viewing systems have many advantages over the direct-viewing conditions such as safety, image enhancement, and the capability to produce permanent records. This report reviews real-time imaging system parameters and components

Overview of the Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study: theoretical background and model for design of field experiments.

Science.gov (United States)

Hahn, Intaek; Wiener, Russell W; Richmond-Bryant, Jennifer; Brixey, Laurie A; Henkle, Stacy W

2009-12-01

The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study was a multidisciplinary field research project that investigated the transport, dispersion, and infiltration processes of traffic emission particulate matter (PM) pollutants in a near-highway urban residential area. The urban PM transport, dispersion, and infiltration processes were described mathematically in a theoretical model that was constructed to develop the experimental objectives of the B-TRAPPED study. In the study, simultaneous and continuous time-series PM concentration and meteorological data collected at multiple outdoor and indoor monitoring locations were used to characterize both temporal and spatial patterns of the PM concentration movements within microscale distances (street canyon; (2) investigating the effects of urban structures such as a tall building or an intersection on the transport and dispersion of PM; (3) studying the influence of meteorological variables on the transport, dispersion, and infiltration processes; (4) characterizing the relationships between the building parameters and the infiltration mechanisms; (5) establishing a cause-and-effect relationship between outdoor-released PM and indoor PM concentrations and identifying the dominant mechanisms involved in the infiltration process; (6) evaluating the effectiveness of a shelter-in-place area for protection against outdoor-released PM pollutants; and (7) understanding the predominant airflow and pollutant dispersion patterns within the neighborhood using wind tunnel and CFD simulations. The 10 papers in this first set of papers presenting the results from the B-TRAPPED study address these objectives. This paper describes the theoretical background and models representing the interrelated processes of transport, dispersion, and infiltration. The theoretical solution for the relationship between the time-dependent indoor PM concentration and the initial PM concentration

Real-time vision systems

Energy Technology Data Exchange (ETDEWEB)

Johnson, R.; Hernandez, J.E.; Lu, Shin-yee [Lawrence Livermore National Lab., CA (United States)

1994-11-15

Many industrial and defence applications require an ability to make instantaneous decisions based on sensor input of a time varying process. Such systems are referred to as `real-time systems` because they process and act on data as it occurs in time. When a vision sensor is used in a real-time system, the processing demands can be quite substantial, with typical data rates of 10-20 million samples per second. A real-time Machine Vision Laboratory (MVL) was established in FY94 to extend our years of experience in developing computer vision algorithms to include the development and implementation of real-time vision systems. The laboratory is equipped with a variety of hardware components, including Datacube image acquisition and processing boards, a Sun workstation, and several different types of CCD cameras, including monochrome and color area cameras and analog and digital line-scan cameras. The equipment is reconfigurable for prototyping different applications. This facility has been used to support several programs at LLNL, including O Division`s Peacemaker and Deadeye Projects as well as the CRADA with the U.S. Textile Industry, CAFE (Computer Aided Fabric Inspection). To date, we have successfully demonstrated several real-time applications: bullet tracking, stereo tracking and ranging, and web inspection. This work has been documented in the ongoing development of a real-time software library.

Elastic LiDAR Fusion: Dense Map-Centric Continuous-Time SLAM

OpenAIRE

Park, Chanoh; Moghadam, Peyman; Kim, Soohwan; Elfes, Alberto; Fookes, Clinton; Sridharan, Sridha

2017-01-01

The concept of continuous-time trajectory representation has brought increased accuracy and efficiency to multi-modal sensor fusion in modern SLAM. However, regardless of these advantages, its offline property caused by the requirement of global batch optimization is critically hindering its relevance for real-time and life-long applications. In this paper, we present a dense map-centric SLAM method based on a continuous-time trajectory to cope with this problem. The proposed system locally f...

An Information-Theoretic Approach for Indirect Train Traffic Monitoring Using Building Vibration

OpenAIRE

Xu, Susu; Zhang, Lin; Zhang, Pei; Noh, Hae Young

2017-01-01

This paper introduces an indirect train traffic monitoring method to detect and infer real-time train events based on the vibration response of a nearby building. Monitoring and characterizing traffic events are important for cities to improve the efficiency of transportation systems (e.g., train passing, heavy trucks, and traffic). Most prior work falls into two categories: (1) methods that require intensive labor to manually record events or (2) systems that require deployment of dedicated ...

Performance Evaluation of RIPng, EIGRPv6 and OSPFv3 for Real Time Applications

Directory of Open Access Journals (Sweden)

Sama Salam Samaan

2018-01-01

Full Text Available In this modern Internet era and the transition to IPv6, routing protocols must adjust to assist this transformation. RIPng, EIGRPv6 and OSPFv3 are the dominant IPv6 IGRP (Interior Gateway Routing Protocols. Selecting the best routing protocol among the available is a critical task, which depends upon the network requirement and performance parameters of different real time applications. The primary motivation of this paper is to estimate the performance of these protocols in real time applications. The evaluation is based on a number of criteria including: network convergence duration, Http Page Response Time, DB Query Response Time, IPv6 traffic dropped, video packet delay variation and video packet end to end delay. After examining the simulation results, a conclusion will be extracted to reveal the findings of which protocol performs the best upon implementation within a IPv6 WAN. OPNET modeler simulator is used to evaluate the accomplishment of these protocols. To get the results, three scenarios are designed, one for each protocol.

Wetland Plant Guide for Assessing Habitat Impacts of Real-Time Salinity Management

OpenAIRE

Quinn, Nigel W.T.; Feldmann, Sara A.

2004-01-01

This wetland plant guide was developed to aid moist soil plant identification and to assist in the mapping of waterfowl and shorebird habitat in the Grassland Water District and surrounding wetland areas. The motivation for this habitat mapping project was a concern that real-time salinity management of wetland drainage might have long-term consequences for wildfowl habitat health -- changes in wetland drawdown schedules might, over the long term, lead to increased soil salinity and othe...

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

Science.gov (United States)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

Near-real-time simulation and internet-based delivery of forecast-flood inundation maps using two-dimensional hydraulic modeling--A pilot study for the Snoqualmie River, Washington

Science.gov (United States)

Jones, Joseph L.; Fulford, Janice M.; Voss, Frank D.

2002-01-01

A system of numerical hydraulic modeling, geographic information system processing, and Internet map serving, supported by new data sources and application automation, was developed that generates inundation maps for forecast floods in near real time and makes them available through the Internet. Forecasts for flooding are generated by the National Weather Service (NWS) River Forecast Center (RFC); these forecasts are retrieved automatically by the system and prepared for input to a hydraulic model. The model, TrimR2D, is a new, robust, two-dimensional model capable of simulating wide varieties of discharge hydrographs and relatively long stream reaches. TrimR2D was calibrated for a 28-kilometer reach of the Snoqualmie River in Washington State, and is used to estimate flood extent, depth, arrival time, and peak time for the RFC forecast. The results of the model are processed automatically by a Geographic Information System (GIS) into maps of flood extent, depth, and arrival and peak times. These maps subsequently are processed into formats acceptable by an Internet map server (IMS). The IMS application is a user-friendly interface to access the maps over the Internet; it allows users to select what information they wish to see presented and allows the authors to define scale-dependent availability of map layers and their symbology (appearance of map features). For example, the IMS presents a background of a digital USGS 1:100,000-scale quadrangle at smaller scales, and automatically switches to an ortho-rectified aerial photograph (a digital photograph that has camera angle and tilt distortions removed) at larger scales so viewers can see ground features that help them identify their area of interest more effectively. For the user, the option exists to select either background at any scale. Similar options are provided for both the map creator and the viewer for the various flood maps. This combination of a robust model, emerging IMS software, and application

Automated Traffic Management System and Method

Science.gov (United States)

Glass, Brian J. (Inventor); Spirkovska, Liljana (Inventor); McDermott, William J. (Inventor); Reisman, Ronald J. (Inventor); Gibson, James (Inventor); Iverson, David L. (Inventor)

2000-01-01

A data management system and method that enables acquisition, integration, and management of real-time data generated at different rates, by multiple heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data, and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators, or commercial airline personnel in airfield surface operations.

Time-based collision risk modeling for air traffic management

Science.gov (United States)

Bell, Alan E.

Since the emergence of commercial aviation in the early part of last century, economic forces have driven a steadily increasing demand for air transportation. Increasing density of aircraft operating in a finite volume of airspace is accompanied by a corresponding increase in the risk of collision, and in response to a growing number of incidents and accidents involving collisions between aircraft, governments worldwide have developed air traffic control systems and procedures to mitigate this risk. The objective of any collision risk management system is to project conflicts and provide operators with sufficient opportunity to recognize potential collisions and take necessary actions to avoid them. It is therefore the assertion of this research that the currency of collision risk management is time. Future Air Traffic Management Systems are being designed around the foundational principle of four dimensional trajectory based operations, a method that replaces legacy first-come, first-served sequencing priorities with time-based reservations throughout the airspace system. This research will demonstrate that if aircraft are to be sequenced in four dimensions, they must also be separated in four dimensions. In order to separate aircraft in four dimensions, time must emerge as the primary tool by which air traffic is managed. A functional relationship exists between the time-based performance of aircraft, the interval between aircraft scheduled to cross some three dimensional point in space, and the risk of collision. This research models that relationship and presents two key findings. First, a method is developed by which the ability of an aircraft to meet a required time of arrival may be expressed as a robust standard for both industry and operations. Second, a method by which airspace system capacity may be increased while maintaining an acceptable level of collision risk is presented and demonstrated for the purpose of formulating recommendations for procedures

Rotating-Disk-Based Hybridized Electromagnetic-Triboelectric Nanogenerator for Sustainably Powering Wireless Traffic Volume Sensors.

Science.gov (United States)

Zhang, Binbin; Chen, Jun; Jin, Long; Deng, Weili; Zhang, Lei; Zhang, Haitao; Zhu, Minhao; Yang, Weiqing; Wang, Zhong Lin

2016-06-28

Wireless traffic volume detectors play a critical role for measuring the traffic-flow in a real-time for current Intelligent Traffic System. However, as a battery-operated electronic device, regularly replacing battery remains a great challenge, especially in the remote area and wide distribution. Here, we report a self-powered active wireless traffic volume sensor by using a rotating-disk-based hybridized nanogenerator of triboelectric nanogenerator and electromagnetic generator as the sustainable power source. Operated at a rotating rate of 1000 rpm, the device delivered an output power of 17.5 mW, corresponding to a volume power density of 55.7 W/m(3) (Pd = P/V, see Supporting Information for detailed calculation) at a loading resistance of 700 Ω. The hybridized nanogenerator was demonstrated to effectively harvest energy from wind generated by a moving vehicle through the tunnel. And the delivered power is capable of triggering a counter via a wireless transmitter for real-time monitoring the traffic volume in the tunnel. This study further expands the applications of triboelectric nanogenerators for high-performance ambient mechanical energy harvesting and as sustainable power sources for driving wireless traffic volume sensors.

Memory controllers for real-time embedded systems predictable and composable real-time systems

CERN Document Server

Akesson, Benny

2012-01-01

  Verification of real-time requirements in systems-on-chip becomes more complex as more applications are integrated. Predictable and composable systems can manage the increasing complexity using formal verification and simulation.  This book explains the concepts of predictability and composability and shows how to apply them to the design and analysis of a memory controller, which is a key component in any real-time system. This book is generally intended for readers interested in Systems-on-Chips with real-time applications.   It is especially well-suited for readers looking to use SDRAM memories in systems with hard or firm real-time requirements. There is a strong focus on real-time concepts, such as predictability and composability, as well as a brief discussion about memory controller architectures for high-performance computing. Readers will learn step-by-step how to go from an unpredictable SDRAM memory, offering highly variable bandwidth and latency, to a predictable and composable shared memory...

Spatiotemporal characteristics of elderly population's traffic accidents in Seoul using space-time cube and space-time kernel density estimation.

Science.gov (United States)

Kang, Youngok; Cho, Nahye; Son, Serin

2018-01-01

The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people's traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people's traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people's traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers' traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims' hotspots are more sporadic than elderly drivers' hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future.

A natural-color mapping for single-band night-time image based on FPGA

Science.gov (United States)

Wang, Yilun; Qian, Yunsheng

2018-01-01

A natural-color mapping for single-band night-time image method based on FPGA can transmit the color of the reference image to single-band night-time image, which is consistent with human visual habits and can help observers identify the target. This paper introduces the processing of the natural-color mapping algorithm based on FPGA. Firstly, the image can be transformed based on histogram equalization, and the intensity features and standard deviation features of reference image are stored in SRAM. Then, the real-time digital images' intensity features and standard deviation features are calculated by FPGA. At last, FPGA completes the color mapping through matching pixels between images using the features in luminance channel.

Real-time bus location monitoring using Arduino

Science.gov (United States)

Ibrahim, Mohammad Y. M.; Audah, Lukman

2017-09-01

The Internet of Things (IoT) is the network of objects, such as a vehicles, mobile devices, and buildings that have electronic components, software, and network connectivity that enable them to collect data, run commands, and be controlled through the Internet. Controlling physical items from the Internet will increase efficiency and save time. The growing number of devices used by people increases the practicality of having IoT devices on the market. The IoT is also an opportunity to develop products that can save money and time and increase work efficiency. Initially, they need more efficiency for real-time bus location systems, especially in university campuses. This system can easily find the accurate locations of and distances between each bus stop and the estimated time to reach a new location. This system has been separated into two parts, which are the hardware and the software. The hardware parts are the Arduino Uno and the Global Positioning System (GPS), while Google Earth and GpsGate are the software parts. The GPS continuously takes input data from the satellite and stores the latitude and longitude values in the Arduino Uno. If we want to track the vehicle, we need to send the longitude and latitude as a message to the Google Earth software to convert these into maps for navigation. Once the Arduino Uno is activated, it takes the last received latitude and longitude positions' values from GpsGate and sends a message to Google Earth. Once the message has been sent to Google Earth, the current location will be shown, and navigation will be activated automatically. Then it will be broadcast using ManyCam, Google+ Hangouts, and YouTube, as well as Facebook, and appear to users. The additional features use Google Forms for determining problems faced by students, who can also take immediate action against the responsible department. Then after several successful simulations, the results will be shown in real time on a map.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery.

Science.gov (United States)

Qi, Baogui; Shi, Hao; Zhuang, Yin; Chen, He; Chen, Liang

2018-04-25

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery

Science.gov (United States)

Qi, Baogui; Zhuang, Yin; Chen, He; Chen, Liang

2018-01-01

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited. PMID:29693585

Evaluating Environmental Impact of Traffic Congestion in Real Time Based on Sparse Mobile Crowd-sourced Data

Science.gov (United States)

2018-02-02

Traffic congestion at arterial intersections and freeway bottlenecks degrades the air quality and threatens the public health. Conventionally, air pollutants are monitored by sparsely-distributed Quality Assurance Air Monitoring Sites. Sparse mobile ...

QoS Support Polling Scheme for Multimedia Traffic in Wireless LAN MAC Protocol

Institute of Scientific and Technical Information of China (English)

YANG Zhijun; ZHAO Dongfeng

2008-01-01

Quality of service (QoS) support is a key attribute for multimedia traffic including video, voice, and data in wireless local area networks (LANs) but is limited in 802.11-based wireless LANs. A polling-based scheme called the point coordination function (PCF) was developed for 802.11 LANs to support the trans-mission of multimedia traffic. However, the PCF is not able to meet the desired practical traffic differentiation requirements for real-time data. This paper describes a QoS support polling scheme based on the IEEE 802.11 medium access control (MAC) protocol. The scheme uses a two-level polling mechanism with the QoS classes differentiated by two different access policies. Stations with higher priority traffic such as key or real-time data form the first level and can access the common channel through an exhaustive access policy. Other stations with lower priority traffic form the second level and can access the channel through a gated access policy. A system model based on imbedded Markov chain theory and a generation function were setup to explicitly analyze the mean information packet waiting time of the two-level polling scheme. Theo-retical and simulation results show that the new scheme efficiently differentiates services to guarantee better QoS and system stability.

Traffic congestion forecasting model for the INFORM System. Final report

Energy Technology Data Exchange (ETDEWEB)

Azarm, A.; Mughabghab, S.; Stock, D.

1995-05-01

This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

Highway traffic simulation on multi-processor computers

Energy Technology Data Exchange (ETDEWEB)

Hanebutte, U.R.; Doss, E.; Tentner, A.M.

1997-04-01

A computer model has been developed to simulate highway traffic for various degrees of automation with a high level of fidelity in regard to driver control and vehicle characteristics. The model simulates vehicle maneuvering in a multi-lane highway traffic system and allows for the use of Intelligent Transportation System (ITS) technologies such as an Automated Intelligent Cruise Control (AICC). The structure of the computer model facilitates the use of parallel computers for the highway traffic simulation, since domain decomposition techniques can be applied in a straight forward fashion. In this model, the highway system (i.e. a network of road links) is divided into multiple regions; each region is controlled by a separate link manager residing on an individual processor. A graphical user interface augments the computer model kv allowing for real-time interactive simulation control and interaction with each individual vehicle and road side infrastructure element on each link. Average speed and traffic volume data is collected at user-specified loop detector locations. Further, as a measure of safety the so- called Time To Collision (TTC) parameter is being recorded.

A sensemaking perspective on framing the mental picture of air traffic controllers.

Science.gov (United States)

Malakis, Stathis; Kontogiannis, Tom

2013-03-01

It has long been recognized that controller strategies are based on a 'mental picture' or representation of traffic situations. Earlier studies indicated that controllers tend to maintain a selective representation of traffic flows based on a few salient traffic features that point out to interesting events (e.g., potential conflicts). A field study is presented in this paper that examines salient features or 'knowledge variables' that constitute the building blocks of controller mental pictures. Verbal reports from participants, a field experiment and observations of real-life scenarios provided insights into the cognitive processes that shape and reframe the mental pictures of controllers. Several cognitive processes (i.e., problem detection, elaboration, reframing and replanning) have been explored within a particular framework of sensemaking stemming from the data/frame theory (Klein et al., 2007). Cognitive maps, representing standard and non-standard air traffic flows, emerged as an explanatory framework for making sense of traffic patterns and for reframing mental pictures. The data/frame theory proved to be a useful theoretical tool for investigating complex cognitive phenomena. The findings of the study have implications for the design of training curricula and decision support systems in air traffic control systems. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

High-speed and high-fidelity system and method for collecting network traffic

Science.gov (United States)

Weigle, Eric H [Los Alamos, NM

2010-08-24

A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

Traffic State Estimation Using Connected Vehicles and Stationary Detectors

Directory of Open Access Journals (Sweden)

Ellen F. Grumert

2018-01-01

Full Text Available Real-time traffic state estimation is of importance for efficient traffic management. This is especially the case for traffic management systems that require fast detection of changes in the traffic conditions in order to apply an effective control measure. In this paper, we propose a method for estimating the traffic state and speed and density, by using connected vehicles combined with stationary detectors. The aim is to allow fast and accurate estimation of changes in the traffic conditions. The proposed method does only require information about the speed and the position of connected vehicles and can make use of sparsely located stationary detectors to limit the dependence on the infrastructure equipment. An evaluation of the proposed method is carried out by microscopic traffic simulation. The traffic state estimated using the proposed method is compared to the true simulated traffic state. Further, the density estimates are compared to density estimates from one detector-based method, one combined method, and one connected-vehicle-based method. The results of the study show that the proposed method is a promising alternative for estimating the traffic state in traffic management applications.

Mahanaxar: quality of service guarantees in high-bandwidth, real-time streaming data storage

Energy Technology Data Exchange (ETDEWEB)

Bigelow, David [Los Alamos National Laboratory; Bent, John [Los Alamos National Laboratory; Chen, Hsing-Bung [Los Alamos National Laboratory; Brandt, Scott [UCSC

2010-04-05

Large radio telescopes, cyber-security systems monitoring real-time network traffic, and others have specialized data storage needs: guaranteed capture of an ultra-high-bandwidth data stream, retention of the data long enough to determine what is 'interesting,' retention of interesting data indefinitely, and concurrent read/write access to determine what data is interesting, without interrupting the ongoing capture of incoming data. Mahanaxar addresses this problem. Mahanaxar guarantees streaming real-time data capture at (nearly) the full rate of the raw device, allows concurrent read and write access to the device on a best-effort basis without interrupting the data capture, and retains data as long as possible given the available storage. It has built in mechanisms for reliability and indexing, can scale to meet arbitrary bandwidth requirements, and handles both small and large data elements equally well. Results from our prototype implementation shows that Mahanaxar provides both better guarantees and better performance than traditional file systems.

Cross-Layer Scheduling and Resource Allocation for Heterogeneous Traffic in 3G LTE

Directory of Open Access Journals (Sweden)

Richard Musabe

2014-01-01

Full Text Available 3G long term evolution (LTE introduces stringent needs in order to provide different kinds of traffic with Quality of Service (QoS characteristics. The major problem with this nature of LTE is that it does not have any paradigm scheduling algorithm that will ideally control the assignment of resources which in turn will improve the user satisfaction. This has become an open subject and different scheduling algorithms have been proposed which are quite challenging and complex. To address this issue, in this paper, we investigate how our proposed algorithm improves the user satisfaction for heterogeneous traffic, that is, best-effort traffic such as file transfer protocol (FTP and real-time traffic such as voice over internet protocol (VoIP. Our proposed algorithm is formulated using the cross-layer technique. The goal of our proposed algorithm is to maximize the expected total user satisfaction (total-utility under different constraints. We compared our proposed algorithm with proportional fair (PF, exponential proportional fair (EXP-PF, and U-delay. Using simulations, our proposed algorithm improved the performance of real-time traffic based on throughput, VoIP delay, and VoIP packet loss ratio metrics while PF improved the performance of best-effort traffic based on FTP traffic received, FTP packet loss ratio, and FTP throughput metrics.

Essays in real-time forecasting

OpenAIRE

Liebermann, Joelle

2012-01-01

This thesis contains three essays in the field of real-time econometrics, and more particularlyforecasting.The issue of using data as available in real-time to forecasters, policymakers or financialmarkets is an important one which has only recently been taken on board in the empiricalliterature. Data available and used in real-time are preliminary and differ from ex-postrevised data, and given that data revisions may be quite substantial, the use of latestavailable instead of real-time can s...

REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO

Directory of Open Access Journals (Sweden)

M. S. Temiz

2012-07-01

Full Text Available In this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ±1 – 2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications.

Ovation Prime Real-Time

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Ovation Prime Real-Time (OPRT) product is a real-time forecast and nowcast model of auroral power and is an operational implementation of the work by Newell et...

Optimal task mapping in safety-critical real-time parallel systems; Placement optimal de taches pour les systemes paralleles temps-reel critiques

Energy Technology Data Exchange (ETDEWEB)

Aussagues, Ch

1998-12-11

This PhD thesis is dealing with the correct design of safety-critical real-time parallel systems. Such systems constitutes a fundamental part of high-performance systems for command and control that can be found in the nuclear domain or more generally in parallel embedded systems. The verification of their temporal correctness is the core of this thesis. our contribution is mainly in the following three points: the analysis and extension of a programming model for such real-time parallel systems; the proposal of an original method based on a new operator of synchronized product of state machines task-graphs; the validation of the approach by its implementation and evaluation. The work addresses particularly the main problem of optimal task mapping on a parallel architecture, such that the temporal constraints are globally guaranteed, i.e. the timeliness property is valid. The results incorporate also optimally criteria for the sizing and correct dimensioning of a parallel system, for instance in the number of processing elements. These criteria are connected with operational constraints of the application domain. Our approach is based on the off-line analysis of the feasibility of the deadline-driven dynamic scheduling that is used to schedule tasks inside one processor. This leads us to define the synchronized-product, a system of linear, constraints is automatically generated and then allows to calculate a maximum load of a group of tasks and then to verify their timeliness constraints. The communications, their timeliness verification and incorporation to the mapping problem is the second main contribution of this thesis. FInally, the global solving technique dealing with both task and communication aspects has been implemented and evaluated in the framework of the OASIS project in the LETI research center at the CEA/Saclay. (author) 96 refs.

Real-time data collection technologies: Enhanced decision-making and cost savings January, 2005

International Nuclear Information System (INIS)

Rust, T.L.; Vu, H.Q.

2006-01-01

Hand-held computers, Geographic Information Systems (GIS), and wireless communication devices are rapidly replacing traditional methods for field monitoring and data collection. Although pencil and paper remain important means of data transcription, field technicians can now use Personal Digital Assistants (PDA) to record their field notes and monitoring data. As data are uploaded wirelessly from the field, decision-makers can view realtime reports and maps that identify sample locations and monitoring results. The combination of PDAs, wireless communications, and web-based GIS provides field personnel and decision-makers many benefits throughout the life cycle of a project, including improved data consistency, real-time transfer of data from field locations to centralized databases, input validation, elimination of transcription errors, and cost savings. Concerns have been expressed however, about investing in hardware, software, and training for a new technology. This paper, based on several years of experience using wireless technologies for dozens of projects, is focused specifically on two case studies. The first case study is a large lead removal site in the Midwest at which real-time data collection technologies were used throughout the project to collect thousands of data points. The second is the Hurricane Katrina/Rita emergency response requiring rapid data collection under extraordinary circumstances. At both sites, the use of real-time data collection technologies significantly improved the data management process which reduced overall costs and increased efficiency. These results could not have been achieved using traditional data collection procedures. The oral presentation will focus on the advantages and disadvantages of the real-time data collection technologies, lessons learned, and planning considerations. A live demonstration, following a typical data collection scenario in which data are collected and plotted on a GIS map in near real-time

Specification and Verification of Distributed Embedded Systems: A Traffic Intersection Product Family

Directory of Open Access Journals (Sweden)

José Meseguer

2010-09-01

Full Text Available Distributed embedded systems (DESs are no longer the exception; they are the rule in many application areas such as avionics, the automotive industry, traffic systems, sensor networks, and medical devices. Formal DES specification and verification is challenging due to state space explosion and the need to support real-time features. This paper reports on an extensive industry-based case study involving a DES product family for a pedestrian and car 4-way traffic intersection in which autonomous devices communicate by asynchronous message passing without a centralized controller. All the safety requirements and a liveness requirement informally specified in the requirements document have been formally verified using Real-Time Maude and its model checking features.

Real-time monitoring of radiofrequency ablation of liver tumors using thermal-dose calculation by MR temperature imaging: initial results in nine patients, including follow-up

International Nuclear Information System (INIS)

Lepetit-Coiffe, Matthieu; Quesson, Bruno; Moonen, Chrit T.W.; Laumonier, Herve; Trillaud, Herve; Seror, Olivier; Sesay, Musa-Bahazid; Grenier, Nicolas

2010-01-01

To assess the practical feasibility and effectiveness of real-time magnetic resonance (MR) temperature monitoring for the radiofrequency (RF) ablation of liver tumours in a clinical setting, nine patients (aged 49-87 years, five men and four women) with one malignant tumour (14-50 mm, eight hepatocellular carcinomas and one colorectal metastasis), were treated by 12-min RF ablation using a 1.5-T closed magnet for real-time temperature monitoring. The clinical monopolar RF device was filtered at 64 MHz to avoid electromagnetic interference. Real-time computation of thermal-dose (TD) maps, based on Sapareto and Dewey's equation, was studied to determine its ability to provide a clear end-point of the RF procedure. Absence of local recurrence on follow-up MR images obtained 45 days after the RF ablation was used to assess the apoptotic and necrotic prediction obtained by real-time TD maps. Seven out of nine tumours were completely ablated according to the real-time TD maps. Compared with 45-day follow-up MR images, TD maps accurately predicted two primary treatment failures, but were not relevant in the later progression of one case of secondary local tumour. The real-time TD concept is a feasible and promising monitoring method for the RF ablation of liver tumours. (orig.)

Real-time monitoring of radiofrequency ablation of liver tumors using thermal-dose calculation by MR temperature imaging: initial results in nine patients, including follow-up

Energy Technology Data Exchange (ETDEWEB)

Lepetit-Coiffe, Matthieu; Quesson, Bruno; Moonen, Chrit T.W. [Universite Victor Segalen Bordeaux 2, Laboratoire Imagerie Moleculaire et Fonctionnelle: de la physiologie a la therapie CNRS UMR 5231, Bordeaux Cedex (France); Laumonier, Herve; Trillaud, Herve [Universite Victor Segalen Bordeaux 2, Laboratoire Imagerie Moleculaire et Fonctionnelle: de la physiologie a la therapie CNRS UMR 5231, Bordeaux Cedex (France); Service de Radiologie, Hopital Saint-Andre, CHU Bordeaux, Bordeaux (France); Seror, Olivier [Universite Victor Segalen Bordeaux 2, Laboratoire Imagerie Moleculaire et Fonctionnelle: de la physiologie a la therapie CNRS UMR 5231, Bordeaux Cedex (France); Service de Radiologie, Hopital Jean Verdier, Bondy (France); Sesay, Musa-Bahazid [Service d' Anesthesie Reanimation III, Hopital Pellegrin, CHU Bordeaux, Bordeaux (France); Grenier, Nicolas [Universite Victor Segalen Bordeaux 2, Laboratoire Imagerie Moleculaire et Fonctionnelle: de la physiologie a la therapie CNRS UMR 5231, Bordeaux Cedex (France); Service d' Imagerie Diagnostique et Therapeutique de l' Adulte, Hopital Pellegrin, CHU Bordeaux, Bordeaux (France)

2010-01-15

To assess the practical feasibility and effectiveness of real-time magnetic resonance (MR) temperature monitoring for the radiofrequency (RF) ablation of liver tumours in a clinical setting, nine patients (aged 49-87 years, five men and four women) with one malignant tumour (14-50 mm, eight hepatocellular carcinomas and one colorectal metastasis), were treated by 12-min RF ablation using a 1.5-T closed magnet for real-time temperature monitoring. The clinical monopolar RF device was filtered at 64 MHz to avoid electromagnetic interference. Real-time computation of thermal-dose (TD) maps, based on Sapareto and Dewey's equation, was studied to determine its ability to provide a clear end-point of the RF procedure. Absence of local recurrence on follow-up MR images obtained 45 days after the RF ablation was used to assess the apoptotic and necrotic prediction obtained by real-time TD maps. Seven out of nine tumours were completely ablated according to the real-time TD maps. Compared with 45-day follow-up MR images, TD maps accurately predicted two primary treatment failures, but were not relevant in the later progression of one case of secondary local tumour. The real-time TD concept is a feasible and promising monitoring method for the RF ablation of liver tumours. (orig.)

Automated real-time testing (ARTT) for embedded control systems (ECS)

International Nuclear Information System (INIS)

Hawkins, J; Howard, R; Nguyen, H.

2001-01-01

Many of today's automated real-time testing systems for embedded systems were developed using expensive custom hardware and software. In this article they describe how to use commercially available off-the-shelf hardware and software to design and develop an automated real-time test systems for Embedded Programmable Logic Controller (PLC) Based Control Systems. The system development began with the implementation of the VALI/TEST Pro testing methodology as a means for structuring the testing. Using this methodology, they were able to decompose system requirement documents for a Personnel Safety System (PSS) into its high, intermediate and detail level requirements. next, the validation procedures for the PSS system were decomposed into testing units called builds, test runs and test cases. To measure the PSS system's test coverage three levels of system requirements were mapped to their respective unit level of test using a specially constructed validation matrix that was designed to handle over 150 test cases and requirements. All of the above work led to the development of an Automated Real-Time Test System (ARTTS) that is capable of performing complete black box testing in real-time for Embedded PLC Based Control Systems. Also note, that the PSS system under test and mentioned in this paper is located at the Advance Photon Source (APS) at Argonne National Laboratory Basic Energy Science Facility in Argonne, Illinois

High-resolution, real-time mapping of surface soil moisture at the field scale using ground penetrating radar

Science.gov (United States)

Lambot, S.; Minet, J.; Slob, E.; Vereecken, H.; Vanclooster, M.

2008-12-01

Measuring soil surface water content is essential in hydrology and agriculture as this variable controls important key processes of the hydrological cycle such as infiltration, runoff, evaporation, and energy exchanges between the earth and the atmosphere. We present a ground-penetrating radar (GPR) method for automated, high-resolution, real-time mapping of soil surface dielectric permittivity and correlated water content at the field scale. Field scale characterization and monitoring is not only necessary for field scale management applications, but also for unravelling upscaling issues in hydrology and bridging the scale gap between local measurements and remote sensing. In particular, such methods are necessary to validate and improve remote sensing data products. The radar system consists of a vector network analyzer combined with an off-ground, ultra-wideband monostatic horn antenna, thereby setting up a continuous-wave steeped-frequency GPR. Radar signal analysis is based on three-dimensional electromagnetic inverse modelling. The forward model accounts for all antenna effects, antenna-soil interactions, and wave propagation in three-dimensional multilayered media. A fast procedure was developed to evaluate the involved Green's function, resulting from a singular, complex integral. Radar data inversion is focused on the surface reflection in the time domain. The method presents considerable advantages compared to the current surface characterization methods using GPR, namely, the ground wave and common reflection methods. Theoretical analyses were performed, dealing with the effects of electric conductivity on the surface reflection when non-negligible, and on near-surface layering, which may lead to unrealistic values for the surface dielectric permittivity if not properly accounted for. Inversion strategies are proposed. In particular the combination of GPR with electromagnetic induction data appears to be promising to deal with highly conductive soils

Minimal-Intrusion Traffic Monitoring And Analysis In Mission-Critical Communication Networks

Directory of Open Access Journals (Sweden)

Alberto Domingo Ajenjo

2003-10-01

Full Text Available A good knowledge of expected and actual traffic patterns is an essential tool for network planning, design and operation in deployed, mission-critical applications. This paper describes those needs, and explains the Traffic Monitoring and Analysis Platform (TMAP concept, as developed in support of NATO deployed military headquarters Communications and Information Systems. It shows how a TMAP was deployed to a real NATO exercise, to prove the concept and baseline the traffic needs per application, per user community and per time of day. Then, it analyses the obtained results and derives conclusions on how to integrate traffic monitoring and analysis platforms in future deployments.

The Traffic Adaptive Data Dissemination (TrAD Protocol for both Urban and Highway Scenarios

Directory of Open Access Journals (Sweden)

Bin Tian

2016-06-01

Full Text Available The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.

The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios.

Science.gov (United States)

Tian, Bin; Hou, Kun Mean; Zhou, Haiying

2016-06-21

The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.

VERSE - Virtual Equivalent Real-time Simulation

Science.gov (United States)

Zheng, Yang; Martin, Bryan J.; Villaume, Nathaniel

2005-01-01

Distributed real-time simulations provide important timing validation and hardware in the- loop results for the spacecraft flight software development cycle. Occasionally, the need for higher fidelity modeling and more comprehensive debugging capabilities - combined with a limited amount of computational resources - calls for a non real-time simulation environment that mimics the real-time environment. By creating a non real-time environment that accommodates simulations and flight software designed for a multi-CPU real-time system, we can save development time, cut mission costs, and reduce the likelihood of errors. This paper presents such a solution: Virtual Equivalent Real-time Simulation Environment (VERSE). VERSE turns the real-time operating system RTAI (Real-time Application Interface) into an event driven simulator that runs in virtual real time. Designed to keep the original RTAI architecture as intact as possible, and therefore inheriting RTAI's many capabilities, VERSE was implemented with remarkably little change to the RTAI source code. This small footprint together with use of the same API allows users to easily run the same application in both real-time and virtual time environments. VERSE has been used to build a workstation testbed for NASA's Space Interferometry Mission (SIM PlanetQuest) instrument flight software. With its flexible simulation controls and inexpensive setup and replication costs, VERSE will become an invaluable tool in future mission development.

High-resolution mapping of motor vehicle carbon dioxide emissions

Science.gov (United States)

McDonald, Brian C.; McBride, Zoe C.; Martin, Elliot W.; Harley, Robert A.

2014-05-01

A fuel-based inventory for vehicle emissions is presented for carbon dioxide (CO2) and mapped at various spatial resolutions (10 km, 4 km, 1 km, and 500 m) using fuel sales and traffic count data. The mapping is done separately for gasoline-powered vehicles and heavy-duty diesel trucks. Emission estimates from this study are compared with the Emissions Database for Global Atmospheric Research (EDGAR) and VULCAN. All three inventories agree at the national level within 5%. EDGAR uses road density as a surrogate to apportion vehicle emissions, which leads to 20-80% overestimates of on-road CO2 emissions in the largest U.S. cities. High-resolution emission maps are presented for Los Angeles, New York City, San Francisco-San Jose, Houston, and Dallas-Fort Worth. Sharp emission gradients that exist near major highways are not apparent when emissions are mapped at 10 km resolution. High CO2 emission fluxes over highways become apparent at grid resolutions of 1 km and finer. Temporal variations in vehicle emissions are characterized using extensive day- and time-specific traffic count data and are described over diurnal, day of week, and seasonal time scales. Clear differences are observed when comparing light- and heavy-duty vehicle traffic patterns and comparing urban and rural areas. Decadal emission trends were analyzed from 2000 to 2007 when traffic volumes were increasing and a more recent period (2007-2010) when traffic volumes declined due to recession. We found large nonuniform changes in on-road CO2 emissions over a period of 5 years, highlighting the importance of timely updates to motor vehicle emission inventories.

Spatiotemporal characteristics of elderly population’s traffic accidents in Seoul using space-time cube and space-time kernel density estimation

Science.gov (United States)

Cho, Nahye; Son, Serin

2018-01-01

The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people’s traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people’s traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people’s traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers’ traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims’ hotspots are more sporadic than elderly drivers’ hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future. PMID:29768453