The Experts below are selected from a list of 243 Experts worldwide ranked by ideXlab platform
Carl B. Dietrich - One of the best experts on this subject based on the ideXlab platform.
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CAVS - Experimental Analysis of DSRC for Radio Signaling at Grade Crossings
2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS), 2019Co-Authors: Junsung Choi, Vuk Marojevic, Christopher R. Anderson, Carl B. DietrichAbstract:Despite the breakthroughs of wireless technology, only a few systems have been proposed for improving the safety at Railroad Crossings. We propose using and adapting the Dedicated Short-Range Communications (DSRC) protocol for Railroad crossing protection to improve the safety of both trains and vehicles. This paper analyzes the radio frequency (RF) propagation channel and the DSRC system performance based on measurements at Railroad Crossings on a test track in wide-open spaces and artificial shadowing environments. These environments assimilate typical rural and urban settings. Our results show that the channel around Railroad Crossings has an approximately 3 to 5 dB lower Rician K factor and 2 higher path loss exponent when compared to typical Vehicle-to-Vehicle or Vehicle-to-Infrastructure environments; the RMS delay spread in the shadowing environment is similar to that of a tunnel or non-line of sight highway scenario. For the DSRC performance evaluation we use the packet error rate of the warning messages transmitted by the approaching train and received by cars near the Railroad crossing. We find that warning messages are reliably received before the minimum notification distance in a wide-open space regardless of the train speed and in an artificial shadowing environment only when LoS condition provided.
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Experimental Analysis of DSRC for Radio Signaling at Grade Crossings
2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS), 2019Co-Authors: Junsung Choi, Vuk Marojevic, Christopher R. Anderson, Carl B. DietrichAbstract:Despite the breakthroughs of wireless technology, only a few systems have been proposed for improving the safety at Railroad Crossings. We propose using and adapting the Dedicated Short-Range Communications (DSRC) protocol for Railroad crossing protection to improve the safety of both trains and vehicles. This paper analyzes the radio frequency (RF) propagation channel and the DSRC system performance based on measurements at Railroad Crossings on a test track in wide-open spaces and artificial shadowing environments. These environments assimilate typical rural and urban settings. Our results show that the channel around Railroad Crossings has an approximately 3 to 5 dB lower Rician K factor and 2 higher path loss exponent when compared to typical Vehicle-to-Vehicle or Vehicle-to-Infrastructure environments; the RMS delay spread in the shadowing environment is similar to that of a tunnel or non-line of sight highway scenario. For the DSRC performance evaluation we use the packet error rate of the warning messages transmitted by the approaching train and received by cars near the Railroad crossing. We find that warning messages are reliably received before the minimum notification distance in a wide-open space regardless of the train speed and in an artificial shadowing environment only when LoS condition provided.
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VTC-Fall - Measurements and Analysis of DSRC for V2T Safety-Critical Communications
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 2018Co-Authors: Junsung Choi, Vuk Marojevic, Carl B. DietrichAbstract:Despite the evolution of wireless technology, enabling safety-critical applications, only a few systems have been developed for improving the safety at Railroad Crossings. We present a Vehicle-to-Train (V2T) communications architecture for an early warning application carried over Dedicated Short-Range Communications (DSRC) radios. We conduct DSRC performance measurements at Railroad Crossings in suburban environments in the US to evaluate its feasibility. Two types of measurement setups are proposed: direct warning and indirect warning. Our results show that DSRC can be deployed and configured for effectively providing a V2T communications system to warn drivers of an approaching train.
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measurement and configuration of dsrc radios for vehicle to train v2t safety critical communications
IEEE Wireless Communications Letters, 2018Co-Authors: Junsung Choi, Vuk Marojevic, Christopher R. Anderson, Aakanksha Sharma, Biniyam Zewede, Randall Nealy, Jared Withers, Carl B. DietrichAbstract:Despite the rapid development of wireless technology, there has been little application of the technology to improve Railroad crossing safety. We present vehicle-to-Railroad channel characterization and dedicated short range communications (DSRC) performance results at Railroad Crossings in rural and suburban environments. Our results show that an omnidirectional antenna provides slightly better performance in rural conditions. However, a bi-directional antenna increased warning range by more than 200 m in suburban conditions. A proper configuration of the DSRC radio provides reliable warning of an approaching train for cars near a Railroad crossing.
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Measurements and Analysis of DSRC for V2T Safety-Critical Communications
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 2018Co-Authors: Junsung Choi, Vuk Marojevic, Carl B. DietrichAbstract:Despite the evolution of wireless technology, enabling safety-critical applications, only a few systems have been developed for improving the safety at Railroad Crossings. We present a Vehicle-to-Train (V2T) communications architecture for an early warning application carried over Dedicated Short-Range Communications (DSRC) radios. We conduct DSRC performance measurements at Railroad Crossings in suburban environments in the US to evaluate its feasibility. Two types of measurement setups are proposed: direct warning and indirect warning. Our results show that DSRC can be deployed and configured for effectively providing a V2T communications system to warn drivers of an approaching train.
Simon Washington - One of the best experts on this subject based on the ideXlab platform.
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bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty example applied to at grade Railroad Crossings in korea
Accident Analysis & Prevention, 2006Co-Authors: Simon Washington, Juhwan OhAbstract:Transportation professionals are sometimes required to make difficult transportation safety investment decisions in the face of uncertainty. In particular, an engineer may be expected to choose among an array of technologies and/or countermeasures to remediate perceived safety problems when: (1) little information is known about the countermeasure effects on safety; (2) information is known but from different regions, states, or countries where a direct generalization may not be appropriate; (3) where the technologies and/or countermeasures are relatively untested, or (4) where costs prohibit the full and careful testing of each of the candidate countermeasures via before-after studies. The importance of an informed and well-considered decision based on the best possible engineering knowledge and information is imperative due to the potential impact on the numbers of human injuries and deaths that may result from these investments. This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade Railroad Crossings (AGRXs) in the Republic of Korea are considered. Akin to "stated preference" methods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain 'best' estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade Railroad Crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems.
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Bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty: Example applied to at grade Railroad Crossings in Korea
Accident Analysis and Prevention, 2006Co-Authors: Simon Washington, Jutaek OhAbstract:Transportation professionals are sometimes required to make difficult transportation safety investment decisions in the face of uncertainty. In particular, an engineer may be expected to choose among an array of technologies and/or countermeasures to remediate perceived safety problems when: (1) little information is known about the countermeasure effects on safety; (2) information is known but from different regions, states, or countries where a direct generalization may not be appropriate; (3) where the technologies and/or countermeasures are relatively untested, or (4) where costs prohibit the full and careful testing of each of the candidate countermeasures via before-after studies. The importance of an informed and well-considered decision based on the best possible engineering knowledge and information is imperative due to the potential impact on the numbers of human injuries and deaths that may result from these investments. This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade Railroad Crossings (AGRXs) in the Republic of Korea are considered. Akin to "stated preference" methods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain 'best' estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade Railroad Crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems. ?? 2005 Elsevier Ltd. All rights reserved.
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bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty example applied to at grade Railroad Crossings in korea
Centre for Accident Research & Road Safety - Qld (CARRS-Q); Faculty of Health, 2006Co-Authors: Simon Washington, Juhwan OhAbstract:This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade Railroad Crossings (AGRXs) in the Republic of Korea are considered. Akin to “stated preference” methods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain ‘best’ estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade Railroad Crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems.
Li Zhang - One of the best experts on this subject based on the ideXlab platform.
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PROMOTING SAFETY AT Railroad Crossings BY REDUCING TRAFFIC DELAYS
2002Co-Authors: Antoine G. Hobeika, Li ZhangAbstract:This study develops an artificial neural network traffic control algorithm in order to optimize traffic delays around highway Railroad Crossings. The 2-step algorithm first designs a proper preemption phase plan, and then finds the optimized phase length. The aim of the preemption plan design is to maximize safety at grade Crossings. This can be achieved by designing the preemption plan so that highway traffic will be prevented from queuing on the grade crossing intersection. The optimized process will use as objective function traffic delays at intersections surrounding the grade crossing area. That function will be approximated and represented by neural network. Next, mathematical algorithms are employed to get the optimized length of phases so that total delays can be minimized. This research uses the CORSIM simulated traffic network package to conduct analysis and determine results.
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optimizing traffic network signals around Railroad Crossings model validations
Transportation Research Record, 2002Co-Authors: Li Zhang, Antoine G. Hobeika, Raj GhamanAbstract:A model entitled SOURCAO (signal optimization under rail crossing safety constraints) is discussed. There are two objectives in SOURCAO design: highway rail grade crossing (HRGC) safety consideration and highway traffic delay reduction around the Crossings. The first step in SOURCAO is to choose a proper preemption phase sequence to promote HRGC safety. This is done by the inference engine in an intelligent agent. The second step in SOURCAO is to find the optimized signal phase length to reduce highway traffic delay. The optimization process uses an objective function of the network traffic delay. The delay is approximated and represented by a multilayer perceptron neural network. The system inputs are online surveillance detector data and HRGC closure information. The system architecture of SOURCAO is briefly discussed. Various types of surveillance schemes in the proposed delay model are introduced. Emphasis is on validating the various models applied in SOURCAO. First, the proposed delay model is compared with queue delays obtained from the TSIS/CORSIM traffic simulation package. Second, the neural network delay forecast is verified through a cross-validation procedure. Finally, the objectives of SOURCAO are evaluated by TSIS/CORSIM. The average network delay for 20 runs of simulation is reduced over 8% (P = 0.05; t-test), and the unsafe queue time of the highway vehicle on HRGC in a test case is reduced.
D. Hosotani - One of the best experts on this subject based on the ideXlab platform.
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ICVS - Development and Long-Term Verification of Stereo Vision Sensor System for Controlling Safety at Railroad Crossing
Lecture Notes in Computer Science, 2009Co-Authors: D. Hosotani, I. Yoda, K. SakaueAbstract:Many people are involved in accidents every year at Railroad Crossings, but there is no suitable sensor for detecting pedestrians. We are therefore developing a stereo vision based system for ensuring safety at Railroad Crossings. In this system, stereo cameras are installed at the corners and are pointed toward the center of the Railroad crossing to monitor the passage of people. The system determines automatically and in real-time whether anyone or anything is inside the Railroad crossing, and whether anyone remains in the crossing. The system can be configured to automatically switch over to a surveillance monitor or automatically connect to an emergency brake system in the event of trouble. We have developed an original stereovision device and installed the remote controlled experimental system applied human detection algorithm in the commercial Railroad crossing. Then we store and analyze image data and tracking data throughout two years for standardization of system requirement specification.
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ICVS - Multi-point Stereo Camera System for Controlling Safety at Railroad Crossings
Fourth IEEE International Conference on Computer Vision Systems (ICVS'06), 2006Co-Authors: I. Yoda, K. Sakaue, D. HosotaniAbstract:Dozens of people are killed every year at Railroad Crossings, a situation that requires urgent action by Railroad companies, especially in major cities. We are therefore developing a ubiquitous stereo vision based system for ensuring safety at Railroad Crossings. In this system, stereo cameras are installed at four corners and are pointed toward the center of the Railroad crossing to monitor the passage of people. The system determines automatically and in real-time whether anyone or anything is inside the Railroad crossing, and whether anyone remains in the crossing. The system can be configured to automatically switch over to a surveillance monitor or automatically connect to an emergency brake system in the event of trouble.
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Multi-point Stereo Camera System for Controlling Safety at Railroad Crossings
Fourth IEEE International Conference on Computer Vision Systems (ICVS'06), 2006Co-Authors: I. Yoda, K. Sakaue, D. HosotaniAbstract:Dozens of people are killed every year at Railroad Crossings, a situation that requires urgent action by Railroad companies, especially in major cities. We are therefore developing a ubiquitous stereo vision based system for ensuring safety at Railroad Crossings. In this system, stereo cameras are installed at four corners and are pointed toward the center of the Railroad crossing to monitor the passage of people. The system determines automatically and in real-time whether anyone or anything is inside the Railroad crossing, and whether anyone remains in the crossing. The system can be configured to automatically switch over to a surveillance monitor or automatically connect to an emergency brake system in the event of trouble.
Juhwan Oh - One of the best experts on this subject based on the ideXlab platform.
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bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty example applied to at grade Railroad Crossings in korea
Accident Analysis & Prevention, 2006Co-Authors: Simon Washington, Juhwan OhAbstract:Transportation professionals are sometimes required to make difficult transportation safety investment decisions in the face of uncertainty. In particular, an engineer may be expected to choose among an array of technologies and/or countermeasures to remediate perceived safety problems when: (1) little information is known about the countermeasure effects on safety; (2) information is known but from different regions, states, or countries where a direct generalization may not be appropriate; (3) where the technologies and/or countermeasures are relatively untested, or (4) where costs prohibit the full and careful testing of each of the candidate countermeasures via before-after studies. The importance of an informed and well-considered decision based on the best possible engineering knowledge and information is imperative due to the potential impact on the numbers of human injuries and deaths that may result from these investments. This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade Railroad Crossings (AGRXs) in the Republic of Korea are considered. Akin to "stated preference" methods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain 'best' estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade Railroad Crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems.
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bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty example applied to at grade Railroad Crossings in korea
Centre for Accident Research & Road Safety - Qld (CARRS-Q); Faculty of Health, 2006Co-Authors: Simon Washington, Juhwan OhAbstract:This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade Railroad Crossings (AGRXs) in the Republic of Korea are considered. Akin to “stated preference” methods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain ‘best’ estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade Railroad Crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems.
