Modeling reaction time within a traffic simulation model
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Ben-Akiva_Modeling reaction.pdf
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Author(s)
Basak, Kakali
Hetu, Seth N.
Azevedo, Carlos Lima
Loganathan, Harish
Toledo, Tomer
Xu, Runmin
Xu, Yan
Peh, Li-Shiuan
Ben-Akiva, Moshe E.
Li, Zhemin
Date Issued
October 2013
Journal
Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Basak, Kakali, Seth N. Hetu, Zhemin Li, Carlos Lima Azevedo, Harish Loganathan, Tomer Toledo, Runmin Xu, Yan Xu, Li-Shiuan Peh, and Moshe Ben-Akiva. “Modeling Reaction Time Within a Traffic Simulation Model.” 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) (October 2013).
Version
Author's final manuscript
Abstract
Human reaction time has a substantial effect on modeling of human behavior at a microscopic level. Drivers and pedestrian do not react to an event instantaneously; rather, they take time to perceive the event, process the information, decide on a response and finally enact their decision. All these processes introduce delay. As human movement is simulated at increasingly fine-grained resolutions, it becomes critical to consider the delay due to reaction time if one is to achieve accurate results. Most existing simulators over-simplify the reaction time implementation to reduce computational overhead and memory requirements. In this paper, we detail the framework which we are developing within the SimMobility Short Term Simulator (a microscopic traffic simulator), which is capable of explicitly modeling reaction time for each person in a detailed, flexible manner. This framework will enable modelers to set realistic reaction time values, relying on the simulator to handle implementation and optimization considerations. Following this, we report our findings demonstrating the impact of reaction time on traffic dynamics within several simulation scenarios. The findings indicate that in the incorporation of reaction time within microscopic simulations improves the traffic dynamics that produces more realistic traffic condition.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1109/ITSC.2013.6728249
