A novel pedestrian road crossing simulator for dynamic traffic light scheduling systems





Citation of Original Publication

Dayuan Tan, Mohamed Younis, Wassila Lalouani, Shuyao Fan & Guozhi Song (2023) A novel pedestrian road crossing simulator for dynamic traffic light scheduling systems, Journal of Intelligent Transportation Systems, DOI: 10.1080/15472450.2023.2186229


This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Intelligent Transportation Systems on 12 March, 2023, available online: http://www.tandfonline.com/https://doi.org/10.1080/15472450.2023.2186229.
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The major advances in intelligent transportation systems are pushing societal services toward autonomy where road management is to be more agile in order to cope with changes and continue to yield optimal performance. However, the pedestrian experience is not sufficiently considered. Particularly, signalized intersections are expected to be popular if not dominant in urban settings where pedestrian density is high. This paper presents the design of a novel environment for simulating human motion on signalized crosswalks at a fine-grained level. Such a simulation not only captures typical behavior, but also handles cases where large pedestrian groups cross from both directions. The proposed simulator is instrumental for optimized road configuration management where the pedestrians’ quality of experience, for example, waiting time, is factored in. The validation results using field data show that an accuracy of 98.37% can be obtained for the estimated crossing time. Other results using synthetic data show that our simulator enables optimized traffic light scheduling that diminishes pedestrians’ waiting time without sacrificing vehicular throughput.