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Real Time Safety Model for Pedestrian Red-Light Running at Signalized Intersections in China

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  • Yao Wu

    (Jiangsu Key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China
    School of Modern Posts & Institute of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)

  • Yanyong Guo

    (Jiangsu Key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China
    Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 210096, China)

  • Wei Yin

    (Jiangsu Key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China)

Abstract

The traditional way to evaluate pedestrian safety is a reactive approach using the data at an aggregate level. The objective of this study is to develop real-time safety models for pedestrian red-light running using the signal cycle level traffic data. Traffic data for 464 signal cycles during 16 h were collected at eight crosswalks on two intersections in the city of Nanjing, China. Various real-time safety models of pedestrian red-light running were developed based on the different combination of explanatory variables using the Bayesian Poisson-lognormal (PLN) model. The Bayesian estimation approach based on Markov chain Monte Carlo simulation is utilized for the real-time safety models estimates. The models’ comparison results show that the model incorporated exposure, pedestrians’ characteristics and crossing maneuver, and traffic control and crosswalk design outperforms the model incorporated exposure and the model incorporated exposure, pedestrians’ characteristics, and crossing maneuver. The result indicates that including more variables in the real-time safety model could improve the model fit. The model estimation results show that pedestrian volume, ratio of males, ratio of pedestrians on phone talking, pedestrian waiting time, green ratio, signal type, and length of crosswalk are statistically significantly associated with the pedestrians’ red-light running. The findings from this study could be useful in real-time pedestrian safety evaluation as well as in crosswalk design and pedestrian signal optimization.

Suggested Citation

  • Yao Wu & Yanyong Guo & Wei Yin, 2021. "Real Time Safety Model for Pedestrian Red-Light Running at Signalized Intersections in China," Sustainability, MDPI, vol. 13(4), pages 1-11, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1695-:d:493424
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    References listed on IDEAS

    as
    1. Yang, Jianguo & Deng, Wen & Wang, Jinmei & Li, Qingfeng & Wang, Zhaoan, 2006. "Modeling pedestrians' road crossing behavior in traffic system micro-simulation in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 280-290, March.
    2. Behram Wali & Asad Khattak & Thomas Karnowski, 2020. "The relationship between driving volatility in time to collision and crash injury severity in a naturalistic driving environment," Papers 2010.04719, arXiv.org.
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