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Assessment of Pedestrian Fatality Risk at Unsignalized Crosswalks by Means of Simulation

In: Traffic and Granular Flow '17

Author

Listed:
  • Claudio Feliciani

    (The University of Tokyo)

  • Luca Crociani

    (University of Milano-Bicocca)

  • Andrea Gorrini

    (University of Milano-Bicocca)

  • Giuseppe Vizzari

    (University of Milano-Bicocca)

  • Katsuhiro Nishinari

    (The University of Tokyo)

  • Stefania Bandini

    (The University of Tokyo
    University of Milano-Bicocca)

Abstract

Unsignalized crosswalks are one of the most critical/risky traffic infrastructures in terms of safety, due to potentially vehicle–pedestrian conflictual interactions. Many accidents occur there and elderly pedestrians are among the most vulnerable victims. In a previous work, a simulation model has been developed with the aim of predicting traffic volumes and waiting times by reproducing the behavior of pedestrians and drivers during crossing attempts. Calibration and validation was performed based on experimental data gained through a field observation in an area with a significant population of elderlies. In this paper, we are focusing on safety issues and the simulation model has been adapted to include collisions between vehicles and pedestrians. The new simulation model presented here allows to compute the risk of an unsignalized crosswalk by considering both frequency and gravity of collisions. We consequently used the simulation model to evaluate the efficacy of particular policies. Simulation results show that while speed limit enforcement has an important effect in reducing pedestrian causalities, alternative and indirect solutions aiming at improving drivers’ awareness are also effective to improve safety.

Suggested Citation

  • Claudio Feliciani & Luca Crociani & Andrea Gorrini & Giuseppe Vizzari & Katsuhiro Nishinari & Stefania Bandini, 2019. "Assessment of Pedestrian Fatality Risk at Unsignalized Crosswalks by Means of Simulation," Springer Books, in: Samer H. Hamdar (ed.), Traffic and Granular Flow '17, pages 423-431, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-11440-4_46
    DOI: 10.1007/978-3-030-11440-4_46
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