A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks

Accid Anal Prev. 2016 Oct;95(Pt B):425-437. doi: 10.1016/j.aap.2016.04.014. Epub 2016 May 18.

Abstract

At unsignalized crosswalks, interactions between pedestrians and vehicles often lead to traffic safety hazards due to absence of traffic control and unclear right-of-ways. To address this safety problem, there is a need to understand the interaction behaviors of pedestrians and vehicles that are complicated by a variety of traffic and roadway attributes. The prime objective of this study is to establish a reliable simulation model to represent the vehicle yielding and pedestrian crossing behaviors at unsignalized crosswalks in a realistic way. The model is calibrated with detailed behavioral data collected and extracted from field observations. The capability of the calibrated model in predicting the pedestrian-interaction events as well as estimating the driver yielding rate and pedestrian delay are also tested and demonstrated. Meanwhile, the traffic dynamics in the vicinity of the crosswalk can be meaningfully represented with simulation results based on the model. Moreover, with the definitions of the vehicle-pedestrian conflicts, the proposed model is capable to evaluate the pedestrian safety. Thereby, the simulation model has the potential to serve as a useful tool for assessing safety performance and traffic operations at existing facilities. Furthermore, the model can enable the evaluation of policy effectiveness and the selection of engineering treatments at unsignalized crosswalks to improve safety and efficiency of pedestrian crossing.

Keywords: Cellular automaton model; Crossing behavior; Simulation; Unsignalized crosswalks; Yielding behavior.

MeSH terms

  • Accidents, Traffic* / statistics & numerical data
  • Automobile Driving*
  • Calibration
  • Engineering
  • Environment Design*
  • Female
  • Humans
  • Male
  • Models, Biological*
  • Pedestrians*
  • Risk-Taking*
  • Safety*
  • Walking