DDDAS-based multi-scale framework for pedestrian behavior modeling and interactions with drivers

  • Hui Xi
  • Published 2012 in Winter Simulation Conference

Abstract

A multi-scale simulation framework is proposed to analyze pedestrian delays at signalized crosswalks in large urban areas under different conditions. An aggregated-level model runs in normal conditions, where each crosswalk is represented as an agent. A derived probability function extended from Adams' model is utilized to estimate an average pedestrian delay with corresponding traffic flow rate and traffic light control at each crosswalk. When an abnormality is detected, a detailed-level model with each pedestrian being an agent is executed in the affected subareas. Pedestrian decision-making under abnormal conditions, physical movement, and crowd congestion are explicitly considered in the detailed-level model. In addition, pedestrian-driver interactions under unsignalized condition such as midblock crossing have been modeled as a two-player Pareto game. By mimicking cognitive decision making processes of drivers and pedestrians, we intend to identify the significant variables that help improve comfort and convenience as well as safety of pedestrian crossing.

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Cite this paper

@inproceedings{Xi2012DDDASbasedMF, title={DDDAS-based multi-scale framework for pedestrian behavior modeling and interactions with drivers}, author={Hui Xi}, booktitle={Winter Simulation Conference}, year={2012} }