Abstract
This study aims to develop a microscopic pedestrian behavior model considering various interactions on pedestrian dynamics at crosswalks. Particularly, we take into account the evasion behavior with counter-flow pedestrians, the following behavior with leader pedestrians, and the collision avoidance behavior with vehicles. Aerial video data at one intersection in Beijing, China are extracted for model calibration. A microscopic calibration approach based on maximum likelihood estimation is applied to estimate the parameters of a modified social force model. Finally, we validate step-wise speed, step-wise acceleration, step-wise direction change, crossing time and lane formation phenomenon by comparing the real data and simulation outputs.
Highlights
Studying the self-organization phenomena of pedestrian crowd is an active subject in transportation science
Existing pedestrian behavior models can be classified into three categories: macroscopic, mesoscopic and microscopic models
This study aims to fill this gap by developing a microscopic model considering various interaction behaviors among road users at crosswalk
Summary
Studying the self-organization phenomena of pedestrian crowd is an active subject in transportation science. Pedestrian behavior modeling has attracted considerable attentions [1,2,3,4,5,6,7]. A better understanding of the interaction behavior would help to improve microscopic simulation and allow more accurate prediction of their behavior for various situations. This helps to evaluate the service and safety level on pedestrian related traffic, such as pedestrian movement in urban streets and crosswalks. Mesoscopic and microscopic models have attracted much attention because they enable to offer a more detailed analysis on pedestrian behavior
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