Behavior Evolution of Multi-Group in the Process of Pedestrian Crossing Based on Evolutionary Game Theory

Ran Zhang, Zhonghua Wei, Heng Gu and Shi Qiu
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Ran Zhang: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Zhonghua Wei: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Heng Gu: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Shi Qiu: School of Civil Engineering, Central South University, Changsha 410083, China

Sustainability, 2021, vol. 13, issue 4, 1-17

Abstract: The mixed traffic flow has an increasingly impact on the operation of urban traffic. To study the evolution law of multi-group behaviors in pedestrian crossing, we used the evolutionary game theory to establish a multi-group behavior evolution model for pedestrian crossing. The process of concern started from the risk perception and multi-group behavior choice. The evolutionary stability strategies, evolution trends, and factors affecting the evolutionary path of multi-group behaviors are discussed in this paper. This study found that evolutionary strategy equilibrium of pedestrians, drivers, and traffic managers not only relied on their own earning, but also on those of the other two groups. The factors affecting its behavior included the revenue factor and the limiting factor. Evolutionary game theory was used to analyze the multi-group interaction behavior of pedestrians, vehicle drivers, and traffic managers in the process of pedestrian crossing, as well as to analyze the behavior of traffic subjects in the process of pedestrian crossing. This paper provides a basis for decision-making for the traffic management department to manage road traffic, offering a new idea from the perspective of evolution for solving the conflict of interest at the crosswalk of the road section.

Keywords: multi-group behavior; pedestrian crossing; evolutionary game theory; behavioral evolution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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