A probabilistic model of pedestrian crossing behavior at signalized intersections for connected vehicles

被引:50
|
作者
Hashimoto, Yoriyoshi [1 ]
Gu, Yanlei [2 ]
Hsu, Li-Ta [2 ]
Iryo-Asano, Miho [2 ]
Kamijo, Shunsuke [2 ]
机构
[1] Univ Tokyo, Grad Sch Informat Sci & Technol, Bunkyo Ku, Tokyo 1138654, Japan
[2] Univ Tokyo, Inst Ind Sci, Meguro Ku, Tokyo 1538505, Japan
关键词
Pedestrian behavior; Signalized intersection; Active safety system; Connected vehicle; Dynamic Bayesian Network; CROSSWALKS; TIME;
D O I
10.1016/j.trc.2016.07.011
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Active safety systems which assess highly dynamic traffic situations including pedestrians are required with growing demands in autonomous driving and Connected Vehicles. In this paper, we focus on one of the most hazardous traffic situations: the possible collision between a pedestrian and a turning vehicle at signalized intersections. This paper presents a probabilistic model of pedestrian behavior to signalized crosswalks. In order to model the behavior of pedestrian, we take not only pedestrian physical states but also contextual information into account. We propose a model based on the Dynamic Bayesian Network which integrates relationships among the intersection context information and the pedestrian behavior in the same way as a human. The particle filter is used to estimate the pedestrian states, including position, crossing decision and motion type. Experimental evaluation using real traffic data shows that this model is able to recognize the pedestrian crossing decision in a few seconds from the traffic signal and pedestrian position information. This information is assumed to be obtained with the development of Connected Vehicle. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:164 / 181
页数:18
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