中国安全科学学报 ›› 2017, Vol. 27 ›› Issue (5): 25-30.doi: 10.16265/j.cnki.issn1003-3033.2017.05.005

• 安全人体学 • 上一篇    下一篇

无信号控制路段行人过街决策研究

赵佳, 宋柱, 张名芳, 王畅 副教授   

  1. 长安大学 汽车学院,陕西 西安 710064
  • 收稿日期:2017-01-10 修回日期:2017-03-31 出版日期:2017-05-20 发布日期:2020-10-30
  • 作者简介:赵 佳 (1992—),女,陕西凤翔人,硕士研究生,主要研究方向为交通安全工程。E-mail: zhaojia1101@126.com。
  • 基金资助:
    “十二五”国家科技支撑计划项目(2014BAG01B05);陕西省自然科学基金资助(2016JQ5096);中央高校基本科研业务费专项资金项目(310822161009,310822171118,310822172001)。

Research on pedestrian crossing decision without signal control

ZHAO Jia, SONG Zhu, ZHANG Mingfang, WANG Chang   

  1. School of Automobile, Chang'an University, Xi'an Shaanxi 710064, China
  • Received:2017-01-10 Revised:2017-03-31 Online:2017-05-20 Published:2020-10-30

摘要: 为更深入研究无信号控制路段行人过街的交通特性,通过激光雷达采集行人过街过程中来车的运动状态数据,考虑外部因素对行人过街决策的影响及行人对安全过街的心理需求,利用人车间距、车辆速度和可穿越间隙等参数分析直接过街和等待过街2种决策结果下的数据特性。基于上述参数建立行人过街安全心理距离模型和多元Logistic回归决策模型,并验证模型有效性。结果表明:当人车间距越大、车速越低、可穿越间隙越大时,行人过街概率越大;相同可穿越间隙下,车速越快,行人过街概率越大;所建立二模型均有较高有效性。研究成果可为车载行人预警系统的优化提供依据。

关键词: 过街决策, 无信号路段, 行为特性, 可穿越间隙, 多元Logistic回归

Abstract: In order to study the traffic characteristics of pedestrian crossing the street without signal control further, data on motion of incoming vehicle during the process of pedestrian crossing the street were collected by using a Lidar, and effects of external factors on pedestrian crossing decision and those of the psychological needs of pedestrians on safe crossing were taken into consideration. The parameters, including the distance between the pedestrian and the incoming vehicle, the velocity of the vehicle and the gap for crossing, were analyzed for two decision results, crossing directly and crossing after waiting. The above parameters were used to build a psychological distance model for the pedestrian crossing the street safely and a multivariate Logistic regression decision model. The effectiveness of the two models was evaluated. The results show that the probability of crossing the street for the pedestrian increases when the distance between the pedestrian and the incoming vehicle grows, the velocity of the vehicle decreases, and the gap of crossing becomes larger, that with the same gap of crossing, as the velocity grows, the probability of crossing gets larger, that the effectiveness of the models is great, and that the research results can provide a basis for the optimization of the on-board pedestrian warning system.

Key words: crossing decision, without signal control, behavioral characteristics, acceptance gap, multivariate Logistic regression

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