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Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections

机译:信号交叉口交叉行为及侵犯电动骑车者的分析

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摘要

This paper focuses on investigating electric bikers’ (e-bikers) crossing behavior and violations based on survey data of 3,126 e-bikers collected at signalized intersections in Nantong, China. We first explore e-bikers’ characteristics of late crossing, incomplete crossing, and violating crossing behaviors by frequency analysis and duration distribution, and examine a few influential factors for e-bikers’ red-light running (RLR) behavior, including site type, crossing length and traffic signal countdown timers (TSCTs). E-bikers’ RLR behavior is further divided into three categories, namely GR near-violations, RR violations, and RG violations. Second, we use a binary logistic regression model to identify the relationship between e-bikers’ RLR behavior and potential influential factors, including demographic attributes, movement information, and infrastructure conditions. We not only make regression analysis for respective violation type, but also carry out an integrated regression of a census of all three types of violations. Some insightful findings are revealed: (i) the green signal time and site type are the most significant factors to GR near-violations, but with little impact on the other two violation types; (ii) the waiting time, waiting position, passing cars and crossing length exert considerable impact on RR violations; (iii) for RG violations, TSCTs, leading violators and gender are the most significant factors; (iv) it is also unveiled that site type, green signal time and TSCTs have negligible impact on the whole violations regardless of the violation types. Thus, it is more meaningful to investigate the impacts of these variables on e-bikers’ RLR behavior according to different violation types; otherwise, the potential relationship between some crucial factors and e-bikers’ RLR behavior might be ignored. These findings would help to improve intersection crossing safety for traffic management.
机译:本文着重研究基础上,在中国南通的信号交叉口收集3,126 E-车友调查数据电动自行车手(E-骑自行车的人)穿越行为和违规行为。首先,我们通过频率分析和时间的分布晚渡,不完整的交叉,以及违反交叉行为的特点,并检查电子骑自行车的几个影响因素探索电子骑自行车闯红灯(RLR)的行为,包括立地类型,交叉长度和交通信号倒计时定时器(TSCTs)。 E-车友RLR行为被进一步划分为三类,即GR近违法行为,违反RR和RG违法行为。其次,我们使用二进制逻辑回归模型来识别电子车友RLR行为和潜在的影响因素,包括人口属性,运动信息和基础设施条件之间的关系。我们不仅做出相应的违规类型的回归分析,同时也开展所有三种类型的违法行为的普查综合回归。一些有见地的研究结果表明:(一)绿色信号时间和场地类型是最显著因素GR近违法行为,但对其他两种类型的违规影响不大; (ii)所述等待时间,等待位置时,使汽车和交叉长度上施加RR侵犯相当大的影响; (三)违反RG,TSCTs,导致违法者的性别是最显著的因素; (四)它也推出了该网站的类型,绿色信号时间和TSCTs对整个违反不可忽视的影响,无论违规类型。因此,更有意义的探讨根据不同的违反类型的电子车友RLR行为这些变量的影响;否则,一些关键性的因素和电子车友RLR行为之间的潜在关系可能被忽略。这些发现将有助于改善交通管理路口道口安全。

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