考虑驾驶员行为特征和主观认知的交叉口复杂性量化方法

IF 2 4区 工程技术 Q2 ENGINEERING, CIVIL
Fengxiang Guo, Lei Yang, Chang’an Xiong, Wenchen Yang, Wei Li, Yiwen Zhou
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引用次数: 0

摘要

高度复杂的十字路口往往会增加交通事故的风险,从而降低交通安全。现有的交叉口复杂性测量模型主要关注影响交叉口运行的客观因素。然而,他们没有考虑交叉口复杂性对驾驶员行为的影响,也没有考虑驾驶员在交叉口复杂交通环境下表现出的反馈机制。本研究旨在探讨驾驶员行为与交叉口复杂性之间的内在联系。采用目标复杂度不同的三个两相信号控制水平交叉口进行了实车实验。实验收集了28名被试的驾驶员行为特征和主观认知相关的7项指标数据。采用两种方法对数据进行分析:(1)对不同交叉口复杂程度下的驾驶行为特征进行描述性分析;(2)基于驾驶员行为特征和主观认知的熵-目标拓扑综合评价法测量两相交叉口复杂性。结果表明:(1)驾驶员对两相信号控制交叉口复杂性的主观感知与客观复杂性的计算差异显著;(2)复杂交叉口不同信号转换方式对驾驶员行为的影响差异无统计学意义;(3)建立并验证了基于驾驶员行为特征和主观感知的两相交叉口复杂性测量模型。这些发现有助于理解城市环境下驾驶员行为与交叉口复杂性之间的内在关系。未来的研究可能会整合智能算法,以提高自动驾驶汽车在十字路口行驶的安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Intersection Complexity Quantification Considering Driver Behavior Characteristics and Subjective Cognition

Intersection Complexity Quantification Considering Driver Behavior Characteristics and Subjective Cognition

Intersections with high complexity often present an increased risk of accidents, thereby reducing traffic safety. Current models for measuring intersection complexity primarily focus on objective factors that influence intersection operation. However, they fail to consider the impact of intersection complexity on driver behavior or the feedback mechanism drivers exhibit in response to complex traffic environments at intersections. This study aims to investigate the intrinsic connection between driver behavior and intersection complexity. A real-vehicle experiment was conducted using three two-phase signal-controlled level intersections, each varying in objective complexity. Data on seven indices related to driver behavior characteristics and subjective cognition were collected from 28 participants during the experiment. Two methods were employed to analyze the data: (1) a descriptive analysis of driving behavior characteristics under varying levels of intersection complexity and (2) an entropy-object topologically comprehensive evaluation method for measuring two-phase intersection complexity based on driver behavior characteristics and subjective cognition. The results indicated that (1) drivers’ subjective perceptions of the complexity of two-phase signal-controlled intersections significantly differed from the calculated objective complexity, (2) differences in the effects of varying signal transition methods on driver behavior at complex intersections were not statistically significant, and (3) a two-phase intersection complexity measurement model based on driver behavior characteristics and subjective perceptions was developed and validated. These findings contribute to understanding the intrinsic relationship between driver behavior and intersection complexity in urban settings. Future research could integrate intelligent algorithms to enhance the safety of autonomous vehicles navigating intersections.

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来源期刊
Journal of Advanced Transportation
Journal of Advanced Transportation 工程技术-工程:土木
CiteScore
5.00
自引率
8.70%
发文量
466
审稿时长
7.3 months
期刊介绍: The Journal of Advanced Transportation (JAT) is a fully peer reviewed international journal in transportation research areas related to public transit, road traffic, transport networks and air transport. It publishes theoretical and innovative papers on analysis, design, operations, optimization and planning of multi-modal transport networks, transit & traffic systems, transport technology and traffic safety. Urban rail and bus systems, Pedestrian studies, traffic flow theory and control, Intelligent Transport Systems (ITS) and automated and/or connected vehicles are some topics of interest. Highway engineering, railway engineering and logistics do not fall within the aims and scope of JAT.
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