考虑驾驶人感知特性的城市隧道合流区综合风险场模型

doi:10.16265/j.cnki.issn1003-3033.2026.06.0914

摘要/Abstract

摘要：

为精准识别城市隧道合流区车辆交互风险,揭示由隧道环境、车辆行为及驾驶人特性共同驱动的动态风险演变特征,提出考虑隧道环境约束、车辆风险扩散效应及驾驶人风险感知特性的综合风险场模型,并以重庆市典型隧道合流区为对象开展实证研究。首先,针对直接式与平行式2类典型加速车道合流区,将合流区域细分为汇入段、交汇段、合流段与主线段等4个关键行驶路段;其次,基于实车试验采集的驾驶数据,系统分析各区段的驾驶行为特征及驾驶人风险感知差异,揭示其对行车风险形成的作用机制;最后,对比评估不同隧道合流区行车风险的分布特征,实现风险可视化,并提出差异化风险防控建议。结果表明:驾驶人的风险感知因子在合流区负荷最大,呈显著区段差异;2类隧道合流区行车风险均表现为合流段最高、主线段次之、交汇段与汇入段依次降低;相较于直接式加速车道,平行式加速车道在汇入、交汇、合流及主线段的风险场强分别降低8.22%、8.71%、9.35%和6.57%,整体行车风险水平更低。

关键词: 城市隧道合流区, 行车风险, 驾驶人, 感知特性, 综合风险场

Abstract:

In order to accurately identify vehicle interaction risk in urban tunnel merging zones and to reveal the dynamic evolution of risk driven by the interaction among tunnel environment, vehicle behavior, and driver characteristics, a comprehensive risk-field model was proposed. The model incorporates tunnel environmental constraints, vehicle risk propagation effects, and driver risk perception characteristics. An empirical study was conducted using a typical tunnel merging zone in Chongqing as the case study. First, two typical acceleration-lane configurations, namely direct and parallel types, were examined. Each merging zone was divided into four critical sections: the entering, converging, merging, and mainline sections. Second, based on driving data collected from real-world vehicle tests, the distributions of vehicle speed across different sections, driving behavior patterns, and variations in drivers' risk perception were systematically analyzed. The mechanisms through which these factors contributed to driving risk formation were then examined. Finally, the spatiotemporal distribution of driving risk in different tunnel merging zones was compared and evaluated. Risk visualization was also performed, and differentiated risk prevention and control strategies were proposed. The results show that driver risk perception reaches its highest level in the merging section and varied significantly across sections. Driving risk in both types of tunnel merging zones is highest in the merging section, followed by the mainline section, and then gradually decrease in the converging and entering sections. Compared with the direct acceleration lane, the parallel acceleration lane shows reductions in risk-field strength of 8.22%, 8.71%, 9.35%, and 6.57% in the entering, converging, merging, and mainline sections, respectively, indicating a lower overall driving risk level.

Key words: urban tunnel confluence zone, risk perceptionl, driver, perception characteristics, comprehensive risk field

中图分类号:

X951交通运输安全

尚婷, 徐钰婷, 刘唐志. 考虑驾驶人感知特性的城市隧道合流区综合风险场模型[J]. 中国安全科学学报, 2026, 36(6): 82-90.

Shang Ting, Xu Yuting, Liu Tangzhi. Comprehensive risk field model of urban tunnel confluence area considering driver perception characteristics[J]. China Safety Science Journal, 2026, 36(6): 82-90.

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