How do the drivers react to different C-V2X-based communication conditions in dilemma zones? A driving simulator study

IF 6.2 1区 工程技术 Q1 ERGONOMICS
Shi Ye , Tiantian Chen , Oscar Oviedo-Trespalacios , Yasir Ali , Taeho Oh , Inhi Kim
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引用次数: 0

Abstract

Drivers should react quickly in dilemma zones at signalized intersections, where ill-timed decisions may result in rear-end or angular collisions with other vehicles. Recent advancements in connected vehicle (CV) technologies, particularly cellular vehicle-to-everything (C-V2X), are expected to enhance driver decision-making by providing real-time traffic information. Despite this, most previous studies have not considered the latest C-V2X specifications, leaving critical questions unanswered about how drivers interact with and benefit from this technology in dilemma-zone scenarios. To address this gap, this study builds a co-simulation platform that integrates Unity and VISSIM to simulate four communication conditions: (1) no communication (baseline), (2) perfect communication (green-light countdown), (3) interrupted communication (green-light countdown with loading delays), and (4) communication loss due to the absence of smart infrastructure (out of service information). Sixty-two licensed drivers participated in four randomized trials, each with multiple unpredictable green-to-yellow transitions designed to capture dilemma-zone responses. Driving performance was assessed in terms of stop-or-go decisions and red-light running outcomes. Results of the random parameters binary logit model for stop-or-go decisions indicate that, compared to no communication, drivers are more inclined to proceed through the intersection when communication is lost. In contrast, perfect communication and communication interruption generally reduce this tendency. Furthermore, significant interaction effects revealed the observed heterogeneity, indicating that drivers with specific driving histories respond differently under communication interruption and loss conditions. For the red-light running outcomes, the descriptive analysis shows that under the perfect communication condition, the proportion of red-light running decreases by 3.44% among drivers. Interestingly, even interrupted communication leads to a 2.19% decrease in the proportion of red-light running outcomes. These findings demonstrate the complex ways in which C-V2X-based information can influence driver decisions, emphasizing the need for robust implementation strategies that are context-aware. This study sheds light on how drivers interact with emerging C-V2X systems and provides insights for road authorities and policymakers seeking to enhance safety and reduce crash risks at signalized intersections.
在困境区,驾驶员对基于c - v2x的不同通信条件有何反应?驾驶模拟器研究
在信号交叉口的两难区,驾驶员应迅速作出反应,因为不合时宜的决定可能导致与其他车辆追尾或发生角度碰撞。互联汽车(CV)技术的最新进展,特别是蜂窝车联网(C-V2X),有望通过提供实时交通信息来增强驾驶员的决策能力。尽管如此,之前的大多数研究都没有考虑到最新的C-V2X规范,因此,关于驾驶员如何在困境区场景中与该技术互动并从中受益的关键问题尚未得到解答。为了解决这一空白,本研究构建了一个集成Unity和VISSIM的联合仿真平台,模拟了四种通信情况:(1)无通信(基线),(2)通信完美(绿灯倒计时),(3)通信中断(绿灯倒计时伴有加载延迟),以及(4)由于缺乏智能基础设施导致的通信丢失(无服务信息)。62名有驾照的司机参加了四项随机试验,每项试验都有多个不可预测的绿色到黄色的过渡,旨在捕捉困境区的反应。驾驶表现的评估依据是停车或走的决定和闯红灯的结果。停车或通行决策的随机参数二值logit模型结果表明,与无通信相比,无通信时驾驶员更倾向于继续通过交叉口。相比之下,完善的沟通和沟通中断通常会减少这种倾向。此外,显著的交互效应揭示了观察到的异质性,表明具有特定驾驶历史的驾驶员在通信中断和通信丢失条件下的反应不同。对于闯红灯结果,描述性分析表明,在完全交通条件下,司机闯红灯的比例下降了3.44%。有趣的是,即使通信中断也会导致闯红灯的比例下降2.19%。这些发现证明了基于c - v2x的信息可以影响驾驶员决策的复杂方式,强调了对上下文感知的强大实施策略的需求。这项研究揭示了驾驶员如何与新兴的C-V2X系统互动,并为道路当局和政策制定者提供了见解,以寻求在信号交叉路口提高安全性并降低碰撞风险。
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来源期刊
CiteScore
11.90
自引率
16.90%
发文量
264
审稿时长
48 days
期刊介绍: Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.
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