Bayesian survival analysis of interactions between truck platoons and surrounding vehicles through a two-dimensional surrogate safety measure

IF 6.2 1区 工程技术 Q1 ERGONOMICS Accident; analysis and prevention Pub Date : 2025-02-09 DOI:10.1016/j.aap.2025.107945
Ma Xiaoxiang , Xiang Mingxin , Jiang Xinguo , Shao Xiaojun
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Abstract

The road freight transport sector is one of the largest contributors to carbon emissions. To address this issue and reduce both carbon emissions and fuel consumption, the road transportation system is undergoing a significant transformation with the development of autonomous truck platoons (ATPs). Despite the promising potential for large-scale deployment of ATPs and the substantial number of human-driven heavy-duty trucks currently in operation, research on the lateral interactions between truck platoons—whether human-driven or automated—and surrounding passenger cars remains limited. Given the absence of commercially deployed ATPs, this study proposes extracting truck platoons from real-world trajectory datasets to investigate the interactions between truck platoons and surrounding vehicles. A two-dimensional surrogate safety measure (SSM) known as Anticipated Collision Time (ACT) was employed to characterize these interactions. Bayesian Survival Analysis was developed to examine the interactions between truck platoons and adjacent passenger cars to provide some insights into how truck platoon might impact surrounding traffic. The results reveal that the position of the adjacent or right-leading truck in the platoon greatly influence the hazard of a minimum collision time. The increase of average time headway between trucks in platoon is found to shorten human drivers’ responsiveness time to truck platoons. Moreover, the presence of a leading vehicle causes human drivers to reach the minimum collision time with truck platoons earlier, and this impact strengthens as the passenger car overtakes the truck platoon. These findings help us better understand the lateral interactions between truck platoon and adjacent passenger car, offering a theoretical foundation for traffic simulation involving heavy-duty truck platoons and recommendations for safety management of traffic flow involving truck platoons for future highways.
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基于二维替代安全措施的卡车排与周围车辆相互作用的贝叶斯生存分析
公路货运部门是碳排放的最大贡献者之一。为了解决这一问题,减少碳排放和燃料消耗,道路运输系统正在经历一场重大变革,自动卡车排(atp)的发展。尽管大规模部署atp的潜力巨大,而且目前有大量人工驾驶的重型卡车投入运营,但对卡车车队(无论是人工驾驶还是自动驾驶)与周围乘用车之间横向相互作用的研究仍然有限。考虑到没有商业部署的atp,本研究建议从现实世界的轨迹数据集中提取卡车排,以研究卡车排与周围车辆之间的相互作用。一种称为预期碰撞时间(ACT)的二维替代安全措施(SSM)被用来表征这些相互作用。开发贝叶斯生存分析是为了检查卡车排和相邻乘用车之间的相互作用,以提供卡车排如何影响周围交通的一些见解。结果表明,相邻或右领先卡车在队列中的位置对最小碰撞时间的危害有较大影响。车队车辆平均车头时距的增加会缩短驾驶员对车队车辆的响应时间。此外,领先车辆的存在使人类驾驶员更早地达到与卡车排碰撞的最短时间,并且随着乘用车超过卡车排,这种影响会增强。这些发现有助于我们更好地理解卡车排与相邻客车之间的横向相互作用,为重型卡车排的交通模拟提供理论基础,并为未来公路卡车排交通流的安全管理提供建议。
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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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