基于自然驾驶数据和均值和方差均异的随机参数多项logit模型的驾驶员跟车风险演化实证研究

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Analytic Methods in Accident Research Pub Date : 2023-06-01 DOI:10.1016/j.amar.2022.100265
Qiangqiang Shangguan , Junhua Wang , Ting Fu , Shou'en Fang , Liping Fu
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引用次数: 1

摘要

这项研究旨在解决在跟车过程中驾驶风险如何演变的问题,以及哪些因素促成了潜在的演变模式。利用上海自然驾驶研究(SH-NDS)收集的真实世界跟车数据进行了实证研究。在跟车过程中,由前车和跟车之间的动态耦合引起的驾驶风险的演变特征在于瞬时碰撞风险度量——后部碰撞风险指数(RCRI)——如何随时间变化。首先进行了谱聚类分析,对观察到的跟车动作的驾驶风险演化进行了分类,表明在跟车过程中存在五种不同的风险演化模式。为了研究已识别的驾驶风险演变集群及其影响因素之间的关系,采用均值和方差异质的随机参数多项式logit模型进行回归分析,揭示了对跟车风险演变模式的几个重要影响因素,如拥堵程度、,驾驶员保持稳定车头时距和车辆减速的能力。这项研究从风险演变模式的新角度对驾驶风险提供了重要见解,预计将对未来先进交通管理和出行信息系统(ATMS/ATIS)策略、先进驾驶员辅助系统(ADAS)以及联网和自动驾驶汽车(CAV)的发展产生重大影响。
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An empirical investigation of driver car-following risk evolution using naturistic driving data and random parameters multinomial logit model with heterogeneity in means and variances

This study aims to address the questions of how driving risk evolves during car-following processes and what factors contribute to the underlying evolution patterns. An empirical study is conducted using real world car-following data collected in the Shanghai Naturalistic Driving Study (SH-NDS). The evolution of the driving risk induced by the dynamic coupling between the leading and following vehicles during the car-following process is characterized by how an instantaneous crash-risk measure - rear crash risk index (RCRI) - changes by time. A spectral clustering analysis is first conducted to classify the driving risk evolution of the observed car-following maneuvers, showing the existence of five distinctive risk evolution patterns in the car-following processes. In order to investigate the relationship between the identified driving risk evolution clusters and their contributing factors, a regression analysis employing a random parameter multinomial logit model with heterogeneity in means and variances is followed, revealing several significant contributing factors to the car-following risk evolution patterns, such as congestion level, driver’s ability to maintain stable headways, and vehicle deceleration. This study has provided important insights into driving risk from the new perspective of risk evolution patterns, which is expected to have significant implications for the future development of advanced traffic management and traveler information systems (ATMS/ATIS) strategies, advanced driver assistance systems (ADAS), and connected and autonomous vehicles (CAV).

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来源期刊
CiteScore
22.10
自引率
34.10%
发文量
35
审稿时长
24 days
期刊介绍: Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.
期刊最新文献
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