危险货物道路运输车辆驾驶人风险倾向性分类研究

doi:10.16097/j.cnki.1009-6744.2023.03.018

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (3): 161-173.DOI: 10.16097/j.cnki.1009-6744.2023.03.018

危险货物道路运输车辆驾驶人风险倾向性分类研究

李思贤¹，邢增勇²，钱大琳^*1，李鹏程¹，袁梦¹

1.北京交通大学，综合交通运输人数据应用技术交通运输行业重点实验室，北京100044；2.海南省道路运输局，海口570105

收稿日期:2023-01-22 修回日期:2023-03-28 接受日期:2023-04-04 出版日期:2023-06-25 发布日期:2023-06-23
作者简介:李思贤(1993-)，女，山东烟台人，博士生
基金资助:
国家自然科学基金 (62272030，52072289)；中央高校基本科研业务费专项资金 (2021YJS084)

Risk Tendency Classification of Drivers of Road Transport Vehicles of Hazardous Materials

LI Si-xian¹, XING Zeng-yong², QIAN Da-lin^*1, LI Peng-cheng¹, YUAN Meng¹

1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China; 2. Road Transport Bureau of Hainan Provincial, Haikou 570105, China

Received:2023-01-22 Revised:2023-03-28 Accepted:2023-04-04 Online:2023-06-25 Published:2023-06-23
Supported by:
National Natural Science Foundation of China(62272030，52072289)；Fundamental Research Funds for the Central Universities of Ministry of Education of China (2021YJS084)

摘要/Abstract

摘要： 为加强危险货物道路运输安全风险源头管控，本文充分挖掘轨迹大数据和动态监控数据等多源异构行车数据，研究危险货物道路运输车辆（危货车）驾驶人风险倾向性分类。基于广泛可用的GPS轨迹数据所蕴含的驾驶行为模式和运行环境特性，引入时变随机波动率的概念，提取5种速度波动性指标，构建表征驾驶风格的属性特征集，加之行为抑制控制力、认知抑制控制力和生理负荷特征，共同组建危货车驾驶人风险倾向属性指标体系；利用CC赋权法计算各指标客观权重，并基于多准则妥协解排序算法(VIse Kriterijumski Optimizacioni Racun,.VIKOR)对危货车驾驶人的属性进行评分；建立基于K-medoids聚类算法的危货车驾驶人风险倾向性分类模型。结果表明：运用分类模型，本文将危货车驾驶人分为4类。其中，驾驶风格激进加行为抑制控制力薄弱型驾驶人面对拥堵路段和恶劣天气时表现出更大的速度波动和更多的车辆控制报警；认知抑制控制力薄弱型驾驶人分心次数更多，愿意将更多的注意力分配给分心对象，且更频繁地在分心对象和前方路况间进行注意力转移；易疲劳型驾驶人表现出更多的疲劳报警和超时驾驶报警，驾驶人承受更大的生理负荷。研究成果可以为危货车驾驶人主要风险倾向类型识别和风险评估提供理论依据。

关键词: 交通工程, 风险倾向性, 驾驶人分类, 危货车, 驾驶风格, 抑制控制

Abstract: In order to strengthen the safety risk source control of road transport vehicles of hazardous materials (RTVHM), this study fully excavates the trajectory big data, monitoring data, and other multi-source heterogeneous traffic data to study the risk tendency classification of RTVHM drivers. Based on the driving behavior patterns and environmental characteristics contained in the widely available GPS trajectory data, this study introduces the concept of time-varying random volatility and extracts five measures of speed volatility to construct an attribute feature set that characterizes driving style. Coupled with the characteristics of behavior inhibition control, cognitive inhibition control, and physiological load, risk tendency classification indexes are established for RTVHM drivers. The weight of each index is calculated based on the CRITIC method, and the four kinds of attributes describing the RTVHM drivers are scored by the VIKOR algorithm. The risk tendency classification model based on the K-medoids clustering algorithm is established. The results showed that using the classification model, RTVHM drivers were divided into four categories. Among them, drivers with aggressive driving styles and weak behavior inhibition control showed greater speed fluctuations and more vehicle control alarms in face of congested roads and bad weather. Drivers with weak cognitive inhibition control had more distracted duration, allocated more attention to distractions, and diverted attention more frequently between distraction objects and road conditions ahead. Fatigue drivers showed more fatigue alarms and overtime driving alarms, and bear greater physiological loads. The research results can provide a theoretical basis for the identification and risk assessment of the main risk tendency types of RTVHM drivers.

Key words: traffic engineering, risk tendency, driver classification, road transport vehicles of hazardous materials; driving style, inhibition control

中图分类号:

U491.2

李思贤, 邢增勇, 钱大琳, 李鹏程, 袁梦. 危险货物道路运输车辆驾驶人风险倾向性分类研究[J]. 交通运输系统工程与信息, 2023, 23(3): 161-173.

LI Si-xian, XING Zeng-yong, QIAN Da-lin, LI Peng-cheng, YUAN Meng. Risk Tendency Classification of Drivers of Road Transport Vehicles of Hazardous Materials[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(3): 161-173.

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http://www.tseit.org.cn/CN/Y2023/V23/I3/161

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危险货物道路运输车辆驾驶人风险倾向性分类研究

Risk Tendency Classification of Drivers of Road Transport Vehicles of Hazardous Materials

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