Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, PR China.
Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, PR China.
Accid Anal Prev. 2024 Oct;206:107694. doi: 10.1016/j.aap.2024.107694. Epub 2024 Jul 13.
The trucking industry urgently requires comprehensive methods to evaluate driver safety, given the high incidence of serious traffic accidents involving trucks. The concept of a "truck driver persona" emerges as a crucial tool in enhancing driver safety and enabling precise management of road transportation safety. Currently, the road transport sector is only beginning to adopt the user persona approach, and thus the development of such personas for road transport remains an exploratory endeavor. This paper delves into three key aspects: identifying safety risk characteristic parameters, exploring methods for constructing personas and designing safety management interventions. Initially, bibliometric methods are employed to analyze safety risk factors across five domains: truck drivers, vehicles, roads, the environment, and management. This analysis provides the variables necessary to develop personas for road transportation drivers. Existing methods for constructing user personas are then reviewed, with a particular focus on their application in the context of road transportation. Integrating contemporary ideas in persona creation, we propose a framework for developing safety risk personas specific to road transportation drivers. These personas are intended to inform and guide safety management interventions. Moreover, the four stages of driver post-evaluation are integrated into the persona development process, outlining tailored safety management interventions for each stage: pre-post, pre-transit, in-transit, and on-post. These interventions are designed to be orderly and finely tuned. Lastly, we offer optimization recommendations and suggest future research directions based on safety risk factors, persona construction, and safety management interventions. Overall, this paper presents a safety management-oriented research technology system for constructing safety risk personas for truck drivers. We argue that improving the design of the persona index system, driven by big data, and encompassing the entire driver duty cycle-from pre-post to on-post-will significantly enhance truck driver safety. This represents a vital direction for future development in the field.
鉴于涉及卡车的严重交通事故发生率居高不下,卡车运输行业迫切需要全面的方法来评估驾驶员安全。“卡车驾驶员角色”的概念作为提高驾驶员安全性和实现道路运输安全精确管理的关键工具出现了。目前,道路运输部门才刚刚开始采用用户角色方法,因此,开发道路运输角色仍然是一项探索性工作。本文深入探讨了三个关键方面:确定安全风险特征参数、探索构建角色和设计安全管理干预措施的方法。首先,采用文献计量学方法分析了卡车司机、车辆、道路、环境和管理五个领域的安全风险因素。这一分析提供了为道路运输司机开发角色所需的变量。然后,回顾了现有的构建用户角色的方法,特别关注它们在道路运输中的应用。我们整合了当代角色创建思想,提出了一个针对道路运输司机的安全风险角色开发框架。这些角色旨在为安全管理干预措施提供信息和指导。此外,将驾驶员事后评估的四个阶段整合到角色开发过程中,为每个阶段制定了定制的安全管理干预措施:预后、预运输、运输中和运输后。这些干预措施旨在有序且精细地进行。最后,根据安全风险因素、角色构建和安全管理干预措施,提出了优化建议和未来研究方向。总体而言,本文提出了一种以安全管理为导向的研究技术系统,用于构建卡车驾驶员的安全风险角色。我们认为,通过大数据驱动改进角色指标系统的设计,并涵盖整个驾驶员职责周期——从预后到运输后,将显著提高卡车驾驶员的安全性。这是该领域未来发展的重要方向。