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Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

机译:评估未来智能交通系统对铁路平交道口安全影响的方法

摘要

There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX.
机译:有一致的证据表明,驾驶员的行为助长了铁路平交道口(RLX)的撞车事故和未遂事故。新兴的车辆对车辆和车辆对基础设施技术的发展是提高RLX安全性的极有前途的方法。迄今为止,研究尚未全面评估此类技术对RLX驾驶行为的潜在影响。本文提出了一个正在进行的研究计划,评估了此类新技术对RLX人为因素和驾驶员的态势感知的影响。另外,系统地审查了对这种有前途的技术的设计要求以及向驾驶员显示安全信息的方法。最后,讨论了一种方法,该方法可全面评估在RLXs上警告来车列车驾驶员的车载和基于道路的干预措施的效果,重点关注收益和潜在的不良行为适应。该方法旨在在驾驶模拟器中实施,涵盖合规性,车辆控制,分心,精神工作量和驾驶员的接受程度。这项研究有可能广泛了解在RLX处部署新的车载和基于道路的技术的效果,从而为决策者提供有关RLX的安全改进计划的信息。

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