Real-time Proactive Road Safety Management Techniques

实时主动道路安全管理技术

• 批准号: RGPIN-2022-04486
• 负责人: Sayed, Tarek
• 金额: $ 5.32万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749419
• 关键词: Real; time; Proactive; Road; Safety

For many years, the road safety profession has relied on police-reported crashes to evaluate crash risk, implement measures to improve safety, and evaluate their effectiveness. While several excellent methodologies have been developed to make the best use of crash data, their limitations are no longer acceptable in light of the massive technological advances available today and the advent of smart cities. Limitations with the quality of crash data and crash-based safety analysis methods are giving rise to the use of alternate measures of safety such as the presence of `critical' traffic conflicts, or near misses. The traffic conflict technique has gained considerable popularity as a proactive surrogate tool for road safety analysis. Conflicts occur much more frequently than crashes, are more readily available and provide significant advantage in safety analysis. Additionally, using conflicts for road safety analysis offers the advantage of timeliness and avoids the ethical dilemma of the need to first observe crashes to then prevent them. This proposal focuses on addressing the challenges of current reactive road safety analysis by developing a new evaluation methodology and applications that proactively and dynamically evaluate road safety using traffic conflicts to fundamentally change road safety management practices in Canada and worldwide. A major contribution of this Discovery Grant research program is the development of real-time traffic conflict-based models that provide instantaneous and continuous safety measures that can be used to dynamically change the traffic environment and optimize safety-a methodology that departs fundamentally from the past 50 years of reactive safety management. The research also introduces three novel applications of the real-time safety models which include: a) dynamic identification of crash prone locations which can be improved by making changes to traffic control at the locations or at the network level, b) dynamic identification of the safest routes to destinations which can provide significant safety benefits for the whole network and c) the development of an adaptive traffic control algorithm to optimize traffic safety in real time by minimizing crash risk. These applications rely on vehicle trajectories as the main input and can be used with data from connected and autonomous vehicles which is becoming increasingly available. The models and applications will lead to new insights into crash causation as a function of transport network microscopic operations. Such a methodology will revolutionize road safety management practice globally. A second contribution of this research is the development of a simulation framework for in-depth understanding of road user collision avoidance mechanisms. The framework should improve our ability to implement and evaluate novel safety treatments and shift safety professionals' focus from fixing existing safety problems to planning roads that will be problem-free.

多年来，道路安全行业一直依靠警察报告的撞车事故来评估坠机风险，实施改善安全性并评估其有效性。尽管已经开发了几种出色的方法来充分利用崩溃数据，但鉴于当今可用的巨大技术进步和智能城市的出现，它们的局限性不再可以接受。碰撞数据质量和基于崩溃的安全分析方法的局限性导致了使用替代措施的安全性措施，例如存在“关键”交通冲突或接近遗失。作为道路安全分析的主动替代工具，交通冲突技术已获得了广泛的知名度。冲突比崩溃更频繁，更容易获得，并在安全分析中提供了重要的优势。此外，使用冲突进行道路安全分析提供了及时性的优势，并避免了首先观察崩溃以防止它们的道德困境。该提案着重于通过开发一种新的评估方法和应用来应对当前反应性道路安全分析的挑战，这些方法和应用使用交通冲突积极，动态地评估道路安全，从而从根本上改变加拿大和全球的道路安全管理实践。这项发现赠款研究计划的主要贡献是开发基于交通冲突的模型，这些模型提供了瞬时，连续的安全措施，可用于动态改变交通环境并优化安全A的方法，从根本上讲，该方法从根本上偏离了过去反应性安全管理50年。该研究还介绍了实时安全模型的三个新颖应用，其中包括：a）撞车容易碰撞位置的动态识别，可以通过在位置或网络级别上进行交通控制来改进，b）动态识别。最安全的目的地路线可以为整个网络提供重大安全益处，c）开发自适应交通控制算法，以最大程度地降低崩溃风险，从而实时优化交通安全。这些应用依赖于车辆轨迹作为主要输入，可以与越来越多的连接和自动驾驶汽车的数据一起使用。这些模型和应用程序将导致对崩溃因果关系的新见解，这是传输网络微观操作的函数。这种方法将在全球范围内彻底改变道路安全管理实践。这项研究的第二个贡献是开发模拟框架，以深入了解道路用户碰撞机制。该框架应提高我们实施和评估新型安全治疗的能力，并将安全专业人员的重点从解决现有的安全问题转变为计划道路，这些道路将是无问题的。