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量化自动驾驶车辆和智能道路部署对中国道路安全的影响:一项国家级建模研究。

Quantifying the Impact of Deployments of Autonomous Vehicles and Intelligent Roads on Road Safety in China: A Country-Level Modeling Study.

机构信息

State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China.

Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China.

出版信息

Int J Environ Res Public Health. 2023 Feb 24;20(5):4069. doi: 10.3390/ijerph20054069.

Abstract

Approximately 1.35 million people lose their lives due to road traffic collisions worldwide per year. However, the variation of road safety depending on the deployment of Autonomous Vehicles (AV), Intelligent Roads (IR), and Vehicle-to-Vehicle technology (V2V) is largely unknown. In this analysis, a bottom-up analytical framework was developed to evaluate the safety benefits of avoiding road injuries and reducing crash-related economic costs from the deployment of AVs, IRs, and V2Vs in China in 26 deployment scenarios from 2020 to 2050. The results indicate that compared with only deploying AVs, increasing the availability of IRs and V2V while reducing the deployment of fully AVs can achieve larger safety benefits in China. Increasing the deployment of V2V while reducing the deployment of IRs can sometimes achieve similar safety benefits. The deployment of AVs, IRs, and V2V plays different roles in achieving safety benefits. The large-scale deployment of AVs is the foundation of reducing traffic collisions; the construction of IRs would determine the upper limit of reducing traffic collisions, and the readiness of connected vehicles would influence the pace of reducing traffic collisions, which should be designed in a coordinated manner. Only six synergetic scenarios with full equipment of V2V can meet the SDG 3.6 target for reducing casualties by 50% in 2030 compared to 2020. In general, our results highlight the importance and the potential of the deployment of AVs, IRs, and V2V to reduce road fatalities and injuries. To achieve greater and faster safety benefits, the government should prioritize to the deployment of IRs and V2V. The framework developed in this study can provide practical support for decision-makers to design strategies and policies on the deployment of AVs and IRs, which can also be applied in other countries.

摘要

全球每年约有 135 万人死于道路交通碰撞。然而,由于自动驾驶汽车(AV)、智能道路(IR)和车对车技术(V2V)的部署,道路安全的变化在很大程度上尚不清楚。在本分析中,开发了一个自下而上的分析框架,以评估在中国 26 种部署情景下(2020 年至 2050 年),部署 AV、IR 和 V2V 以避免道路伤害和降低与碰撞相关的经济成本的安全效益。结果表明,与仅部署 AV 相比,在增加 IR 和 V2V 的可用性的同时减少完全 AV 的部署,可以在中国实现更大的安全效益。增加 V2V 的部署,同时减少 IR 的部署,有时可以实现类似的安全效益。AV、IR 和 V2V 的部署在实现安全效益方面发挥着不同的作用。大规模部署 AV 是减少交通事故的基础;IR 的建设将决定减少交通事故的上限,而联网车辆的准备情况将影响减少交通事故的速度,这应协调设计。只有在 2030 年与 2020 年相比,实现了 V2V 全面设备的六个协同情景,才能达到减少 50%伤亡的可持续发展目标 3.6。总的来说,我们的结果强调了部署 AV、IR 和 V2V 以减少道路伤亡和伤害的重要性和潜力。为了实现更大和更快的安全效益,政府应优先部署 IR 和 V2V。本研究中开发的框架可以为决策者提供设计 AV 和 IR 部署策略和政策的实际支持,也可以应用于其他国家。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27bf/10002037/ecf6c504fce0/ijerph-20-04069-g001.jpg

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