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Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic

机译:量化连接和自主车辆对混合交通的交通效率和安全的影响

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Connected and Autonomous Vehicles (CAVs) are expected to bring major transformations to transport efficiency and safety. Studies show a range of possible impacts, from worse efficiency of CAVs at low penetration rates, to significant improvements in both efficiency and safety at high penetration rates and loads. However, these studies tend to explore efficiency and safety separately, focus on one type of a road network, and include only cars rather than other vehicle types. This paper presents a comprehensive study on impact of CAVs on both efficiency and safety, in three types of networks (urban, national, motorway), simulating different penetration rates of vehicles with multiple levels of automation, using historical traffic data captured on Irish roads. Our study confirms existing results that near-maximum efficiency improvements are observed at relatively low penetration rates, but reveals further insights that the exact penetration ranges between 20% and 40% depending on the network type and traffic conditions. Safety results show a 30% increase of conflicts at lower penetration rates, but 50-80% reduction at higher ones, with consistent improvement for increased penetration. We further show that congestion has a higher impact on conflicts than penetration rates, highlighting the importance of unified evaluation of efficiency and safety.
机译:连接和自主车(骑士)预计将带来重大变革,以运输效率和安全性。研究表明,各种可能的影响,从低渗透率骑士的糟糕效率,在效率和安全性的高普及率和负载显著的改善。然而,这些研究往往单独探索的效率和安全性,专注于一种类型的道路网,并且仅包括轿车,而不是其他车型。本文介绍了关于在效率和安全性,在三种类型的网络(城市,国家,高速公路),模拟与自动化的多层次,用爱尔兰的道路拍摄的历史交通数据车辆的不同普及率骑士队的影响的全面研究。我们的研究证实,接近最大效率的改善是在相对较低的普及率观察到,但揭示了进一步的洞察力,准确的渗透率20%,并根据网络类型和交通条件40%之间现有的成果。安全性结果表明在较低的普及率的冲突增加了30%,但在更高的人减少50-80%,而增加的渗透持续改善。进一步的研究表明拥堵有比普及率冲突,突出效率和安全性的统一评价的重要性更大的影响。

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