提出通用协同变道规划，40%车辆联网即可显著提升城市交通效率。
Generalized Coordination of Partially Cooperative Urban Traffic
- 基于优化与高效启发式算法，处理混行交通场景。
- 合作率仅40%时，通行量提升，平均等待时间与停车数下降。
- 适合智能网联城市交通系统部署，兼顾效率与安全。
车联网，特别是自动驾驶车辆间的连接，可提升乘客舒适度与道路安全，例如共享感知与驾驶意图信息。协同变道规划利用连接性提升交通效率，以往主要聚焦于自动化交叉口管理。本文提出一种广义化协同变道规划方法，适用于城市交通中的多种复杂场景。框架能有效处理混合交通流——即任意比例的联网协作车辆与其他普通车辆共存的情况。解决方案采用优化方法，并结合高效启发式算法应对高负载场景。我们在高度真实的仿真环境中进行了广泛评估，结果表明，当协作率仅为40%时，交通吞吐量显著提升，平均等待时间与停止车辆数均减少，且未影响交通安全性。
原文摘要 · Abstract (English)
Vehicle-to-anything connectivity, especially for autonomous vehicles, promises to increase passenger comfort and safety of road traffic, for example, by sharing perception and driving intention. Cooperative maneuver planning uses connectivity to enhance traffic efficiency, which has, so far, been mainly considered for automated intersection management. In this article, we present a novel cooperative maneuver planning approach that is generalized to various situations found in urban traffic. Our framework handles challenging mixed traffic, that is, traffic comprising both cooperative connected vehicles and other vehicles at any distribution. Our solution is based on an optimization approach accompanied by an efficient heuristic method for high-load scenarios. We extensively evaluate the proposed planer in a distinctly realistic simulation framework and show significant efficiency gains already at a cooperation rate of 40%. Traffic throughput increases, while the average waiting time and the number of stopped vehicles are reduced, without impacting traffic safety.
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