车辆通过双向网络协作,实现无中心化路口决策。
Decentralized Opinion-Integrated Decision making at Unsignalized Intersections via Signed Networks
- 用双重符号网络传递意图,无需中央协调
- 决策冻结为通行或让行,提前预判冲突行为
- 无需联合优化,适合复杂交叉口场景
本文研究连通自动驾驶车辆在无信号灯交叉口的去中心化决策问题。现有集中式方法在混合行驶意图和协调器失效时难以扩展。提出一种闭环意见动态决策模型,车辆通过两种符号网络交换意图:基于冲突拓扑的通信网络与驱动承诺的信任网络,实现无中心协调下的合作。连续意见状态调节速度优化权重,在承诺前;闭式预测可行性门将每辆车决策固化为通行或让行,反向传播至信任网络以预调邻车行为,避免物理冲突。通行顺序由几何可行性与到达优先级决定,不依赖联合优化或求解器。在全竞争、汇合及混合冲突拓扑三种场景下验证,结果表明所有非平凡冲突配置下均实现零碰撞协调,且最后车辆离场时间优于先到先服务(FCFS)。
原文摘要 · Abstract (English)
In this letter, we consider the problem of decentralized decision making among connected autonomous vehicles at unsignalized intersections, where existing centralized approaches do not scale gracefully under mixed maneuver intentions and coordinator failure. We propose a closed-loop opinion-dynamic decision model for intersection coordination, where vehicles exchange intent through dual signed networks: a conflict topology based communication network and a commitment-driven belief network that enable cooperation without a centralized coordinator. Continuous opinion states modulate velocity optimizer weights prior to commitment; a closed-form predictive feasibility gate then freezes each vehicle's decision into a GO or YIELD commitment, which propagates back through the belief network to pre-condition neighbor behavior ahead of physical conflicts. Crossing order emerges from geometric feasibility and arrival priority without the use of joint optimization or a solver. The approach is validated across three scenarios spanning fully competitive, merge, and mixed conflict topologies. The results demonstrate collision-free coordination and lower last-vehicle exit times compared to first come first served (FCFS) in all conflict non-trivial configurations.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。