Exploiting Beneficial Information Sharing Among Autonomous Vehicles
Exploiting Beneficial Information Sharing Among Autonomous Vehicles
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DOI：
10.1109/cdc40024.2019.9029438
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发表时间：
2019-12
期刊：
影响因子：
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通讯作者：
Songyang Han;Jie Fu;Fei Miao
中科院分区：
文献类型：
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作者：
Songyang Han;Jie Fu;Fei Miao
随着通信技术的发展，自动驾驶汽车不仅可以从自己的传感系统接收信息，还可以通过通信从基础设施和其他车辆接收信息。本文讨论了如何利用自动驾驶车辆之间共享的一系列未来信息，包括计划的位置，速度和车道数。构建了混合系统模型，设计了利用共享序列信息进行导航决策的控制策略。对于高层次的离散状态转换，共享信息用于确定何时换道，换道是否会给自主车辆带来奖励，以及是否存在可行的连续状态控制器。对于低层连续状态空间控制器的生成，共享信息可以放松现有模型预测控制方法中的安全区间约束。在系统层面，信息共享可以增加交通流量，提高驾驶舒适性。我们证明了信息共享的优势，在控制和导航仿真。
As communication technologies develop, an autonomous vehicle will receive information not only from its own sensing system but also from infrastructures and other vehicles through communication. This paper discusses how to exploit a sequence of future information that is shared among autonomous vehicles, including the planned positions, the velocities and the lane numbers. A hybrid system model is constructed, and a control policy is designed to utilize shared sequence information for making navigation decisions. For the high-level discrete state transitions, the shared information is used to determine when to change lane, if lane changing will bring reward for the autonomous vehicle and there exists a feasible continuous state controller. For the low-level continuous state space controller generation, the shared information can relax the safety interval constraints in the existing model predictive control method. In the system level, the information sharing can increase the traffic flow and improve driving comfort. We demonstrate the advantages of information sharing in control and navigation in simulation.