标题： 面向紧急场景：多车道车队重组的集成决策框架 显示英文标题

标题： Towards Emergency Scenarios: An Integrated Decision-making Framework of Multi-lane Platoon Reorganization

摘要： 为了提高车队应对紧急情况的能力，提出了一种车队分布重组决策框架。 该框架包含车队分布层、车辆协同决策层和车辆规划与控制层。 首先，提出了一种基于强化学习的车队分布模型，在其中建立风险势场以定量评估驾驶风险，并构建专门针对车队重组过程的奖励函数。 然后，提出了基于联盟博弈的车辆协同决策模型，通过划分联盟来建模车辆之间的协同关系，并为每辆车生成最优决策结果。 此外，引入了基于图论的新车队部署指数（PDI）到博弈奖励函数中，以衡量重组过程中车队的分布状态，从而加速重组过程。 最后，在随机交通流下的两个高风险场景中验证了所提出的框架。 结果显示，与基线模型相比，所提出的方法可以显著降低碰撞率并提高驾驶效率。 此外，具有PDI的模型可以显著减少车队形成重组时间并提高重组效率。 显示英文摘要

摘要： To enhance the ability for vehicle platoons to respond to emergency scenarios, a platoon distribution reorganization decision-making framework is proposed. This framework contains platoon distribution layer, vehicle cooperative decision-making layer and vehicle planning and control layer. Firstly, a reinforcement-learning-based platoon distribution model is presented, where a risk potential field is established to quantitatively assess driving risks, and a reward function tailored to the platoon reorganization process is constructed. Then, a coalition-game-based vehicle cooperative decision-making model is put forward, modeling the cooperative relationships among vehicles through dividing coalitions and generating the optimal decision results for each vehicle. Additionally, a novel graph-theory-based Platoon Disposition Index (PDI) is incorporated into the game reward function to measure the platoon's distribution state during the reorganization process, in order to accelerating the reorganization process. Finally, the validation of the proposed framework is conducted in two high-risk scenarios under random traffic flows. The results show that, compared to the baseline models, the proposed method can significantly reduce the collision rate and improve driving efficiency. Moreover, the model with PDI can significantly decrease the platoon formation reorganization time and improve the reorganization efficiency.