Cooperative Game Approach to Optimal Merging Sequence and on-Ramp Merging Control of Connected and Automated Vehicles
Cooperative Game Approach to Optimal Merging Sequence and on-Ramp Merging Control of Connected and Automated Vehicles
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DOI：
10.1109/tits.2019.2925871
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发表时间：
2019-07
影响因子：
8.5
通讯作者：
Shoucai Jing;F. Hui;Xiangmo Zhao;Jackeline Rios-Torres;A. Khattak
中科院分区：
文献类型：
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作者：
Shoucai Jing;F. Hui;Xiangmo Zhao;Jackeline Rios-Torres;A. Khattak
车辆并道是降低交通效率、增加碰撞风险和燃料消耗的主要原因之一。互联和自动驾驶汽车（CAV）可以通过有效的通信和控制来提高交通效率，提高安全性并减少对环境的负面影响。因此，为了提高入口匝道的通行效率，降低燃油消耗，本文研究了合流区多个CAV的全局最优协调问题。在此，提出了一种基于多人合作博弈的优化框架和算法，以协调车辆，并实现全局支付条件的最小值。燃料消耗，乘客舒适度，并在合并控制区内的旅行时间被用作支付条件。通过分析合并控制区的特点，选择合适的控制决策持续时间，将多人博弈分解为多个二人博弈。最佳合并策略，从而，来自一个支付矩阵，并预测了一些不同的潜在战略的最低收益。最后，利用预测最小收益对应的最优轨迹作为控制律，协调车辆并车。所提出的控制方案推导出一个最佳的合并序列和最佳的轨迹为每个车辆。仿真结果验证了该模型的有效性。所提出的控制器相比，两种替代方法，以证明其潜力，以减少燃料消耗和旅行时间，并提高乘客的舒适度和交通效率。
Vehicle merging is one of the main causes of reduced traffic efficiency, increased risk of collision, and fuel consumption. Connected and automated vehicles (CAVs) can improve traffic efficiency, increase safety, and reduce the negative environmental impacts through effective communication and control. Therefore, to improve the traffic efficiency and reduce the fuel consumption in on-ramp scenarios, this paper addresses the global and optimal coordination of the CAVs in a merging zone. Herein, a cooperative multi-player game-based optimization framework and an algorithm are presented to coordinate vehicles and achieve minimum values for the global pay-off conditions. Fuel consumption, passenger comfort, and travel time within the merging control zone were used as the pay-off conditions. After analyzing the characteristics of the merging control zone and selecting the appropriate control decision duration, multi-player games were decomposed into multiple two-player games. An optimal merging strategy was, thereby, derived from a pay-off matrix, and minimum payoffs were predicted for a number of different potential strategies. The optimal trajectory corresponding to the predicted minimum payoffs was then utilized as the control law to coordinate the vehicles merging. The proposed control scheme derives an optimal merging sequence and an optimal trajectory for each vehicle. The effectiveness of the proposed model is validated through simulation. The proposed controller is compared with two alternative methods to demonstrate its potential to reduce fuel consumption and travel time and to improve passenger comfort and traffic efficiency.