快速路匝道入口智能网联车协同合并控制研究

针对快速路匝道入口场景在高车流量的情况下容易发生交通拥堵的问题，提出了一种快速路匝道入口智能网联车(connected and automated vehicles, CAV)协同合并控制的解决方案，将问题解耦成多车顺序决策和车辆运动规划两部分。其中多车顺序决策对通行效率起到重要作用，因此设计了一种基于状态评价模型(state evaluation model, SEM)的多车顺序决策算法。该算法首先建立状态空间并初始化，考虑通行效率和车辆延迟设计状态评价函数，通过状态转移关系选择出最优状态，最终回溯得到最优通行顺序。根据车辆状态和到达冲突点时间，控制器实时推导各车辆纵向速度的解析解，实现车辆运动规划。仿真和实验结果表明，该方案在满足交通系统实时性要求的同时能有效提高快速路匝道入口的通行效率，缩短车辆延迟，降低燃油消耗。

Cooperative merging control of connected and automated vehicles at freeway on-ramp entrance

Aiming at the problem of traffic congestion in freeway on-ramp entrance under the condition of high traffic flow, this paper proposed a cooperative merging control solution of CAV at freeway on-ramp entrance, which divided the problem into multi-vehicle sequential decision making and vehicle motion planning. Multi-vehicle sequential decision making played an important role in traffic efficiency, so this paper proposed a multi-vehicle sequential decision algorithm based on SEM. This algorithm firstly established the state space and initialization, designed the state evaluation function by considering the traffic efficiency and the vehicle delay. It selected the optimal state through the state transition relationship, and finally got the optimal passing order by backtracking. According to the state of the vehicles and the time to reach the conflict point, the controller deduced the analytic solution of the longitudinal velocity of each vehicle in real time to realize the vehicle motion planning. Simulation and experiment results show that the solution can not only meet the real-time requirements of the traffic system, but also effectively improve the efficiency of freeway on-ramp entrance, shorten vehicle delay and reduce fuel consumption.