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Stability-based analysis of autonomous intersection management with pedestrians

机译:基于稳定性的行人自主交叉管理分析

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With the development of vehicle-to-infrastructure and vehicle-to-vehicle technologies, vehicles will be able to communicate with the controller at the intersection. Autonomous driving technology enables vehicles to follow the instructions sent from the controller precisely. Autonomous intersection management considers each vehicle as an agent and coordinates vehicle trajectories to resolve vehicle conflicts inside an intersection. This study proposes an autonomous intersection management algorithm called AIM-ped considering both vehicles and pedestrians which is able to produce the total optimal throughput when combined with max pressure control. This study analyzes the stability properties of the algorithm based on a simpler version of AIM-ped, which is a conflict region model of the autonomous intersection management. To implement the proposed algorithm in simulation, this study combines the max-pressure control with an existing trajectory optimization algorithm to calculate optimal vehicle trajectories. Simulations are conducted to test the effects of pedestrian demand on intersection efficiency. The simulation results show that delays of pedestrians and vehicles are negatively correlated and the proposed algorithm can adapt to the change in the pedestrian demand and activate vehicle movements with conflicting trajectories.
机译:随着车辆到基础设施和车辆到车辆技术的开发,车辆将能够与控制器通信。自主驾驶技术使车辆能够精确地遵循从控制器发送的指令。自主交叉管理管理每辆车都认为是代理商,并协调车辆轨迹,以解决交叉口内的车辆冲突。本研究提出了一种称为AIM-PED的自主交叉口管理算法,考虑到能够在与最大压力控制结合时产生总优化吞吐量的车辆和行人。本研究分析了基于简单版本的AIM-PED算法的稳定性特性,这是自主交叉管理的冲突区域模型。为了实现仿真中提出的算法,本研究结合了具有现有轨迹优化算法的最大压力控制来计算最佳车辆轨迹。进行仿真以测试行人需求对交叉效率的影响。仿真结果表明,行人和车辆的延迟是负相关的,所提出的算法可以适应行人需求的变化,并通过冲突的轨迹激活车辆运动。

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