论文标题
交通微仿真的车辆的纵向控制
Longitudinal Control of Vehicles in Traffic Microsimulation
论文作者
论文摘要
由于不考虑车辆和阻力力的物理和动力总成特性，因此当前的最新交通微仿真工具无法准确估计自动驾驶系统和车辆连接的安全性，效率和行动益处。本文提出了带有和没有车辆到车辆通信的自动驾驶汽车的逼真的纵向控制功能，并考虑了驾驶员特性和车辆动力学的人类驱动车辆的逼真的车辆跟踪模型。常规的纵向控制功能采用恒定的时间间隙策略，并使用经验恒定控制器系数，可能牺牲安全性或减少吞吐量。提出的纵向控制功能计算每个模拟时间步长和调谐控制器系数在加速和减速过程中的每个仿真时间步长处的最小安全时间差距，以最大程度地提高吞吐量而不会损害安全性。
Current state-of-art traffic microsimulation tools cannot accurately estimate safety, efficiency, and mobility benefits of automated driving systems and vehicle connectivity because of not considering physical and powertrain characteristics of vehicles and resistance forces. This paper proposes realistic longitudinal control functions for autonomous vehicles with and without vehicle-to-vehicle communications and a realistic vehicle-following model for human-driven vehicles, considering driver characteristics and vehicle dynamics. Conventional longitudinal control functions apply a constant time gap policy and use empirical constant controller coefficients, potentially sacrificing safety or reducing throughput. Proposed longitudinal control functions calculate minimum safe time gaps at each simulation time step and tune controller coefficients at each simulation time step during acceleration and deceleration to maximize throughput without compromising safety.
