论文标题

通过分布式协调控制的白相交点控制:混合流量流中的移动控制器范式

White Phase Intersection Control through Distributed Coordination: A Mobile Controller Paradigm in a Mixed Traffic Stream

论文作者

Niroumand, Ramin, Hajibabai, Leila, Hajbabaie, Ali

论文摘要

这项研究提出了一种车辆级分布式协调策略,以控制连接的自动化车辆(CAVS)的混合交通流量以及通过信号交叉点进行连接的人类驱动车辆(CHV)。我们在新引入的白色阶段使用骑士作为移动交通管制员,在此期间,骑士将协商通行权,以领导一组CHV,而CHV必须遵循其直接的前车。在低CAV渗透率下,白色相将不会激活,在该速度较低的情况下,车辆必须等待绿色信号。我们已经将此问题提出为分布式的混合企业非线性程序,并开发了一种方法,以在其轨迹和信号正时参数的所有车辆之间达成协议。通过迭代过程达成了有关轨迹的协议,在该过程中,骑士根据其他车辆的共享轨迹更新其轨迹,以避免碰撞并与其他车辆共享其轨迹。此外,信号正时参数的协议是通过选择最可行的信号正时参数的投票过程形成的。数值实验表明,所提出的方法可以在各种CAV市场份额下有效地控制信号交叉点的车辆运动。与合作轨迹和信号优化在我们的测试中,引入的白相可将总延迟减少3.2%至94.06%。此外,我们的数值结果表明,与从实践先进的交通信号优化软件获得的完全插入信号控制相比,该提议的技术总延迟减少了40.2%-98.9%。

This study presents a vehicle-level distributed coordination strategy to control a mixed traffic stream of connected automated vehicles (CAVs) and connected human-driven vehicles (CHVs) through signalized intersections. We use CAVs as mobile traffic controllers during a newly introduced white phase, during which CAVs will negotiate the right-of-way to lead a group of CHVs while CHVs must follow their immediate front vehicle. The white phase will not be activated under low CAV penetration rates, where vehicles must wait for green signals. We have formulated this problem as a distributed mixed-integer non-linear program and developed a methodology to form an agreement among all vehicles on their trajectories and signal timing parameters. The agreement on trajectories is reached through an iterative process, where CAVs update their trajectory based on shared trajectory of other vehicles to avoid collisions and share their trajectory with other vehicles. Additionally, the agreement on signal timing parameters is formed through a voting process where the most voted feasible signal timing parameters are selected. The numerical experiments indicate that the proposed methodology can efficiently control vehicle movements at signalized intersections under various CAV market shares. The introduced white phase reduces the total delay by 3.2% to 94.06% compared to cooperative trajectory and signal optimization under different CAV market shares in our tests. In addition, our numerical results show that the proposed technique yields reductions in total delay, ranging from 40.2% - 98.9%, compared to those of a fully-actuated signal control obtained from a state-of-practice traffic signal optimization software.

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