通过总线跟随模型和总线对总线的合作来减少拥挤

K. Ampountolas, Malcolm Kring
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引用次数: 18

摘要

公交集群是指在高频公共交通线路上运行的公交车成群到达站点的不稳定性问题。在这项工作中,我们揭示了总线跟随模型可以用于设计总线到总线的合作控制策略和减轻群集。公交跟随模型的使用避免了公交站点的显式建模,这将使最终问题离散,事件在任意时间间隔发生。在“跟在前面”的双总线系统中,总线对总线通信允许后面总线的司机(从远处)观察在同一运输线路上运行的领头总线的位置和速度。然后,从引线总线传输的信息用于控制从动器的速度,以消除串。在这种情况下,我们首先提出了实用的线性和非线性控制律来调节空间前进和速度,这将导致束固化。然后,提出了一种基于线性二次高斯理论的状态估计与远程控制相结合的方案,以捕捉公交站点、交通干扰和乘客到达随机性的影响。为了研究已开发方法的行为和性能,使用了旧金山的9公里1-加利福尼亚线,其中约有50个任意间隔的公交车站。利用旧金山市交通局提供的真实乘客数据进行了仿真。结果表明,在公交服务的调度可靠性和延误方面,群集避免和显着改善。所提出的控制在公共交通网络规模方面具有鲁棒性和可扩展性,因此易于在现实环境中实施。
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Mitigating Bunching with Bus-following Models and Bus-to-Bus Cooperation
Bus bunching is an instability problem where buses operating on high frequency public transport lines arrive at stops in bunches. In this work, we unveil that bus-following models can be used to design bus-to-bus cooperative control strategies and mitigate bunching. The use of bus-following models avoids the explicit modelling of bus-stops, which would render the resulting problem discrete, with events occurring at arbitrary time intervals. In a "follow-the-leader" two-bus system, bus-to-bus communication allows the driver of the following bus to observe (from a remote distance) the position and speed of a lead bus operating in the same transport line. The information transmitted from the lead bus is then used to control the speed of the follower to eliminate bunching. In this context, we first propose practical linear and nonlinear control laws to regulate space headways and speeds, which would lead to bunching cure. Then a combined state estimation and remote control scheme, which is based on the Linear-Quadratic Gaussian theory, is developed to capture the effect of bus stops, traffic disturbances, and randomness in passenger arrivals. To investigate the behaviour and performance of the developed approaches the 9-km 1-California line in San Francisco with about 50 arbitrary spaced bus stops is used. Simulations with real passenger data obtained from the San Francisco Municipal Transportation Agency are carried out. Results show bunching avoidance and significant improvements in terms of schedule reliability of bus services and delays. The proposed control is robust, scalable in terms of public transport network size, and thus easy to implement in real-world settings.
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