Abstract

Bus signal priority (BSP) is an active traffic management measure to reduce bus travel delay at signalized intersections and to improve the bus service reliability. In this paper, we present a real-time BSP system with a primary focus on its practical implementation. We tackle two inter-related issues of existing priority systems, namely, real-time computation and solution optimality, using an analytical approach. The core of the proposed priority system involves two signal controller actions – red truncation (RT) and green extension (GE), which determine the priority timings based on the objective of minimizing total person delay incurring at the subject intersection. We demonstrate the analytical approach by deriving closed-form expressions for optimal RT and GE for a two-phase signal using cumulative count curves. The inputs required for these priority models are based on average traffic and bus conditions limited to the current signal cycle alone. Solutions for the RT and GE models indicate that three dimensionless variables – ratio of bus-arrival time to traffic queuing time, ratio of bus passenger occupancy to other vehicles’ average passenger occupancy, and ratio of traffic demand to saturation flow ratio – govern the priority decisions. Simulation results showed significant delay reduction for buses (≈22%) with a negligible impact on other traffic users during low to medium traffic conditions and high bus frequencies (3 min headway).

摘要

公交信号优先（BSP）是一种主动交通管理措施，旨在减少信号交叉口的公交出行延误，提高公交服务的可靠性。在本文中，我们提出了一个实时 BSP 系统，主要关注其实际实现。我们使用分析方法解决现有优先系统的两个相互关联的问题，即实时计算和解决方案最优性。提议的优先系统的核心涉及两个信号控制器动作——红色截断 (RT) 和绿色延伸 (GE)，它们根据目标交叉口处发生的总人员延误最小化来确定优先时间。我们通过使用累积计数曲线推导两相信号的最佳 RT 和 GE 的闭式表达式来演示分析方法。这些优先级模型所需的输入基于平均流量和仅限于当前信号周期的总线条件。RT 和 GE 模型的解决方案表明，三个无量纲变量——公交车到达时间与交通排队时间的比率、公交车乘客占有率与其他车辆平均乘客占有率的比率以及交通需求与饱和流量的比率——控制着优先级决定。仿真结果表明，在中低交通条件和高公交车频率（3 分钟车距）期间，公交车的延误显着减少（≈22%），而对其他交通用户的影响可以忽略不计。RT 和 GE 模型的解决方案表明，三个无量纲变量——公交车到达时间与交通排队时间的比率、公交车乘客占有率与其他车辆平均乘客占有率的比率以及交通需求与饱和流量的比率——控制着优先级决定。仿真结果表明，在中低交通条件和高公交车频率（3 分钟车距）期间，公交车的延误显着减少（≈22%），而对其他交通用户的影响可以忽略不计。RT 和 GE 模型的解决方案表明，三个无量纲变量——公交车到达时间与交通排队时间的比率、公交车乘客占有率与其他车辆平均乘客占有率的比率以及交通需求与饱和流量的比率——控制着优先级决定。仿真结果表明，在中低交通条件和高公交车频率（3 分钟车距）期间，公交车的延误显着减少（≈22%），而对其他交通用户的影响可以忽略不计。