Operations Design of Modular Vehicles on an Oversaturated Corridor with First-in, First-out Passenger Queueing
Operations Design of Modular Vehicles on an Oversaturated Corridor with First-in, First-out Passenger Queueing
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DOI：
10.1287/trsc.2021.1074
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发表时间：
2021-08
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通讯作者：
Xiaowei Shi;X. Li
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文献类型：
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作者：
Xiaowei Shi;X. Li
尽管城市交通系统 (UTS) 通常具有固定的车辆容量和相对恒定的发车间隔，但它们可能需要适应空间和时间上剧烈波动的乘客需求，从而导致乘客过度等待或车辆容量和能源浪费。因此，一方面，UTS 的优化运行依赖于乘客排队动态的准确建模，这在多站公交走廊上尤其复杂。另一方面，交通车辆的容量可以改变并适应随时间变化的乘客需求，从而最大限度地减少能源浪费，特别是随着模块化车辆技术的出现。本文研究了多站交通走廊的运营，其中车辆在不同的调度过程中可能具有不同的容量。我们指定倾斜的时间坐标来简化问题结构，同时考虑交通拥堵。然后，我们提出了一种混合整数线性规划模型，该模型确定研究时间范围内的最佳动态车头时距和车辆容量，以最大限度地降低公交走廊的总体系统成本。特别是，所提出的模型考虑了现实的多站先进先出（MSFIFO）规则，该规则为在相同时间间隔但目的地不同的到达车站的乘客提供相同的登机优先权。提出了一种定制的动态规划（DP）算法来有效地求解该模型。为了避免典型 DP 算法状态空间的快速增加，我们分析了所研究问题的理论特性并确定了可行解的上限和下限。这些界限极大地减少了DP迭代期间的状态空间，并大大提高了所提出的DP算法的效率。使用 MSFIFO 规则还可以减少状态维度，以便可以在每个阶段使用单个登机位置状态变量来跟踪同一起点、不同目的地的所有队列。假设示例和实际案例研究表明，所提出的 DP 算法在解质量和时间方面都远远优于最先进的商业求解器 (Gurobi)。
Although urban transit systems (UTS) often have fixed vehicle capacity and relatively constant departure headways, they may need to accommodate dramatically fluctuating passenger demands over space and time, resulting in either excessive passenger waiting or vehicle capacity and energy waste. Therefore, on the one hand, optimal operations of UTS rely on accurate modeling of passenger queuing dynamics, which is particularly complex on a multistop transit corridor. On the other hand, capacities of transit vehicles can be made variable and adaptive to time-variant passenger demand so as to minimize energy waste, especially with the emergence of modular vehicle technologies. This paper investigates operations of a multistop transit corridor in which vehicles may have different capacities across dispatches. We specify skewed time coordinates to simplify the problem structure while incorporating traffic congestion. Then, we propose a mixed integer linear programming model that determines the optimal dynamic headways and vehicle capacities over the study time horizon to minimize the overall system cost for the transit corridor. In particular, the proposed model considers a realistic multistop first-in, first-out (MSFIFO) rule that gives the same boarding priority to passengers arriving at a station in the same time interval yet with different destinations. A customized dynamic programming (DP) algorithm is proposed to solve this model efficiently. To circumvent the rapid increase of the state space of a typical DP algorithm, we analyze the theoretical properties of the investigated problem and identify upper and lower bounds to a feasible solution. The bounds largely reduce the state space during the DP iterations and greatly improve the efficiency of the proposed DP algorithm. The state dimensions are also reduced with the MSFIFO rule such that all queues with different destinations at the same origin can be tracked with a single boarding position state variable at each stage. A hypothetical example and a real-world case study show that the proposed DP algorithm greatly outperforms a state-of-the-art commercial solver (Gurobi) in both solution quality and time.