Auad Ramon, Dalmeijer Kevin, Riley Connor, Santanam Tejas, Trasatti Anthony, Van Hentenryck Pascal, Zhang Hanyu
H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, United States of America.
Departamento de Ingeniería Industrial, Universidad Católica del Norte, Chile.
Transp Res Part C Emerg Technol. 2021 Dec;133:103418. doi: 10.1016/j.trc.2021.103418. Epub 2021 Oct 27.
During the COVID-19 pandemic, the collapse of the public transit ridership led to significant budget deficits due to dramatic decreases in fare revenues. Additionally, public transit agencies are facing challenges of reduced vehicle capacity due to social distancing requirements, additional costs of cleaning and protective equipment, and increased downtime for vehicle cleaning. Due to these constraints on resources and budgets, many transit agencies have adopted essential service plans with reduced service hours, number of routes, or frequencies. This paper studies the resiliency during a pandemic of On-Demand Multimodal Transit Systems (ODMTS), a new generation of transit systems that combine a network of high-frequency trains and buses with on-demand shuttles to serve the first and last miles and act as feeders to the fixed network. It presents a case study for the city of Atlanta and evaluates ODMTS for multiple scenarios of depressed demand and social distancing representing various stages of the pandemic. The case study relies on an optimization pipeline that provides an end-to-end ODMTS solution by bringing together methods for demand estimation, network design, fleet sizing, and real-time dispatching. These methods are adapted to work in a multimodal setting and to satisfy practical constraints. In particular, a limit is imposed on the number of passenger transfers, and a new network design model is introduced to avoid the computational burden stemming from this constraint. Real data from the Metropolitan Atlanta Rapid Transit Authority (MARTA) is used to conduct the case study, and the results are evaluated with a high-fidelity simulation. The case study demonstrates how ODMTS provide a resilient solution in terms of cost, convenience, and accessibility for this wide range of scenarios.
在新冠疫情期间，公共交通客流量的崩溃导致票价收入大幅下降，从而造成了严重的预算赤字。此外，由于社交距离要求，公共交通机构面临着车辆运力降低的挑战，清洁和防护设备的额外成本，以及车辆清洁导致的停机时间增加。由于这些资源和预算的限制，许多公交机构采用了基本服务计划，减少了服务时间、线路数量或班次频率。本文研究了按需多式联运系统（ODMTS）在疫情期间的弹性，这是一种新一代的交通系统，它将高频火车和公交车网络与按需班车相结合，用于服务首末英里，并作为固定网络的支线。它以亚特兰大市为例进行了案例研究，并针对需求低迷和社交距离的多种情景对ODMTS进行了评估，这些情景代表了疫情的不同阶段。该案例研究依赖于一个优化流程，该流程通过整合需求估计、网络设计、车队规模确定和实时调度的方法，提供了一个端到端的ODMTS解决方案。这些方法经过调整以在多式联运环境中运行，并满足实际约束条件。特别是，对乘客换乘次数进行了限制，并引入了一种新的网络设计模型，以避免由此约束带来的计算负担。使用来自亚特兰大大都会快速交通管理局（MARTA）的实际数据进行案例研究，并通过高保真模拟对结果进行评估。该案例研究展示了ODMTS如何在成本、便利性和可达性方面为广泛的情景提供一个有弹性的解决方案。
