Optimal routing of multimodal mobility systems with ride‐sharing

• Author: Meigui Yu,Xi Chen,Xiao Yu,Armagan Bayram,Huimin Miao
• DOI: http://doi.org/10.1111/itor.12870
• Date: 01 May 2021
• Published date: 01 May 2021

Intl. Trans. in Op. Res. 28 (2021) 1164–1189

DOI: 10.1111/itor.12870

INTERNATIONAL

TRANSACTIONS

IN OPERATIONAL

RESEARCH

Optimal routing of multimodal mobility systems with

ride-sharing

Xiao Yu, Huimin Miao, Armagan Bayram∗, Meigui Yu and Xi Chen

Department of Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn, Dearborn,

MI 48128, USA

E-mail: xiaoyuu@umich.edu [Yu]; huiminm@umich.edu[Miao]; armagan@umich.edu [Bayram]; meiguiy@umich.edu

[Yu]; xichenxi@umich.edu [Chen]

Received 6 April 2019; received in revised form 25 May 2020; accepted 10 August2020

Abstract

Multimodal transportation systems are a combination of more environmentally friendly shared transport

modes including public transport, ride-sharing, shuttle-sharing, or even completely carbon-free modes such

as cycling to better meet customer needs. Multimodal mobility solutions are expected to contribute in mit-

igating traffic congestion and carbon emissions, and to result in savings in costs. They are also expected to

improve access to transportation, more specifically for those in rural or low-populated communities (i.e.,

difficult to serve by public transportation only). Motivated by its benefits, in this study, we consider the com-

bination of the ride-sharing and public transportation services and formulate a mixed integer programming

model for the multimodal transportation planning problem. We propose a heuristic approach (i.e., angle-

based clustering [AC] algorithm) and compare its efficiency with the exact solution for different settings.

We find that the AC algorithm works well in both small and large settings. We further show that the mul-

timodal transportation system with ride-sharing can yield significant benefits on travel distances and travel

times.

Keywords:mobility; multimodal transportation; ride-sharing; vehicle routing

1. Introduction

Public transportation is a form of travel provided by cities that enable affordable transportation for

the residents. Public transportation systems have provided communities with a valuable means of

transportation for severalcenturies. According to the American Public Transportation Association,

there were 10.1 billion trips taken via transit in 2017 alone (Dickens, 2018). Public transportation

can lead to various social, economic, and environmental benefits, for example, significant financial

∗Corresponding author.

© 2020 The Authors.

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X. Yu et al. / Intl. Trans. in Op. Res. 28 (2021) 1164–1189 1165

savings and more economic opportunities for passengers, higher fuel efficiency and loweremissions,

and improved safety (Dickens and Neff, 2011). Despite its benefits, public transportation systems

are often unavailable or unreliable for serving first- and last-mile travel, especially in rural or low-

populated regions (Jennings, 2015). In fact, as much as 45% of Americans have no access to public

transportation (Dickens and Neff, 2011). In recent years, private companies (e.g., Uber, Lyft) have

contributed to filling the gaps by providing more flexible ride-sharing services. However, the rel-

atively high prices of their services restrict the widespread use of ride-sharing services by most

residents, especially living in rural areas (Cohen and Shaheen, 2018). To enable affordable and

flexible transportation services for residents and to improve access to transportation, multimodal

transportation has been introduced as a new way to provide effective and consistent transportation

services.

The multimodal transportation system is the combination of various modes of transporta-

tion mechanisms such as walking, cycling, buses, trains, and ride/shuttle-sharing systems.

Multimodal transportation has the capability to provide more efficient and fairer transportation

compared to any single-mode transportation deployed alone (Horn, 2002; Mishra et al., 2012; Lit-

man, 2017). Moreover, it can offer additional benefits including mitigating traffic congestions, re-

ducing emissions, and improving customer experience (Daganzo, 2007; Yao et al., 2012). Demand

for multimodal transportation is also growing. According to the study of millennials and mobility

(Parker, 2017), nearly 70% of millennials use multimodal travel options several times or more per

week. Similarly, people living in rural areas prefer multimodal transportationincreasingly (Litman,

2018). As cities aim to improve transportation services, many cities have committed to develop-

ing multimodal transportation systems to harbor their benefits through public–private partner-

ships. For example, Detroit, Michigan; Summit, New Jersey; and Arlington, Texas are among the

cities that partner with private companies such as Uber and Lyft in implementing the combina-

tion of public transportation systems with ride-sharing services (Boll, 2018). However, despite the

increased usage and need for multimodal transportation and their observed benefits in improving

mobility, the integration of different transportation modes requires effectiveplanning and limits the

large-scale adoption. In this paper, we address this important challenge by developing a model and

solution algorithms for the integrated planning of a multimodal transportation system involving

both public transportation system and ride-sharing service.

We study a multimodal transportation system in which the passengers are transported to their

final destinations via public transportation and shared services (i.e., shuttles). Recently, many cities

are looking for alternative ways to improve access to transportation, more specifically for those in

rural or low-populated communities (Boll, 2018). We consider a set of passengers who go to the

same or nearby locations and who can travel together (i.e., going for grocery shopping or the daily

commute to work). For example, consider a setting where employees living in various regions of

the city use a shuttle service to go to their work or to the public transportation station. Some of

the employees may work at the same company or at the companies that are close to each other by

walking distance. Hence, some employees may have common destination locations. All employees

are picked via a shared vehicle (i.e., shuttle), and they havean option to transfer to a mode of public

transport to reach their final destination. We consider the mixed load case where the employees

traveling to a different destination but living close to each other can also share the same shared

vehicle. We address the benefits of multimodal transportation with ride-sharing, and we develop

answers to the following operational questions:

© 2020 The Authors.

International Transactionsin Operational Research © 2020 International Federation of OperationalResearch Societies