Algorithms and computational study on a transportation system integrating public transit and ridesharing of personal vehicles

• Published in: Computers & operations research Vol. 164; p. 106529
• Main Authors: Gu, Qian-Ping, Liang, Jiajian Leo
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-04-2024
• Subjects: Approximation algorithms; Computational study; Multimodal transportation; Ridesharing; Approximation algorithms; Multimodal transportation; Computational study; Ridesharing
• ISSN: 0305-0548; 1873-765X
• DOI: 10.1016/j.cor.2024.106529

The potential of integrating public transit with ridesharing includes shorter travel time for commuters and higher occupancy rate of personal vehicles and public transit ridership. In this paper, we describe a centralized transit system that integrates public transit and ridesharing to reduce travel time for commuters. In the system, a set of ridesharing providers (drivers) and a set of public transit riders are received. The optimization goal of the system is to assign riders to drivers by arranging public transit and ridesharing combined routes for as many riders as possible subject to shorter commuting time. As an exact algorithm approach, we give a (0,1) integer linear programming (ILP) formulation based on a hypergraph representation of the problem. Leveraging the ILP and hypergraph, we give approximation algorithms based on LP-rounding and hypergraph matching/weighted set packing, respectively. As a case study, we conduct an extensive computational study based on real-world public transit dataset and ridesharing dataset in Chicago city. To evaluate the effectiveness of the transit system and our algorithms, we generate data instances from the datasets. The experimental results show that more than 60% of riders are assigned to drivers on average, riders’ commuting time is reduced by 23% and vehicle occupancy rate is improved to almost 3. Our proposed algorithms are efficient for practical scenarios.
•Study the benefits of integrating the public transit with ridesharing.•Reduce commuting time for transit riders by an integrated transit system.•Maximize the number of transit riders assigned integrated routes of shorter time.•Maximization problem is NP-hard, exact and approximation algorithms are proposed.•Integrated transit system can benefit drivers, riders and the public transit.