Planning and Operation Optimization of Mobility-on-Demand Services in the Multimodal Mobility System
Time: Mon 2025-06-02 10.00
Location: M108, Brinellvägen 23, Stockholm
Video link: https://kth-se.zoom.us/j/64248832324
Language: English
Subject area: Transport Science, Transport Systems
Doctoral student: Haoye Chen , Transportplanering
Opponent: Professor Clas Rydergren, Linköping University
Supervisor: Docent Zhenliang Ma, Transportplanering; Assistant Professor Jan Kronqvist, Numerisk analys, optimeringslära och systemteori
QC 20250512
Abstract
Multimodal mobility systems provide seamless service by integrating various travel modes like driving, cycling, Mobility-on-Demand (MoD) services, and Public Transit (PT) services. With the advancement in autonomous driving and electric vehicles, MoD services show their significant potential in coordinating with other travel modes, especially for PT services. To make the best use of its potential, it is essential to investigate the planning and operations of MoD and PT services in the multimodal mobility system.
In the multimodal mobility system, service operations on the supply side should focus on intermodal coordination. On the demand side, customers decide on routes and modes according to service levels such as travel time and price.However, research gaps exist in the planning and operations of integrated MoD and PT services. First, existing literature lacks in optimizing service operations that conform to customer behavior for multimodal mobility systems. Second, existing methods are not applicable to solve such an optimization problem with consistent 'expected' (from service operations) and 'actual' customer behavior. Third, there is a lack of operational optimization models with temporal dynamics for electric MoD vehicles integrated with PT service. To address the above issues, the included papers propose (1) service operation planning in multimodal mobility systems, (2) a generic mathematical solution algorithm for the choice-based optimization problem, and (3) electric MoD operation in multimodal mobility systems.
Paper I proposes a choice-based optimization model for planning MoD services in the multimodal system with the consideration of customer behavior. The optimization of service operations embeds the travelers' choices over modes and routes through a multinomial logit (MNL) model. An efficient linearization method is proposed for transformed MNL constraints to solve the choice-based optimization model. The case study and numerical experiments demonstrate the method's accuracy, efficiency, and advantages compared to existing methods. Paper II further extends the approach to propose the generic outer-inner approximation methods to solve the choice-based optimization problem, which is applicable to problems, such as, location planning, network expansion, and pricing.
Paper III optimizes the integrated operations between MoD and PT services through a network flow model describing the interactions among customer flows, MoD vehicles, and PT services. It embeds the temporal dynamics and charging actions of MoD vehicles using the expanded network with each dimension representing a location, a moment, a state of charge, or a mode. The case study uses real data in Färingsö island, Stockholm. The results show that, compared to existing PT services, the integration of 10 MoD vehicles generally reduces 11.35% average travel time and 1.90% average travel distance. It also significantly (around 40%) reduces maximum travel time, average waiting time, average initial waiting time, and average/maximum transfer time for customers. The intermodal transfers mainly happen in limited locations, suggesting that only minor modifications to the existing infrastructure are required for the integration.