ITSC 2025 Paper Abstract

Paper FR-LA-T32.1

Shang, Yueru (Loughborough University), WOODWARD, JOHN (Heriot Watt university), Wang, Xinwei (TU Delft)

Multimodal Transport Path Optimisation with Fixed Timetable Constraints

Scheduled for presentation during the Regular Session "S32c-AI-Driven Traffic Monitoring, Safety, and Anomaly Detection" (FR-LA-T32), Friday, November 21, 2025, 16:00−16:20, Southport 2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Keywords Smart Logistics with Real-time Traffic Data for Freight Routing and Optimization, Multimodal Transportation Networks for Efficient Urban Mobility, Transportation Optimization Techniques and Multi-modal Urban Mobility

Abstract

In multimodal transport systems, rail and maritime modes operate according to fixed timetables, making effective timetable coordination essential for ensuring operational efficiency. However, previous approaches often oversimplify these constraints, leading to impractical or unrealistic solutions. This study proposes a bi-objective optimisation model for multimodal route selection that simultaneously minimises time and cost, while explicitly modelling waiting times induced by fixed timetables. Cross-validation experiments revealed notable discrepancies between predicted and actual performance, with existing models underestimating or overestimating transit outcomes by 5.6%--7.3%. These results confirm fundamental limitations in simplistic waiting time modelling approaches. The proposed model yields practical Pareto-optimal routes that effectively balance economic efficiency and service quality, offering logistics planners actionable solutions within realistic timetable constraints.