ITSC 2025 Paper Abstract

Paper TH-LA-T19.2

Chen, Wang (The University of Hong Kong), Shi, Hongzheng (The University of Hong Kong), Ke, Jintao (The University of Hong Kong)

HRSim: An Agent-Based Simulation Platform for High-Capacity Ride-Sharing Services

Scheduled for presentation during the Invited Session "S19c-Artificial Transportation Systems and Simulation" (TH-LA-T19), Thursday, November 20, 2025, 16:20−16:40, Surfers Paradise 1

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 Digital Twin Modeling for ITS Infrastructure and Traffic Simulation, Field Test Methodologies for ITS Integration in Smart Cities, Testing and Validation of ITS Data for Accuracy and Reliability

Abstract

The rapid growth of ride-sharing services presents a promising solution to urban transportation challenges, such as congestion and carbon emissions. However, developing efficient operational strategies—such as pricing, matching, and fleet management—requires robust simulation tools that can replicate real-world dynamics at scale. Existing platforms often lack the capacity, flexibility, or open-source accessibility needed to support large-scale, high-capacity ride-sharing services. To address these gaps, we introduce HRSim, an open-source, agent-based High-capacity Ride-sharing Simulator. HRSim integrates real-world road networks and demand data to simulate dynamic ride-sharing operations, including pricing, routing, matching, and repositioning. Its module design supports both ride-sharing and solo-hailing service modes. Also, it includes a visualization module for real-time performance analysis. In addition, HRSim incorporates integer linear programming and heuristic algorithms, which can achieve large-scale simulations of high-capacity ride-sharing services. Applications demonstrate HRSim’s utility in various perspectives, including quantifying carbon emissions, scaling ride-sharing performance, evaluating new strategies, etc. By bridging the gap between theoretical research and practical implementation, HRSim serves as a versatile testbed for policymakers and transportation network companies to optimize ride-sharing systems for efficiency and sustainability.