6 papers
A Comprehensive Evaluation Framework for Synthetic Trip Data Generation in Public Transport
Yuanyuan Wu, Zhenlin Qin, Zhenliang Ma
Synthetic data offers a promising solution to the privacy and accessibility challenges of using smart card data in public transport research. Despite rapid progress in generative m…
Group Effect Enhanced Generative Adversarial Imitation Learning for Individual Travel Behavior Modeling under Incentives
Yuanyuan Wu, Zhenlin Qin, Leizhen Wang +2
Understanding and modeling individual travel behavior responses is crucial for urban mobility regulation and policy evaluation. The Markov decision process (MDP) provides a structu…
Chat2SPaT: A Large Language Model Based Tool for Automating Traffic Signal Control Plan Management
Yue Wang, Miao Zhou, Guijing Huang +3
Pre-timed traffic signal control, commonly used for operating signalized intersections and coordinated arterials, requires tedious manual work for signaling plan creating and updat…
Scalable and Reliable Multi-agent Reinforcement Learning for Traffic Assignment
Leizhen Wang, Peibo Duan, Cheng Lyu +4
The evolution of metropolitan cities and the increase in travel demands impose stringent requirements on traffic assignment methods. Multi-agent reinforcement learning (MARL) appro…
Reinforcement Learning-based Sequential Route Recommendation for System-Optimal Traffic Assignment
Leizhen Wang, Peibo Duan, Cheng Lyu +1
Modern navigation systems and shared mobility platforms increasingly rely on personalized route recommendations to improve individual travel experience and operational efficiency.…
AI-Driven Day-to-Day Route Choice
Leizhen Wang, Peibo Duan, Zhengbing He +5
Understanding travelers' route choices can help policymakers devise optimal operational and planning strategies for both normal and abnormal circumstances. However, existing choice…