22 citations · 28 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
EvolveSignal: A Large Language Model Powered Coding Agent for Discovering Traffic Signal Control Strategies
Leizhen Wang, Peibo Duan, Hao Wang +4
In traffic engineering, fixed-time traffic signal control remains widely used for its low cost, stability, and interpretability. However, its design relies on hand-crafted formulas…
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.…
A Foundational Individual Mobility Prediction Model based on Open-Source Large Language Models
Zhenlin Qin, Leizhen Wang, Yancheng Ling +2
Individual mobility prediction plays a key role in urban transport, enabling personalized service recommendations and effective travel management. It is widely modeled by data-driv…