5 papers
A Bayesian Framework for Evaluating Scenario Compatibility in Generative Population Synthesis
Zhenlin Qin, Leizhen Wang, Yancheng Ling +1
Scenario-based transportation analysis specifies future assumptions through aggregate population targets, whereas generative population synthesis models produce detailed individual…
SemaPop: Semantic-Persona Conditioned and Controllable Population Synthesis
Zhenlin Qin, Yancheng Ling, Leizhen Wang +2
Population synthesis is essential for individual-level simulation in transport planning and socio-economic analysis, yet remains challenging due to the need to capture both statist…
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…
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…