9 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…
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…
BoostTaxo: Zero-Shot Taxonomy Induction via Boosting-Style Agentic Reasoning and Constraint-Aware Calibration
Yancheng Ling, Zhenlin Qin, Leizhen Wang +1
Taxonomy induction is crucial for organizing concepts into explicit and interpretable semantic hierarchies. While existing methods have achieved promising results, their generaliza…
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…
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…