Agentic Mobility
A day-to-day mobility system populated by LLM-based travellers and traffic managers with distinct roles, memories, actions, and channels for interaction.
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02Research focus
Artificial intelligence for next-generation transportation systems
A day-to-day mobility system populated by LLM-based travellers and traffic managers with distinct roles, memories, actions, and channels for interaction.
Developed the DPIU trajectory prediction framework to bridge future intentions with historical behavioral experiences, focusing on uncovering pedestrians’ implicit motion intentions.
03Publications
04Academic record
A day-to-day mobility system populated by LLM-based travellers and traffic managers.
Modeled high-order pedestrian social relations with hypergraphs and state-space models.
Developed cognitive and uncertainty-aware models for robust trajectory prediction in long-tail scenarios.
University of Nottingham Ningbo China
SupervisorZhengbing He
Jilin University
SupervisorZhaowei Qu & Zhihui Li
Jilin University
SupervisorZhihui Li