7 papers
Fenchel-Young Estimators of Perturbed Utility Models
Xi Lin, Yafeng Yin, Tianming Liu
The Perturbed Utility Model (PUM) framework provides a generalization of discrete choice analysis, unifying models like Multinomial Logit (MNL) and Sparsemax through convex optimiz…
Valuing Time in Silicon: Can Large Language Models Replicate Human Value of Travel Time
Yingnan Yan, Tianming Liu, Yafeng Yin
As a key advancement in artificial intelligence, large language models (LLMs) are set to transform transportation systems. While LLMs offer the potential to simulate human traveler…
Aligning LLM agents with human learning and adjustment behavior: a dual agent approach
Tianming Liu, Jirong Yang, Yafeng Yin +3
Effective modeling of how human travelers learn and adjust their travel behavior from interacting with transportation systems is critical for system assessment and planning. Howeve…
Managing ride-sourcing drivers at transportation terminals: a lottery-based queueing approach
Tianming Liu, Yafeng Yin, Vijay Subramanian
Problem definition: Transportation terminals such as airports often experience persistent oversupply of idle ride-sourcing drivers, resulting in long driver waiting times and induc…
Aligning LLM with human travel choices: a persona-based embedding learning approach
Tianming Liu, Manzi Li, Yafeng Yin
The advent of large language models (LLMs) presents new opportunities for travel demand modeling. However, behavioral misalignment between LLMs and humans presents obstacles for th…
Toward LLM-Agent-Based Modeling of Transportation Systems: A Conceptual Framework
Tianming Liu, Jirong Yang, Yafeng Yin
In transportation system demand modeling and simulation, agent-based models and microsimulations are current state-of-the-art approaches. However, existing agent-based models still…