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This research aims to evaluate how well large language models mimic human value of travel time in various transportation contexts.

December 22, 2025Open Access

Valuing Time in Silicon: Can Large Language Models Replicate Human Value of Travel Time

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This research aims to evaluate how well large language models mimic human value of travel time in various transportation contexts.
Conducted a comprehensive analysis of value of travel time (VOT) among three popular large language models.
Employed a full factorial experimental design to examine sensitivities to transportation contexts.
Considered factors such as choice setting, travel purpose, and socio-demographic factors.
Found high behavioral similarity between LLMs and humans in valuing travel time.
Some LLMs showed aggregate VOT comparable to humans, demonstrating human-like sensitivity to travel purpose and income.
Identified some heterogeneity across models in sensitivity to travel contexts and income elasticity.

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Comprehensive analysis reveals large language models replicate human value of travel time, indicating robust decision-making capabilities.

Yan et al. (2025) studied this question.

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Comprehensive analysis reveals large language models replicate human value of travel time, indicating robust decision-making capabilities.