An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction
Travel behavior research increasingly combines digital data collection with predictive modeling, yet these stages are often developed and evaluated separately. This study proposes a three-agent workflow integrating conversational data collection, structured data processing, and behavioral prediction. A chatbot-administered, image-augmented stated-preference survey collected mode choices from student commuters across five predefined weather scenarios, yielding 454 respondent-scenario observations. Weather-related associations were analyzed using a multinomial logit model, while logistic regress
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- PossiblePossibly related (embedding) · 47%Build a unified semantic layer across datasets with multi-dataset Topics in Amazon Quick →
- FuzzySimilar title/name (fuzzy) · 87%ai-collection/ai-collection →
“Fuzzy title match (0.94): “An Agentic Approach for Active Data Collection, Travel Behav” ≈ “ai-collection/ai-collection””
- FuzzySimilar title/name (fuzzy) · 59%WenyuChiou/awesome-agentic-ai-zh →
“Fuzzy title match (0.73): “An Agentic Approach for Active Data Collection, Travel Behav” ≈ “WenyuChiou/awesome-agentic-ai-zh””
- FuzzySimilar title/name (fuzzy) · 59%Fosowl/agenticSeek →
“Fuzzy title match (0.73): “An Agentic Approach for Active Data Collection, Travel Behav” ≈ “Fosowl/agenticSeek””
- LinkedLinked via arxiv author · 85%Narges Ahmadi →
“An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction”
- LinkedLinked via arxiv author · 85%Yubo Jiao →
“An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction”
- LinkedLinked via arxiv author · 85%Jônatas Augusto Manzolli →
“An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction”
- LinkedLinked via arxiv author · 85%Jiangbo Yu →
“An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction”