Modular AI agents for transportation surveys and interviews:Advancing engagement,transparency,and cost efficiencyOA
Modular AI agents for transportation surveys and interviews:Advancing engagement,transparency,and cost efficiency
Jiangbo Yu;Jinhua Zhao;Luis Miranda-Moreno;Matthew Korp
Department of Civil Engineering,McGill University,Montreal,H3A 0C3,CanadaDepartment of Urban Studies and Planning,Massachusetts Institute of Technology,Cambridge,02139,USADepartment of Civil Engineering,McGill University,Montreal,H3A 0C3,CanadaDepartment of Mechanical Engineering,McGill University,Montreal,H3A 0C3,Canada
Travel surveyPreference elicitationLarge language modelNatural language processingHuman-computer interactionArtificial intelligence(AI)Public consultation
Travel surveyPreference elicitationLarge language modelNatural language processingHuman-computer interactionArtificial intelligence(AI)Public consultation
《交通研究通讯（英文）》 2025 (1)
100-116,17
For Experiment 1,we are thankful for the financial support provided by Environment and Climate Change Canada(ECCC)and the support from Narges Ahmadi(Ph.D.candidate in civil engineering at McGill University)and Nelly Nicola(M.S.student in civil engineering at McGill University).For Experiment 2,we greatly appreciate the support from the City of Candiac.We also thank the contributions from Ana María Ospina Salazar(M.S.candidate in civil engineering at McGill University),Nicol'as Alessandroni(FRQSC postdoctoral fellow in psychology at Concordia University),and Alejandro Pérez Villase～nor(Ph.D.candidate in civil engineering at McGill University).For Experiment 3,we are grateful for the support from the Mens,Manus,and Machina(M3S)program,at the Singapore-MIT Alliance for Research and Technology(SMART),a research enterprise established by the Massachusetts Institute of Tech-nology(MIT)in partnership with the National Research Foundation of Singapore(NRF).We also appreciate the staff of MIT Mobility Initiatives(MMI),especially Bhuvan Atluri,and the valuable feedback from stu-dents and researchers at the MIT JTL Urban Mobility Lab,including Raha Peyravi,Amelia Baum,Awad Abdelhaim,and Hanyong Tang.We also acknowledge the input from Ph.D.candidate Fuqiang Liu at McGill University,who provided high-quality responses and some design sug-gestions in the early stage of agent development.For all three experi-ments,the presented results are preliminary for the purpose of demonstrating the modular framework and not final.Any mistakes are the sole responsibility of the authors.
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