Inferring origin-destination pairs and utility-based travel preferences of shared mobility system users in a multi-modal environment |
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| Institution: | 1. Department of Industrial and Systems Engineering, University at Buffalo, SUNY, United States;2. Department of Industrial and Management Systems Engineering, University of South Florida, United States;1. School of Management, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, PR China;2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, PR China;1. Department of Urban and Regional Planning, University at Buffalo, The State University of New York, United States;2. Department of Public Administration and Graduate School of Governance, Sungkyunkwan University, South Korea;3. Department of Industrial and Systems Engineering, University at Buffalo, The State University of New York, United States;4. Department of Agricultural Economics and Rural Development, Seoul National University, South Korea |
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| Abstract: | This paper presents a methodological framework to identify population-wide traveler type distribution and simultaneously infer individual travelers’ Origin-Destination (OD) pairs, based on the individual records of a shared mobility (bike) system use in a multimodal travel environment. Given the information about the travelers’ outbound and inbound bike stations under varied price settings, the developed Selective Set Expectation Maximization (SSEM) algorithm infers an underlying distribution of travelers over the given traveler “types,” or “classes,” treating each traveler’s OD pair as a latent variable; the inferred most likely traveler type for each traveler then informs their most likely OD pair. The experimental results based on simulated data demonstrate high SSEM learning accuracy both on the aggregate and dissagregate levels. |
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