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Evolution of latent modal captivity and mode choice patterns for commuting trips: A longitudinal analysis using repeated cross-sectional datasets
Institution:1. Institute of Transport and Logistics Studies, The University of Sydney, Australia;2. Institute of Transport Studies, University of Leeds, United Kingdom;1. Department of Health, 189 Royal Street, East Perth, Western Australia, Australia;2. Department of Spatial Sciences, Curtin University, Kent St Bentley, Western Australia, Australia;3. Department of Geography, University of California, Santa Barbara, USA;1. School of Architecture and Urban Planning, University of Wisconsin-Milwaukee, United States;2. School of Government, Peking University, China;3. China Academy of Public Finance and Public Policy, Central University of Finance and Economics, China;1. Department of Civil and Environmental Engineering, University of Connecticut, 261 Glenbrook Road, Unit 3037, Storrs, CT 06269-3037, United States;2. Department of Civil Engineering, Center for Infrastructure, Sustainable Transportation and Urban Planning, Indian Institute of Science, Bangalore 560012, India;3. Department of Civil, Environmental and Construction Engineering, University of Central Florida, 12800 Pegasus Drive, Room 301D, Orlando, FL 32816, United States;1. Massachusetts Institute of Technology, USA;2. University of Queensland, Australia;3. Queensland University of Technology, Australia
Abstract:This paper presents an investigation of the temporal evolution of commuting mode choice preference structures. It contributes to two specific modelling issues: latent modal captivity and working with multiple repeated crossectional datasets. In this paper latent modal captivity refers to captive reliance on a specific mode rather than all feasible modes. Three household travel survey datasets collected in the Greater Toronto and Hamilton Area (GTHA) over a ten-year time period are used for empirical modelling. Datasets collected in different years are pooled and separate year-specific scale parameters and coefficients of key variables are estimated for different years. The empirical model clearly explains that there have been significant changes in latent modal captivity and the mode choice preference structures for commuting in the GTHA. Changes have occurred in the unexplained component of latent captivities, in transportation cost perceptions, and in the scales of commuting mode choice preferences. The empirical model also demonstrates that pooling multiple repeated cross-sectional datasets is an efficient way of capturing behavioural changes over time. Application of the proposed mode choice model for practical policy analysis and forecasting will ensure accurate forecasting and an enhanced understanding of policy impacts.
Keywords:Commuting mode choice  Latent captivity  Parameterized logit captivity model  Pooled model  Longitudinal analysis  Mode choice preference structure
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