Synthetic household travel survey data simulation |
| |
| Institution: | 1. Department of Civil and Materials Engineering, University of Illinois at Chicago, 842 West Taylor Street, Chicago, IL 60607-7023, United States;2. Southern California Association of Governments, 818 W. Seventh Street, 12th Floor, Los Angeles, CA 90017, United States;1. Department of Computer Science, University of Southern California, 941 Bloom Walk, SAL300, Los Angeles, CA 90089-0781, United States;2. Department of Industrial and Systems Engineering, University of Southern California, 3715 McClintock Avenue, GER240, Los Angeles, CA 90089-0193, United States;3. Industrial Engineering Department, Universidad de Chile, Republica 701, Santiago, Chile;4. Department of Electrical and Computer Engineering, McGill University, 3630 University Street, Montreal, Quebec H3A 0C6, Canada;1. Department of Civil Engineering, McGill University, Canada;2. School of Urban Planning, McGill University, Canada;3. Department of Geography and Planning, University of Saskatchewan, 117 Science Place, Saskatoon, Saskatchewan S7N 5C8, Canada;4. Operations Planning and Development, TriMet, United States;1. Department of Geography and Environmental Studies, Saint Mary’s University, 923 Robie St., Halifax, NS, Canada;2. Department of Civil and Resource Engineering, Dalhousie University, 1360 Barrington St., Halifax, NS B3H 4R2, Canada;1. Systems Engineering, University of California, Berkeley, United States;2. Industrial Engineering & Operations Research, University of California, Berkeley, United States;3. Institute of Transportation Studies, University of California, Berkeley, United States;4. Systems Engineering & Institute of Transportation Studies, University of California, Berkeley, United States;1. Department of Sociology, Portland State University, P.O. Box 751, Portland, OR 97207-0751, USA;2. Department of Sociology, University of Oregon, Eugene, OR 97403-1291, USA;3. Urban Studies and Planning, Portland State University, USA |
| |
| Abstract: | Due to the high cost, low response rate and time-consuming data processing, few Metropolitan Planning Organizations can afford collecting household travel survey data as frequently as needed. This paper presents a methodology to simulate disaggregate and synthetic household travel survey data by examining the feasibility of the spatial transferability of travel data. Households are clustered into several homogeneous groups to identify the distributions of their travel attributes. These distributions are then transferred to similar groups in other regions. Furthermore, updating methods are suggested and developed to calibrate the parameters of the transferred distributions for the application area. A user friendly software is developed that facilitates the entire process. To validate the model, a synthetic population for the state of New York, excluding the New York City, is generated by a two-stage population synthesis procedure. Then, travel attributes of each household are simulated and by linking the generated travel data to the synthetic population, a synthetic household travel dataset is generated for the application context. Finally, using a new validation dataset from the application area, comparisons against the simulated data are made to examine the effectiveness of the simulation process. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
