Hazard-Based Analysis of Travel Distance in Urban Environments: Longitudinal Data Approach
Publication: Journal of Urban Planning and Development
Volume 138, Issue 1
Abstract
This paper focuses on identifying important factors that determine activity-based travel distance in urban areas. Building on past research that has demonstrated the conceptual equivalence of hazard models applied to either temporal or spatial settings, the length of the distance from origin to destination is statistically modeled as longitudinal data using hazard-based modeling methods with data from Athens, Greece. Based on the data analysis, the Weibull model with gamma heterogeneity provides the best statistical fit, and a number of factors significantly affect travel distance, including socioeconomics and demographics, trip characteristics, mode choice, trip frequency, time of day for the trip, and type of activity participation. The proposed methodological approach and the research findings help to better understand travel behavior in terms of trip distance in the urban areas, an issue of significant importance for both transportation researchers and planners.
Get full access to this article
View all available purchase options and get full access to this article.
References
Algers, S., Eliasson, J., and Mattsson, L. G. (2001). “Activity-based model development to support transport planning in the Stockholm region.” Proc., 41st Congress of the European Regional Science Association, Louvain-la-Neuve, Belgium.
Anastasopoulos, P. (2009). “Infrastructure asset management: A case study on pavement rehabilitation.” Ph.D. dissertation, Purdue Univ., West Lafayette, IN. 〈http://upload.cos.com/etdadmin/files/43/13462_pdf_A7F9D4C8-2E08-11DE-B14E-0869F0E6BF1D.pdf〉 (Aug. 2011).
Anastasopoulos, P. Ch., Labi, S., and McCullouch, B. (2009). “Analyzing duration and prolongation of performance-based contracts using hazard-based duration and zero-inflated random parameters Poisson models.” Transportation Research Record 2136, Transportation Research Board, Washington, DC, 11–19.
Axhausen, K. W. (2002). “A dynamic understanding of travel demand: A sketch.” Arbeitsberichte Verkehrs- und Raumplanung, 119, Institut für Verkehrsplanung, Transporttechnik, Strassenund Eisenbahnbau (IVT), ETH Zurich, Zurich, Switzerland.
Ben-Akiva, M. E., Bowman, J. L., and Gopinath, D. (1996). “Travel demand model system for the information era.” Transportation, 23(3), 241–266.
Bhat, C. R., and Steed, J. L. (2002). “A continuous-time model of departure time choice for urban shopping trips.” Transp. Res., Part B: Methodol., 36(3), 207–224.
Cabanne, I. (2003). “Long term models for long distance travel in France.” European Transport Conference, Association for European Transport, Strasbourg, France.
Fan, Y., and Khattak, A. J. (2009). “Impact of the built environment on travel distance and time costs: A trip-level analysis.” 88th Annual Meeting of the Transportation Research Board, Washington, DC.
Gourieroux, C., Monfort, A., and Trogon, A. (1984). “Pseudo maximum likelihood methods: Theory.” Econometrica, 52(3), 681–700.
Hamed, M. M., and Easa, S. M. (1998). “Integrated modeling of urban shopping activities.” J. Urban Plann. Dev., 124(3), 115–131.
Handy, S. L., Boarnet, M. G., Ewing, R., and Killingsworth, R. E. (2002). “How the built environment affects physical activity.” Am. J. Prev. Med., 23(2S), 64–73.
Heckman, J., and Singer, B. (1984). “A method for minimizing the impact of distributional assumptions in econometric models for duration data.” Econometrica, 52(2), 271–320.
Kockelman, K. M. (2007). “Travel behavior as function of accessibility, land uses mixing, and land use balance: Evidence from San Francisco Bay area.” Transportation Research Record 1607, Transportation Research Board, Washington, DC, 116–125.
Luk, J. Y. K. (2003). “Reducing car travel in Australian cities: Review report.” J. Urban Plann. Dev., 129(2), 84–96.
Mannering, F. L., and Hamed, M. (1990). “Occurrence, frequency and duration of commuters’ work-to-home departure delay.” Transp. Res., Part B: Methodol., 24(2), 99–109.
Niemeier, D., and Morita, J. (1996). “Duration of trip-making activities by men and women: A survival analysis.” Transportation, 23(4), 353–371.
Perperidou, D. G. (2010). “Development of methodology for the record & analysis of systematic activities & travels with use of geostatistical methods—Contribution in the estimation of the exposure to air pollution.” Ph.D. dissertation, National Technical Univ. of Athens, Greece.
Randall, T. A., and Baetz, B. W. (2001). “Evaluating pedestrian connectivity for suburban sustainability.” J. Urban Plann. Dev., 127(1), 1–15.
Soltani, A., and Allan, A. (2006). “Analyzing the impacts of microscale urban attributes on travel: Evidence from suburban Adelaide, Australia.” J. Urban Plann. Dev., 132(3), 132–137.
Tam, M. L., and Lam, W. H. K. (2004). “Balance of car ownership under user demand and road network supply conditions—Case study in Hong Kong.” J. Urban Plann. Dev., 130(1), 24–36.
Tilahun, N., and Levinson, D. (2010). “Contacts and meetings: Location, duration and distance traveled.” 89th Annual Meeting of the Transportation Research Board, Washington, DC.
Waldorf, B. S. (2003). “Spatial patterns and processes in a longitudinal framework.” Int. Reg. Sci. Rev., 26(3), 269–288.
Washington, S. P., Karlaftis, M. G., and Mannering, F. L. (2011). Statistical and econometric methods for transportation data analysis, 2nd Ed., Chapman and Hall/CRC, Boca Raton, FL.
Wellman, B. (1996). “Are personal communities local? A dumptarian reconsideration.” Soc. Netw., 18(4), 347–354.
Information & Authors
Information
Published In
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Dec 9, 2010
Accepted: Aug 16, 2011
Published online: Feb 15, 2012
Published in print: Mar 1, 2012
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.