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Moving from trip-based to activity-based measures of accessibility

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  • Dong, Xiaojing
  • Ben-Akiva, Moshe E.
  • Bowman, John L.
  • Walker, Joan L.
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    Abstract

    This paper studies the properties and performance of a new measure of accessibility, called the activity-based accessibility (ABA) measure, and compares it to traditional measures of accessibility, including isochrone, gravity and utility-based measures. The novel aspect of the ABA is that it measures accessibility to all activities in which an individual engages, incorporating constraints such as scheduling, and travel characteristics such as trip chaining. The ABA is generated from the day activity schedule (DAS) model system, an integrated system based on the concept of an activity pattern, which identifies the sequence and tour structure among all the activities and trips taken by an individual during a day. A byproduct is an individual's expected maximum utility over the choices of all available activity patterns, and from this the ABA is derived. The ABA is related to the logsum accessibility measures frequently derived from destination and mode discrete choice models. The key difference is that it is generated not by examining a particular trip, but by examining all trips and activities throughout the day. A case study using data from Portland, Oregon, demonstrates the rich picture of accessibility made available by use of the ABA, and highlights differences between the ABA and more traditional measures of accessibility. The ABA is successful in (a) capturing taste heterogeneity across individuals (not possible with aggregate accessibility measures), (b) combining different types of trips into a unified measure of accessibility (not possible with trip-based measures), (c) reflecting the impact of scheduling and trip chaining on accessibility (not possible with trip-based measures), and (d) quantifying differing accessibility impacts on important segments of the population such as unemployed and zero auto households (not possible with aggregate measures, and limited with trip-based measures).

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 40 (2006)
    Issue (Month): 2 (February)
    Pages: 163-180

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    Handle: RePEc:eee:transa:v:40:y:2006:i:2:p:163-180

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    References

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    1. Olu Ashiru & John Polak & Robert B. Noland, 2003. "Development and Application of an Activity Based Space-Time Accessibility Measure for Individual Activity Schedules," ERSA conference papers ersa03p137, European Regional Science Association.
    2. Chen, Chienho, 1996. "An Activity-Based Approach to Accessibility," University of California Transportation Center, Working Papers qt44g1f7cg, University of California Transportation Center.
    3. S L Handy & D A Niemeier, 1997. "Measuring accessibility: an exploration of issues and alternatives," Environment and Planning A, Pion Ltd, London, vol. 29(7), pages 1175-1194, July.
    4. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    5. Wachs, Martin & Kumagai, T. Gordon, 1973. "Physical accessibility as a social indicator," Socio-Economic Planning Sciences, Elsevier, vol. 7(5), pages 437-456, October.
    6. G H Pirie, 1979. "Measuring accessibility: a review and proposal," Environment and Planning A, Pion Ltd, London, vol. 11(3), pages 299-312, March.
    7. Recker, W. W., 1995. "The household activity pattern problem: General formulation and solution," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 61-77, February.
    8. R W Vickerman, 1974. "Accessibility, attraction, and potential: a review of some concepts and their use in determining mobility," Environment and Planning A, Pion Ltd, London, vol. 6(6), pages 675-691, June.
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    Cited by:
    1. Lois, David & López-Sáez, Mercedes, 2009. "The relationship between instrumental, symbolic and affective factors as predictors of car use: A structural equation modeling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(9-10), pages 790-799, November.
    2. Karel Martens, 2011. "Substance precedes methodology: on cost–benefit analysis and equity," Transportation, Springer, vol. 38(6), pages 959-974, November.
    3. Matisziw, T.C. & Grubesic, T.H., 2010. "Evaluating locational accessibility to the US air transportation system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 710-722, November.
    4. Martens, Karel & Golub, Aaron & Robinson, Glenn, 2012. "A justice-theoretic approach to the distribution of transportation benefits: Implications for transportation planning practice in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 684-695.
    5. Deutsch, Kathleen E & Yoon, Seo Youn & Goulias, Konstadinos G., 2011. "Using Sense of Place to Model Behavioral Choices," University of California Transportation Center, Working Papers qt78t5j0x1, University of California Transportation Center.
    6. Chorus, Caspar G., 2012. "Logsums for utility-maximizers and regret-minimizers, and their relation with desirability and satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1003-1012.
    7. Itzhak Benenson & Karel Martens & Yodan Rofé & Ariela Kwartler, 2011. "Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area," The Annals of Regional Science, Springer, vol. 47(3), pages 499-515, December.
    8. Mateus Ara√∫jo E Silva & Eiji Kawamoto, 2011. "An overview of accessibility measures," ERSA conference papers ersa10p602, European Regional Science Association.
    9. Deutsch, Kathleen & Yoon, SeoYoun & Goulias, Konstadinos G., 2011. "Using Sense of Place to Model Behavioral Choices," University of California Transportation Center, Working Papers qt99c1k2kr, University of California Transportation Center.
    10. Yoram Shiftan & Moshe Ben-Akiva, 2011. "A practical policy-sensitive, activity-based, travel-demand model," The Annals of Regional Science, Springer, vol. 47(3), pages 517-541, December.
    11. Chorus, Caspar G. & Timmermans, Harry J.P., 2009. "Measuring user benefits of changes in the transport system when traveler awareness is limited," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 536-547, June.
    12. Lo, Ria S. Hutabarat, 2011. "Walkability Planning in Jakarta," University of California Transportation Center, Working Papers qt05p5r596, University of California Transportation Center.
    13. Krygsman, Stephan & Arentze, Theo & Timmermans, Harry, 2007. "Capturing tour mode and activity choice interdependencies: A co-evolutionary logit modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 913-933, December.

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