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

  • Dong, Xiaojing
  • Ben-Akiva, Moshe E.
  • Bowman, John L.
  • Walker, Joan L.
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    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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    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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    1. Wachs, Martin & Kumagai, T. Gordon, 1973. "Physical accessibility as a social indicator," Socio-Economic Planning Sciences, Elsevier, vol. 7(5), pages 437-456, October.
    2. Chen, Chienho, 1996. "An Activity-Based Approach to Accessibility," University of California Transportation Center, Working Papers qt44g1f7cg, University of California Transportation Center.
    3. G H Pirie, 1979. "Measuring accessibility: a review and proposal," Environment and Planning A, Pion Ltd, London, vol. 11(3), pages 299-312, March.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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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