Integration of Locational Decisions with the Household Activity Pattern Problem and Its Applications in Transportation Sustainability

This dissertation focuses on the integration of the Household Activity Pattern Problem (HAPP) with various locational decisions considering both supply and demand sides. We present several methods to merge these two distinct areas—transportation infrastructure and travel demand procedures—into an integrated framework that has been previously exogenously linked by feedback or equilibrium processes. This work demonstrates the significance of the integration between travel demand model and infrastructure problems, but also draws insightful policy measurements regarding alternative fuel vehicle adoption. One of the early adoption communities targeted by auto manufacturers is chosen as the study area, and then three different values of accessibility are tested and measured in terms of tolerances to added travel time. Under optimal conditions, refueling trips are found to be toured with other activities. More importantly, there is evidence that excluding such vehicle-infrastructure interactions as well as routing and scheduling interactions can result in overestimation of minimum facility requirement.

  • Record URL:
  • Availability:
  • Supplemental Notes:
    • Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Civil Engineering, University of California, Irvine. This research was sponsored by the U.S. Department of Transportation, University Transportation Centers program.
  • Corporate Authors:

    University of California, Irvine

    Department of Civil and Environmental Engineering
    Irvine, CA  United States  92697

    University of California Transportation Center (UCTC)

    University of California, Berkeley
    2614 Dwight Way, 2nd Floor
    Berkeley, CA  United States  94720-1782

    California Department of Transportation

    Division of Research and Innovation
    1227 O Street, MS-83
    Sacramento, CA  United States  94273-0001

    Research and Innovative Technology Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Kang, Jee Eun
  • Publication Date: 2013-9-1


  • English

Media Info

  • Media Type: Digital/other
  • Features: Appendices; Figures; References; Tables;
  • Pagination: 242p

Subject/Index Terms

Filing Info

  • Accession Number: 01497389
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Report/Paper Numbers: UCTC-DISS-2013-5
  • Created Date: Sep 17 2013 4:07PM