Long-Term-C-TAP Simulation: Generating Long Distance Travel Demand for a full Year

To date, travel demand generation for microscopic traffic simulation has focused mostly on reproducing daily life. This stands in contrast to the significant part of traffic caused by journeys related to activities not usually undertaken in daily life. The paper investigates the possibilities of extending an existing approach (continuous target-based planning) to cover some of these exceptional activities. A microscopic continuous target-based model applies the idea of agents which try to satisfy individual, behavioral targets by execution of corresponding activities. The decisions on the executed activities are based on heuristic functions. Simulations using this model usually produce data for a few weeks and thus take only daily life into account. This paper shows how to modify this approach in order to generate travel demand for a full year. The main proposed modification is a new model for the activity planning module. This leads to an enormous reduction in the number of calibration parameters in comparison to similar models. Additionally, validation results show that the simulation is able to produce reasonable travel demand patterns including the impact of weekdays as well as seasonal effects.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB40 Transportation Demand Forecasting.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Janzen, Maxim
    • Axhausen, Kay W
  • Conference:
  • Date: 2015

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 16p
  • Monograph Title: TRB 94th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01556276
  • Record Type: Publication
  • Report/Paper Numbers: 15-2759
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 3 2015 11:43AM