Individuals’ Activity-Travel Behavior in Travel Demand Models: A Review of Recent Progress

Transportation planners and engineers seek to make informed decisions on transportation infrastructure development and planning. Travel demand models forecast the usage demands on transportation infrastructure and services under various socio-demographic scenarios, and for different mode choices and land-use characteristics. The transportation literature emphasizes that accurate prediction of travel behavior is a required input to travel demand models. This need has increased with a recent shift from long-term transport infrastructure investment to shorter-term management policies, such as staggering work schedules, tele-commuting, and congestion pricing. These paradigm shifts have resulted in replacement of statistically-oriented, trip-based models by behaviorally-oriented, activity-based models. This paper discusses the strengths and weaknesses of these models and their relationship to broader travel behavioral issues, with special consideration to the needs of transportation planners and modelers.

• Record URL:
  https://doi.org/10.1061/9780784481523.260
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
• Supplemental Notes:
  • © 2018 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Daisy, Naznin Sultana
  • Millward, Hugh
  • Liu, Lei
• Conference:
  • 18th COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2018-7-5 to 2018-7-8
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 2615-2625
• Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility

Subject/Index Terms

• TRT Terms: Infrastructure; Land use planning; Mode choice; Transportation planning; Travel behavior; Travel demand
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01871660
• Record Type: Publication
• ISBN: 9780784481523
• Files: TRIS, ASCE
• Created Date: Jan 24 2023 11:15AM