Travel Time Prediction: Issues and Benefits

This paper addresses the issues and benefits pertaining to travel time prediction and incorporates an on-line survey of the Tokyo Metropolitan Expressways (MEX) users. While travel time has the potential to mitigate congestion spatially and temporally, little is known about how the travel time information is used. The MEX survey found that 78% of drivers would change route or departure time if there is time savings. However, the amount of time savings to prompt drivers taking such action depends on the characteristic of the drivers. Not surprisingly drivers rate pre-trip information higher than on-route information as a more desired information because pre-trip information allows drivers to make a more informed travel decision. The MEX survey clearly shows that users’ acceptance of prediction accuracy is dependent on the amount of time gain or lost and is insensitive to the trip length. Approximately 70% of the survey participants acknowledge that ±5 minutes as an acceptable level of accuracy. Therefore a more appropriate measure when evaluating travel time prediction models, taking users’ expectation into account, would be to use percentage error within ±5 minutes or ±10 minutes.

• Corporate Authors:

  World Conference on Transport Research Society

  Secretariat, 14 Avenue Berthelot
  69363 Lyon cedex 07,   France 
• Authors:
  • Chung, Edward
  • Warita, Hiroshi
  • Bajwa, Shamas ul Islam
  • Kuwaharac, Masao
• Conference:
  • 10th World Conference on Transport Research
  • Location: Istanbul , Turkey
  • Date: 2004-7-4 to 2004-7-8
• Publication Date: 2004

Language

• English

Media Info

• Media Type: CD-ROM
• Features: Figures; Maps; References; Tables;
• Pagination: 10p
• Monograph Title: 10th World Conference on Transport Research

Subject/Index Terms

• TRT Terms: Computer online services; Decision making; Information dissemination; Information systems; Surveys; Travel time; Trip purpose
• Identifier Terms: Tokyo Metropolitan Expressway (Japan); Travel Time Prediction System
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Society; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01084948
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 28 2008 8:14AM