An Application of Bayesian Statistics to Estimating Travel Time on an Urban Expressway

Estimating travel time on an urban expressway can be difficult, primarily because traffic congestion varies from day to day and even from hour to hour, and unpredictable incidents or inclement weather add other complexity. This paper proposes the use of Bayesian statistics to the estimation approach in order to address these problems. From Bayesian theorem a vague prior probability of the occurrence of a certain travel time is revised by a conditional probability; the latter is calculated as a joint probability of occurrence of these factors under a certain travel time. The revision accomplishes more accurate estimated travel time from the posterior probability. The authors use a case study from the Metropolitan Expressway (MEX) in Tokyo, Japan, to demonstrate the use of their method. The authors conclude that the use of Bayesian statistics is crucial to the accurate estimate of travel time on expressways.

• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Kasai, Makoto
  • Rokutan, Masato
  • Uchiyama, Hisao
• Conference:
  • 15th World Congress on Intelligent Transport Systems and ITS America's 2008 Annual Meeting
  • Location: New York NY, United States
  • Date: 2008-11-16 to 2008-11-20
• Publication Date: 2008

Language

• English

Media Info

• Media Type: CD-ROM
• Features: Figures; Maps; References; Tables;
• Pagination: 10p
• Monograph Title: ITS Connections: Saving Time. Saving Lives

Subject/Index Terms

• TRT Terms: Bayes' theorem; Estimation theory; Expressways; Traffic congestion; Traffic crashes; Travel time; Urban areas
• Identifier Terms: Tokyo Metropolitan Expressway (Japan)
• Geographic Terms: Tokyo (Japan)
• Subject Areas: Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01137202
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 29 2009 1:53PM