Estimating Link Travel Time Correlation: An Application of Bayesian Smoothing Splines

The estimation and forecasting of travel times has become an increasingly important topic as Advanced Traveler Information Systems (ATIS) have moved from conceptualization to deployment. This paper focuses on an important, but often neglected, component of ATIS - the estimation of link travel time correlation. Natural cubic splines are used to model the mean link travel time. Subsequently, a Bayesian based methodology is developed for estimating the posterior distribution of the correlation of travel times between links along a corridor. The approach is illustrated on a corridor in Houston, Texas, that is instrumented with an Automatic Vehicle Identification system.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/37387952
• Authors:
  • Gajewski, Byron J
  • Rilett, Laurence R
• Publication Date: 2004

Language

• English

Media Info

• Media Type: Print
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 53-70
• Serial:
  • Journal of Transportation and Statistics
  • Volume: 7
  • Issue Number: 2/3
  • Publisher: Research and Innovative Technology Administration
  • ISSN: 1094-8848
  • Serial URL: http://www.bts.gov/publications/journal_of_transportation_and_statistics/

Subject/Index Terms

• TRT Terms: Advanced traveler information systems; Automatic vehicle identification; Intelligent transportation systems; Monte Carlo method; Splines; Travel time
• Geographic Terms: Houston (Texas)
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01000899
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: May 30 2005 2:44PM