REAL-TIME ESTIMATION OF INCIDENT DELAY IN DYNAMIC AND STOCHASTIC NETWORKS

The ability to predict the link travel times is a necessary requirement for most intelligent transportation systems (ITS) applications such as route guidance systems. In an urban traffic environment, these travel times are dynamic and stochastic and should be modeled as such, especially during incident conditions. In contrast to traditional deterministic incident delay models, the model presented explicitly considers the stochastic attributes of incident duration. This new model can be used for predicting the delay that a vehicle would experience as it travels through nonrecurring congestion brought about by an incident. The model is operational in the sense that it does not require significant data and computational abilities beyond that which is traditionally used and can be used within traffic models or within actual ITS implementations. A mixed discrete and continuous vehicle-delay model is first derived and estimators of the mean and variance of vehicle delay are identified. A sensitivity analysis subsequently is performed, and a method for updating the estimated delay as new information becomes available is provided.

• Record URL:
  • https://doi.org/10.3141/1603-13
• Summary URL:
  • http://scholar.google.com/scholar_lookup?title=REAL-TIME+ESTIMATION+OF+INCIDENT+DELAY+IN+DYNAMIC+AND+STOCHASTIC+NETWORKS&author=L.+Fu&author=L.+Rilett&publication_year=1997
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/0309062039
• Supplemental Notes:
  • This paper appears in Transportation Research Record No. 1603, Advanced Transportation Management Systems and Transportation System Management.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Fu, Liping
  • Rilett, L R
• Publication Date: 1997

Language

• English

Media Info

• Features: Figures; References;
• Pagination: p. 99-105
• Serial:
  • Transportation Research Record
  • Issue Number: 1603
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Estimating; Estimation theory; Intelligent transportation systems; Mathematical models; Modernization; Real time control; Real time data processing; Sensitivity analysis; Stochastic processes; Traffic delays; Traffic incidents; Traffic models
• Uncontrolled Terms: Incidents
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 00743687
• Record Type: Publication
• ISBN: 0309062039
• Files: TRIS, TRB, ATRI
• Created Date: Dec 19 1997 12:00AM