Daniel B. Fambro Student Paper Award: A Stochastic Delay Prediction Model for Real-Time Incident Management

This paper considers the impact of uncertainty in predicting incident duration, and presents a model for predicting incident delay that explicitly provides prediction in the context of uncertain incident duration and eliminates this source of error. Analytical incident delay formulas are extended to account for uncertain incident duration. A series of computer simulation experiments were conducted with Monte Carlo sampling to study scenarios that are too complex for easy analysis. These scenarios indicate that different demand profiles play an important role in determining the impact of an incident and should be taken into account in any delay prediction model.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/614107147
• Authors:
  • Boyles, Steve
  • Waller, S Travis
• Publication Date: 2007-11

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 18-24
• Serial:
  • ITE Journal
  • Volume: 77
  • Issue Number: 11
  • Publisher: Institute of Transportation Engineers (ITE)
  • ISSN: 0162-8178
  • Serial URL: https://www.ite.org/publications/ite-journal/

Subject/Index Terms

• TRT Terms: Incident management; Mathematical prediction; Monte Carlo method; Real time control; Simulation; Stochastic programming; Time duration; Traffic delays; Traffic incidents; Traffic models; Travel demand; Uncertainty
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning; I73: Traffic Control;

Filing Info

• Accession Number: 01083144
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Dec 31 2007 7:36AM