CHARACTERIZATION OF ACCIDENT CAPACITY REDUCTION

The premise of this project is that the incident capacity reduction is best modeled as a random variable, not a deterministic value, as is the current practice. Extensive traffic flow and incident data for the Hampton Roads region of Virginia in the Smart Travel Laboratory provides us the opportunity to model incident capacity reduction as a random variable. Capacity under prevailing conditions can be estimated by calibrating a speed-flow and /or density-flow curve for a given highway. The peak of this curve defines capacity. When an incident occurs and a bottleneck is formed, the reduced capacity of the roadway is reached and can be measured directly as incident capacity. Incident capacity reduction can be computed as the difference between these two values over the capacity under prevailing conditions, and then modeled as a random variable. This research focuses on estimating accident capacity reductions with one lane and two lanes out of three lanes blocked, and modeling them as random variables based on the traffic flow and accident data for the Hampton Roads region. The results indicate that accident capacity reduction with one lane out of three lanes blocked can be modeled as Beta distribution with an average of 63 percent, which is fairly higher than the result of previous research (50 percent), and accident capacity reduction with two lanes out of three lanes blocked can be modeled as Beta distribution with an average of 77 percent which is slightly lower than the result of previous research (79 percent)

  • Record URL:
  • Supplemental Notes:
    • Publication Date: 2001. National ITS Implementation Research Center, George Mason University, Fairfax VA. Format: website
  • Corporate Authors:

    National ITS Implementation Research Center

    ,    
  • Authors:
    • Qin, Ling
    • Smith, Brian Lee
  • Publication Date: 2001

Language

  • English

Subject/Index Terms

Filing Info

  • Accession Number: 00962438
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Report/Paper Numbers: STL-2001-02
  • Files: PATH, NTL
  • Created Date: Sep 2 2003 12:00AM