In studies on the influence of incidents on travel time, researchers rely on Monte Carlo simulation. Because this procedure is demanding computationally, the research scope is limited. This paper presents a highly efficient method for approximately quantifying congestion spillback due to incidents: marginal incident computation (MIC). MIC superimposes the effect of an incident on a single base simulation run (without incidents) instead of carrying out a complete dynamic network loading with the incident, which would involve many calculations identical to the base simulation (e.g., before or far away from the incident). Whereas the results obtained with MIC vary only slightly from the outcome of a complete dynamic network loading, the gain in computation time is significant: a factor > 1,100 for a case study of the Sioux Falls, South Dakota, benchmark network.
Marginal Incident Computation
An Efficient Algorithm to Determine Congestion Spillback due to Incidents
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2099 , 1 ; 22-29
01.01.2009
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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