Estimation of Incident Delay and Its Uncertainty on Freeway Networks

Abstract

Estimating incident-induced delay on freeways is important for measuring the impacts of incidents. Information regarding delay can be used for transportation planning or the assessment of traffic improvement projects. Traditional delay estimation methods cannot account for the stochastic attributes of dynamic traffic networks. Introducing the incident duration model and the reduced capacity model into the traditional deterministic queuing model allows researchers to understand better the stochastic characteristics of dynamic networks and to develop a new stochastic incident-induced delay model. The mean delay, the variance of delay, and the expected total delay are estimated on the basis of the proposed model. The analysis shows that the deterministic queuing model can estimate the mean delay as well as the stochastic delay model, but it seriously underestimates the variance of delay and the expected total delay in dynamic networks, which are found to be dominated by incident duration. In addition, depending on the parameter values in the probability distribution of incident duration and reduced capacity, the standard deviation of delay can be higher than the mean delay.