Weibull dependence stochastic traffic assignment model considering risk prone drivers

A Weibull dependence stochastic traffic assignment (Weibull-DSA) model considering risk prone drivers was established. The Weibull marginal survival function of perceived equivalent route disutility was analyzed.It was assumed that travelers always chose the routes with the minimized expected perceived equivalent route disutility to reach their destinations.Thejoint survival function of perceived equivalent route disutility was constructed by using Copula method, and the route choice probability was predicted.An iterative solution algorithm was designed for the model, and the theoretical analysis and numerical verification of the model were carried out.Risk coefficient obtained from the traffic survey in Guangzhou was analyzed.The route choice probabilities, road section traffic volumes, saturation degrees and total travel times were calculated by using Weibull-DSA model, classic Logit stochastic user equilibrium (LogitSUE) model and Weibit stochastic user equilibrium (Weibit-SUE) model under the assumption of risk prone and risk neutral drivers, respectively.Calculation result shows that as the risk coefficient becomes smaller, the total travel times of traffic system for all three kinds of traffic assignment models become larger.Under the risk neutral condition, the maximum differences among the route choice probabilities of all alternative routes connecting each OD pair are 0.17, 0.33, 0.34, respectively calculated by using Weibull-DSA model, Logit-SUE and Weibit-SUE model.Similarly, under the risk prone condition, the maximum differences calculated by the three models are 0.20, 0.36 and 0.41, respectively.Therefore, the maximum difference of different route choice probabilities calculated by Weibull-DSA model is obviously less than the maximum differences obtained by two classical models.Compared with the risk neutral situation, the risk coefficient increases the maximum difference of the route choice probabilities of all alternative routes connecting each OD pair.For either risk prone or risk neutral drivers, the saturation degrees of each road section calculated by Logit-SUE and Weibit-SUE models are all less than 0.9, whereas the saturation degrees obtained by Weibull-DSA model are more than 0.9.Unlike the calculation results of classical models, the maximum difference of route choice probabilities obtained by Weibull-DSA model is smaller, some routes get more traffic volumes, which makes the saturation degrees of road sections with the smallest capacity in the route are greater than 0.9.This feature gives a new explanation for the congestion phenomenon at some bottlenecks in the urban road network.