Travel Behavior And Tolling Strategies In A Bottleneck Model With Stochastic Demand

Bottleneck model is a very classical commute travel choice model, which can improve our understanding of the underlying principle of urban commute travel behavior. The related study on road congestion pricing in the bottleneck model is very helpful for traffic management department developing reasonable road pricing schemes. Different from most of existing bottlenecks that assume traffic demand is fixed, this thesis developed a bottleneck model with stochastic traffic demand and proposed effective road congestion pricing strategies. The main contents of the thesis are summarized as follows:This thesis firstly proposed a novel bottleneck model, which assumes that the traffic demand of the bottleneck is stochastic and follows a random distribution. Also, the commuters’departure time choice is assumed to follow the User Equilibrium principle in terms of their average trip cost. the analytical solution of the proposed model is derived, including commuters’ departure rates of all time periods and the critical times. Both the analytical and numerical results showed that the random traffic demand indeed changes the commuters’travel behavior by increasing the mean trip cost and lengthening the peak time period.Based on the analysis of the proposed bottleneck model with stochastic traffic demand, two road congestion pricing strategies are developed:a time-varying toll and a single-step coarse toll. Commuters’travel choice behaviors under toll charging were formulated, and the detailed toll charging schemes under the two congestion pricing strategies were analytically determined. Numerical results showed that the proposed charging schemes can effectively reduce the queues behind the bottleneck, improve the efficiency of the stochastic bottleneck, and reduce the total system travel cost.