Mixed traffic equilibrium assignment model considering automated parking behaviors of CAV
In order to evaluate the impacts of automated parking behaviors of connected and autonomous vehi-cle(CAV)on the traffic system efficiency,a traffic equilibrium assignment model is established in the context of the mixed traffic flows consisting of the commuter flows of CAV and human-driven vehicle(HDV)and au-tomated parking flows of CAV.By introducing the endogenous variables of CAV parking demands and consid-ering the improvement effect of CAV on road capacity,the demand distribution of CAV parking flows and the congestion effects of three types of mixed traffic flows on a road section are described quantitatively.The user equilibrium(UE)and stochastic user equilibrium(SUE)principles are adopted to describe the route choice behaviors of CAV and HDV travelers,respectively.Meanwhile,the Logit-based discrete choice model is adopted to describe the parking facility choice behaviors of the parking CAV.Based on them,the multi-class mixed traffic equilibrium conditions and the equivalent variational inequality(VI)model are established.Since the CAV parking demands are unknown endogenous variables in the model,the modified method of suc-cessive weighted averaging(MSWA)is developed to solve the model.Finally,numerical examples are pro-vided to validate the effectiveness of the mixed traffic equilibrium assignment model and its solution algorithm.
intelligent transportationtraffic assignmentautomated parking behaviorsconnected and auton-omous vehicle(CAV)mixed traffic flow
万方数据
维普
