In order to get the optimal road congestion charging scheme in mixed driving environment of connected autonomous vehicles (CAV) and human-driven vehicles (HDV), this paper conducts a quantitative analysis of the impact of CAV on road networks (especially on road capacity), and analyzes the functional relationship between the road capacity and HDV flows as well as CAV flows. Secondly, the traditional Bureau of Public Road (BPR) Function is improved, and the system optimal allocation model is established based on the new BPR function. The system optimum (SO) assignment is performed on the traffic flow under the conditions of different CAV proportions and different HDV-CAV headways. Then, Frank-Wolfe algorithm is used to solve the SO model, by considering the extra traffic cost of HDV in the differences of SO results under different conditions. The corresponding road networks are formulated using the optimal toll theory charge plan. Finally, the model and the algorithm are applied to the Nguyen-Dupuis transportation network. The results show that under the coexisting condition of HDV and CAV, the marginal cost under the optimal allocation result of the system is the optimal congestion charging which can be the basis for the road toll scheme design under the coexistence of HDV and CAV.

connected autonomous vehicles, road network, Bureau of Public Road (BPR) function, system optimum assignment, Frank-Wolfe algorithm, congestion charging