Dynamic Origin Destination Estimation of Urban Expressway under Speed Guidance

Abstract

With the growing of traffic demand and much more traffic congestion, integrated active traffic management should be involved in urban expressway management on the back ground of car-road coordination. Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. In order to solve the current dynamic OD estimation problems on the background of speed guidance control, the relationship between dynamic OD estimation and traffic parameters is analyzed. The dynamic OD estimation model basing on kalman filter algorithm is established. The coefficient matrixes of state equation and observation equation are calibrated dynamically by neural network respectively. Finally, part of urban expressway is used as numerical analysis. The simulation results show that the model has higher estimation accuracy. The model can be adopted as one of the theoretical models supporting urban expressway traffic control and management.