Study On Dynamic Origin-Destination Matrix Estimation Of Urban Expressway

With the development of national economy and accelerating urbanization process, the traffic researchers have paid more attention to the jam of city traffic. In the past several decades, many theories of intelligent traffic and management methods have been applied to real traffic management, which is important to make the traffic conditions of traffic networks better and improve traffic efficiency. Function of urban traffic facility is an important measure to make deteriorating traffic conditions better and decrease traffic jams. Urban Expressways that load heavy and long-distance traffic volume have arised. Dynamic Origin-Destination(OD) demands are essential input for on-line traffic control, dynamic traffic-assignment simulation and management systems. Hence, study on dynamic OD estimation of expressway has important significance.The purpose of the dissertation is to develop effective models and algorithms for dynamic OD estimation of urban expressway. This study mainly follows the research line of non-assignment-based methods to investigate dynamic OD estimation of expressway networks. Firstly, the thesis summarizes and analysises existing static and dynamic of OD models and algorithms. Secondly, the thesis purposes a state-space model of traffic flow model parameters and its algorithm to apply to the travel time estimation of dynamic OD matrix. Thirdly, on the basis of the assumption of normal distribution of the travel time, we study dynamic OD estimation of urban expressway corridor and urban expressway network, establish the models and design the corresponding solving algorithms. The thesis evaluates the proposed models based on numerical tests of dynamic traffic assignment.The main innovation points and contents of the study include:1. Construct a state-space model of traffic flow parameters. To obtain the travel time estimation of dynamic OD matrix, we propose the state-space model and evaluate the models of computering the travel times of OD demand.2. Propose two dynamic OD estimation models of urban expressway corridor based on Unscented Kalman Filter. The proposed models capture the speed discrepancy among drivers and integrate the state-space model of traffic flow parameters. Numeral experiments compare and analyze the two models. The results show the proposed dynamic OD estimation is stable and robust. 3. Introduce and improve Unscented Kalman Filter (UKF) algorithm. UKF algorithm is an important core algorithm for the thesis. The advantage of UKF does not need to obtain Jacobian matrix of measurement equations. Normal UKF algorithm does not consider existing constraints, which leads to larger errors. The thesis considers the problem of UKF under constraint conditions, which have important significance to solve other problems based on UKF under constraint conditions.4. Propose a dynamic OD estimation model of expressway network with screenline flows based on the assumption of normal distribution of travel times of OD pairs. By modifying measurement equations and the estimation of travel time, the thesis extends the linear dynamic OD estimation model of expressway network to a no-linear model.5. Propose a dynamic OD estimation model of expressway network based on a dynamic traffic assignment model. Considering that the information of road network is uncomplete, the thesis extends the dynamic OD estimation model proposed by K. Ashok based on a traffic assignment model and the assumpation of normal distribution of the travel times of OD pairs, which doesn't denpend on a historic OD matrix. Subsequencely, the thesis proposes an integrated dynamic OD model for expressway network based on the technique of screenline flow and a dynamic traffic assignment model. The thesis evaluates and analyzes the proposed models by numerical tests. Numerical results show that our proposed models are stable and robust.