Traffic Assignment Model And Algorithm With Combined Modes On Urban Transportation Network

With the acceleration of urbanization and the improvement of the transportation infrastructure, the combined travel mode becomes the main commuting mode in the daily life. The combined travel mode means that travelers reach their destination by using more than one traffic modals. Most of the current researches on the traffic assignment, however, focus on the single-modal travel mode, or assume travelers only use one traffic modal in a trip. The ignorance of the transfer behavior cannot fully describe the real travel behavior and the traffic operating condition. Therefore, it is imperative to further investigate into the traffic assignment model and algorithm with combined modes, in order to provide the theoretic foundation for the multi-modal coordinated operation, as well as help to alleviate traffic congestion.The dissertation focuses on the urban traffic assignment model and algorithm with combined modes, taking into account the travel characteristics in the multi-modal transportation network. Firstly, the existing relevant researches were reviewed, analyzed and summarized from the methods and ideas, which lays foundations for the further research in this dissertation. Secondly, focusing on the structure characteristics of the multi-modal transportation networks, the multi-modal super network is built based on the super network theory and the expanding technique. Thirdly, the static analysis model, dynamic analysis model and the dynamic simulation model are proposed with consideration of the combined travel mode, and the solution algorithms are discussed separately. Finally, the verifications of the proposed models and their algorithms are given through the ideal experiment network and the real transportation network. Also, the influence caused by parameters changes and the management measures are investigated.The major attained in this dissertation are listed as follows:1. Super network theory and the expanding technique are introduced to build the multi-modal transportation networks, which are mutually dependent and interacting. Based on this network, the influence factors that affect the travel choice are analyzed including travel time, travel cost and travel comfort. The generalized travel cost function is given to quantize these influences.2. The choice preferences for the travel mode and the route are modeled based on the Logit model. And the equivalent stochastic traffic assignment model is proposed by using the traffic equilibrium theory and the variational inequality theory. A solution algorithm is designed on the basis of Method of Successive Weight Average (MSWA). The model and the solution algorithm are verified by an experiment network. The results showed that:MSWA method is superior to MSA when solving the Logit-SUE model; the model and the algorithm can contribute to determine the reasonable position of park and ride site; it can also scientifically determine the reasonable range of parking fee cost in park and ride and bicycle rental cost in renting bicycles; moreover, the trip-chain-based traffic assignment and degradable network cases are discussed with corresponding experiments.3. The simultaneous combined departure time and dynamic stochastic user equilibrium assignment (DDSUE) problem is investigated with combined modes. The DDSUE condition is analyzed based on the Logit model from the path formulation perspective. The direct solution algorithm is given based on the dynamic stochastic network loading. The experiment is designed not only to illustrate the model and algorithm, but discuss the sensitivity of the model parameters. Moreover, the multi-users behavior and accident case are also undertaken in the experiment.4. A simulation-based dynamic traffic assignment model for urban multi-modal transportation network is presented with combined models. The mesoscopic simulator consists of a mesoscopic supply simulator based on MesoTS model and a time-depended demand simulator. The mesoscopic supply simulator includes four parts: vehicle generation module, traffic cell module, modal-route choice module and vehicle movement module. The mode choice is simultaneously considered with the route choice based on the improved C-Logit model. The traffic assignment procedure is implemented by a time-dependent shortest path algorithm in which travelers choose their modes and routes based on a range of choice criteria. The model is particularly suited for appraising a variety of transportation management measures, especially for the application of Intelligent Transport Systems (ITS). Five example cases including OD demand level, bus frequency, parking fee, information supply and car ownership are designed to test the proposed simulation model through a medium-scale case study in Beijing Chaoyang District in China. Computational results illustrate excellent performance and the application of the model to analysis of urban multi-modal transportation networks.