Research On Collaborative Optimization Of Urban Traffic Control System And Traffic Flow Guidance System At Miniature Road Network Considering Priority Signals At Intersections

With the development of Intelligent Transportation System (ITS), collaborative optimization of urban traffic control system (UTCS) and urban traffic flow guidance system (UTFGS) has been considered as a state-of-art and feasible technology to alleviate urban traffic congestion and enhance the efficiency of urban traffic operation. Based on existing achievements in this field, this dissertation researches on the theories and methods of collaborative optimization of UTCS and UTFGS focus on non-priority vehicles under the circumstance that setting up priority signals at intersections. The method aims at decreasing the delays at intersections and total travel time on road network for non-priority vehicles as far as possible and then reducing the impact of priority vehicles on non-priorities by implementing collaborative optimization of UTCS and UTFGS on non-priorities, while ensuring priorities passing the intersections smoothly under the control of priority signals. The main contents are as the following:1. Researching on the feasibilities of collaborative optimization of priority signal control, general signal control and traffic flow guidance system based on analyzing traffic flow movement characteristics and logical structures of existing systems; analyzing the main factors influencing on collaborative patterns; proposing different collaborative strategies under different levels that priority vehicles have impacts on non-priorities, and then proposing the relevant structures of the system.2. Establishing the bi-level programming model for collaborative optimization of UTCS and UTFGS considering priority signals at intersections, based on analyzing the adaptabilities of several existing and commonly used collaborative methods under the circumstance of priority signals; pointing out the established models consist of three parts, including traffic control model, traffic guidance model and route selection model; providing methods for working out the model based on available theories and Genetic Algorithm.3. Using field data to calculate the collaborative model taking a small road network in Chengdu City as an example; illustrating the feasibilities and efficiency of the proposed model by conducting a significance analysis between the calculating results from the proposed model and simulation results according to actual situation.4. Summarizing the dissertation and proposing recommendations for further research.The above research contributions may have state-of-practical reference value for researching on collaborative optimization of UTCS and UTFGS under specific conditions, releasing road network information, alleviating urban traffic congestion, enhancing the efficiency of urban traffic operation and increasing the level of data sharing among different urban traffic management systems.