Research On Traffic Flow Assignment And Signal Control Technology For Urban Road

With rapid social and economic development, the number of cars is increasing quickly, which makes the city traffic jam more and more serious. The most effective method to solve this problem is to adopt the intelligent traffic control technology. Traffic guidance and traffic control are the two key parts of the intelligent transportation system. The essence of traffic guidance is the use of traffic assignment theory to achieve equilibrium of traffic flow in road in term of space. On the other hand, traffic control is to use signal control theory to realize the reasonable optimization of traffic flow in view of passage time. Therefore, it is of great significance to study traffic assignment and signal control.In this paper, we gain an insight into the traffic assignment, signal control and coordination of them, according to the characteristics of the urban road network of China, using automatic control theory, operations research, artificial intelligence and traffic engineering technologies.Three main contributions of this paper are listed as follows:1. The traditional Dijkstra algorithm is improved based on the topological structure of the actual road network. In addition, to achieve balance of the traffic flow in real road network, one traffic flow assignment algorithm is proposed according to the traffic distribution model.2. An optimization model for city traffic signal control is established, whose objective function is composed of weighting and synthesizing delay, stop frequency, capacity and saturation, and constraint condition consists of the duration of green lights. Through the improvement of the selection, crossover and mutation strategy, the promoted genetic algorithm is used as a calculation method for the optimization model.3. Based on the regional coordinated signal control theory and traffic flow assignment theory, a bi-level programming model for traffic flow assignment and signal control optimization is put forward. The upper programming model is used to optimize the public signal cycle, split and offset in the regional coordination control; the lower level programming model is used to achieve a balanced distribution of traffic flow in the area. By combining the genetic algorithm with the allocation algorithm for traffic flow, a heuristic algorithm is proposed for the bi-level programming model.