Research On Traffic Signal Control Strategies In Urban Intersections Based On Emission Factors

Traffic is the foundation and the economic lifelines of the modern society. In China, the quantity of vehicles increases rapidly, at the same time, traffic infrastructure and management methods have some shortages. As a result, the traffic congestions in intersections become more and more serious. It makes intersections have become bottlenecks of the urban traffic. Traffic signal is an essential element to manage the transportation network. Nevertheless, it is widely accepted that the benefits of traffic control signal systems are not being fully practiced. Along with the development of Intelligent Transportation System (ITS), the research on traffic signal control is by no means complete and traffic signal control remains one of the most heavily funded research and development items. A number of models of the traffic signal control have been developed in the past. However, those models mainly focus on the traffic flow and don't take other factors into account.With the development of urban transportation, large numbers of vehicles cause serious air pollution and noise pollution. The authoritative statistics shows that the share rate of vehicles exhaust emission to atmosphere has an obvious increasing tendency. This problem, how to establish an harmonious traffic systems of human, vehicles, roads and environment, has been recognized as one of the most critical, yet challenging problems for the world. Therefore, it has practical significance to establish a new traffic signal control model based on the condition of the traffic flow and vehicle exhaust emissions.In this dissertation, the research of theoretical analysis and application methods are given on base of summarizing the domestic and overseas research progress and analyzing the development trends of urban traffic signal control. The principle of the traffic signal control by intelligent optimization, mainly the basic optimal theories and the methods of Genetic Algorithm as well as Ant Colony Algorithm are proposed firstly. Through the study and the analysis of traffic streams in an intersection, a bi-level multi-object optimization model of traffic signal control in an intersection is established. The simulation tests are conducted using Genetic Algorithm and The Fusion Algorithm of Genetic and Ant Colony. The simulation results show that the optimal algorithms are superior to the traditional methods, and the fusion algorithm is most suitable for determining the green split in a single intersection.The main achievements of the dissertation are as follow:(1) A bi-level multi-object model is established for optimizing the signal cycle length and green time by considering the constraint of automotive exhaust emission. The performance index function for optimization is defined to improve traffic quality and reduce emission at intersections. The research tries to limit the range of vehicle exhaust emissions on the premise of unimpeded transport by changing the traffic signal control strategy.(2) The heuristic genetic algorithm is designed to solve the problem, simplifying the model by means of penalty strategy. Subsequently MATLAB program is given to simulate the solution process. The simulation results show that very nice effects are obtained.(3) The fusion algorithm of genetic and Ant Colony applied in solving the function optimization problem is presented. By comparing with other solution methods, the fusion algorithm has the best performance.(4) The typical topological structure of urban road network is designed by combining the features of traffic signal control with the study perspective of this research.(5) Traffic simulation system (VISSIM) is used to simulate the situation of traffic flow in the typical urban road network and gains the results on the condition of fix signal timing plan. The function of the results is substituting into the model as parameters and verifying the optimization effect of above algorithms.