Reaserch On Multi-Objective Optimization Of Traffic Signal Timing Consindering Emission Characteristics

In recent years, with the continued development of national economy and vehicle ownership and increased road traffic dramatically, the traffic congestion and environmental pollution problems become more and more serious. The traffic congestion occurs at urban signalized intersections, which leads to the increase of vehicle delay, low speed of vehicle and increase of fuel consumption. The degree of pollution of the urban environment is increasing. Therefore, improving the traffic conditions will have great significance for improving vehicle efficiency and environmental benefits. In the methods of improving the traffic conditions of urban intersections, the signal timing optimization can be efficient to reduce emission and improve operational efficiency. Therefore, the multi-objective optimization method of traffic control which based on emission characteristics is studied in this thesis. The main work includes the following aspects:Firstly, this thesis introduces the vehicle emission model which based on VSP variable and VISSIM simulation software and builds the microcosmic traffic exhaust simulation platform. The microcosmic traffic exhaust simulation platform is used to analyze the motion of vehicle when approaching intersection and emission characteristics of each traffic mode, which can provide theoretical basis for researching of timing optimization.Secondly, this thesis embarks from the vehicle operation benefit and environment benefit, the model of multi-objective optimization method and simulation of multi-objective optimization method are studied respectively. The multi-objective optimization model is established considering vehicle delay, queue length, and exhaust emission as optimization objectives. The genetic algorithm is used to solve the model. When the simulation of multi-objective optimization is studied, the intersections signal timing is optimized based on VISSIM simulation software, emission model based on VSP variable and genetic algorithm. The results show that two optimization methods have better control effects.Thirdly, the arterial coordination model based on multi-objective optimization is established with the timing parameters as optimization variables, considering arterial vehicle delay, queue length, and exhaust emission as optimization objectives. The genetic algorithm is used to solve the model. Finally, the urban arterial coordination multi-objective optimization method is verified through a concrete example. The results show that arterial signal coordinated control method which based on multi-objective optimization model can reduce vehicle delays and queue length, exhaust emission increased, but increased modestly.Finally, based on theoretical analysis of the influence of emission and delay of right-turn vehicle by setting the right-turn signal, the different right-turn vehicle flow under three different pedestrian flow is studied and simulated to analyze the vehicle and emission changes of right-turn signal phase setting before and after under three different pedestrian flow. Then the effectiveness of the right-turn signal is analyzed. The results indicate that the right-turn signal is suitable to set when the right-turn vehicles flow is below 615±20/( 1pcu h-×).It needs to consider other factors which can determine whether suit to set up the right-turn signal with the increase of right-turn vehicles flow.