Effect Analysis And Optimizing Control Of Bus Operation On Air Pollution In Urban Areas

With rapid increasing of motor vehicle quantities in urban area, motor vehicle exhaust has become the main source of atmospheric pollution. The vehicle emission has restricted the sustainable development of the city. Under this situation, the control of vehicle emission has become an urgent research issues. Bus is the most popular public transportation mode in the cities of China. Because of running long time in the urban centers, frequent start-up, brake, acceleration and deceleration, buses produce serious exhaust pollution and make a major contribution to the total vehicular emissions in the urban area. The main purposes of this dissertation are to understand the impact of bus operation on atmospheric environment and establish the bus transit system in a green manner. According to the experimental data and survey data, motor vehicle emission inventory is developed by the vehicle emission model. Some easy-to-control factors are picked out which have significant influences on bus emission. The problems, including transit fleet management, regional bus scheduling and bus fares, are studied by mathematical programming method. The optimization models are established and swarm intelligence algorithms to solve the models are also presented. The main study works in this dissertation are as following:1) Buses in the city of Wuhan are used as the study object. The driving characteristics of bus are analyzed based on experimental and cruising data. The IVE model designed for developing nations is adopted to estimate the emission of buses. Bus emission inventory is calculated according to the driving cycle. Then the contribution rates of different types of vehicle to the total vehicular emissions in the urban are studied. The factors that affect bus exhaust emissions are classified analysis. Three factors are selected as the object of a follow-up study for easy-to-control characteristics.2) The purchase cost, use costs, scrap cost and exhaust emission of various vehicles are also different. According to the analysis results of the comprehensive costs and exhaust emission, a transit fleet management model is developed based on integer linear programming method. The model can make vehicle purchase and replacement decisions under environmental constraints. The model can minimize total costs of bus companies in the whole planning period with given emission constraints. Other factors including capital budget, facility capacity, and passenger demand are also considered in the model. The dissertation chooses a transit fleet of Wuhan as case study. The results show that subsidies for vehicles purchase and fuel prices are the sensitive factors affecting the configuration of fleet. The procurement of CNG and conventional diesel vehicles will increase and number of early retirement will also rise when the subsidies decline or price difference between diesel and natural gas widen.3) The dissertation takes environmental impacts of vehicles operation into consider when making transit buses scheduling. According to the operation characteristics and related requirements, the bus scheduling model is established with the target of minimizing fixed costs, operation cost and exhaust pollution cost. The best parking depot and operation schedules of vehicles could be made by the help of the model. The fusion algorithm of Ant Colony Optimization and Variable Neighborhood Search is put forward for better performance. A network composed of different bus lines is selected for case analysis. The results show that the model can put forward the better resource utilization scheme. With contrast to independent optimization scheme of each line, regional scheduling scheme will cut the number of vehicles, reduce comprehensive cost and decrease exhaust pollution costs.4) A Bus toll model under urban road congestion pricing is proposed in the dissertation based on the bi-level programming method. The target of minimizing the travel time cost and pollution cost of the whole system is realized by the combination scheme of bus toll and congestion pricing, which have impacts on user trip mode and trip route selection. Economic benefits and environmental benefits are all considered. Logit-based effectiveness model is applied to describe the behavior of mode choice between public transport and private transport. The low-level model is established based on user equilibrium principle. By Analysis of travel time and exhaust emissions in the whole traffic network the upper level model is established. The upper model takes into account bus fees, congestion pricing and other factors. An improved Particle Swarm Algorithm is developed to solve the up-level model and Convex Combination Method Algorithm is used to solve low-level model. The validity and feasibility of the model is verified by a case study in small traffic network.