Vehicle Operating Mode Distribution Model For Emission Evaluation On Traffic Networks

As a main contributor to the air pollution and climate change, vehicle emissions have become a primary target of worldwide governments on pollution controls. In the process of emission controls, it is critical to first accurately determine the level of the pollution. The operating mode of vehicles and the corresponding emissions are the basis in accurately quantifying emissions and the determining factor in evaluating environmental benefits of different traffic control strategies. Existing emission models were developed through extensive emission testing experiments, which attempted to describe in details the emission conditions under different operating modes. However, the modeling issues of the operating modes of vehicles in traffic networks have rarely been studied, thus vehicles'operating conditions are usually provided through rough default values or inputs by users, which could potentially result in huge erros in emission estimations. At present, there is lack of an approach that can capture dynamic variational characteristics of traffic networks as well as effectively connect with vehicle emission models, making it difficult to evaluate emission benefits of traffic control strategies in road networks, which further affects the decision making of governments.In this context, the research in this dissertation intends to develop operating mode distribution models for urban roads and intersection. The feature of the proposed study lies in its selection of traditional traffic parameters as independent variables of both road segment operating mode distribution models and intersection operating mode distribution models. Since traditional traffic parameters can be easily obtained from road traffic networks, the modeling results could be used directly in the calculation in emission models, thus enabling the the dynamic evaluation of emission benefits of traffic networks. Further, since the proposed models are developed based on the analysis of huge amount of the real data, they could effectively characterize the attributes of the road network. The research in the dissertation consists of the following accomplishments:1. Data processing methods are proposed for the road segment operating mode distribution models and intersection operating mode distribution models, thus some key issues are resolved related to road classification and the identification of intersection area. 2. The impact of different time aggregation intervals on the accuracy of operating model distribution reflectec by the average speed is studied. It is found that the shorter the time interval the higher the accuracy. Then, the impact of different speed divisions on the accuracy of driving behavior modes reflected by the average speed is analyzed. The result shows that the shorter the speed division the higher the accuracy. Further, the impact of different VSP division methods on emission estimations is analyzed. It is found that due to the weighted average calculation approach and the stability of emission rate with the change of VSP, the impact of VSP division methods on emission estimatins is very minimum.3. Gaussion function is used to curve fit the road segment operating mode distributions under different average speeds. It is found that the curves are well fited for both expressways and non-expressways. Then, the Gaussian parameter model is esblished with the average speed as the indepdent parameter. As a result, the operating mode distribution can be derived by using the average speed with the linkage of Gaussion function. Furthermore, the Genetic Algorithm is used to improve the accuracy of the model.4. The sample size of the road segment operating mode distribution model is analyzed. The minimum sample sizes for different road classes and different average speeds are determined to ensure the conditions for model applications.5. Based on the character analysis of the operating mode distribution at intersections, the characteristic parameters of intersection operating modesare identified. Then, the parameter weight matrix is developed based on both the stepwise regression model and the distribution rates of operating modes. Finally, the intersection operating mode distribution model is established based on the Partical Swarm Optimization K-Means cluster algorithm.6. The road segment operating mode distribution model is applied to the emission analysis of the vehicle restriction policy in Beijing. The intersection operating mode distribution model is applied to the emission evalution of signal timing program.