Analysis And Management Measures Of Urban Traffic Network Considering Human Exposure To Vehicular Emissions

With the rapid development of China’s economy,the urbanization level has exceeded 60%,and the per capita GDP is more than $10,000 by 2020.At the same time,due to the increasing improvement of the living standard,people require a higher quality of travel experience.The most popular travel tools for families are cars which contain the characteristics of comfort,convenience,and door-to-door.However,the sharply increasing number of vehicles leads to more vehicular emissions which heavy urban’s air pollution and harm people’s health.Recently,the air pollution problem caused by transportation activities has been increasingly noticed,and it is also an urgent problem for traffic managers to solve.In the research field of transportation engineering and management,the efforts mostly are spent to model and control the vehicular emissions at the source,without paying much attention to the impacts of vehicular emissions on people(vehicular emission exposure).On the one hand,transportation activities lead to air pollution(exposure);on the other hand,travelers are the victims of air pollution since they are directly exposed to vehicular emissions,and this,in turn,affects travelers’ trip-making decisions.Such inter-relationship between trip-making decisions and human exposure to vehicular emissions has not been fully studied.The study aims at studying the impact of network traffic on emission exposure and exploring traffic organization and traffic management methods when considering human exposure to vehicular emissions.The research main contents of this thesis are summarized as follows:(1)An integrated analytical model consists of a traffic flow model,a traffic emission estimation model,and a dispersion model are proposed to describe the impact of vehicular emissions on people’s health within the traffic network.The related theory of modeling including the traffic network equilibrium principle,the methods of estimating the vehicular emission source,and the methods of extending the point source dispersion model to the line source dispersion mod el are introduced.Then,the impacts of vehicular emission within the traffic network on travelers and area residents are modeled.These theories and methods form the foundation of the following research contents.(2)An integrated modeling framework is applied to analytically estimate travelers’ vehicular emission exposure within the traffic network,which is considered as a part of the generalized travel cost.The proposed method adopts the BPR function and a macroscopic emission model to describe the source of emissions.Gaussian line source dispersion model is then used to capture the dispersion of emissions from the source.We further assume that a proportion of the transportation users are environmental advocates and their route choice decisions are based on some composite cost functions comprise of a travel time component and an emission e xposure component.We then study the multiple equilibrium behaviors with multiple types of users on a traffic network.The multiple equilibrium problems are further converted into variational inequality(VI)problems and they are solved using a method of successive average(MSA)-based diagonalization method.The results show that as travelers become more concerned about their exposure to vehicular emissions,the system emission exposure,travel time,as well as the total cost all get reduced.(3)A dynamic traffic flow model named "double-queue" and a time-dependent macroscopic emission model are incorporated into the emission exposure integrated model to extend the static one.From the area residents’(non-traveler)perspective,a network dynamic system-optimal problem that considers human exposure to vehicular emissions(called DSO-HE)is formulated to minimize regional emission exposure.An illustrative network and the Sioux Falls network are used to test the proposed model.Under certain meteorological conditions,we show that the emission exposure in a residential area with a high population-sensitivity parameter can be reduced by properly managing network traffic flow.The DSO-HE results are compared with the time cost-based dynamic system optimal(DSO-TC)model.The results show that the total time cost and emission exposure cannot be minimized simultaneously,which implies that traffic system operators must properl y leverage the tradeoff between congestion and emissions.The results show that the emission exposure at different study area locations is different under variable wind direction and wind speed,and the regional emission exposure can be reduced by managing network traffic flow.(4)Based on the above research,we design road pricing models to guide the traveler to choose more rational routes to optimize network emission exposure.To clarify the relationship among regional emission exposure,travelers’ emission exposure,and the system total emission exposure,we establish three bi-level optimization models with different management purposes.The low er-level of these bilevel optimization models is the user equilibrium model considering road toll and travel time,and the objective function of upper-level is to minimize regional emission exposure(U1),minimize traveler’s emission exposure(U2),and to minimize the system total emission exposure(U3=U1+U2),respectively.A mixed solution method of Frank-Wolfe-based improved genetic algorithm is developed to solve these bi-level models.A numerical example is used to test the proposed bi-level models and solution algorithm.We also analyze the change of network emission exposure under the first-best pricing situation and the second-best pricing situation.The results show that the road toll scheme is more reasonable when considering simultaneously regional emission exposure and travelers’ emission exposure.The network emission exposure can be significantly reduced by charging tolls on a few key roads.(5)Walking is the last part of the morning commute for commuters after parking.Walking commuters risk exposure to vehicular emissions.To better understand the impacts of emission exposure on commuters’ departure time choice and parking behavior,we establish an analytical model to capture emission exposure and incorporate it into the generalized cost of commuters based on the classical bottleneck model.To reduce the vehicular emission exposure of commuters,w e design an optimal parking pricing scheme with time-varying and location characteristics.The analysis of the proposed model shows that the parking pricing scheme can induce commuters to change their departure time choice and parking order,which can achieve system optimum.The research work in this thesis provides a novel idea for the prevention and control of urban air pollution and also can provide analysis methods and decisionmaking basis for traffic managers to develop reasonable traffic organization and management policies.