文献类型：期刊文献

英文题名：A Rolling-Horizon Approach for Mitigation of Exhaust Emissions in Urban Traffic Networks

作者：Liu, Hualing[1]; Zhou, Zhao[1]; Liang, Haili[2]

机构：[1] East China University of Science and Technology, Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, 200237, China; [2] School of Mechatronic Engineering and Automation, Shanghai University, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai, 200444, China

年份：2023

起止页码：2253

外文期刊名：Proceedings - 2023 China Automation Congress, CAC 2023

收录：EI(收录号：20241515852816)

语种：英文

外文关键词：Air pollution - Air pollution control - Motor transportation - Road vehicles - Roads and streets - Street traffic control - Traffic congestion - Urban transportation

摘要：With the continuous and rapid increase in the number of motor vehicles in our country, vehicle exhaust emission pollution is one of the important sources of air pollution, so the prevention and control of motor vehicle exhaust pollution is becoming more and more severe. Aiming at the problem of vehicle exhaust emissions in the urban transportation networks, this paper proposes a predictive control method based on the Macroscopic Fundamental Diagram, which can not only reduce vehicle exhaust emissions, but also alleviate the congestion of the transportation network. According to the historical traffic data of the road network, we obtain the macroscopic fundamental diagram of the sub-road networks through the polynomial fitting method, and then construct the traffic dynamics model between multi-sub road networks on this basis. Then, a mixed pollutant emission model is constructed by using the relationship between the pollutant emission rate and the state of the vehicles in the road network. With the objective function of minimizing pollutant emissions, we design a model-based road network optimization control method, and simulate three different traffic scenarios. The results show that the proposed predictive control method can effectively alleviate the congestion of the road network and reduce the pollutant emissions of vehicles. ? 2023 IEEE.