文献类型：期刊文献

英文题名：Distributed optimization for traffic-emission control in urban road networks via cooperative game approach

作者：Zhou, Zhao[1];Shen, Junhan[1];Wu, Qun[1];Liang, Haili[2]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200444, Peoples R China

年份：2025

卷号：35

期号：5

外文期刊名：CHAOS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001501673700005)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant No. 62373153, the Science and Technology Commission of Shanghai Municipality under Grant No. 22JC1401401, and the Open Research Project of the State Key Laboratory of Industrial Control Technology of China under Grant No. ICT2024B67.

语种：英文

摘要：In this study, we introduce a cooperative game-based distributed optimization strategy for green-time traffic signals to balance traffic-emission reduction and computational efficiency. Utilizing a macroscopic link traffic-flow model for the road network and a microscopic vehicle-emission model for traffic emissions, we apply a cooperative game framework to enable communication and coordination among traffic subnetworks. The optimization problem is decomposed into subproblems using the augmented Lagrangian alternating-direction inexact Newton (ALADIN) algorithm, thus enabling effective collaboration among subnetworks. Our findings reveal that this cooperative approach, which leverages the ALADIN algorithm, closely approximates the optimal solution achieved via centralized control, thereby significantly enhancing the computational efficiency while preserving the performance. Through simulation experiments, during both peak and off-peak hours, our approach reduces average computation time by over 48.58% compared to centralized methods. Additionally, our distributed control strategy outperforms fixed-time control, reducing traffic emissions by at least 3.3% in both scenarios.