EcoMRL：基于深度强化学习的城市空气质量交通信号控制

IF 3.1 3区工程技术 Q2 ENVIRONMENTAL STUDIES

International Journal of Sustainable Transportation Pub Date : 2024-06-12 DOI:10.1080/15568318.2024.2364728

Jaeeun Jung, Inhi Kim, Jinwon Yoon

引用次数: 0

摘要

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EcoMRL: Deep reinforcement learning-based traffic signal control for urban air quality

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来源期刊

International Journal of Sustainable Transportation Multiple-

CiteScore

8.90

自引率

2.60%

发文量

期刊介绍： The International Journal of Sustainable Transportation provides a discussion forum for the exchange of new and innovative ideas on sustainable transportation research in the context of environmental, economical, social, and engineering aspects, as well as current and future interactions of transportation systems and other urban subsystems. The scope includes the examination of overall sustainability of any transportation system, including its infrastructure, vehicle, operation, and maintenance; the integration of social science disciplines, engineering, and information technology with transportation; the understanding of the comparative aspects of different transportation systems from a global perspective; qualitative and quantitative transportation studies; and case studies, surveys, and expository papers in an international or local context. Equal emphasis is placed on the problems of sustainable transportation that are associated with passenger and freight transportation modes in both industrialized and non-industrialized areas. All submitted manuscripts are subject to initial evaluation by the Editors and, if found suitable for further consideration, to peer review by independent, anonymous expert reviewers. All peer review is single-blind. Submissions are made online via ScholarOne Manuscripts.