V2X Empowered Non-Signalized Intersection Management in the AI Era: Opportunities and Solutions

被引:7
|
作者
Xu Y. [1 ]
Zhou H. [1 ]
Chen J. [2 ]
Qian B. [1 ]
Zhuang W. [3 ]
Shen S.X. [3 ]
机构
[1] Nanjing University, China
[2] Peng Cheng Laboratory, China
[3] University of Waterloo, Canada
来源
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
Vehicles - Intelligent vehicle highway systems - Multi agent systems - Vehicle to vehicle communications - Intelligent systems - Motor transportation;
D O I
10.1109/MCOMSTD.001.2000020
中图分类号
学科分类号
摘要
With significant advancements of vehicle-to-everything (V2X) communication technologies in recent years, intelligent collaboration between connected vehicles and roadside units provides new opportunities for better road safety and vehicle traffic management via innovative non-sig-nalized intersections. In this article, to deal with sophisticated traffic information brought about by a dynamic non-signalized intersection environment, artificial intelligence (AI) solutions together with V2X communication technologies are proposed to provide data-driven intersection management strategies. We first present the emerging technologies and key challenges toward V2X empowered non-signalized intersection management. By introducing the applications of typical AI technologies, we pinpoint three main research issues on V2X empowered non-signal-ized intersection management, leveraging various AI approaches. Finally, we present a case study where a multi-agent learning approach is applied for intelligent multiple intersection management to demonstrate the effectiveness of our non-sig-nalized intersection solution. © 2017 IEEE.
引用
收藏
页码:18 / 25
页数:7
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