Alleviating Road Traffic Congestion with Artificial Intelligence

被引：0

作者：

Sharon, Guni ^{[1
]}

机构：

[1] Texas A&M Univ, Comp Sci & Engn, College Stn, TX 77843 USA

来源：

PROCEEDINGS OF THE THIRTIETH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2021 | 2021年

关键词：

REPRESENTATION; GRADIENT; WAVES; TIME;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper reviews current AI solutions towards road traffic congestion alleviation. Three specific AI technologies are discussed, (1) intersection management protocols for coordinating vehicles through a roads intersection in a safe and efficient manner, (2) road pricing protocol that induce optimized traffic flow, and (3) partial or full autonomous driving that can stabilize traffic flow and mitigate adverse traffic shock waves. The paper briefly presents the challenges affiliated with each of these applications along with an overview of state-of-the-art solutions. Finally, real-world implementation gaps and challenges are discussed.

引用

页码：4965 / 4969

页数：5

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