4.7 Article

Merging and Diverging Impact on Mixed Traffic of Regular and Autonomous Vehicles

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2020.2974291

关键词

Merging; Autonomous vehicles; Roads; Vehicle dynamics; Reinforcement learning; Decision making; Connected and Autonomous Vehicles (CAVs); ramp; lane-changing behavior; traffic flow

资金

  1. National Key Research and Development Program of China [2018YFB1600500]

向作者/读者索取更多资源

This paper examines the impacts of Connected and Autonomous Vehicles (CAVs) on mixed regular-automated traffic flow, introducing a cooperative lane-changing strategy to improve traffic efficiency. Results suggest that CAVs considerably enhance traffic flow, mean speed, and traffic capacity, while the presence of on/off-ramps significantly affects lane-changing processes.
In the context of Connected and Autonomous Vehicles (CAVs), this paper aims to examine the impacts of CAVs on mixed regular-automated traffic flow with the increase of the market penetration rate, in consideration of on-ramp merging and off-ramp diverging of vehicles. Lane changes are a major part of lateral motions, affecting surrounding vehicles locally and traffic flow collectively. On the basis of reinforcement learning technique, a cooperative lane-changing strategy was first developed to enable farsighted lane-changing behavior by CAVs in favor of traffic efficiency. The 3-lane highway stretch with one on-ramp and one off-ramp was applied in this study. With extensive simulations, the results suggest that the inclusion of CAVs considerably improves traffic flow, mean speed, and traffic capacity. Meanwhile, the existence of on/off-ramps has substantial impacts on the lane-changing processes. This work can shed some light on an aspect of the mixed traffic network dynamics for future mobility.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据