文献类型：期刊文献

英文题名：A Collision Avoidance Model for On-Ramp Merging of Autonomous Vehicles

作者：Sheikh, Muhammad Sameer[1];Peng, Yinqiao[1]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China

年份：2023

卷号：27

期号：3

起止页码：1323

外文期刊名：KSCE JOURNAL OF CIVIL ENGINEERING

收录：SCI-EXPANDED(收录号：WOS:000903504300005)、、EI(收录号：20225213302817)、Scopus(收录号：2-s2.0-85144669234)、WOS

基金：AcknowledgmentsThis work was supported in part by the Program for Scientific Research Start-up Funds of Guangdong Ocean University under Grant 060302112202.

语种：英文

外文关键词：Autonomous vehicles; Collision avoidance; Risk assessment; Vehicle safety

外文摘要：Connected and autonomous vehicles (CAVs) have the ability to enhance traffic flow and road safety by significantly reducing human error. Although some collision risks may be eliminated in autonomous vehicles, other potential risks remain, especially at on-ramp merging areas. This paper proposes a collision avoidance model for on-ramp merging of autonomous vehicles under different scenarios. Simulation results suggest that the proposed method can reduce the risks of collision at on-ramp merging areas. Moreover, we assessed the effectiveness of the strategy in terms of traffic flow speed variations with different penetration rates of CAVs. Results show that the collision avoidance strategy leads to lower speed variations. This study reveals that the information obtained from the proposed collision avoidance model could be helpful for improving traffic safety and enhancing urban mobility.