TY - JOUR
T1 - A cooperative space distribution method for autonomous vehicles at a lane-drop bottleneck on multi-lane freeways
AU - Phan, Tung Thanh
AU - Le, Long Bao
AU - Ngoduy, Dong
PY - 2022/4
Y1 - 2022/4
N2 - With the help of inter-vehicle communication (IVC), autonomous vehicles (AVs) can drive cooperatively, thus significantly improve road safety, traffic efficiency, and environmental sustainability. While substantial research has been conducted to investigate the efficiency of AVs in transportation systems, few attempts have been carried out to explore the lane-changing operations of AVs in multi-lane freeways, especially the dynamics of AVs at lane-drop bottlenecks. To this end, this paper aims to develop a cooperative space distribution method (CSDM) not only to increase the lane-drop bottleneck's throughput but also to equally distribute the AVs in the dropped lane to other lanes by efficiently coordinating the dynamics of AVs upstream of the bottleneck in a multi-lane freeway. More specifically, we propose a novel framework where the freeway (region of interest) is divided into three segments: i) platoon segment, ii) acceleration segment, and iii) merging segment. In the first segment, AVs travel together in the platoon to guarantee their safety; they will then speed up to attain the maximum velocity and reach the determined position in the second segment. Finally, these AVs change lanes in the last segment and pass through the bottleneck with maximum velocity and minimum gap (i.e., gap distance). Simulation results are tested to demonstrate the performance of the proposed method, where we show that the proposed framework can significantly decrease the average travel time of all vehicles.
AB - With the help of inter-vehicle communication (IVC), autonomous vehicles (AVs) can drive cooperatively, thus significantly improve road safety, traffic efficiency, and environmental sustainability. While substantial research has been conducted to investigate the efficiency of AVs in transportation systems, few attempts have been carried out to explore the lane-changing operations of AVs in multi-lane freeways, especially the dynamics of AVs at lane-drop bottlenecks. To this end, this paper aims to develop a cooperative space distribution method (CSDM) not only to increase the lane-drop bottleneck's throughput but also to equally distribute the AVs in the dropped lane to other lanes by efficiently coordinating the dynamics of AVs upstream of the bottleneck in a multi-lane freeway. More specifically, we propose a novel framework where the freeway (region of interest) is divided into three segments: i) platoon segment, ii) acceleration segment, and iii) merging segment. In the first segment, AVs travel together in the platoon to guarantee their safety; they will then speed up to attain the maximum velocity and reach the determined position in the second segment. Finally, these AVs change lanes in the last segment and pass through the bottleneck with maximum velocity and minimum gap (i.e., gap distance). Simulation results are tested to demonstrate the performance of the proposed method, where we show that the proposed framework can significantly decrease the average travel time of all vehicles.
KW - Autonomous vehicles (AVs)
KW - flow rate
KW - platoon
KW - throughput.
UR - http://www.scopus.com/inward/record.url?scp=85097922757&partnerID=8YFLogxK
U2 - 10.1109/TITS.2020.3040431
DO - 10.1109/TITS.2020.3040431
M3 - Article
AN - SCOPUS:85097922757
SN - 1524-9050
VL - 23
SP - 3710
EP - 3723
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 4
ER -