A Study on Reducing Traffic Congestion in the Roadside Unit for Autonomous Vehicles Using BSM and PVD
-
Published:2024-03-18
Issue:3
Volume:15
Page:117
-
ISSN:2032-6653
-
Container-title:World Electric Vehicle Journal
-
language:en
-
Short-container-title:WEVJ
Author:
Lee Sangmin1, Oh Jinhyeok1, Kim Minchul1ORCID, Lim Myongcheol1, Yun Keon1, Yun Heesun1, Kim Chanmin2, Lee Juntaek2
Affiliation:
1. Pentasecurity, Incorporated, 9F, 115, Yeouigongwon-ro, Yeongdeungpo-gu, Seoul 07241, Republic of Korea 2. Korea Automotive Technology Institute, 4F, 94, Cheongna emerald-ro, Seo-gu, Incheon 22739, Republic of Korea
Abstract
With the rapid advancement of autonomous vehicles reshaping urban transportation, the importance of innovative traffic management solutions has escalated. This research addresses these challenges through the deployment of roadside units (RSUs), aimed at enhancing traffic flow and safety within the autonomous driving era. Our research, conducted in diverse road settings such as straight and traffic circle roads, delves into the RSUs’ capacity to diminish traffic density and alleviate congestion. Employing vehicle-to-infrastructure communication, we can scrutinize its essential role in navigating autonomous vehicles, incorporating basic safety messages (BSMs) and probe vehicle data (PVD) to accurately monitor vehicle presence and status. This paper presupposes the connectivity of all vehicles, contemplating the integration of on-board units or on-board diagnostics in legacy vehicles to extend connectivity, albeit this aspect falls beyond the work’s current ambit. Our detailed experiments on two types of roads demonstrate that vehicle behavior is significantly impacted when density reaches critical thresholds of 3.57% on straight roads and 34.41% on traffic circle roads. However, it is important to note that the identified threshold values are not absolute. In our experiments, these thresholds represent points at which the behavior of one vehicle begins to significantly impact the flow of two or more vehicles. At these levels, we propose that RSUs intervene to mitigate traffic issues by implementing measures such as prohibiting lane changes or restricting entry to traffic circles. We propose a new message set in PVD for RSUs: road balance. Using this message, RSUs can negotiate between vehicles. This approach underscores the RSUs’ capability to actively manage traffic flow and prevent congestion, highlighting their critical role in maintaining optimal traffic conditions and enhancing road safety.
Funder
Institute of Information & communications Technology Planning & Evaluation
Reference38 articles.
1. Yeong, D.J., Velasco-Hernandez, G., Barry, J., and Walsh, J. (2021). Sensor and sensor fusion technology in autonomous vehicles: A review. Sensors, 21. 2. An overview of sensors in Autonomous Vehicles;Ignatious;Procedia Comput. Sci.,2022 3. Fayyad, J., Jaradat, M.A., Gruyer, D., and Najjaran, H. (2020). Deep learning sensor fusion for autonomous vehicle perception and localization: A review. Sensors, 20. 4. Artificial intelligence applications in the development of autonomous vehicles: A survey;Ma;IEEE/CAA J. Autom. Sin.,2020 5. Khayyam, H., Javadi, B., Jalili, M., and Jazar, R.N. (2020). Nonlinear Approaches in Engineering Applications: Automotive Applications of Engineering Problems, Springer.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|