Home // ICONS 2023, The Eighteenth International Conference on Systems // View article
Authors:
Jie Zhang
Marian Göllner
Xiaobo Liu-Henke
Keywords: Optimal intersection management; cooperative intersection control; connected autonomous vehicles; Vehicle-to-Vehicle (V2V) communication; Model-in-the-Loop-Simulations; model-based systems engineering.
Abstract:
Considering the increasing population and vehicle demand, the development of a safer and more efficient intersection management system is of critical importance. The following paper addresses decentralized intersection management through synergetic cooperation of networked autonomous vehicles to optimize intersection throughput as well as ensure proactive safety of all vehicles. Through Vehicle-to-Vehicle (V2V) communication, autonomous vehicles can obtain real-time information from all road users within the effective communication range, including position, speed, direction of travel, and destination. Based on the information, the priority for crossing the intersection or the order of passage can be determined by coordination between vehicles, so that the conflict zone of the intersection always remains free of traffic. At the same time, low-priority vehicles can also adjust their speed in advance to avoid potential conflicts with other vehicles. A pilot application is used to validate and demonstrate the model-based developed intersection management in a virtual simulation environment. Quantitative analysis of the simulation results proves the performance of the management system, especially in extremely high traffic intensity where the management system can keep traffic flowing in the conflict zone, ensuring efficient operation. The generalizability of the developed management system is also verified by applying it to a complex traffic network consisting of multiple intersections.
Pages: 41 to 49
Copyright: Copyright (c) IARIA, 2023
Publication date: April 24, 2023
Published in: conference
ISSN: 2308-4243
ISBN: 978-1-68558-037-7
Location: Venice, Italy
Dates: from April 24, 2023 to April 28, 2023