Affiliation:
1. University of California, Riverside, Fremont, CA
2. National Taiwan University, Taipei, Taiwan
3. TOYOTA InfoTechnology Center, Chuo-ku, Tokyo, Japan
4. Northwestern University and University of California, Riverside, Evanston, IL
Abstract
The rapid development of vehicular network and autonomous driving technologies provides opportunities to significantly improve transportation safety and efficiency. One promising application is centralized intelligent intersection management, where an intersection manager accepts requests from approaching vehicles (via vehicle-to-infrastructure communication messages) and schedules the order for those vehicles to safely crossing the intersection. However, communication delays and packet losses may occur due to the unreliable nature of wireless communication or malicious security attacks (e.g., jamming and flooding), and could cause deadlocks and unsafe situations. In our previous work, we considered these issues and proposed a delay-tolerant intersection management protocol for intersections with a single lane in each direction. In this work, we address key challenges in efficiency and deadlock when there are multiple lanes from each direction, and propose a delay-tolerant protocol for general multi-lane intersection management. We prove that this protocol is deadlock free, safe, and satisfies the liveness property. Furthermore, we extend the traffic simulation suite SUMO with communication modules, implement our protocol in the extended simulator, and quantitatively analyze its performance with the consideration of communication delays. Finally, we also model systems that use smart traffic lights with various back-pressure scheduling methods in SUMO, including the basic back-pressure control, the capacity-aware back-pressure control, and the adaptive max-pressure control. We then compare our delay-tolerant intelligent intersection protocol with smart traffic lights that use the three back-pressure scheduling methods, in the case of a network of interconnected intersections. Simulation results demonstrate that our approach significant outperforms the smart traffic lights under normal operation (i.e., when the communication delay is not too large).
Funder
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction
Reference34 articles.
1. DLR. 2018. SUMO. Retrieved October 7 2019 from http://www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931_read-41000/. DLR. 2018. SUMO. Retrieved October 7 2019 from http://www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931_read-41000/.
2. UPPAAL. 2018. Home Page. Retrieved October 7 2019 from http://uppaal.org/. UPPAAL. 2018. Home Page. Retrieved October 7 2019 from http://uppaal.org/.
3. Modeling and controlling an isolated urban intersection based on cooperative vehicles
4. STIP: Spatio-temporal intersection protocols for autonomous vehicles
5. Reliable intersection protocols using vehicular networks
Cited by
21 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