An Intelligent V2I-Based Traffic Management System

• Published in: IEEE transactions on intelligent transportation systems Vol. 13; no. 1; pp. 49 - 58
• Main Authors: Milanes, V., Villagra, J., Godoy, J., Simo, J., Perez, J., Onieva, E.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2012; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accidents; Artificial Intelligence; Collision avoidance; Computer Science; Computer simulation; Data communication; Delay; Management systems; Mathematical models; Quality of service; road vehicles; Roads; Safety; Studies; Traffic accidents & safety; traffic control; Traffic engineering; Traffic flow; traffic management; Vehicle dynamics; vehicle-to-infrastructure (V2I) communication; Vehicles
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2011.2178839

Vehicles equipped with intelligent systems designed to prevent accidents, such as collision warning systems (CWSs) or lane-keeping assistance (LKA), are now on the market. The next step in reducing road accidents is to coordinate such vehicles in advance not only to avoid collisions but to improve traffic flow as well. To this end, vehicle-to-infrastructure (V2I) communications are essential to properly manage traffic situations. This paper describes the AUTOPIA approach toward an intelligent traffic management system based on V2I communications. A fuzzy-based control algorithm that takes into account each vehicle's safe and comfortable distance and speed adjustment for collision avoidance and better traffic flow has been developed. The proposed solution was validated by an IEEE-802.11p-based communications study. The entire system showed good performance in testing in real-world scenarios, first by computer simulation and then with real vehicles.