An Intelligent V2I-Based Traffic Management System

International audienceVehicles 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

Cooperative maneuvers applied to automated vehicles in real and virtual environments

[ES] En los últimos años los Sistemas Inteligentes de Transporte, ITS (del inglés, Intelligent Transportation System) se han convertido en una realidad dentro de la sociedad, aportando soluciones y beneficios a la conducción. Con el fin de contribuir a su desarrollo, el presente trabajo describe un marco cooperativo híbrido capaz de validar maniobras entre múltiples vehículos (virtuales y reales), con el fin de disminuir los costos, tiempos y riesgos asociados al ajuste de los controladores. Para su validación se presentan 3 casos de estudios. El primero consiste en utilizar dos vehículos virtuales para realizar un Control de Crucero Adaptativo, ACC (del inglés, Adaptive Cruise Control) con seguidor de trayectoria. El segundo, emplea un coche real como seguidor y un coche virtual como líder para la maniobra de Stop & Go. Finalmente, se utilizan dos vehículos reales para el ACC. Los algoritmos de seguimiento empleados para las maniobras cooperativas están basados en controladores de lógi[EN] In recent years, Intelligent Transportation Systems (ITS) have become a reality within society, by providing benefits and solutions to the conduction. With the aim of contributing with the development of the ITS, the present work describes a hybrid cooperative framework for the validation of maneuvers between multiple vehicles (virtual and real), in order to reduce cost, time and risks associated with the controllers adjustment. For its validation three case of studies are presented. The first one consists of using two virtual vehicles to perform an Adaptive Cruise Control (ACC) with trajectory tracker. The second one, in using a real car as the follower and a virtual vehicle as the lider to perform a Stop & Go. And finally, two real cars are used to carry out an ACC. The tracker algorithms employed for the cooperative maneuvers are based in fuzzy logic controllers. 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Model-free control techniques for Stop & Go systems

International audienceThis paper presents a comparison of Stop & Go control algorithms, which deal with car following scenarios in urban environments. Since many vehicle/road interaction factors (road slope, aerodynamic forces) and actuator dynamics are very poorly known, two robust control strategies are proposed: an intelligent PID controller and a fuzzy controller. Both model-free techniques will be implemented and compared in simulation to show their suitability for demanding scenarios