Intelligent automatic overtaking system using vision for vehicle detection

Vicente Milanés (1) , David Llorca (2) , Jorge Villagra (3) , Joshué Pérez Rastelli (3, 4) , Carlos Fernandez (2) , Ignacio Parra (2) , Carlos González (3) , M.A. Sotelo (5)

1 PATH
2 Polytechnic School - Computer Engineering Department
3 CAR - Centre for Automation and Robotics
4 IMARA - Informatique, Mathématiques et Automatique pour la Route Automatisée
5 b Computer Engineering Department, Polytechnic School

There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manoeuvres involving vehicles - overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manoeuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle's actuators, i.e., the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroën car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles - a motorbike, car, and truck - with encouraging results.

Domaines: Intelligence artificielle [cs.AI]

Vicente Milanés, David Llorca, Jorge Villagra, Joshué Pérez Rastelli, Carlos Fernandez, et al.. Intelligent automatic overtaking system using vision for vehicle detection. Expert Systems with Applications, 2012, 39 (3), pp.3362-3373. ⟨hal-00741406⟩