Extraction of contextual information for automotive applications

In the near future automatic systems able to detect the traffic situation and to understand driver behavior and intent will probably become vehicle tools important for improving driver safety. Therefore, robust video processing techniques able to cope with difficult environmental road condition such as luminosity changes, dynamic and cluttered background, etc. are necessary for these applications. In this work, lanes detection, vehicle position and traffic analysis are the information extracted to characterize the driving situation and the proposed techniques try to cope with the above mentioned issues. The presented framework is tested using an on-board camera in real-world scenario respecting the real-time constraint and showing good performances in highways and urban roads.