A driving assistance system with vision based vehicle detection techniques

Lane departure and forward collision detection plays an important role in autonomous driving and commercial driver-assistance systems. This paper presents an integrative approach to vision-based lane departure detection which aims to be as simple as possible to enable the real-time computation while being able to adapt to a variety of highway and urban scenarios on different weather conditions. In this work, we also implement a vision-based forward collision warning system and an overtaking vehicle detection system. The forward collision warning system aims to detect other vehicles driving ahead of the host vehicle so as to avoid the potential traffic accidents. On the other hand, the overtaking vehicle detection system is to detect other vehicles behind or on the side of the host vehicle so as to give an alert to the driver when the vehicle begins overtaking. Experimental results are presented with real scene video sequences. The performance evaluation has demonstrated the effectiveness of the proposed techniques.