Stereo Vision-Based Road Debris Detection System for Advanced Driver
Assistance Systems 09-10-01-0003
This also appears in
SAE International Journal of Transportation Safety-V131-9EJ
Reliable detection of obstacles around an autonomous vehicle is essential to
avoid potential collision and ensure safe driving. However, a vast majority of
existing systems are mainly focused on detecting large obstacles such as
vehicles, pedestrians, and so on. Detection of small obstacles such as road
debris, which pose a serious potential threat are often overlooked. In this
article, a novel stereo vision-based road debris detection algorithm is proposed
that detects debris on the road surfaces and estimates their height accurately.
Moreover, a collision warning system that could warn the driver of an imminent
crash by using 3D information of detected debris has been studied. A novel
feature-based classifier that uses a combination of strong and weak features has
been developed for the proposed algorithm, which identifies debris from selected
candidates and calculates its height. 3D information of detected debris and
vehicle’s speed are used in the collision warning system to warn the driver to
safely maneuver the vehicle. The performance of the proposed algorithm has been
evaluated by implementing it on a passenger vehicle. Experimental results
confirm that the proposed algorithm can successfully detect debris of ≥5 cm
height for up to a 22 m distance with an accuracy of 90%. Moreover, the debris
detection algorithm runs at 20 Hz in a commercially available stereo camera
making it suitable for real-time applications in commercial vehicles.