A Hyperbola - Pair Based Lane Detection System for Vehicle Guidance

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. The ability to perceive, or sense, the surrounding environment is essential to driving and thus to the development of autonomous self-guided vehicles However, the time requirements of an autonomous vehicle’s vision system are very demanding, and require careful selection of high speed algorithms for implementation. This paper presents a recent vision-based on-road lane detection system. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. Real time image sequences are used as inputs, which after being processed are used for lanes detection. The lanes are detected using Hough transform and fitted to a hyperbola model. The proposed lane detection algorithm can be applied on both painted and unpainted road as well as curved and straight road. Finally, a critical overview of the methods was discussed, the assessment of their potential for future deployment were highlighted. This approach was tested and the experimental results show that the proposed scheme was robust and fast enough for real time requirements. Eventually, a critical overview of the methods were discussed, their potential for future deployment were assist.