ABSTRACT
The past decade has witnessed a rapid evolution of the sensors technology as well
as the embedded systems which in turn stimulates the development of a futuristic
field such as the autonomous mobile systems. However, the development of an
autonomous ground vehicle that is able to sense and avoid obstacles on its way
represents a major challenge up till now. Various autonomous ground vehicles have
been recently introduced which rely on wide diversity of detection systems such as;
laser systems, acoustic systems and machine vision systems.
This paper proposes an advanced algorithm for an autonomous ground vehicle
based on lane detection and tracking in addition to obstacle avoidance technique.
Through this algorithm, the suitable car heading angle is calculated in order to follow
the lane or avoid predefine obstacles. The lane and / or obstacles are being
recognized based on vision system in which a real time data are collected by a
single camera and analyzed using the color separation technique. An in-house
numerical model is developed to estimate both the relative distance and direction of
the obstacle. Consequently, further actions are considered to enable the vehicle to
drive accurately down a predefined path and at a defined speed. The results reveal
both the fidelity and the robustness of the introduced algorithm.