ABSTRACT
Autonomous vehicles are self-driving vehicles that are capable of sensing their environment and navigating without the need of human intervention. These vehicles use a combination of techniques to perceive their surroundings. These include use of sensors such as LiDAR, RADAR, Visual sensors and motion sensors. Highly advanced control systems and algorithms interpret the sensory information to identify appropriate navigation paths, obstacles and signs. The technical challenges of self-driving vehicles, is to develop the control systems that are capable of analysing the sensory data in order to provide accurate detection of path and obstacles. Modern self-driving vehicle use Simultaneous Localization and Mapping (SLAM) algorithms for navigation. SLAM allows the vehicle to create a map of its environment while at the same time uses the build map for path planning and as well as navigation. These involve complex algorithms and heavy computational power. A simple, less complex method of navigation for autonomous vehicles is discussed in this paper.
