Autonomous Car Controller using Behaviour Planning based on Finite State Machine

Nowadays, with the exponential growth of technology, self-driving cars have become very popular, highly hyped, and brought a new revolution in the automobile industry by sensing the environment through sensors and is capable to drive with no human input. These autonomous cars work mainly with the help of sensors, complex algorithms, and processors which help to plan the path of the journey with efficiency. This paper proposes a controlling mechanism for autonomous cars by developing a model for decision making, speed control, traffic signs detection, and obstacle detection. The goal of this paper is to create a highway driving regulator which is automated based on finite state machines. Feedback control laws describe the regulator in the form of state-to-state conditions based on transition. By using JFLAP (a java-based automata design tool), the proposed research work has designed a finite state machine model and by using Python and also a controller has been developed through its pygame package, which is then implemented and evaluated the performance of the proposed model.