Design Simulation of a Fuzzy Steering Wheel Controller for a buggy car

The development of an autonomous vehicle started since 1960 by Stanford University. Steering wheel control for an autonomous vehicle is important for a successful navigation through the designed road/paths. The recent autonomous vehicles developed by Uber, Waymo, Tesla, and others are still in the experimental stage. The current accident with Uber autonomous car in Arizona shows that the safety of the pedestrian and passengers of the autonomous cars are still at risk. The passenger�s comfort and safety while riding in the AEV can be improved by developing a controller that is precise and accurate in making decisions based on the uncertain environment. The developed Fuzzy controller that uses data from the human drivers in order to develop the Fuzzy membership function is one of the possible approaches. The human navigation experiment is the experiment that gathers data from the human driver as they drive through designed paths. The speed, steering wheel angle, heading, and position of the buggy are collected throughout the human navigation experiments. Then, data used to calculate the mean and standard deviation for each membership variables. In order to study the performance of the developed Fuzzy controller, the simulation studies were developed. The simulations are executed by using LabVIEW software. The simulation uses data from human navigation experiments in order to simulate the Fuzzy controller performance. The simulation results are expected to show the minimum path tracking error. Path tracking error is defined as the distance between the vehicle center of gravity and the desired path. The negative path tracking error indicates that the vehicle is to the left of the path. The path tracking error is expected to less than 1 meter.