AUTOMATIC ROBOT CAR PARALLEL PARKING SYSTEM USING ARTIFICIAL NEURAL NETWORK
SARA GHATTA, SORAYA ZENHARI, Amirhassan Monadjemi · WIT transactions on engineering sciences · 2024
In today's busy world, parking a car in crowded cities is time-consuming and challenging.Parallel parking systems are a valuable innovation, especially for disabled and inexperienced drivers, as they can prevent collisions.Despite their common use, artificial neural networks (ANNs) and backpropagation algorithms (BP) have issues, such as difficulty in estimating network configurations and low accuracy.While BP is traditionally used to train ANNs, it is not effective for parking a car.To achieve accurate vehicle control, a self-organising map (SOM) clusters data from various parking scenarios and uses this information to classify the data.According to simulations conducted using MATLAB, SOM provides better accuracy and reliability for parking cars compared to BP.