Autonomous vehicle parking using finite state automata learned by J-CC artificial neural nets

Abstract

This paper presents the SEVA system, an autonomous vehicle parking simulator. This tool implements a robust control system for autonomous vehicle parking based on the finite-state automata and trained by the Jordan cascade-correlation (J-CC) artificial neural networks.