Implementation of a Real-Time FPGA-Based Intelligent Parallel Parking System

Abstract

Parallel parking is a challenging maneuver for many drivers, especially in crowded cities with heavy traffic congestion and limited parking spaces. This research focuses on the development of an intelligent parallel parking system. Conventional vehicular control techniques generally require the use of analytical models. However, complexities due to nonlinear car dynamics create multiple challenges when modeling car motion. As fuzzy logic control is appropriate for nonlinear and complex systems where human expert knowledge is available, it is well-suited for the parking application. This paper presents the design and implementation of a real-time fuzzy logic based parallel parking system. Two control units consisting of a main controller and a secondary fuzzy logic controller are utilized. The latter controller is employed for the realization of the wall following task, which has an important role in the parking system. Based on performance and flexibility considerations, the control units are implemented onto a reconfigurable hardware platform, namely a Field Programmable Gate Array (FPGA). A prototype vehicle is developed to ensure the proposed algorithm provides vehicular systems with the parallel parking ability.