Auto-Park: Autonomous Self Parking Vehicle Without Human Driver Control

Abstract

This project investigates the design and implementation of an autonomous self-parking system for vehicles, eliminating the need for human driver control. The system utilizes a combination of sensor fusion, computer vision, and advanced control algorithms to navigate a parking space autonomously. The project focuses on enhancing safety and efficiency in parking, addressing limitations of existing driver-assistance systems. Results demonstrate successful autonomous parking in various scenarios, paving the way for improved parking solutions in urban environments. Future work involves refining the system's robustness and expanding its adaptability to different parking space configurations.

Introduction

The increasing urbanization and limited parking availability highlight the need for efficient and safe parking solutions. Current driver-assistance systems offer partial automation, but fully autonomous parking remains a significant challenge. Developing a reliable and robust autonomous self-parking system offers considerable benefits, including reduced parking time, improved parking space utilization, and enhanced safety by minimizing driver error. Key challenges include robust sensor data processing in diverse environmental conditions (e.g., varying lighting, obstacles), precise vehicle control in constrained spaces, and ensuring system safety and reliability.

Objectives

• Develop a robust and reliable autonomous self-parking system for passenger vehicles.
• Achieve a high success rate of autonomous parking in diverse parking scenarios.
• Ensure the safety and security of the system, minimizing the risk of collisions or accidents.

Technical Details

• Use of ultrasonic and infrared sensors for obstacle detection
• Microcontroller-based control system (e.g., Arduino/Raspberry Pi)
• Computer vision module for lane and parking slot detection
• Motor driver circuits for autonomous vehicle motion control
• Algorithms for precise alignment and maneuvering in tight spaces