Smart Park AI

Author(s)	Mr. Shlok Panchal, Mr. Yadnyesh Thakare, Mr. Aryan Giri, Mr. Dhruvansh Gandhi, Prof. Milind Khairnar
Country	India
Abstract	The increasing challenges of urban parking, driven by rapid urbanization and a surge in vehicle ownership, have highlighted the urgent need for intelligent, autonomous parking solutions. Current parking assistance technologies often necessitate human intervention, posing limitations for fully autonomous systems and contributing to parking-related accidents and inefficient maneuvers. The Smart Park AI project addresses this gap by developing an autonomous parking solution utilizing reinforcement learning, specifically Proximal Policy Optimization (PPO), within a high-fidelity Unity simulation environment. The goal is to enhance parking efficiency, precision, and safety by enabling vehicles to autonomously navigate and park, thereby providing a foundation for future advancements in smart urban infrastructure and sustainable mobility.
Keywords	Autonomous Parking, Reinforcement Learning, Smart Park AI, Proximal Policy Optimization (PPO), Unity Simulation, Autonomous Vehicles, Parking Maneuvers, Machine Learning, Collision Avoidance, AI-driven Parking Solutions, Real-time Parking, Urban Mobility.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-01-19
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.65753

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