Authors : Anurag Sharma; Harsh Jangid; Raghvendra Singh Nirwan; Sohit Negi; Rahul Sharma

Volume/Issue : Volume 8 - 2023, Issue 12 - December

Google Scholar : http://tinyurl.com/mvr82tfv

Scribd : http://tinyurl.com/4vxfvapc

DOI : https://doi.org/10.5281/zenodo.10427687

Abstract : Autonomous vehicles (AVs) represent a significant leap in transportation technology, promising safer, more efficient, and convenient means of mobility. The successful deployment of AVs heavily relies on advanced Artificial Intelligence (AI) systems that enable these vehicles to navigate diverse and complex environments. This paper provides a comprehensive overview of the challenges and recent advancements in AI-based navigation systems for autonomous vehicles. The first section delineates the fundamental challenges facing AI-powered navigation in AVs, including real-time decision-making in dynamic environments, robustness in adverse weather conditions, handling unpredictable human behavior, and ensuring regulatory compliance and safety standards. Each challenge is thoroughly examined, highlighting the complexities that arise in creating reliable AI systems for autonomous navigation. The subsequent sections delve into the cutting-edge advancements and methodologies in AI that address these challenges. It explores machine learning techniques, such as deep neural networks, reinforcement learning, and sensor fusion strategies employed to enhance perception, mapping, localization, and path planning capabilities of autonomous vehicles. Furthermore, this paper discusses the role of simulation environments and data-driven approaches in training AI models for better generalization and adaptation to various .Scenarios. Moreover, it scrutinizes ongoing research efforts and industry developments, showcasing case studies and prototypes that demonstrate the practical implementation and performance of AI-based navigation systems in real- world scenarios. The analysis highlights the progress made and the remaining hurdles in achieving fully autonomous vehicles capable of navigating complex urban landscapes and highways safely and efficiently. Finally, the paper concludes by emphasizing the future directions and potential breakthroughs required to overcome the remaining challenges and bring AI-driven autonomous vehicles into widespread adoption, revolutionizing the transportation landscape while ensuring utmost safety and reliability.