Authors : Rugved Naik; Omkar Jadhav; Vaibhav Yelam; Soham Rajopadhye

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://tinyurl.com/4hpzkc8a

Scribd : https://tinyurl.com/5n7uh2v5

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG1392

Abstract : The rapid growth in the transportation sector demands innovative solutions to address safety, efficiency, and environmental challenges, especially in countries with complex and dynamic road infrastructures like India. This research explores the design of a semi-autonomous vehicle tailored for Indian road conditions using reinforcement learning (RL) techniques. The unique characteristics of Indian infrastructure, including mixed traffic, unpredictable behavior of pedestrians, varying road conditions, and inconsistent adherence to traffic regulations, pose challenges to the implementation of autonomous driving technologies. This paper proposes an RL-based approach to navigate these challenges and discusses the potential design, algorithmic frameworks, practical case studies, and implications.

Keywords : Arduino-Based Automation, Autonomous Driving, Obstacle Avoidance, Obstacle Detection, Real- Time Navigation, Reinforcement Learning, Sensor Fusion, Semi-Autonomous Vehicle

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