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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM47285
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
â In recent years, the field of automated mobility has made significant advancements in self-driving vehicle technology. Even so, navigating complex environments such as roads with unexpected pedestrian traffic, uneven surfaces, unforeseen obstacles, and narrow pathways remains challenging. This paper focuses on an innovative AI-based solution to address the unique challenges of autonomous driving in Indian environments. Built on Intelâs CARLA, an open-source autonomous driving simulator. Its focus on simulation-based testing ensures the systemâs reliability in diverse scenarios before real-world deployment, tailored specifically for Indian roads. The system utilizes reinforcement learning for optimal driving strategies with minimal data, computer vision for road signs and obstacle detection, and context-aware navigation to adapt to varying traffic conditions. Offering a promising solution for autonomous driving in regions with similar road conditions by being cost-effective, scalable, and adaptable.
KEYWORDS
Publication Date
5/8/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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