Algorithm development for AI driven Path planning using Augmented reality for navigating in Indian complex road scenarios

The road infrastructure in India has complex navigational challenges, with 82% roads being unstructured according to Ministry of Roads Transports and Highways (MoRTH). Decision-making becomes a challenge for drivers in unpredictable environments such as narrow roads or sometimes flooded roads and heavy traffic. In this paper, an augmented reality (AR) driver assistance algorithm has been proposed that improves awareness to safely maneuver in these conditions.The methodology for development and validation of this AR algorithm contains multiple steps. Firstly, extensive data collection is conducted using real time capture and benchmark datasets like Berkeley Deep Drive (BDD) and Indian Driving Dataset (IDD). Secondly, A machine learning model consisting of the collected data are labelled and trained to rightly identify the complex scenario. In third step, an AR navigation algorithm is developed, integrating these models to accurately detect floods and estimate road widths and provide seamless driver assistance in a Human machine interface. Finally, the AR algorithm undergoes validation to ensure its effectiveness and accuracy in real-world practical scenarios. The results of this study concludes significant improvements in driver decision making and safety of the driver, which highlights the potential of AR-based navigation systems to assist the drivers in complex road scenarios.