Detection of Obstacles and Intelligent Narrow Road Navigation for Autonomous Vehicles – A Hardware Approach

Obstacle detection is the most important functionality in the field of autonomous vehicles. One of the common challenges is detecting a narrow driving lane and navigating through it while performing obstacle identification and handling them. This problem falls under categories such as single-lane road block navigation, ad-hoc obstacles, narrow road path-finding, bridges, tunnel navigation, etc. In this work, we present an algorithm to handle these cases to perform successful detection and navigation through them. The lane navigation algorithm is used to perform autonomous driving under normal circumstances, and under narrow road circumstances, the Narrow Road Navigation (NRN) algorithm will be deployed. As proof of concept, we present a hardware prototype of a miniature car that will use the NRN algorithm. The hardware components and experimental results show that a successful implementation of the said algorithm is possible and can be used in actual real-life models and scenarios.