Version 1
: Received: 5 June 2024 / Approved: 5 June 2024 / Online: 7 June 2024 (11:42:58 CEST)
How to cite:
Dubey, Y.; Tarte, Y.; Talatule, N.; Sable, B.; Taywade, C.; Umate, R. An Artificial Intelligence Based Autonomous Road Lane Detection and Navigation System for Vehicles. Preprints2024, 2024060350. https://doi.org/10.20944/preprints202406.0350.v1
Dubey, Y.; Tarte, Y.; Talatule, N.; Sable, B.; Taywade, C.; Umate, R. An Artificial Intelligence Based Autonomous Road Lane Detection and Navigation System for Vehicles. Preprints 2024, 2024060350. https://doi.org/10.20944/preprints202406.0350.v1
Dubey, Y.; Tarte, Y.; Talatule, N.; Sable, B.; Taywade, C.; Umate, R. An Artificial Intelligence Based Autonomous Road Lane Detection and Navigation System for Vehicles. Preprints2024, 2024060350. https://doi.org/10.20944/preprints202406.0350.v1
APA Style
Dubey, Y., Tarte, Y., Talatule, N., Sable, B., Taywade, C., & Umate, R. (2024). An Artificial Intelligence Based Autonomous Road Lane Detection and Navigation System for Vehicles. Preprints. https://doi.org/10.20944/preprints202406.0350.v1
Chicago/Turabian Style
Dubey, Y., Chetan Taywade and Roshan Umate. 2024 "An Artificial Intelligence Based Autonomous Road Lane Detection and Navigation System for Vehicles" Preprints. https://doi.org/10.20944/preprints202406.0350.v1
Abstract
Lane detection is a foundational technology for autonomous driving systems. It involves identifying the boundaries of lanes on the road and ensuring the vehicle stays within these boundaries. Accurate lane detection is crucial for safety, navigation and traffic management. This paper presents an artificial intelligent based autonomous road lane detection and navigation system for vehicles. The system can detect and analyze road lanes accurately and efficiently in real-time, with frame rates of up to 17 FPS. By utilizing image processing techniques, the system can identify the location and boundaries of road lanes and obstacles on the road and provide accurate and reliable navigation guidance to the driver. The system is integrated with sensors and actuators to provide comprehensive autonomous navigation. The efficiency of the proposed system is demonstrated using accuracy of lane detection on straight and curve lanes covering frames per second and motor of the speed as parameters for assessment. Results show that the proposed system detects lane as entire lane detection, partial lane detection and no detection status on different settings.
Keywords
Artificial Intelligence; Image Processing; IR Sensors; Lane Detection; Navigation; Autonomous Vehicles
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
