Many businesses have been developing self-driving automobiles in recent years. The primary motivation for the development of advanced driver assistance systems is to improve safety and reduce road accidents, therefore saving lives. One of the most difficult problems in an autonomous driving system is detecting the road lane or road limits. Collision avoidance in driving assistance systems may rely heavily on lane and object identification. With the increasing volume of traffic, there is a greater demand for security and comfort, both of which are significant parts of driving; thus, new technologies must focus more on these areas. Computer vision is one of the ways that may be utilized to assist a driver in a variety of situations to improve his safety and comfort. One of the most basic features of self-driving automobiles is lane tracking. Many sensors, including as lasers, radar, and vision sensors, are commonly employed for obstacle detection and lane detection. Computer vision is the primary way for detecting road limits and lanes with a vehicle’s vision system. The system uses a camera installed on the vehicle to capture the front view, which is then subjected to a number of processing steps in order to recognize lanes and objects. To do this, a flexible methodology is utilized. This report focuses on computer vision-based lane detection technique with a camera mounted on the vehicle.


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    Title :

    Lane Detection in Autonomous Vehicles Using AI


    Additional title:

    EAI/Springer Innovations in Communication and Computing


    Contributors:


    Publication date :

    2023-08-24


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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