Using Visual Lane Detection to Control Steering in a Self-driving Vehicle
Using Visual Lane Detection to Control Steering in a Self-driving Vehicle
- New search for: McFall, Kevin
- New search for: McFall, Kevin
Abstract An effective lane detection algorithm employing the Hough transform and inverse perspective mapping to estimate distances in real space is utilized to send steering control commands to a self-driving vehicle. The vehicle is capable of autonomously traversing long stretches of straight road in a wide variety of conditions with the same set of algorithm design parameters. Better performance is hampered by slowly updating inputs to the steering control system. The 5 frames per second (FPS) using a Raspberry Pi 2 for image capture and processing can be improved to 23 FPS with an Odroid XU3. Even at 5 FPS, the vehicle is capable of navigating structured and unstructured roads at slow speed.
Document information
Using Visual Lane Detection to Control Steering in a Self-driving Vehicle
2016-01-01
13 pages
Article/Chapter (Book)
Electronic Resource
English
Self-driving vehicle , Hough transform , Dynamic threshold , Inverse perspective transform , Temporal integration , Angle control Computer Science , Artificial Intelligence (incl. Robotics) , Information Systems Applications (incl. Internet) , Computer Communication Networks , User Interfaces and Human Computer Interaction , Software Engineering , Computers and Society
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