Abstract
With the development of artificial intelligent (AI), more and more fields are embracing the AI technology. Intelligent driving is one of the these fields. The environment perception is the fundamental of intelligent driving while lane detection is one of important part of environment perception. Traditional lane detection methods are based on the features of road edge which is only suited on the road with clear car lanes. In this paper, we propose a lane detection method based on semantic segmentation in which includes two stages for lane detection. In the first stage, we use SegNet which is a deep convolutional neural network to recognize the drivable area. Then, we use edge-extracting algorithm to find features of road edge. Based on the extracting edge features, we use cubic curve to fit lane. The experimental results show that our method has a good generalization. It can achieve a good result in both urban roads and rural roads.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.