Abstract
Vehicle localization is the primary information needed for advanced tasks like navigation. This information is usually provided by the use of Global Positioning System (GPS) receivers. However, the low accuracy of GPS in urban environments makes it unreliable for further treatments. The combination of GPS data and additional sensors can improve the localization precision. In this article, a marking feature based vehicle localization method is proposed, able to enhance the localization performance. To this end, markings are detected using a multi-kernel estimation method from an on-vehicle camera. A particle filter is implemented to estimate the vehicle position with respect to the detected markings. Then, map-based markings are constructed according to an open source map database. Finally, vision-based markings and map-based markings are fused to obtain the improved vehicle fix. The results on road traffic scenarios using a public database show that our method leads to a clear improvement in localization accuracy.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
