Lane Departure Detection for Improved Road Geometry Estimation
2006 (English)In: Proceedings of the 2006 IEEE Intelligent Vehicle Symposium, 2006, 546-551 p.Conference paper (Refereed)
An essential part of future collision avoidance systems is to be able to predict road curvature. This can be based on vision data, but the lateral movement of leading vehicles can also be used to support road geometry estimation. This paper presents a method for detecting lane departures, including lane changes, of leading vehicles. This information is used to adapt the dynamic models used in the estimation algorithm in order to accommodate for the fact that a lane departure is in progress. The goal is to improve the accuracy of the road geometry estimates, which is affected by the motion of leading vehicles. The significantly improved performance is demonstrated using sensor data from authentic traffic environments.
Place, publisher, year, edition, pages
2006. 546-551 p.
Automotive tracking, Change detection, State estimation, Kalman filter, CUSUM-test
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-13923DOI: 10.1109/IVS.2006.1689685OAI: oai:DiVA.org:liu-13923DiVA: diva2:22196
2006 IEEE Intelligent Vehicle Symposium, Tokyo, Japan, June, 2006