Single Camera 3D Lane Detection and Tracking Based on EKF for Urban Intelligent Vehicle

Author

Tian, Min ; Liu, Fuqiang ; Hu, Zhencheng

Author_Institution

Tongji Univ., Shanghai

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

413

Lastpage

418

Abstract

Road boundary detection and tracking is an important and integral function in advanced driver-assistance system. This paper proposes an algorithm, which can follow multi-kinds of lane, straight and curved, quickly and robustly. The algorithm uses several masks to extract blobs of road markings, combining with KNN function to remove the disturbance. Further more, road is modeled as a 3D surface, and some important parameters of current lane are provided on real-time by tracking based on Extended Kalman Filter (EKF). The results of experiments, which have been done in urban road, show that the algorithm is adapted to many road conditions. Even in a complex driving environment, it also has a good performance.

Keywords

Kalman filters; automated highways; cameras; driver information systems; feature extraction; integral equations; nonlinear filters; road vehicles; surface fitting; tracking; 3D surface modeling; KNN function; advanced driver-assistance system; extended Kalman filter; feature detection; integral function; road boundary detection; road boundary tracking; road condition; road marking extraction; single camera 3D lane detection; urban intelligent vehicle; Data mining; Intelligent vehicles; Laser radar; Layout; Radar tracking; Road safety; Smart cameras; Vehicle detection; Vehicle safety; Wavelet transforms; Intelligent vehicle; Kalman Filter; Road condition recognition; Self-adaptive tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Electronics and Safety, 2006. ICVES 2006. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

1-4244-0759-1

Electronic_ISBN

1-4244-0759-1

Type

conf

DOI

10.1109/ICVES.2006.371626

Filename

4234062