Robust Lane Detection and Tracking in Challenging Scenarios
Top Cited Papers
- 26 February 2008
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Intelligent Transportation Systems
- Vol. 9 (1), 16-26
- https://doi.org/10.1109/tits.2007.908582
Abstract
A lane-detection system is an important component of many intelligent transportation systems. We present a robust lane-detection-and-tracking algorithm to deal with challenging scenarios such as a lane curvature, worn lane markings, lane changes, and emerging, ending, merging, and splitting lanes. We first present a comparative study to find a good real-time lane-marking classifier. Once detection is done, the lane markings are grouped into lane-boundary hypotheses. We group left and right lane boundaries separately to effectively handle merging and splitting lanes. A fast and robust algorithm, based on random-sample consensus and particle filtering, is proposed to generate a large number of hypotheses in real time. The generated hypotheses are evaluated and grouped based on a probabilistic framework. The suggested framework effectively combines a likelihood-based object-recognition algorithm with a Markov-style process (tracking) and can also be applied to general-part-based object-tracking problems. An experimental result on local streets and highways shows that the suggested algorithm is very reliable.Keywords
This publication has 17 references indexed in Scilit:
- A robust lane detection and tracking method based on computer visionMeasurement Science and Technology, 2006
- Lane detection and tracking using B-SnakeImage and Vision Computing, 2004
- Object class recognition by unsupervised scale-invariant learningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Expandable bayesian networks for 3D object description from multiple views and multiple mode inputsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2003
- Real-time lane and obstacle detection on the GOLD systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- RALPH: rapidly adapting lateral position handlerPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Stereo for 2D visual navigationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- CLARK: a heterogeneous sensor fusion method for finding lanes and obstaclesImage and Vision Computing, 2000
- A model for reasoning about persistence and causationComputational Intelligence, 1989
- Random sample consensusCommunications of the ACM, 1981