Improved Lane Detection Based on Past Vehicle Trajectories
Knowing where the host lane lies is paramount to the effectiveness of many advanced driver assistance systems (ADAS), such as lane keep assist (LKA) and adaptive cruise control (ACC). This paper presents an approach for improving lane detection based on the past trajectories of vehicles. Instead of expensive high-precision map, the authors use the vehicle trajectory information to provide additional lane-level spatial support of the traffic scene, and combine it with the visual evidence to improve each step of the lane detection procedure, thereby overcoming typical challenges of normal urban streets. Such an approach could serve as an Add-On to enhance the performance of existing lane detection systems in terms of both accuracy and robustness. Experimental results in various typical but challenging scenarios show the effectiveness of the proposed system.
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Availability:
- Find a library where document is available. Order URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6948869
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Supplemental Notes:
- Abstract reprinted with permission of IEEE.
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Corporate Authors:
Institute of Electrical and Electronics Engineers (IEEE)
3 Park Avenue, 17th Floor
New York, NY United States 10016-5997 -
Authors:
- Guo, Chunzhao
- Meguro, J
- Yamaguchi, K
- Kidono, K
- Kojima, Y
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Conference:
- 17th International IEEE Conference on Intelligent Transportation Systems (ITSC14)
- Location: Qingdao , China
- Date: 2014-10-8 to 2014-10-11
- Publication Date: 2014-10
Language
- English
Media Info
- Media Type: Web
- Pagination: pp 1956-1963
- Monograph Title: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC14)
Subject/Index Terms
- TRT Terms: Autonomous intelligent cruise control; Detection and identification systems; Driver support systems; Vehicle electronics; Vehicle trajectories
- Uncontrolled Terms: Lane keeping
- Subject Areas: Highways; Vehicles and Equipment; I91: Vehicle Design and Safety;
Filing Info
- Accession Number: 01562163
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 28 2015 3:09PM