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Development of Lens Condition Diagnosis for Lane Departure Warning by Using Outside Camera
Technical Paper
2014-01-0167
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Driver safety continues to be improved by advances in active safety technologies. One important example is Lane Departure Warning (LDW). European regulators soon will require LDW in big cars to reduce traffic accidents and New Car Assessment Programs in various countries will include LDW in a few years. Our focus is on rear cameras as sensing devices to recognize lane markers. Rear cameras are the most prevalent cameras for outside monitoring, and new Kids and Cars legislation will make them obligatory in the United States from 2014.
As an affordable sensing system, we envision a rear camera which will function both as a rear-view monitoring device for drivers and as an LDW sensing device. However, there is a great difficulty involved in using the rear camera: water-droplets and dirt are directly attached to the lens surface, creating bad lens condition.
The purpose of this study is to improve the durability of lane recognition systems when water-droplets and dirt are deposited on the lens surface. First, we developed various diagnostic logics under various lens conditions. We then analyzed the results of various diagnosis and expressed the lens conditions by using two evaluation axes. After that, we improve the durability of the lane recognition system including a judgment function that determines whether to stop the LDW system under heavy dirt and water-droplets.
We conducted driving tests and captured evaluation movies in the United States, Europe, and Japan. We evaluated the lane recognition rate for a total of 8 hours of evaluation movies under various weather conditions. We achieved a lane recognition rate of 95% and improved the durability of the lane recognition system.
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Authors
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Citation
Takemura, M., Imai, M., Kiyohara, M., Irie, K. et al., "Development of Lens Condition Diagnosis for Lane Departure Warning by Using Outside Camera," SAE Technical Paper 2014-01-0167, 2014, https://doi.org/10.4271/2014-01-0167.Also In
References
- Yamada , K. Road Lane Recognition System for RCAS Intelligent Vehicle Symposium 172 182 1996
- Hong , W. Real-time Lane Detection in Various conditions and Night Case Intelligent Transportation Systems Conference 1226 1231 2006
- Yu-Chi , L. Vision-Based Lane Departure Detection System in Urban Traffic Scenes 1875 1880 2010
- Arata , T. Image Processing Technology for Rear View Camera (1): Development of Lane Detection System R&D Review of Toyota CRDL 38 2 31 36 2003
- Shigang , L. Lane Marking Detection by Side Fisheye Camera Intelligent Robots and Systems 606 611 2008
- Amol , B. A Non Overlapping Camera Network: Calibration and Application Towards Lane Departure Warning International Conference on Image Processing, Computer Vision and Pattern Recognition 2011
- Kshitiz , G. Detection and Removal of Rain from Videos IEEE conference on Computer Vision and Pattern Recognition(CVPR) I 528 535 Jun 2004
- Jinwei , G. Removing Image Artifacts Due to Dirty Camera Lenses and Thin Occluders ACM Transactions on Graphics (Proceeding of SIGGRAPH Asia) 2009
- Miyahara , T. DENSO Technical Review 12 1 2007
- Shirado , R. , Furusho , H. , Mori , H. , & Tuji , M. 2000 9 201 204 2000