Details
| Original language | English |
|---|---|
| Title of host publication | Light-Emitting Devices, Materials, and Applications XXVI |
| Editors | Jong Kyu Kim, Michael R. Krames, Martin Strassburg |
| Publisher | SPIE |
| Number of pages | 10 |
| ISBN (electronic) | 9781510649156 |
| Publication status | Published - 2022 |
| Event | Light-Emitting Devices, Materials, and Applications XXVI 2022 - Virtual, Online Duration: 20 Feb 2022 → 24 Feb 2022 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 12022 |
| ISSN (Print) | 0277-786X |
| ISSN (electronic) | 1996-756X |
Abstract
The advance of automated vehicles imposes increasing requirements on the sensor system of vehicles. Besides the ongoing development of perception algorithms, different hardware approaches exist in order to improve the detection of infrastructure and road users. In the far-field in front of the vehicle, the detection of infrastructure and road users relies on camera and LiDAR systems. However, the reliability of both systems is influenced by weather conditions, especially due to reflections from snow, rain, or fog and the camera by the ambient lighting as well. Optimized algorithms are implemented to improve the vision of both systems but limitations remain. RaDAR is proven to work more reliably in adverse weather conditions but struggles in providing sufficient data for detailed object classification. In combination with data fusion, the sensor systems can provide a partly redundant perception of the road and its users. This paper aims to provide a proof of concept for the improvement of the vision of camera systems in low light by using active NIR illumination. For this purpose, the spectral emission of visible and near-infrared sources is compared with the sensitivity of a camera. Considering regulatory emission limits, an optimal wavelength for additional NIR lighting is determined.
Keywords
- ADAS, Automated driving, Camera, Near-infrared
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Condensed Matter Physics
- Computer Science(all)
- Computer Science Applications
- Mathematics(all)
- Applied Mathematics
- Engineering(all)
- Electrical and Electronic Engineering
Cite this
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- Apa
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- BibTeX
- RIS
Light-Emitting Devices, Materials, and Applications XXVI. ed. / Jong Kyu Kim; Michael R. Krames; Martin Strassburg. SPIE, 2022. 120220A (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 12022).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research
}
TY - GEN
T1 - Active NIR illumination for improved camera view in automated driving application
AU - Sundermeier, Max C.
AU - Dierend, Hauke
AU - Ley, Peer Phillip
AU - Wolf, Alexander
AU - Lachmayer, Roland
PY - 2022
Y1 - 2022
N2 - The advance of automated vehicles imposes increasing requirements on the sensor system of vehicles. Besides the ongoing development of perception algorithms, different hardware approaches exist in order to improve the detection of infrastructure and road users. In the far-field in front of the vehicle, the detection of infrastructure and road users relies on camera and LiDAR systems. However, the reliability of both systems is influenced by weather conditions, especially due to reflections from snow, rain, or fog and the camera by the ambient lighting as well. Optimized algorithms are implemented to improve the vision of both systems but limitations remain. RaDAR is proven to work more reliably in adverse weather conditions but struggles in providing sufficient data for detailed object classification. In combination with data fusion, the sensor systems can provide a partly redundant perception of the road and its users. This paper aims to provide a proof of concept for the improvement of the vision of camera systems in low light by using active NIR illumination. For this purpose, the spectral emission of visible and near-infrared sources is compared with the sensitivity of a camera. Considering regulatory emission limits, an optimal wavelength for additional NIR lighting is determined.
AB - The advance of automated vehicles imposes increasing requirements on the sensor system of vehicles. Besides the ongoing development of perception algorithms, different hardware approaches exist in order to improve the detection of infrastructure and road users. In the far-field in front of the vehicle, the detection of infrastructure and road users relies on camera and LiDAR systems. However, the reliability of both systems is influenced by weather conditions, especially due to reflections from snow, rain, or fog and the camera by the ambient lighting as well. Optimized algorithms are implemented to improve the vision of both systems but limitations remain. RaDAR is proven to work more reliably in adverse weather conditions but struggles in providing sufficient data for detailed object classification. In combination with data fusion, the sensor systems can provide a partly redundant perception of the road and its users. This paper aims to provide a proof of concept for the improvement of the vision of camera systems in low light by using active NIR illumination. For this purpose, the spectral emission of visible and near-infrared sources is compared with the sensitivity of a camera. Considering regulatory emission limits, an optimal wavelength for additional NIR lighting is determined.
KW - ADAS
KW - Automated driving
KW - Camera
KW - Near-infrared
UR - http://www.scopus.com/inward/record.url?scp=85131219298&partnerID=8YFLogxK
U2 - 10.1117/12.2608162
DO - 10.1117/12.2608162
M3 - Conference contribution
AN - SCOPUS:85131219298
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Light-Emitting Devices, Materials, and Applications XXVI
A2 - Kim, Jong Kyu
A2 - Krames, Michael R.
A2 - Strassburg, Martin
PB - SPIE
T2 - Light-Emitting Devices, Materials, and Applications XXVI 2022
Y2 - 20 February 2022 through 24 February 2022
ER -