Articles | Volume 11, issue 1
J. Sens. Sens. Syst., 11, 187–199, 2022
https://doi.org/10.5194/jsss-11-187-2022
J. Sens. Sens. Syst., 11, 187–199, 2022
https://doi.org/10.5194/jsss-11-187-2022
Regular research article
29 Jun 2022
Regular research article | 29 Jun 2022

Near-infrared LED system to recognize road surface conditions for autonomous vehicles

Hongyi Zhang et al.

Related subject area

Sensor principles and phenomena: Optical and infrared sensors
Characterization of specular freeform surfaces from reflected ray directions using experimental ray tracing
Tobias Binkele, David Hilbig, Mahmoud Essameldin, Thomas Henning, Friedrich Fleischmann, and Walter Lang
J. Sens. Sens. Syst., 10, 261–270, https://doi.org/10.5194/jsss-10-261-2021,https://doi.org/10.5194/jsss-10-261-2021, 2021
Short summary
Iterative feature detection of a coded checkerboard target for the geometric calibration of infrared cameras
Sebastian Schramm, Jannik Ebert, Johannes Rangel, Robert Schmoll, and Andreas Kroll
J. Sens. Sens. Syst., 10, 207–218, https://doi.org/10.5194/jsss-10-207-2021,https://doi.org/10.5194/jsss-10-207-2021, 2021
Short summary
The size-of-source effect in thermography
Helmut Budzier and Gerald Gerlach
J. Sens. Sens. Syst., 10, 179–184, https://doi.org/10.5194/jsss-10-179-2021,https://doi.org/10.5194/jsss-10-179-2021, 2021
Short summary
Method for fast determination of the angle of ionizing radiation incidence from data measured by a Timepix3 detector
Felix Lehner, Jürgen Roth, Oliver Hupe, Marc Kassubeck, Benedikt Bergmann, Petr Mánek, and Marcus Magnor
J. Sens. Sens. Syst., 10, 63–70, https://doi.org/10.5194/jsss-10-63-2021,https://doi.org/10.5194/jsss-10-63-2021, 2021
Comparison of laser-based photoacoustic and optical detection of methane
Thomas Strahl, Johannes Herbst, Eric Maier, Sven Rademacher, Christian Weber, Hans-Fridtjof Pernau, Armin Lambrecht, and Jürgen Wöllenstein
J. Sens. Sens. Syst., 10, 25–35, https://doi.org/10.5194/jsss-10-25-2021,https://doi.org/10.5194/jsss-10-25-2021, 2021
Short summary

Cited articles

Anderson, J. M., Nidhi, K., Stanley, K. D., Sorensen, P., Samaras, C., and Oluwatola, O. A.: Autonomous vehicle technology: A guide for policymakers, Rand Corporation, https://www.rand.org/pubs/research_reports/RR443-2.html (last access: October 2021), 2014. a
Casselgren, J., Sjödahl, M., and LeBlanc, J.: Angular spectral response from covered asphalt, Appl. Optics, 46, 4277–4288, 2007. a, b, c, d, e, f, g, h, i, j, k, l, m
Casselgren, J., Sjödahl, M., and LeBlanc, J. P.: Model-based winter road classification, Int. J. Vehic. Syst. Model. Test., 7, 268–284, 2012. a, b, c, d
Casselgren, J., Rosendahl, S., Sjödahl, M., and Jonsson, P.: Road condition analysis using NIR illumination and compensating for surrounding light, Opt. Laser. Eng., 77, 175–182, 2016. a, b, c, d, e, f
Cho, Y. and Kim, J.-J.: Lifetime decrease of halogen lamps for automotive by duty cycle stress, IEEE T. Reliabil., 60, 550–556, 2011. a
Download
Short summary
In this paper, a near-infrared LED system is proposed for autonomous vehicles to distinguish between weather-induced road surface conditions (dry, wet, snow, ice, water). For the LED spectra, the influence of the LED bandwidth is investigated. To assess the performance of the system for a long detection range, experiments with large incident angles are conducted. The feasibility of this system is proved via a laboratory experiment with three near-infrared LEDs and a camera.