Next Article in Journal
Recent Advances in Equalization Technologies for Short-Reach Optical Links Based on PAM4 Modulation: A Review
Next Article in Special Issue
Airborne Waveform Lidar Simulator Using the Radiative Transfer of a Laser Pulse
Previous Article in Journal
Computer Aided Design to Produce High-Detail Models through Low Cost Digital Fabrication for the Conservation of Aerospace Heritage
Previous Article in Special Issue
Calibration of a Rotating or Revolving Platform with a LiDAR Sensor
Article Menu
Issue 11 (June-1) cover image

Export Article

Open AccessArticle

Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

VTT Technical Research Centre of Finland, P.O. Box 1300, FI-33101 Tampere, Finland
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(11), 2341;
Received: 29 March 2019 / Revised: 31 May 2019 / Accepted: 4 June 2019 / Published: 7 June 2019
(This article belongs to the Special Issue LiDAR and Time-of-flight Imaging)
PDF [7461 KB, uploaded 7 June 2019]
  |     |  


Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing principles. This paper investigates proposed methods in the literature and adopts a common validation method to perform both indoor and outdoor tests to examine how fog and snow affect performances of different LiDARs. As suspected, the performance degraded with all tested sensors, but their behavior was not identical. View Full-Text
Keywords: LiDAR; adverse weather; automatic driving LiDAR; adverse weather; automatic driving

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Jokela, M.; Kutila, M.; Pyykönen, P. Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions. Appl. Sci. 2019, 9, 2341.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top