Testing and validation of automotive point-cloud sensors in adverse weather conditions

Maria Jokela (Corresponding Author), Matti Kutila, Pasi Pyykönen

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number2341
Number of pages14
JournalApplied Sciences
Volume9
Issue number11
DOIs
Publication statusPublished - 7 Jun 2019
MoE publication typeA1 Journal article-refereed

Keywords

  • Adverse weather
  • Automatic driving
  • LiDAR

Fingerprint Dive into the research topics of 'Testing and validation of automotive point-cloud sensors in adverse weather conditions'. Together they form a unique fingerprint.

Cite this