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

    64 Citations (Scopus)


    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
    Issue number11
    Publication statusPublished - 7 Jun 2019
    MoE publication typeA1 Journal article-refereed


    • Adverse weather
    • Automatic driving
    • LiDAR


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