DOAJ Open Access 2021

Camera-Based Lane Detection—Can Yellow Road Markings Facilitate Automated Driving in Snow?

Ane Dalsnes Storsæter Kelly Pitera Edward McCormack

Abstrak

Road markings are beneficial to human drivers, advanced driver assistance systems (ADAS), and automated driving systems (ADS); on the contrary, snow coverage on roads poses a challenge to all three of these groups with respect to lane detection, as white road markings are difficult to distinguish from snow. Indeed, yellow road markings provide a visual contrast to snow that can increase a human drivers’ visibility. Yet, in spite of this fact, yellow road markings are becoming increasingly rare in Europe due to the high costs of painting and maintaining two road marking colors. More importantly, in conjunction with our increased reliance on automated driving, the question of whether yellow road markings are of value to automatic lane detection functions arises. To answer this question, images from snowy conditions are assessed to see how different representations of colors in images (color spaces) affect the visibility levels of white and yellow road markings. The results presented in this paper suggest that yellow markings provide a certain number of benefits for automated driving, offering recommendations as to what the most appropriate color spaces are for detecting lanes in snowy conditions. To obtain the safest and most cost-efficient roads in the future, both human and automated drivers’ actions must be considered. Road authorities and car manufacturers also have a shared interest in discovering how road infrastructure design, including road marking, can be adapted to support automated driving.

Penulis (3)

A

Ane Dalsnes Storsæter

K

Kelly Pitera

E

Edward McCormack

Format Sitasi

Storsæter, A.D., Pitera, K., McCormack, E. (2021). Camera-Based Lane Detection—Can Yellow Road Markings Facilitate Automated Driving in Snow?. https://doi.org/10.3390/vehicles3040040

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Informasi Jurnal
Tahun Terbit
2021
Sumber Database
DOAJ
DOI
10.3390/vehicles3040040
Akses
Open Access ✓