Citation

Pike AM, Whitney J, Hedblom T, Clear S. Transp. Res. Rec. 2019; 2673(11): 361-366.

Copyright

(Copyright © 2019, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198119847620

PMID

unavailable

Abstract

This study is a preliminary investigation of the effects of levels of wet retroreflectivity of pavement markings on factors that determine robust feature detection in machine vision and light detection and ranging (LiDAR) systems in continuously wet road conditions. Luminance and Weber contrast of a range of pavement markings were characterized as functions of wet retroreflectivity and distance based on calibrated charge-coupled device (CCD) camera measurements. Both were found to trend with wet retroflectivity over the range of distances considered in this study. Artifacts arising from glare sources in wet conditions and their intensities relative to pavement markings of different wet retroreflectivity levels were demonstrated. Image data suggests that markings with high wet retroreflectivity may help to mitigate identification of these artifacts as false positives in lane awareness/lane detection algorithms. As LiDAR presents a viable sensor fusion approach to identifying and avoiding these false positives and artifacts in both nighttime wet and daytime wet road conditions, LiDAR return was characterized on pavement markings comprising both optics designed only for dry retroreflectivity and optics designed to be retroreflective in both dry and wet conditions. Preliminary results suggest that for common pavement marking constructions based on exposed beaded optics that might be completely immersed by a rainstorm or puddling, incorporation of high index (n~2.4) wet retroreflective beaded optics is likely to be advantageous to both visible machine vision systems and LiDAR for detection of those retroreflective markings in both night and day.

Language: en