  In 2021, Japan recorded more than three times as much snowfall as usual, so
road user maybe come across dangerous situation. The poor visibility caused by
snow triggers traffic accidents. For example, 2021 January 19, due to the dry
snow and the strong wind speed of 27 m / s, blizzards occurred and the outlook
has been ineffective. Because of the whiteout phenomenon, multiple accidents
with 17 casualties occurred, and 134 vehicles were stacked up for 10 hours over
1 km. At the night time zone, the temperature drops and the road surface tends
to freeze. CCTV images on the road surface have the advantage that we enable to
monitor the status of major points at the same time. Road managers are required
to make decisions on road closures and snow removal work owing to the road
surface conditions even at night. In parallel, they would provide road users to
alert for hazardous road surfaces. This paper propose a method to automate a
snow hazard indicator that the road surface region is generated from the night
snow image using the Conditional GAN, pix2pix. In addition, the road surface
and the snow covered ROI are predicted using the semantic segmentation
DeepLabv3+ with a backbone MobileNet, and the snow hazard indicator to
automatically compute how much the night road surface is covered with snow. We
demonstrate several results applied to the cold and snow region in the winter
of Japan January 19 to 21 2021, and mention the usefulness of high similarity
between snowy night-to-day fake output and real snowy day image for night snow
visibility.
