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    The test session was conducted in two different hepatocellular cancer pathology outlines areas in Finland in the middle of January The arctic conditions turned out to be challenging for the sensors dedicated more to areas where temperature stays relatively warm.

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    The aim of this one-week test session was to assess performance deterioration when powdered snow, salted road, snowy ground and sun light influence reliability of the future automated driving functions.

    This study focuses mainly on the issues with hardware that are basic building blocks for the situation awareness software modules.

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    Furthermore, the countermeasures such as protecting sensors and mounting positions have been proposed. The test results indicate that some sensors significantly lose performance when temperature drops to less than degrees centigrade. The problem is not merely mechanical freezing of the spinning LiDAR components but properties of hepatocellular cancer pathology outlines illumination may change due to temperature variation, too.

    Since LiDAR is an optical device, they also suffer when there is turbulent snow hepatocellular cancer pathology outlines front of the sensor.

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    The turbulence looks like a noise and partially blocks the laser echoes from surrounding environment. The performance can with some sensors drop more than 50 percent.

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    This seriously diminishes the sensing range and furthermore, makes pattern recognition unreliable. The two other sensor types which were taken into account are stereo vision and radar.

    They have a role in automated driving to compensate performance degradation of LiDARs due to arctic conditions.

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