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<oembed><version>1.0</version><provider_name>Autonomous Driving in Adverse Weather Conditions</provider_name><provider_url>https://mscvprojects.ri.cmu.edu/2023team3</provider_url><title>Introduction - Autonomous Driving in Adverse Weather Conditions</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="HQ7IpCrk96"&gt;&lt;a href="https://mscvprojects.ri.cmu.edu/2023team3/"&gt;Introduction&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://mscvprojects.ri.cmu.edu/2023team3/embed/#?secret=HQ7IpCrk96" width="600" height="338" title="&#x201C;Introduction&#x201D; &#x2014; Autonomous Driving in Adverse Weather Conditions" data-secret="HQ7IpCrk96" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Motivation Autonomous driving has been a daunting challenge for the last couple decades. Some argue that we are close to level 5 automation, but in reality there are still additional challenges to overcome. One major challenge is the ability to persist optimal perceptual performance across different weather types and lighting conditions. Currently, autonomous vehicle operations &hellip; Continue reading ""</description><thumbnail_url>https://mscvprojects.ri.cmu.edu/2023team3/wp-content/uploads/sites/74/2022/12/Screen-Shot-2022-12-15-at-1.43.46-AM-1024x313.png</thumbnail_url></oembed>

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