Abstract
Just after sunrise and before sunset the sun can shine directly into driver's eyes making it more difficult to see the road ahead. The direct sunlight problem creates a serious risk for human drivers as well as machine vision systems for autonomous vehicles. In 2016, the on-board cameras of a Tesla level 2 autonomy vehicle were unable to detect the side of a white truck due to bright sunlight. In order to solve the direct sunlight problem, we apply high dynamic range (HDR) imaging algorithms to the machine vision system of Lawrence Technological University's autonomous electric research vehicle and measure how well the system performs in direct sunlight. A Raspberry Pi is used to capture several manual exposure frames and compose HDR frames using three HDR algorithms provided by OpenCV 3. The resulting frames are supplied as input to the autonomous vehicle. Standard dynamic range (SDR) images captured using auto exposure are compared to equivalent HDR frames using various quality metrics. Objective assessment metrics are also performed to compare the color and contrast of HDR and SDR frames. Results show the system performs best when using HDR frames generated by the Mertens algorithm.
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