“LiDAR provides ‘ground-truthing,’ a true 3D depth measurement, whereas cameras are only capable of interpreting 3D depth based on a combination of 2D data and clever computer vision algorithms that learn to interpret depth based on training data that combines camera and LiDAR data. Salomonsson also agrees that you can use LiDARs to improve camera accuracy. He is the senior director of product quality and functional safety at AEye. The problem is that having cameras do all the work may not be the most effective or safe option, according to Ove Salomonsson. Clearly, there are issues with Tesla's system if they continue to run into trailers.” Subaru's EyeSight is a well-known example of wide baseline (~50 cm) that provides more distance estimation accuracy. Most ADAS stereo cameras are short baseline (~20 cm). With stereo cameras, you can get rather accurate distance estimation geometrically depending on the baseline – the distance between the two cameras. Usually, these functions are primarily radar-based but this is also done with cameras. If the car is going 50 km/h (~14 m/sec) and a person/vehicle is 30 m away, it implies a different response (emergency brake immediately!) than if they are 100 m away (no need to react).
VELODYNE VS LUMINAR DRIVER
“For perception tasks, such as driver warning through automated functions (AEB, highway pilot, self-parking.), understanding accurate distance is critical. Although Tokic thinks the strategy is plausible, he thinks Tesla needs to perfect it. We asked him if it made sense that Tesla used LiDARs for training.
Dave Tokic is Algolux’s VP for marketing and strategic partnerships.
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