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]]>Generally speaking, to achieve automatic driving is complicated. In the actual use of unmanned vehicles, the system needs to complete three tasks: perception, decision-making and control. The perception needs to collect basic information of the surrounding environment, which is also the basis of autonomous driving. Self-driving cars sense the environment through sensors. Commonly used sensors mainly include LiDAR, millimeter-wave radar and cameras. Based on various requirements for application scenarios and environments, compared with cameras, the biggest advantage of LiDAR is that the use environment is less restrictive, that is, it can be used normally during the day or night. At the same time, LiDAR can detect very small targets, and the measurement accuracy is much higher than millimeter wave radar and other vehicle-mounted radars. Neuvition’s high resolution solid-state LiDAR Titan M1 can achieve a vertical angle resolution of 0.03°, and the measurement accuracy is controlled within 2cm.
‘With the gradual enrichment of driving experience, the continuous learning of the system, and the continuous improvement of technology, more and more traffic conditions can be handled by the automatic driving system.’ Dr. Lin, CTO of Neuvition Inc. said. ‘The sensor technology and computing power of the car must keep up. It is necessary to let the car understand the real traffic situation and make the correct response. This is not only the technical obstacle we are facing right now, but also the direction of the manufacturer’s efforts.’
With the increasing number of LiDAR companies and the continuous development of LiDAR technology, mass production of LiDAR is only a matter of time. At the same time, under the influence of epidemic, it is presumed that autonomous driving will become an inevitable and rapid development trend.
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