Innovations in Automotive LiDAR Technology: Innoviz and Velodyne

March 27, 2018
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Updated February 9, 2026
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2 min read

LiDAR data visualization showing a roadway with detected obstacles, highlighting Innoviz Technologies' automotive LiDAR technology.
It’s difficult to separate the hype from the innovation when it comes to automotive lidar, but that doesn’t mean we are not going to try to separate the two.

Meanwhile Velodyne is taking the position that the problem in last week’s fatal crash is Uber’s, but more on that in a moment.

At a recent imaging sensors conference Oren Rosenzweig, co-founder of Israeli lidar system maker Innoviz Technologies, said that the cost of today’s lidar sensors are prohibitive, and the performance is not good enough. Sounds like an honest man.

Rosenzweig believes that a lidar sensor needs to be able to detect objects 200 meters away, while also sensing small obstacles in the road at an angular resolution of around 0.1 x 0.1 degrees. Perhaps more importantly the cost has to be in the hundreds of dollars, not in the thousands.

Innoviz’s technology is a solid-state lidar sensor combining a MEMS scanner based on a micro-mirror designed by the company. The Innoviz One has a 250-metre detection range, an angular resolution of 0.1 x 0.1 degrees, a frame rate of 25fps, and a depth accuracy of 3cm. “The device is based on 905nm laser light; 1,550nm would cost too much for the lasers and detectors,” Rosenzweig said.




Now to Velodyne. “Our LiDAR sensor is capable of clearly imaging Elaine and her bicycle in this situation. However, our LiDAR doesn’t make the decision to put on the brakes or get out of her way,” said Marta Hall, who is the wife of David Hall, Velodyne’s CEO, founder and inventor of its spinning, multi-laser beam LiDAR units. “We don’t know what sensors were on the Uber car that evening, if they were working, or how they were being used.”

Even with a low cost, highly accurate lidar sensor, there will still be many issues to deal with. In the end the consumer will decide.



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