Velodyne just made self-driving cars a bit less expensive
It cut the price of its most popular lidar sensor in half.
Andrew KrokReviews Editor / Cars
Cars are Andrew's jam, as is strawberry. After spending years as a regular ol' car fanatic, he started working his way through the echelons of the automotive industry, starting out as social-media director of a small European-focused garage outside of Chicago. From there, he moved to the editorial side, penning several written features in Total 911 Magazine before becoming a full-time auto writer, first for a local Chicago outlet and then for CNET Cars.
Velodyne announced this week that it has cut the price of its most popular lidar system, the VLP-16, in half. When the VLP-16 originally went on sale in 2016, it commanded a price of $8,000, so the 50-percent slash is quite the chunk of change. It's unclear if buyers get additional discounts based on volume.
The drop in price comes as a direct result of Velodyne's manufacturing efforts in its new "megafactory." The company opened this new facility in San Jose, California in 2017, and it started out manufacturing the company's flagship HDL-64 system, which emits four times the number of lasers as the VLP-16.
"Since its launch, customers have been lining up to purchase the VLP-16 and we've been able to meet that growing demand by expanding production and developing automated manufacturing for LiDAR sensors at the Megafactory," said David Hall, founder and CEO of Velodyne, in a statement. "With this cost reduction, we'll be able to get more Pucks into the hands of more customers, support the growing number of autonomous vehicle development fleets around the world, and start creating a better tomorrow."
Right now, lidar remains an expensive component of many fledgling self-driving-car systems. Whereas radar uses radio waves, lidar uses laser light to map the world around the sensor. Lidar systems usually take the shape of a can or puck -- if you've seen those spinning things atop some
, it's the lidar array.
Some developers decided to attack lidar cost head-on by investing in other companies or developing their own systems. Uber and Waymo have both decided to develop in-house lidar solutions (and it's part of the court case between the two companies).
and GM have taken the alternate route, investing in lidar startups to bypass dealing with larger, well established suppliers.
While the effects of cheaper lidar solutions won't immediately come to the surface -- it's not like you can go out and buy a Level 5 self-driving car or anything -- any movement to help reduce the cost of the complex systems involved in these vehicles is a positive step to creating one that city governments or individual citizens could afford.