Guillaume Devauchelle, who oversees innovation at Valeo, a major parts supplier to vehicle manufacturers, believes that lidar will be the basis for all autonomous vehicles.
Lidar (pronounced LIE-dar) is an abbreviation for light detection and ranging. It is a sensor that is used for many autonomous car designs. The same technology is used to detect speeding violations and to outline terrain from airplanes.
Waymo, the self-driving car program, is one of many that uses lidar. Waymo is currently looking for East Valley volunteers to use its automated vehicles for free rides around the metro area for the entire family.
The technology uses near-infrared light to detect the shape of objects around it. Lidar can produce exact 3D images of everything from trees to cars to cyclists in many environments and under different lighting conditions. Although autonomous car designs use many different sensors, including radar, ultrasonic and video cameras, lidar has unique abilities. Lidar can for example not be fooled by shadows or be blinded by bright sunlight.
The biggest obstacle to widespread lidar adoption is cost, and that is where a number of battles are being waged.
When Google originally started with autonomous vehicle research eight years ago, a lidar sensor made by Velodyne Lidar, an industry leader, cost about $75,000. Although Velodyne declined to comment on the current price, John Krafcik, Waymo’s chief executive, mentioned recently that his company had reduced the cost of its lidar system by 90 percent.
Even at $7,500, such systems are regarded as being too expensive for car manufacturers.
Omer Keilaf, chief executive of Innoviz Technologies, a lidar developer based in Israel noted that car manufacturers want it to cost $100 and perform 10 times better, be smaller, and very reliable. This has created a big vacuum in the industry.
The race to fill that gap is mainly focused on the manufacture of solid-state lidar systems. This would reduce the size of the sensors by eliminating moving parts involved in optical mechanisms and enable mass manufacturing that would ultimately reduce costs.
Established automotive suppliers, such as Valeo and Velodyne; technology companies like Uber and Waymo; and relative newcomers like LeddarTech, Innoviz and Quanergy are all trying to make cheaper sensors.
Solid-state lidars generally have a reduced field of view – about 120 degrees compared to the 360-degree view that rooftop models are capable of. To create all round vision, four to six solid-state lidar sensors would have to be integrated.
Most researchers working on lidar designs believe they can manufacture them for much lower prices. In its Ioniq autonomous test cars, Hyundai has demonstrated how such sensors could be made less conspicuous by concealing them in the bumpers and roof pillars of vehicles.
Luminar Technologies is focusing on extending the effective range of lidar to more than 200 meters. Current top-of-the-line sensors have a range of 120 meters. Austin Russell, Luminar’s chief executive, noted that they achieved the extended range by using more sensitive receivers, as well as more powerful light outputs that are still safe enough to not damage people’s vision.
Velodyne claims to be the only third-party lidar supplier for fully autonomous vehicles currently being tested. The company is aware that start-ups are gunning for its business and is working on its own solid-state Velarray lidar sensor. Mike Jellen, Velodyne president revealed that they plan on starting mass production next year.
In spite of considerable speculation about Velodyne’s lidar pricing, Jellen declined to estimate how much their new sensors might cost, saying only that a complete lidar sensor package might be priced in the “low thousands” per vehicle.
Other companies manufacturing complete autonomous driving packages expect prices to fall faster.
Jeffrey Owens, chief technology officer for Delphi expects that in five years, the price could be about $8,000, dropping down to $5,000 by 2025. Delphi recently announced it was working with BMW, Intel and Mobileye on an autonomous driving platform.
