Waymo, a driverless company that has just been split from Google X Labs, can't wait to announce its latest achievements in controlling the price of core sensors for driverless cars. On January 9, Waymo CEO John Krafcik announced at the North American Auto Show that the price of Waymo's lidar is down 90% from seven years ago.
It is worth noting that Waymo has already built its own set of driverless sensor systems. Google used to use third-party sensors. At present, many technology companies and even car parks are in the form of investment technology companies to master sensor technology. Waymo believes that Google's driverless software algorithms and their own hardware sensors can be precisely matched.
Wu Gansha, CEO of the company and former Intel China Research Institute, told reporters that Google’s independent research and development of laser radar was not long, but Google recruited a large number of talents in the field. In addition, the outside world is still speculating about the current specific cost of the laser radar to the "one-tenth" of the year.
Sensor cost dropsIn the field of driverless cars, how to emphasize the importance of sensors is not excessive.
At the just-concluded CES, Faraday's future FF 91 officially appeared on the stage of the Las Vegas conference, the sensor that can be lifted and lowered is one of the main features introduced by FF. In the entire FF 91, there are up to thirty sensors: long and short range radar, camera, ultrasonic and lidar sensors.
The only purpose of these different sensors is to ensure that the car “perceives†the changes in the environment and reacts correctly. It can be said that almost every driverless car needs sensors, but the price of these small things is not cheap.
The cost of core components is too high and has been the only way to curb the popularity of driverless commercialization. As a result, electric vehicle manufacturers such as Tesla once chose to avoid core components such as laser radar on the road to autonomous driving, and chose other solutions.
As a result, Waymo CEO John Krafcik recently highlighted the sensor segment and previous product changes at the North American Auto Show. He stressed that the price of a single laser radar has dropped by 90% compared with the previous years, from more than 70,000 US dollars a few years ago to the current more than 7,000 US dollars.
It is reported that the initial Google uses the laser radar sensor provided by partner Velodyne. At that time (2009) the price of a single 64-line laser sensor reached 75,000 US dollars, almost the price of a mid-range car.
Waymo attributed the significant cost reduction to self-developed sensors. Since 2015, Google's driverless cars have begun to use self-developed sensors. In addition to cost reduction, lidar sensors are able to make more precise adjustments and adaptations based on unmanned vehicle conditions.
Wu Gansha told reporters that it is difficult to know the parameters of the latest Waymo radar sensor. In fact, Google has only developed laser radar for two years, and it is not as open to the outside as professional laser radar manufacturers like Quanergy. In addition, John Krafcik's recent public description is quite general: Waymo's current visual sensor resolution has been improved, and the Lidar sensor's sensing distance and accuracy have improved compared with the previous.
So, why can Google control the cost of laser radar in just two years? A person familiar with laser radar told reporters that Google may use the device of the Chinese Academy of Sciences Xiguang in the laser radar. Secondly, Google has been heavily recruited in the field of laser radar, attracting many industry "big cattle" to join. Third, Google developed sensor technology in the Tango program, so they can learn from each other at the bottom of the technology.
However, a large number of unmanned vehicle manufacturers have not embarked on the road of independent research and development of laser radar like Google. "To tell the truth, Lidar is not so easy to do." Wu Gansha told reporters that the high-line mechanical laser radar process requirements are too high, ordinary workers can not complete, the engineers need to personally operate, and the solid-state radar technology is still Not mature.
Large-scale popularization is still earlyA semiconductor enterprise application engineer familiar with driverless cars told 21st Century Business Herald that from the two consecutive years of CES, the obvious trend of laser radar/scanner related products is low cost and solid state. A number of industry insiders told reporters that solid-state radar applications are seen as a trend in the field of unmanned vehicles for the past two years and in the future. Wu Gansha believes that the industry is currently watching Quanergy's first-generation solid-state radar available in the third quarter of this year.
The reason why solid-state radar is highly anticipated is that it eliminates mechanical rotating parts compared with mechanical radar, so it has small volume stability and low cost.
Looking at the world, in the field of laser radar sensors, a number of large and small startups have emerged. Foreign Velodyne, Qunery, ibeo, domestic thinking, Raytheon, etc. are players in this field. Their emergence has also driven the decline in the price of lidar.
Even so, the price of laser radar is still widely spread, and there is still a long way to go.
The above application engineers told reporters that the current laser radar needs 6-8 in each car, the single cost needs to be controlled at 500-1000 US dollars, and the cost requirements of the radar camera are more stringent, requiring a single cost control within 100 dollars. If the cost cannot be reduced to a certain level, the unmanned vehicle cannot achieve mass production.
In addition to the hardware, the software-level algorithm is also the winner of the decision to run the unmanned vehicle. In this area, Google needs to worry about competitors like Tesla or Uber. Compared to Google, which has been in the lab for too long, Tesla has acquired more data to better optimize the driverless algorithm.
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