Google separated the autonomous driving project from the laboratory and established a subsidiary company to move toward the commercialization of autonomous driving. For Google, one of the barriers to commercialization is lidar. At present, whether it is on a modified Lexus self-driving car or Google’s own pod car, the lidar used by it is expensive and does not have the conditions for mass production.
Lidar allows self-driving cars to understand the world around it, but because of its cost, it also widens the distance between self-driving cars and ordinary consumers. Lidar sensors are currently complex and expensive, but the good news is that in the next few years, it will become cheaper, more stable, and more common.
The image generated by the lidar scan. Lidar is a sensing technology similar to radar, which uses laser pointer pulses to detect objects. Although the detection range of lidar is smaller than that of conventional radar (tens of meters versus hundreds of meters), its shorter wavelength ensures a significant increase in its accuracy. The reliable and high-quality data provided by lidar makes it the preferred sensor choice for most autonomous driving applications. In fact, many experts believe that laser sensors are necessary components for unmanned vehicles.
Lidar is one of the key sensors for driverless cars. It ensures the robustness and high-precision positioning capabilities of the vehicle in most situations. The CEO explained that a startup company located in Cambridge, Massachusetts, USA, Currently testing autonomous vehicles in Singapore. He also pointed out that the size, complexity and cost of the current generation of lidar sensors are huge obstacles to the commercialization of any technology that relies on them.
At present, many self-driving cars rely on the HDL-64E produced by companies from Silicon Valley. This lidar sensor can scan 2.2 million data points in its field of view per second, and can locate within 120 meters with centimeter-level accuracy. Objects. But it weighs more than 13 kg and costs 80,000 US dollars. This year, Velodyne released the VLP-32A, which provides a scanning range of 200 meters with a weight of 600 grams. Although the VLP-32A, which costs US$500 in mass production, is two orders of magnitude cheaper than the previous model, it is still too expensive for driverless cars targeting the consumer market.
Recently, some academic and industry researches are focusing on making lidar sensors smaller, easier to install, and cheaper. At the 2016 CES show, Quanergy Systems from Sunnyvale, California, USA demonstrated a Lidar sensor prototype designed for driverless cars. It uses optical phased array technology to manipulate green laser pointer pulses, rather than through a conventional rotating system consisting of mirrors and lenses. Quanergy estimates that its sensor will cost US$250 during the mass production phase and will be available to automakers in early 2017.