IDTechEx’s new report shows that autonomous cars are slowly, but very surely, becoming a part of everyday life. Although they have been hyped and overpromised for a long time, in the last couple of years, the industry has accomplished some significant milestones. The US and China both now have a handful of cities allowing commercial robotaxi services from industry leaders such as Cruise, Waymo, Baidu, AutoX, and more.
Europe, on the other hand, has been plowing ahead with private autonomous vehicles. First, the Mercedes S-Class was given SAE level 3 certification in Germany, meaning that for the first time, drivers could let the car drive for them in very limited conditions. BMW has now entered the mix as well, saying that it will be certifying the 7-series and i7 for level 3 use by the end of the year.
Whether it be a futuristic robotaxi shuffling you driverlessly around a big city or a luxury limousine whisking you autonomously down the autobahn, there is one thing that all autonomous vehicles have in common – sensors, and usually lots of them.
Environmental sensors are not new to the automotive market. Cameras, radars, and ultrasonics have been used across the industry for decades now. So far, they have enabled advanced driver assistance systems (ADAS) such as adaptive cruise control and lane keep assist and have been used for safety features like parking sensors, reverse cameras, and automatic emergency braking. But these features can be enabled with very few sensors; typically, a single forward-facing radar and a couple of cameras can provide enough sensor coverage for a sophisticated SAE level 2 autonomous system. But at level 2, the driver is still responsible for the vehicle, whereas at level 3, the driver can start to disengage from the task.
Moving to SAE level 3 means entrusting the vehicle with far more responsibility than ever before. To do this, OEMs need the vehicle to have the ability to thoroughly monitor its surrounds. As such, IDTechEx has seen through research for its “Autonomous Cars, Robotaxis & Sensors 2024-2044” report that level 3 requires significantly more environmental sensors than ever before. Mercedes, for example, uses eight cameras, five radar, and one LiDAR on its ground baking level 3 drive pilot system. That’s a total of 14 sensors required for autonomous driving, a big step up from the handful of sensors typically seen on level 2 vehicles.
With level 2 vehicles only requiring a single forward-facing radar, level 3 clearly creates a big opportunity for the automotive radar market. However, there are some ADAS functionalities coming to level 2 vehicles and below, which will also demand more radar. Blind spot detection systems have been around for a long time but are still not widely deployed. IDTechEx’s report found that in 2022, approximately 30% of new vehicles were shipped with a blind spot detection system. That’s around 0.6 short-range, side-facing radars per vehicle on average. Not only does level 3 provide a significant opportunity for the growth of the short-range radar market, but growth within ADAS deployment has the potential to increase the market by a factor of five!
This huge growth potential is possible as emerging safety features such as junction automatic emergency braking demand more radars than ever before. Many in the industry predict that four radars per vehicle, used to provide a 360˚ monitoring cocoon, will become common place, driving enormous growth in the short-range radar market.
The front radar should not be neglected, though. IDTechEx finds that 70% of new vehicles are shipped with a forward-facing radar. IDTechEx expects that for most of the market, one radar for forward-facing applications such as adaptive cruise control will be sufficient, meaning there is limited remaining growth possible for this market before saturation. However, that doesn’t immediately translate to limited opportunity.
Radar has further untapped potential as a sensor for automotive applications. It is currently going through a massive technological evolution, with 4D imaging radars emerging and bringing generational performance improvements. This seismic change in radar technology unlocks new performance and new value for this sensor with a long-established presence in the automotive market.
In addition to the additional unit requirements of radar and cameras, level 3 vehicles are a beachhead market for LiDAR. LiDAR has been seen on vehicles before, and there are examples of vehicles that used LiDAR technologies in the early 2000s. However, these were little more than one-dimensional range finders, and the technology has moved a long way since then. Modern LiDARs, such as the Valeo Scala used by Mercedes and the Innoviz system used by BMW, are sophisticated sensors vital for enabling autonomous driving.
LiDARs use narrow beams of laser light, typically scanning across the scene to build a highly detailed 3D rendering of the vehicle’s surroundings. Unlike cameras, LiDAR provides highly accurate ranging information, and compared to radar, LiDAR has significantly better imaging abilities, making it able to classify pedestrians at great distances. The technology helps to fill in the performance gaps left by camera and LiDAR, building a more complete and robust autonomous sensor suite.
For these reasons, LiDAR is a crucial sensor for enabling autonomous driving. The automotive LiDAR market is currently very small, with only a handful of vehicles deploying this futuristic sensor. However, the market will grow as autonomous technologies, like those from Mercedes and BMW, become more common. This will allow prices to come down and make it possible for OEMs to include LiDAR on non-automated vehicles as well.
While LiDAR is a key sensor for enabling autonomous driving, it can also offer performance improvements to ADAS features that make it highly desirable for non-autonomous vehicles. One example is in automatic emergency braking systems. One criticism of these systems so far has been their night-time performance. With conventional cameras struggling in the darkness and radars not having sufficient imaging ability to identify pedestrians, there is a measurable weakness. LiDAR can again fill in this performance gap and offers the potential for significantly improved night-time performance of automatic emergency braking systems.
