Until recently, various vehicle OEMs were vying to be first to put self-driving cars on the road by the magical turn of the decade. But as 2020 arrived, the bullish tone has switched to a more cautionary outlook. While the truly self-driving SAE Level 5 autonomous vehicle (AV) without a steering wheel is still years away, innovations needed to support the intelligent self-driving car of the future continue to emerge and improve.
Developers grapple with the need to comply with safety and security standards as the average car sees more sensor technology connecting it with onboard devices as well as with its environment. Within the increasingly capable sensor suite (see table in gallery), automotive radar is now an indispensable technology that enables sub-systems for advanced driver assistance systems (ADAS).
About a decade ago, 24-GHz radar sensors entered the scene and began to impress engineers, enabling all-weather ADAS functionality such as blind spot detection, lane change and parking assistance, and collision avoidance. Minimally affected by lighting conditions or bad weather, radar quickly gained favor over camera technology for ADAS applications.
Radars evolve and proliferate
The essence of automotive radar is the ability to scan the three-dimensional space and gather information about other road users and stationery objects. This includes picking up the presence of other vehicles or pedestrians and pets, to details such as location, speed, direction, shape, and identity. In most implementations, the radar system generates a RF/microwave or millimeter wave signal and beams it toward the target in question.
The same antenna that transmitted the signal, collects the feedback. The feedback triggers the electronic control units on board the car to activate the appropriate ADAS response. This can be a lane change or vulnerable road user alert, or a trigger to activate adaptive cruise control to help drivers maintain safe platooning distance.
Due to spectrum regulations by the European Telecommunications Standards Institute (ETSI) and the Federal Communications Commission (FCC), the 24-GHz-wide bandwidth and UWB bandwidth will not be available for new automotive radar devices after January 1, 2022. These changes are spurring market growth for 76-81-GHz band usage for automotive radar applications. These higher frequency bands allow designers to create smaller sensor packages, with more bandwidth available to achieve greater resolution of detected objects.
The automotive radar sensor market is growing at a compound annual growth rate of 21%. By 2023, it is expected to exceed $8 billion, according to Microwave Journal, outstripping other radar sectors like environmental monitoring, security surveillance, and aerospace defense. Meeting this market growth without compromising on performance and reliability requires rigorous testing of each radar from chip design to module deployment.
A self-driving car can have up to 24 radar sensors. Interference effects can arise between sensors within the same car or with other onboard devices. Even marginal errors in measurement, such as wrong angle calculation at a busy road junction, can result in dire consequences. Therefore, engineers must characterize the behavior of each new radar module before mass production and installation in the vehicle. These days, engineers use radar emulation equipment to generate and analyze different signals, with software to create test cases for different conformance test standards.
Some test managers also use intelligent laboratory operations software to help them manage the thousands of tests for their devices under test (DUT). This can help them precisely determine prototype DUT readiness for mass production. At the functional test level, engineers can now simulate multiple targets for radars operating in the 76-81-GHz band. This allows both the radar module developers and car makers to test a multitude of realistic scenarios before the car rolls onto real roads.
Current radar technology still struggles with providing greater resolution to discern different objects. This is where lidar does a better job. A lidar sensor uses a pulsed laser to detect objects, usually with higher resolution than radar. Lidar’s higher degree of granularity can provide a much more complete view of the vehicle’s environment.
On the downside, lidar is generally more expensive versus camera and radar sensor technology. New players are trying to produce cheaper lidar, with some innovations going for under $1,000, versus typical prices in the ~$10,000 range. Lidar has other limitations including high data rate and power consumption, and poorer performance in low lighting. It will be interesting to see if new disruptive technologies help make lidar cheaper and better for wider adoption.
Enabling the future connected car
While sensor technology plays a vital role in enabling safety and in-cabin comfort, it is high-bandwidth, low-latency cellular vehicle-to-everything (C-V2X) which will help realize the vision of truly autonomous and connected cars. C-V2X connects the vehicle sensors to driving data such as speed, location, traffic, other cars, and data such as real-time updated maps. With a supercomputer on wheels, testing for signal integrity, performance reliability, and automotive cybersecurity from the physical backplane all the way through the various protocol layers becomes critical.
4G and LTE technology, and eventually 5G, will form the infrastructure to support C-V2X capabilities (see Figure 3). According to S&P Global Market Intelligence, 4G LTE is expected to surpass 80% of total in-vehicle cellular systems in 2024. The industry is concurrently banking on 5G technology, which advocates believe will be able to better carry mission-critical communications faster and better for autonomous vehicles.
The potential of 5G-enabled C-V2X is exciting, and the road ahead is likely to see more collaboration among autonomous vehicle developers who face common challenges of meeting new and evolving industry standards. Global standards organizations including SAE International and IEEE are working on new standards for artificial intelligence in autonomous vehicles. Initiatives to introduce self-driving vehicles currently are confined to service fleets operating in safe zones. It may take several more years to see self-driving cars alongside those still controlled by human drivers.
Meantime, more work lies ahead for automotive design and test engineers to juggle the jungle of conformance standards, alongside customer expectations for the creature comforts of a self-driving gizmo on wheels, with all risks of malfunctions and accidents mitigated.
About the author
Rick Kundi is a Solutions Marketing Engineer within the Automotive and Energy Solutions business at Keysight Technologies, responsible for automotive radar, Ethernet and software solutions. He has over 10 years of industry experience in application engineering, sales, and marketing and has presented at professional events covering topics such as RF and wireless basics, advanced automotive radar analysis, and generation solutions.