AD1012A Radar Scene Emulator

Develop robust autonomous driving radar-based functions with the Radar Scene Emulator. Learn more about the AD1011A and AD1012A.

Creating safe and robust autonomous driving (AD) systems is a complex task. Autonomous vehicles (AVs) have hundreds of sensors, all of which need to work with one another inside the car and with other smart vehicles. The software algorithms enabling autonomous driving features will ultimately need to synthesize all the information collected from these sensors to ensure that the vehicle responds appropriately. These algorithms require testing against millions of complex scenes covering various driving scenarios. Achieving the next level of vehicle autonomy will require many innovations and technological advancements. Continuous investments in sensor technologies such as radar, lidar, and cameras will improve environmental scanning. Each sensor type has its advantages and disadvantages, and they need to complement each other to ensure that the object detection process has built-in redundancy. Software is driving vehicle development trends and topics, such as autonomous driving and electrification. The focus of vehicle development is therefore shifting from hardware to software. Vehicles with ADAS Levels 3 and beyond require testing and validation against the growing number of scenarios and the surrounding environment. Not only will the number of tests increase, but the complexity of the tests will also increase. With the technological advancements and changing development trends, R&D engineers need to reimagine test tactics for ADAS and AV systems. This white paper provides insights and key steps needed to confidently sign off on new ADAS and AV functionality. Download this white paper to find out how you can do the following: Apply DevOps (development and operations) model across software application development cycles, emulate and reproduce test scenarios in the lab, understand the technological concepts of how automotive OEMs emulate the scenes for lab testing, test autonomous driving systems with radar sensors faster and with highly complex, multitarget scenes.

The vision of fully autonomous vehicles (AVs) is fast approaching. Along with improving the overall efficiency of transportation systems, driver and passenger safety is the most compelling advantage of self-driving vehicles. To achieve the next level of vehicle autonomy, the automotive industry faces technological, social, legal, and regulatory concerns. Although many of these issues are difficult to control, technology limitation is one area the automotive community and OEMs can help advance. They can make radar, lidar, cameras, and other sensors smaller, more robust, and less expensive, while improving those sensors’ detection and recognition software. Two obstacles stand in the way of improving the training of those algorithms. Closing the gap between roadway and software simulation testing. Training ADAS / AV algorithms with real-world conditions. This white paper outlines the gaps in autonomous vehicle testing and validation, the key technology advancement to address the challenges, and how you can achieve greater confidence in ADAS functionality with the Keysight Radar Scene Emulator.

Keysight’s Autonomous Drive Emulation (ADE) platform is the environment emulator for in-lab testing versus realistic roadway scenarios, from mundane to one-in-a-million. Using total scene generation, the platform exercises ADAS software using time-synchronized inputs to the actual sensors. Its open architecture also closes the loop with your existing HIL systems and 3D modelers. Enabling you to keep pushing ADAS towards Level 5. Generate total roadway scenes with multi-faceted environment emulation. ADE fills the gap between software simulation and on-the-road testing of ADAS capabilities by performing holistic validation of the actual sensors, ECU software, AI logic, and more. Accelerate the development of new ADAS software features and gain deeper insights into the ADAS software behavior earlier in the development cycle. Develop greater confidence in the validation process by thoroughly validating line-of-sight-based sensors such as radar and cameras and with synchronous testing of communication-based systems (e.g., C-V2X). Cover dangerous situations, risky corner cases and more, in the lab by emulating complex situations with time-synchronized stimulation of the real sensors to be used in vehicles. Find potential issues earlier in the development process, reducing the likelihood of post-release failures. Ultimately test more scenarios, sooner, and achieve greater confidence in required ADAS functionality.

Keysight's RSE can emulate extended objects to add realism to a scenario in a lab environment.