NI unifies replay and HIL test for autonomous vehicles

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NI has announced its latest advanced driver-assistance systems (ADAS) and autonomous driving (AD) offering, a unified test system architecture to move iteratively between data replay and hardware-in-the-loop (HIL) testing.

Validating the perception, planning and control algorithms running on ADAS electronic control units (ECUs) is key to ensuring that safe and reliable vehicles reach the market.

The NI Replay and HIL AD system can aggregate and inject real-world road test data or simulation scenarios to test ADAS ECUs and, by providing a unified toolchain, common hardware configurations and test automation infrastructure across the ADAS workflow, NI said that it would now be possible for companies to reduce capital equipment costs, improve test coverage and efficiency and shorten the time to market.

NI’s approach ensures full validation test coverage for ADAS/AD functions, making existing data more usable throughout the entire product lifecycle.

“NI is working with leaders in autonomous vehicle (AV) testing technology to provide the system-level capabilities our customers need to quickly and efficiently test the complex algorithms and AI-based software embedded within today’s AVs,” said Drita Roggenbuck, senior vice president of NI’s Transportation Business Unit. “Our customers rely on our efficient connected workflow and expertise to help them achieve their goals at their pace.”

“AD and ADAS require the combination of different test methodologies which is challenging but essential to provide driver and passenger safety and ultimately for AVs to become a reality. With NI solutions, we can build up systems and move one step closer to a comprehensive test strategy consisting of both real-world and virtual test efforts,” said Dr. Thomas Herpel, senior manager at ZF Mobility Solutions, one of NI’s leading customers.

AVs are among the most complex systems being tested today, and to bring them to market, manufacturers need to expand test coverage to a nearly infinite number of real-world scenarios, given known limitations on both time and budget.