Euro NCAP 2026: Preparing for the Next Generation of Automotive Safety with Synthetic Data
With Euro NCAP's Safety Assist / Safe Driving assessment protocol slated for an update in 2026, now is the perfect time to reflect on Euro NCAP's remarkable journey in automotive safety. We'll do so by having a look at the current implementation, and how we think synthetic data will help to meet the requirements of the next iteration of the protocol.
Established in 1997, the European New Car Assessment Programme (Euro NCAP) has been a global leader in automotive safety innovation, influencing safety practices across Europe and beyond through a number of rigorous safety protocols. In 2020, it introduced Driver Monitoring Systems (DMS) as part of its safe driving criteria, addressing emerging concerns around driver distraction, drowsiness, and overall alertness. This initiative was part of a broader commitment to adapting safety standards to new technological capabilities and changing driver behavior patterns.
In the current implementation of the Safety Assist / Safe Driving assessment protocol (2023, Version 10.4), the DMS is assessed per its performance in these areas:
- Sensing Capabilities: The DMS must accurately monitor a diverse range of drivers, considering variations in age, gender, stature, skin tone, and other physical factors. It should function reliably in different conditions, accommodating factors such as lighting, eyewear, and facial hair.
- Driver State Detection: The DMS must identify driver states like distraction, fatigue, and unresponsiveness. This includes recognizing behaviors such as prolonged glances away from the road, signs of drowsiness, and delayed reactions.
- Vehicle Response: Upon detecting impairment, the DMS should respond with appropriate interventions, such as warnings or other safety actions, to mitigate risks. The effectiveness and timeliness of these responses are crucial in ensuring driver and occupant safety.
The 2026 implementation will incorporate more detailed scenarios, making DMS and Occupant Monitoring Systems (OMS) even more integral components of a vehicle's total safety rating. Among the notable additions:
- Introduction of non-fatigure related impairment detection: The DMS will need to extend beyond fatigue and distraction detection to assess signs of alcohol and drug impairment through behavioral indicators, enhancing safety in more situations.
- Advanced Seatbelt Detection: The DMS will not only need to detect seatbelt usage, but also verify proper positioning and fastening for maximum effectiveness.
- Occupant Classification: Enhanced monitoring will account for passenger size, position, and posture to optimize restraint systems, such as airbags, accordingly.
As Euro NCAP continues to raise the bar in automotive safety, it is crucial to keep up with the latest advancements to receive high ratings by Euro NCAP.
Devant's synthetic data can play a pivotal role for those looking to build and implement DMS and OMS systems that target these kinds of safety protocols.
Ensuring representation and diversity
Human diversity is challenging to obtain in the real world - especially at scale. Devant's expertise in human centric synthetic data equips us with the tools to create diverse representations of unique individuals, covering different ethnicities, ages, skin tones and BMIs ensuring that the system addresses all intended demographics and reduces bias.
Simulating critical and hard-to-capture scenarios
Ongoing collaborations within the automotive industry have equipped us with the expertise and capabilities to simulate critical scenarios and behaviors. Synthetic data proves particularly valuable in addressing the need for diverse scenarios where different timings and the order of distractions are central to the test scenario. In particular, multi-location short distraction sequences (classified as VATS, as specified by NCAP's Safety Assist / Safe Driving assessment protocol) are naturally expensive to collect and record using real-world data.
Scale-up efficiently and cost effectively
Devant's synthetic data can be generated rapidly, at scale, making it a cost-effective and highly customizable alternative to real data. This allows OEMs to effectively address data gaps by enabling a broad distribution of test cases that are challenging to fill with real-world data, while significantly reducing data collection and model retraining.
If you’re interested in discovering how Devant can help your company align with the current or upcoming implementations of the Euro NCAP protocols - please feel free to reach out to us directly.
