Evolving your ADAS and AV tests with emulation capability
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. This white paper explores miniaturised radar target simulators (mRTS) enabling design and test engineers to emulate complete traffic scenes to train their ADAS and autonomous driving algorithms.
Creating safe and robust autonomous driving (AD) systems is a complex task. Automakers must overcome immediate challenges to realise the future of autonomous mobility.
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. Automakers need to be able to sign off on new advanced driver-assistance systems (ADAS) and AV functionality confidently.
This white paper discusses the following areas for consideration:
- The Evolution of Radar Sensors: A Critical Part of ADAS / AV Systems
- Recognising the Complexity of Radar Sensor Test
- Reimagine Test Tactics
- Testing on open roads
- Shift in thinking
- Setting Up Your AV for Success
- NCAP provides standardised scenarios
- Closing the Technology Gaps with Innovations
- Enable Next-Generation Vehicle Autonomy with In-Lab Full-Scene Emulation
- Scene Emulation Earlier in the Lab Accelerates ADAS / AV Testing
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