THE STRIVE FOR ROBUST AND RELIABLE SENSOR SUITES IN ADAS AND AD

1. AutonomousVehicles Conference THE STRIVE FOR ROBUST AND RELIABLE SENSORS Karsten Bronowski Berlin, 23-24 November 2022

2. Confidential ©2022 XenomatiX Agenda Camera, Radar, Lidar - which Sensors are required Data Analysis - AI vs. rule based approaches Integration aspects – reliable & predictable data Missing links - data for driving comfort and HD Maps 2

3. XenomatiX

4. Confidential ©2022 XenomatiX XenomatiX at a glance 4 Global coverage Unique Technological Offering Multi-Tier I Key stats 2013 70+ 50+ Patents Established Staff 60+ Engaged Customers Cost Size Reliability

5. Confidential ©2022 XenomatiX Next generationTrue Solid State LidarTechnology XenoLiDAR for DrivingAssistance, Autonomous Driving and other applications XenoTrack HD Road andOffroad Data for referencing, simulation and identifying road quality Engineering Services for Software, Simulation and Integration Support

6. Which Sensors?

9. Confidential ©2022 XenomatiX There is no one LiDAR – influences on object detection Consistency of data – e.g. Instant vs. Scanning Information distribution – e.g. even distributed angular resolution and frame rate over the full FoV Using all relevant Data – e.g. combination of 3D-Geometry and Intensity Easy Review / Annotation – e.g. Commenting in fused 2DVideo Visual Image Reflectivity Image Depth Image • Object 3D location • Object 3D dimensions • Object classification XenomatiX 4D AI object detection

10. AI vs. Rule based

15. Confidential ©2022 XenomatiX Comparison Rule-based vs NN artificial intelligence Rule-based Neural Network based Programming work type Hard programming NN training Iterations Debug Retrain Change in object (size) to detect Adapt rules (parameters) Retrain Change in environment/region Adapt rules (parameters) Retrain Speed and latency Fast Fast … TPR/FNR and mAP f(clear rules) f(training) Result understanding High Low 19 Disadvantagers rule-based program More programming work More geometric information required – clear ‘rules’ Advantages on rule-based program Less data collection on site for NN training & validation Validation and functional environment can differ Program easier exportable to other integration positions and situations

16. Integration 20

18. Confidential ©2022 XenomatiX Position: AEB –VRU 22 Windshield (blue) vs. Headlamp (red) EuroNCAP Recent new EuroNCAP test: Child walking out from behind a vehicle or large object: The camera/lidar behind the windshield might not detect the target which is (partially) hidden by the parked cars (+)The headlamp-lidar will have a full image of the child well before the camera/lidar behind the windshield

20. Confidential ©2022 XenomatiX XenoLiDAR stands all challenges of automotive optical sensors Coping harsh environments Low standing sun Lack of ambient light High dynamic range Rain Snow Other LiDAR Sensors Supply chain ready for automotive grade products Emitter and sensing technology already used in automotive applications Existing automotive grade production and assembly lines Established test procedures Scalable and simple BOM Easy integration and repairability A-thermal design Compact size Pre-calibrated, monolithic modules No moving beams for easier calibration No moving parts for long term stability

21. LiDAR in Automotive for Comfort & HD MAPs

23. Confidential ©2022 XenomatiX Active Suspension for superior ride comfort Key benefits: • Millimeter precision, day & night • Control signal for each wheel • Automatic roll & pitch correction Leading Suspension Manufacturer Goal More ride comfort thanks to preview for active suspension Approach XenoTrack measures mm precision road profile & generates suspension control signal Result • Up to 70% more body stability • Best quality road profile measurement 27

25. Confidential ©2022 XenomatiX The (near) future: more sensors, more data More data, new possibilities Make wider use of sensors and think Big Data Amount and type of data creates new ideas and new possibilities Crowd source HD-maps AD can also benefit from smart infrastructure: All roads will be digitized Make/maintain inventory of road infrastructure Collect road quality info automatically Save money thanks to predictive maintenance of infrastructure Cities will become smarter: City crossings will be equipped with LiDAR, camera and other sensors Collaboration between infrastructure and vehicles e.g. for prevention of hazardous situations Save time and emissions with better traffic flow

26. Summary 30

27. Confidential ©2022 XenomatiX Summary LiDAR is one of the SensorTechnologies, that is required in Fusion with other Sensors to reach reliable ADAS functions and AD for SAE Level 3 and higher LiDARs main advantages are real measurements and operation independent of ambient light conditions vs. Cameras and a higher resolution for better object classification compared to Radar LiDAR itself is no Standard but is a technology that is realized by many different approaches, from evolutionary to Cutting Edge LiDAR integration and reliable operation is not as established as the longer existing Camera and Radar sensors deployed in a more standardized way today All this leads to question regarding robustness, scalability and efficiency for the LiDAR sensors and the whole sensor suite that have to be considered 31

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