CyPhy Test Environment for ADAS and Autonomous Driving Systems TEAADS CyPhy Test Environment for ADAS and Autonomous Driving Systems Dr. Helmut Kokal, AVL List GmbH helmut.kokal@avl.com Automotive

Market relevance: Innovation: Business impact: Increasing extension of driver assistance systems in vehicles up to autonomous driving rises the need of automated test tools for cy-phy systems Highly tested safety functionality and reliability of automotive cy-phy systems such as ADAS and autonomous driving systems Guarantee efficiency and emission by the use of ADAS and aut. driving systems Legislation, driver acceptance and social acceptance are mandatory for successful establishing ADAS and autonomous driving Innovation: Automated and reproducible testing of ADAS and autonomous driving systems Business impact: More reliable and efficient testing of cy-phy systems Reduction of costs as disastrous consequences of road traffic accidents

Test generator ECU GPS stimulationsimulation (Rest) Vehicle + powertain simulation Driver simulation Torque Stimuli &Simulation Video Stimuli &Simulation Navi Track simulation Autom.Driving VCU Test generator Radar Stimuli &Simulation ECU TCU ECU Environment + traffic condition simulation (fog, night, rain, snow, traffic jam, ..) Ultrasonic Stimuli &Simulation Lidar Stimuli &Simulation Maneuvers and test Low speed Manoever (Park,. Higher speed (ACC, lane ass,…) V2V + I2V simulation

SIL/MIL HIL xIL Integration WP-Sensors WP-xCU Functions & Dev. WP-Simulation Environment WP-Requirements, Test Methodology Driver Acceptance Driveability, Usability Legislation Legal checks Social Acceptance Maneuvers selection Test generation HiL, Traffic simulation, Vehicle simulation, Test Environment Sensor stimuli and/or Sensor simulation xCU for ADAS and autonomous driving Sensors WP-Test Environment SIL/MIL HIL xIL Integration

XiL with surroundings sensors Current state of technology: Only simple target configurations with physical or electronic targets possible For stimulation by virtual targets totally new approaches are necessary: Situation and sensor type dependent stochastic perception models, calibra- ted on relevant application specific scenarios based on a valid metric Image sources: u.l. Bosch, u.r. Winner et.al., l. l. Continental Stimulation by virtual targets: Camera Possible by image generation Ultrasonic sensors + short range surroundings -- phase sensitive superposition, multipath Infrared Lidar huge range to be considered + ray tracing techniques adaptable mm-Wave Radar - huge range surroundings -- phase sensitive superposition, multipath

Nat. Interested Partners Covered Topics GER VALEO Sensor development, xCU function development AUT University of Linz / Prof. del Re Integration & simulation expertise Daimler Requirements, legislation, acceptance,… Technical University Graz / Prof. Horn Sensor stimuli/Micro Traffic Technical University Darmstadt / Prof. Winner Sensor simulation AVL List GmbH Simulation & test environment, testing methodology, systems engineering AVL Regensburg xCU Function Dev., Requirements Infineon Embedded processors, near field sensors, combined sensors, sensor simulatiuon, Other potential partners Conti (DE), PTV (DE),