1. 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
Automotive

2. 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

3. 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

4. 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

5. 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

6. 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),