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VIRTUAL VEHICLE Research Center is funded within the COMET – Competence Centers for Excellent Technologies – programme by the Austrian Federal
Ministry for Transport, Innovation and Technology (BMVIT), the Federal Ministry of Science, Research and Economy (BMWFW), the Austrian Research
Promotion Agency (FFG), the province of Styria and the Styrian Business Promotion Agency (SFG). The COMET programme is administrated by FFG.
Forschung trifft Praxis
Wertschöpfungspotentiale durch automatisiertes Fahren -
Österreich als Innovationsregion
19. Oktober 2016
Dr. Jost Bernasch
Geschäftsführung, VIRTUAL VEHICLE Research Center
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Das größte COMET K2-Zentrum Österreichs
Wertschöpfungspotenziale Dr. Jost Bernasch 2
AUTOMOTIVE RAIL AEROSPACE
Gesellschafter:
Gegründet: 2002
Mitarbeiter: 204
Umsatz: 20,3 Mio. EUR
Standort: Graz
Website: www.v2c2.at
Dr. Jost Bernasch Geschäftsführer
Prof. Hermann Steffan Wissenschaftlicher Leiter
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AD: Wesentlicher Treiber der Industrie
Wertschöpfungspotenziale Dr. Jost Bernasch 3
Selbstfahrende Autos: Marktpotenzial von $ 87 Milliarden in 2030
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Österreichische F&E-Roadmap für Automatisierte Fahrzeuge
Wertschöpfungspotenziale Dr. Jost Bernasch 4
LEVEL 3
Conditional Automation ▲ Highway driving
▲ Auto Parking
▲ Traffic Jam Assist
2010 2015 2020 2025
▲ accident free driving LEVEL 0
,1
▲ LKA - Lane Keep Assist
▲ ACC Adaptive Cruise Control
▲ AEB - Autonomous Emergency Braking
*only main functions shown
LEVEL 2
Partial Automation
▲ Highway Assist
▲ Park Assist
▲ Lane Change Control
LEVEL4
Full automation ▲ Highway Pilot
▲ City Pilot
▲ Rural Roads Pilot
LEVEL 5
Full automation ▲ Automated Highway
▲ Automated City Driving
▲ Automated Rural Roads
Source: Austrian RDI Roadmap For Automated Vehicles / M. Paulweber, AVL
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Projektbeispiele
Wertschöpfungspotenziale Dr. Jost Bernasch 5
TASTE
Traffic Assistant
(TLA, CACC, TC)
• Kooperativer, adaptiver
Tempomat
• Ampel-Assistent
Plattformen für Traffic-Assistant-
Simulationen
Tests + Testwerkzeuge
Motorway Chauffeur
“Autobahn-Chauffeur”
• Virtuelle Entwicklung des
MWC
Spurhalteassistent
Trajektorienplanung
Etc.
• Frühe Tests und Funktionale
Sicherheit
LaneS
C-ITS und
Verkehrsmanagement
• Automatische Erzeugung
fahrstreifenfeiner
Straßengraphen im urbanen
Raum
• Einsatz für C-ITS-
Anwendungen und
automatisiertes Fahren
Demonstrator
für spurgenaue
C-ITS-Services
© VIRTUAL VEHICLE Wertschöpfungspotenziale Dr. Jost Bernasch 6
Fahrzeug-Demonstrator für
Automatisiertes Fahren
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Roadmap for Full-Vehicle Demonstrator
Electrified vehicle with
internal access;
steer, brake, drive by
wire, dual energy
storage
Demonstrator
Vehicle
ADAS Sensor
Integration Radar, Camera, GPS,
IMU, Ultrasonic,
Lidar, Interior-
Camera, C2X,
Battery-monitoring
Sensor-Fusion
HW-Platform Nvidia, Infineon
Aurix, dSPACE,
Data logging &
measurement
equipment, self-
diagnostics
ADAS Functions
Implementation Advanced control (LKA, ACC,
LCA, Motorway Assistant,
EBA), Online Driver
Monitoring, Collision
detection, Traffic-Light-
Assistant, Infrastructure
interaction, sensor self-
diagnostics …
Optimization and
Validation HW-SW co-simulation,
Distributed vehicle-
Testing, Testdrives,
Function optimization
Vehicle in the loop tests
Wertschöpfungspotenziale 7 Dr. Jost Bernasch
Deep learning Scene interpretation,
Advanced HMI
augmented reality, …
• Graphic processing units (GPUs) for
the gaming market
• System on a chip units (SOCs) for the
mobile computing and automotive
market
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Mobileye
Wertschöpfungspotenziale Dr. Jost Bernasch 8
© VIRTUAL VEHICLE Wertschöpfungspotenziale Dr. Jost Bernasch 9
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Beispiel: Absicherung Assistenzsysteme
Ist ein entwickeltes Assistenzsystem hinsichtlich Reduktion von Unfällen besser?
Unfälle mit
Personenschaden Fahrleistung
Distanz zwischen
zwei Unfällen
180.000 600 Mrd. km 3,3 Mio. km
Für Systemfreigabe (mit 95%er Sicherheit) wären notwendig:
240 Mio. km Fahrzeug-Integrationstests = 1.000 Fahrzeuge je ein Fahrzeugleben (250.000 km) lang
Problematik: Zeit, Kosten und Testwiederholung bei Verbesserung
Absicherung über Simulation von System und Umgebung
Wertschöpfungspotenziale Dr. Jost Bernasch 10
Quelle: H. Winner, 6. FAS Academy Munich, 29th November
2013
PKWs, Deutschland
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Integration Platform (based on Co-Simulation )
Environment/Stimuli Sensors / Models Controllers Vehicle Behavior
Depth of test
integration
ViL
H
iL
SiL
M
iL
ADAS Target Code
ADAS Control Unit Real Sensor Stimuli Real Sensor Hardware
Real Sensor Stimuli Real Sensor
Hardware
Driver Control
Functions Driving
Strategies
Road Traffic Radar Camera
GPS/INS
Car Dynamics
Powertrain Stimuli
Models Others … Others … Others …
Others …
vehicle internal
communication
Sensor Target Code
Real Vehicle Test Bench
Sim
ula
tio
n
Scalable validation framework
Wertschöpfungspotenziale Dr. Jost Bernasch 11
ALP.Lab
ALP.Lab Austrian Light Vehicle Proving Region for Automated Driving
Driver Assistance Partial Automation
Conditional Automation
High Automation Full Automation
ALP.Lab Vision for Alp.Lab
Wertschöpfungspotenziale Dr. Jost Bernasch 13
Fully digitaly integrated testing chain
MIL / SIL (Simulation): Testing of ADAS/ADV software functions
HIL: Driving simulator (test of human interactions)
Sensor validation and qualification
VIL (Driving Cube): ADAS/ADV vehicle qualification prior road test
Proving Ground: Reproducable test of dangerous scenarios
Public Road Testing: Test in regional-specific real-world situations
1
2 3 4 5
2
3
4
5
1
Model-in-the-Loop
Software-in-Loop Hardware-in-the-Loop
Driving Cube
Powertrain Test Bed Proving Ground Test
Public Road Test
(Test Field)
The 5 testing stages are embedded in a system of comprehensive tools and models, for data
management, processing and reporting
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Vielen Dank!
Dr. Jost Bernasch
Geschäftsführung, VIRTUAL VEHICLE Research Center