Forschung trifft Praxis...steer, brake, drive by wire, dual energy storage Demonstrator Vehicle ADAS...

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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


Selbstfahrende Autos: Marktpotenzial von $ 87 Milliarden in 2030

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Österreichische F&E-Roadmap für Automatisierte Fahrzeuge


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


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


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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


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


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


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

Forschung trifft Praxis...steer, brake, drive by wire, dual energy storage Demonstrator Vehicle ADAS...

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