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Dr. Ilja Radusch, [email protected]
10.05.2017
REAL AND VIRTUAL PROVING OFAUTOMATED DRIVING IN BERLIN'S MIXED TRAFFIC
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Director Smart Mobility at Fraunhofer
Fraunhofer is Europe largest applied R&D
society
Technology development and consulting
Connected and automated driving
Security, trust, identity management for vehicle
networks
Analysis of large mobility data sets (big data)
Parking and parking space surveillance
Conducted Europe largest field operational test
on connected driving
GTC 2017 ©Fraunhofer FOKUS
WHO AM I ?
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Director of Daimler Center for Automotive IT Innovations
Pre-competitive R&D applying the latest
information technology to the automotive domain
in both product and process innovations
Fostering tri-lateral cooperation between
automotive industry and Daimler AG
Success stories include prototyping the
Remote Parking Assistant of the current Mercedes
E-Class
GTC 2017 ©Fraunhofer FOKUS
WHO AM II ?
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Industry pushing for following scenarios till 2020
GTC 2017 ©Fraunhofer FOKUS
Scenario 1: Structured and simple environment
Highway traffic jam chauffeur till 60 km/h
Highway chauffeur till 130 km/h
Scenario 2: Complex but still structured environment in
parking garages
Parking chauffeur will allow driver less maneuvers and
parking in environments mixed with non-automated
vehicles and pedestrians
AUTOMATED DRIVING
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PROVING AUTOMATED DRIVING IS TIME CONSUMING
Automotive
Cloud
Automated
Vehicles
Roads &
Infrastructure
GTC 2017 ©Fraunhofer FOKUS
Connected
Vehicles
240 million kilometers or
1.000 vehicle life times
just for a single vehicle
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PROVING AUTOMATED DRIVING IS AN ONGOING PROCESS
Automotive
Cloud
Automated
Vehicles
Roads &
Infrastructure
GTC 2017 ©Fraunhofer FOKUS
Connected
Vehicles
During deployment to
validate your data!
While development to
validate your code!
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PROVING AUTOMATED DRIVING IS AN ONGOING PROCESS
Automotive
Cloud
Automated
Vehicles
Roads &
Infrastructure
GTC 2017 ©Fraunhofer FOKUS
Connected
Vehicles
Combining real and
virtual proving
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Virtual Proving consists of either
replay of pre-recorded data
real-time simulation of vehicles and sensors in relevant traffic scenarios
Time and cost effective solution
Allows to simulate vehicles and sensors for
Quick validation during development
Input data generation
Virtual validation of whole system with
estimated improvements in algorithms or sensors
GTC 2017 ©Fraunhofer FOKUS
BENEFITS OF VIRTUAL PROVING
9GTC 2017 ©Fraunhofer FOKUS
Area will be equipped with sensors for ground truth collection
Support for vehicle-2-x communication, including traffic lights
Connected and automated driving functions
Situation analysis and prediction
HD maps for robust self-localization
TEST FIELD FOR AUTOMATED DRIVING IN BERLIN
10GTC 2017 ©Fraunhofer FOKUS
INDEPENDENCE OF ENVIRONMENTAL CONDITIONS
11GTC 2017 ©Fraunhofer FOKUS
OUR APPROACH EVEN WORKS INSIDE GARAGES
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Vehicle SimulationLIDAR, vehicle dynamics,
in-vehicle sensors, …
Traffic Simulationvehicle flow, traffic lights,
real traffic patterns , …Communication
SimulationITS G5 ad-hoc,
LTE, 5G
Virtual Provingwith Simulation
GTC 2017 ©Fraunhofer FOKUS
DYNAMIC COUPLING OF BEST-IN-CLASS SIMULATORS
ADAS Functionsplatooning, self-driving, …
User Simulationdriving behaviour,
emotions, mood, …
ISAAC
Robot Simulator
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Virtual proving environment allows for quick synthetic data generation
GTC 2017 ©Fraunhofer FOKUS
Passive data
Vehicle probe data, from vehicle fleets, …
xFCD probe data, from smart phones, busses, …
Infrastructure traffic data, from infrastructure operators, …
Active data
generated dynamically through interconnected, best-of-
class simulators
Synthetic data allows testing of algorithms independent of
probe data quality, feature set, and quantity
DECOUPLING ALGORITHM AND DATA GROOMING
Quality
Quantity
Signal set
14GTC 2017 ©Fraunhofer FOKUS
Comprehensive virtual proving testbed VSimRTI
Integrates best-in-class simulators
Already bundled with extendable LIDAR, vehicle, traffic, and communication simulators
Research and commercial licenses offered
Developed for over 10 years, used by over 140 institutions all over the world
Makes development of self-driving functions more time and cost effective
Puts several vehicles and sensors in traffic scenarios for
(regression) testing during development
Active data generation
REAL AND VIRTUAL PROVING TESTBED
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