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KIT – Universität des Landes Baden-Württemberg und nationales Forschungszentrum in der Helmholtz-Gemeinschaft
Institut für Technik der Informationsverarbeitung (ITIV)
www.kit.edu
Institut für Technik der Informationsverarbeitung
„ Neue Applikationen erfordern ein Umdenken im E/E-Lebenszyklus Stuttgart, 2016-11-29 Prof. Dr.-Ing. Eric Sax • Leiter des Instituts für Technik der Informationsverarbeitung (ITIV) am KIT • Direktor im Bereich (ESS) am FZI Forschungszentrum Informatik am KIT • Programm-Direktor ESEM an der Hector-School eric.sax@kit.edu
, fahr schon mal den vor“ Harry Wagen
Institute for Information Processing Technology (ITIV) 2
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Content
Introduction
State of the Art („Enabler“)
Trends, Show Cases and new Applications
Challenges
Processes, Methods and Tools
Summary
Institute for Information Processing Technology (ITIV) 3
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Berühmte Persönlichkeiten aus Karlsruhe „Die Liebe zum Erfinden höret niemals auf“ Carl Benz
Heinrich Hertz 1886/88 der Nachweis der elektromagnetischen Wellen in Karlsruhe, die Basis für alle heutigen „over-the-air“ Kommunikationen.
Carl Benz Geboren und studiert in Karlsruhe; Sein Benz Patent-Motorwagen Nummer 1 von 1885 gilt als erstes praxistaugliches Automobil.
Emile Skoda Studierte in Karlsruhe; Namengeber des Automobilherstellers „Škoda Auto“.
Karl Steinbuch Gilt als Begründer der Informatik; war von 1958-1980 Professor an der Fakultät. Die Zukunft neuer Automotive-Anwendungen steckt in der Informationsverarbeitung und Digitalisierung.
Dieter Zetsche Vorstandsvorsitzender der Daimler AG seit 2006 ist. Von 1971 bis 1976 studierte er an der Fridericiana Elektrotechnik. Seit 1. Oktober 2009 gehört er dem Aufsichtsrat des KIT an.
Die Region Karlsruhe ist traditionsreich in den großen, aktuellen Themen der Mobilität (connected, E-mobility, autonomous-driving) seit über 125 Jahren.
Institute for Information Processing Technology (ITIV) 4
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
ITIV: Inhalte der Wissenschaft und Lehre
1958 Gründung des Instituts Leitung Prof. K. Steinbuch „Geburtsort“ der Informatik in Deutschland
Institut für Technik der Informationsverarbeitung (ITIV)
Eines der 13 Institute der Fakultät für Elektrotechnik und Informationstechnik www.kit.itiv.edu
Aktuell 50 Wissenschaftliche Mitarbeiter Inklusive Gruppen am Forschungszentrum Informatik (www.fzi.de)
Forschungsschwerpunkt Systems Engineering Eingebettete elektronische Systeme Mikrosystemtechnik und Optik
Institute for Information Processing Technology (ITIV) 5
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Content
Introduction
State of the Art („Enabler“)
Trends, Show Cases and new Applications
Challenges
Processes, Methods and Tools
Summary
Institute for Information Processing Technology (ITIV) 6
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
1941: Z3, first computer world wide (relais technology)
Semi-Conductors Key to automotive innovations
1947: controllable voltage opens the digital world with semi-conductors
1985: continuation of integration1) enables for micro-electronics applications
1960: silicon enables assembly line production of transistors
1) the number of chips on an integrated circuit is 4 times bigger than 3 years ago
Institute for Information Processing Technology (ITIV) 7
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Semi-Conductors Key to automotive innovations
Seit 2000: In Mikro-Prozessoren/-Controllern integrierte Halbleiter-Technik bzw. darauf ausführbare Software sind der Schlüssel zu mechatronischen Systemen
1947: controllable voltage opens the digital world with semi-conductors
1985: continuation of integration1) enables for micro-electronics applications
1960: silicon enables assembly line production of transistors
1) the number of chips on an integrated circuit is 4 times bigger than 3 years ago
1941: Z3, first computer world wide (relais technology)
Institute for Information Processing Technology (ITIV) 8
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Enabler: Sensors
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Enabler: Car2X Communication
Vehicles become part of the „Internet of things“ (everything)
Quelle: Vector Informatik
Institute for Information Processing Technology (ITIV) 10
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Enabler: Electric Drives
HVAC Front
Li-Ion Battery
Battery cooling
Inverters front drive, Fusebox
HVAC Back
High / Low Temperature Cooling System
Inverters rear drive
Articulated link
Electrical drive axles (Wheelhub motors)
Ancillaries
Quelle Daimler AG
Institute for Information Processing Technology (ITIV) 11
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Content
Introduction
State of the Art („Enabler“)
Trends, Show Cases and new Applications
Challenges
Processes, Methods and Tools
Summary
Institute for Information Processing Technology (ITIV) 12
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Increasing Functionality (Automotive)
* Source Vector Informatik
Semi-Conductor (Technology) improvement is the front runner Applications follow
• Electric fuel injection • Cruise control
• Gearbox control • Traction control • ABS • Electric fuel injection • Cruise control
• Airbags • ESP • Active body control • Adaptive gearbox contr. • Adaptive cruise control • Emergency call • Gearbox control • Traction control • ABS • Electric fuel injection • Cruise control
• Adaptive low beam • Active steering • Turn warning signal • Stop and go • Lane assistant • Automatic parking • Collision avoidance • Hybridization • Telediagnosis • Vehicle-to-vehicle
communication • Alternative Drivetrains • Airbags • ESP • Active body control • Adaptive gearbox control • Adaptive cruise control • Emergency call • Gearbox control • Traction control • ABS • Electric fuel injection • Cruise control
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Enabler: Driver Assistent Systems vs. „good old times“
• No pedestrian protection
• No brake assist
• No speed limiter
• No lane departure warning
• No hill holder
• No automated parking
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Project-References for Auto-Driving
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Big Data Management („Telediagnosis“)
Vehicle is part of Internet of things (everything) Communication with a vehicle enables to check the current status online Typical Use Cases:
Telediagnosis in case of breakdown (24h Service) Error recognition and diagnosis Online repair support Optimized preparation and logistics of spare parts Updates „over the air“ …
Consequently: Prediction less breakdown Reduced time in the workshop Business case
Quelle: Vector Informatik
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Business Cases Commercial Vehicles
driver 66,5%
price 12,0%
tires maintenance
utilities
fuel 13,7%
insurance
Workshop- Management
Diver Duty
Predictive Energy Management
Automated Bus Stop Approach
Avoid Damages
Quelle: Daimler
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
More and more HMI in a modern car
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Content
Introduction
State of the Art („Enabler“)
Trends, Show Cases and new Applications
Challenges
Processes, Methods and Tools
Summary
Institute for Information Processing Technology (ITIV) 22
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Emission Standards 2012
Euro V
Euro IV
Euro III
Euro II
Euro IV for 15 metropolitan
areas
Alternativ: EPA 07
Alternativ: EPA 98
Hong Kong Euro V
Alternativ: EPA 10
Alternativ: EPA 04
Singapore: EURO IV
Alternative: EPA98, Japan 98
Legislation for China III-V stages are based on EURO
III-V
JP 09
EPA 10
Alternative: EPA 04
Alternativ: EPA 04
Alternativ: EPA 94
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Emission Standards 2014
Euro V
Euro IV
Euro III
Euro II
Alternativ: EPA 07
Alternativ: EPA 04
Hong Kong Euro V
Alternativ: EPA 10 EURO V
Q4, 2014 Alternativ:
EPA 07
Singapore: EURO IV
Alternative: EPA98, Japan 98
Legislation for China III-V stages are based on EURO
III-V
JP 09
GHG14
Alternative: EPA 10
Alternativ: EPA 07
Alternativ: EPA 94
Euro VI
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Emission Standards 2018
Euro V
Euro IV
Euro III
Euro II
Alternativ: EPA 10
Alternativ: EPA 04
Hong Kong Euro V
Alternativ: EPA 10 Alternativ:
EPA 07
Singapore: EURO V
Alternative: EPA98, Japan 98
Legislation for China III-V stages are based on EURO
III-V
JP 09
GHG17
Alternative: EPA 10
Alternativ: EPA 07
Alternativ: EPA 94
Euro VI
Institute for Information Processing Technology (ITIV) 25
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Emission Standards 2020
Euro V
Euro IV
Euro III
Euro II
Alternativ: EPA 10
Alternativ: EPA 04
Hong Kong Euro V
Alternativ: EPA 10 Alternativ:
EPA 07
Singapore: EURO V
Alternative: EPA98, Japan 98
Legislation for China III-V stages are based on EURO
III-V
JP 09
GHG17
Alternative: EPA 10
Alternativ: EPA 07
Alternativ: EPA 94
Euro VI
Institute for Information Processing Technology (ITIV) 26
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Different Markets (Mega-Cities) Be
völk
erun
g in
Mill
iard
en
Bangalore Metropolitan Transport Corporation
• ca. 8,5 Mill. citizens.
• ca. 4,35 Millionen passengers/day
• Over 6.000 Buses
• 36 Depots
• More than 32.000 employees
Institute for Information Processing Technology (ITIV) 27
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Mega-Cities Be
völk
erun
g in
Mill
iard
en
Bangalore Metropolitan Transport Corporation
• ca. 8,5 Mill. citizens.
• ca. 4,35 Millionen passengers/day
• Over 6.000 Buses
• 36 Depots
• More than 32.000 employees
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Product Variants in parallel
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Characteristics and Categories
Consumer/PC-Electronics Life cycle
2 years for one innovation cycle (Enabler: technological improvement of semi- conductors) 1 year for warranty
Further examples Software-Updates of Windows Memory capacity of USB sticks
Re-boot- and throw away mentality
Transportation/automotive Life cycle Reaction in real time in any case
50-100.000km p.a., Warranty of more than 30 years (trucks/buses, aircrafts) Stable value
development: production: áfter-sales: Pass.: 3 6 15 Truck: 5 10 15
Bus: 5 15 15
?
Institute for Information Processing Technology (ITIV) 30
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Example: Decision Making for auto. Driving
v3 = 180 km/h
v2 = 120 km/h
v1 = 80 km/h
v0 = 80 km/h
Institute for Information Processing Technology (ITIV) 31
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Example
v3 = 180 km/h
v2 = 120 km/h
v1 = 80 km/h
v0 = 80 km/h
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Alternatives in scenario
Initial situation Blue truck and orange car at 80 km/h orange car changes lane
∆s2; ∆v2 ∆s1; ∆v1
• ∆v from 0 km/h to 120 km/h in 10 km/h steps → 12 variants • ∆s from 0 m to 100 m in 10 m steps → 10 variants
• Two pairs → 12*12*10*10* = 14,400 variants for initial situation
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Challenge: Sensors
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Challenge: Sensors
Institute for Information Processing Technology (ITIV) 35
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Challenge: Sensors
Institute for Information Processing Technology (ITIV) 36
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Challenge: Sensors
Institute for Information Processing Technology (ITIV) 37
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Further Challenges
BIG DATA SAFETY
Liability Ethic questions Standards Sociological aspects …
Institute for Information Processing Technology (ITIV) 38
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Content
Introduction
State of the Art („Enabler“)
Trends, Show Cases and new Applications
Challenges
Processes, Methods and Tools
Summary
Institute for Information Processing Technology (ITIV) 39
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Processes, Methods and Tools (Automotive)
* Source Vector Informatik
Semi-Conductor (Technology) improvement is the front runner Applications follow Processes, methods and tools lack behind
• Electric fuel injection • Cruise control
• Gearbox control • Traction control • ABS • Electric fuel injection • Cruise control
• Airbags • ESP • Active body control • Adaptive gearbox contr. • Adaptive cruise control • Emergency call • Gearbox control • Traction control • ABS • Electric fuel injection • Cruise control
• Adaptive low beam • Active steering • Turn warning signal • Stop and go • Lane assistant • Automatic parking • Collision avoidance • Hybridization • Telediagnosis • Vehicle-to-vehicle
communication • Alternative Drivetrains • Airbags • ESP • Active body control • Adaptive gearbox control • Adaptive cruise control • Emergency call • Gearbox control • Traction control • ABS • Electric fuel injection • Cruise control
Institute for Information Processing Technology (ITIV) 40
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Realisation of functions
EE-Architektur (n ECUs)
ECU (Electronic Control Unit)
PCB (Printed Circuit Board)
Micro-Controller
Software
Source: Daimler
Institute for Information Processing Technology (ITIV) 41
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Questions
Creativity falls by the way side
Institute for Information Processing Technology (ITIV) 42
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
How it all started … (Things used to be much better …)
Chance of working on
demand
Small, manageable teams
No electronics No software
Great depth of own production
Small quantities Few variants
No Big Data
Institute for Information Processing Technology (ITIV) 43
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Back to Start!
Institute for Information Processing Technology (ITIV) 44
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Make the right Choice
Institute for Information Processing Technology (ITIV) 45
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
anal
ysis
de
sign
test
im
plem
enta
tion
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless Design Flow (HW/SW)
Test
Preliminary Hardware
Detailed H
ware Design
Hardware Implementation
Hardware Integration
Institute for Information Processing Technology (ITIV) 46
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Detailed H
ware Design
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless Design Flow (RCP)
Test
anal
ysis
de
sign
test
im
plem
enta
tion
Institute for Information Processing Technology (ITIV) 47
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Detailed H
ware Design
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless Design Flow (RCP)
Test
anal
ysis
de
sign
test
im
plem
enta
tion
Institute for Information Processing Technology (ITIV) 48
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless testing
MiL
SiL K-HiL
I-HiL
Tet
anal
ysis
de
sign
test
im
plem
enta
tion
Institute for Information Processing Technology (ITIV) 49
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Test as part of the Life Cycle Model (V-Model as an Example)
MiL
SiL K-HiL
I-HiL
Institute for Information Processing Technology (ITIV) 50
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
analysis
design
test
implementation
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless testing
MiL
SiL K-HiL
I-HiL
Tet
Institute for Information Processing Technology (ITIV) 51
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
test
implementation
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless testing
MiL
SiL K-HiL
I-HiL
Test
Institute for Information Processing Technology (ITIV) 52
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless testing
MiL
SiL K-HiL
I-HiL
Test ViL
Use complete car simulators Use robots Use objects Use Vehicle-in-the-Loop
Virtualize real world Find abnormalities Set prioritities Training / learning techniques Swarm intelligence
Institute for Information Processing Technology (ITIV) 53
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Preliminary Hardware
Hardware Implementation
Hardware Integration
System Requirements Analysis
System Design
SW / HW Requirements Analysis
Detailed Software Design
Software Implementation
Software Integration
System Integration
Transition to Utilization
analysis
design
test
implementation
Verification
Validation
Acceptance test
Software Integration
System Integration
Transition to Utilization
Preliminary Software Design
Seamless testing
MiL
SiL K-HiL
I-HiL
Test ViL
Use complete car simulators Use robots Use objects Use Vehicle-in-the-Loop
Virtualize real world Find abnormalities Set prioritities Training / learning techniques Swarm intelligence
Institute for Information Processing Technology (ITIV) 54
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Testfeld in Karlsruhe!
Institute for Information Processing Technology (ITIV) 55
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Test Case Conflicts
http://www.autobild.de/bilder/autonomes-fahren-mit-der-s-klasse
„… it was surprising that in Bad Mingolsheim suddenly "Bertha" ran into a deadlock. When a few pedestrians were waving at a zebra crossing without the intention to cross the road, „Bertha“ neglected to drive on.“ How can we find the critical situations?
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
New goal: find the needle in the haystack
Find abnormalities use science of „anomaly“ Use them reverse from the field to prioritize test scenarios the abnormal test responses will guide us to the relevant stimuli
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
New goal: find the needle in the haystack
Anomalous Subsequence
Find abnormalities use science of „anomaly“ Use them reverse from the field to prioritize test scenarios the abnormal test responses will guide us to the relevant stimuli Probabilistic instead of constructive Methods will more and more dominate
Institute for Information Processing Technology (ITIV) 58
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Data Management
„Wer es fertig bringt 2 Halme wachsen zu lassen, wo bisher nur 1 wächst, der ist größer als der größte
Feldherr.“ (Friedrich der Große)
„Wer es fertig bringt die großen Datenmengen, die im Fahrzeug
künftig anfallen, wertschöpfend zu interpretieren, der ist größer als…“
• Telediagnosis • Fleetmanagement • Environmental Conditions • Swarm-Knowledge • …
Institute for Information Processing Technology (ITIV) 59
Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Decision Making based on „big“ data
Knowledge
• Telediagnosis • Fleetmanagement • Environmental Conditions • Swarm-Knowledge • …
Physical Environment
Sensors
Filtered Data
Pattern
Selection
Interpretation Evaluation
Selected Data
Normed Data
Transformation
Data-Mining
Pre- Processing
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Content
Introduction
State of the Art („Enabler“)
Trends, Show Cases and new Applications
Challenges
Processes, Methods and Tools
Summary
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
Main Areas of Research
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Prof. Dr.-Ing. Eric Sax Stuttgart, 2016-11-29 © 2016
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