the data defined-vehicle_architecture

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The Data-defined Vehicle Architecture The AUTOmobile becomes the autoMOBILE Dr. Sebastian Wedeniwski IBM Distinguished Engineer, CTO Global Industrial Sector

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Page 1: The data defined-vehicle_architecture

The Data-defined Vehicle ArchitectureThe AUTOmobile becomes the autoMOBILE

Dr. Sebastian WedeniwskiIBM Distinguished Engineer, CTO Global Industrial Sector

Page 2: The data defined-vehicle_architecture

Agenda

Ø Software-defined vehicles surrounded by historical structuresØ The mobility revolution shifts the vehicle to a software-defined serviceØ Critical business competencies in a globally transforming autoMOBILEØ Fundamental challenges to master data-defined vehiclesØ Outlook of a data-driven architecture for mobility as a service

Page 3: The data defined-vehicle_architecture

Patent No. 37435 “Vehicle powered by gas engine” of 29 January 1886 is the birth certificate of the automobile

Absolutely no software!

Page 4: The data defined-vehicle_architecture

In the mid-1960s, a Volkswagen Beetle contained only very few electrical parts – BUT no software-defined hardware

Some electrical parts in mass production

VW1300LEFT RIGHT

J1

Turn

signal

Turn

signal

Fig.1.Wiring DiagramVW1300(U.S.version)FromAugust1965 toJuly1966

J3J2

G1

H1

H2

G

Sealed

beam unit

Parking lightParking light

1,0 1,0

0,5

1,5 2,5

2,5

Fuel

gauge

light

Interior

light

Transmission

to frame

ground strap

Battery

T1

S

K

1,5

LEFT RIGHT

Blackdotted line=Optionalextrasor serviceinstallation

0,7

5

EK1

K2 K3 K4

K5

Windshield wiper switch

Light switch

Turn s ignal switch with dimmer switch

Emergency flasher switch

Horn button

Steering column connection

Emergency flasher relay

Dimmer relay

Brake light switch

High beam warning light

Generator warning light

Turn s ignal warning light

Oil pressure warning light

Speedometer light

Automatic choke

Electro-magnetic pilot jet

Spark plug connector, No. 1 cyl.

Spark plug connector, No. 2 cyl.

Spark plug connector, No. 3 cyl.

Spark plug connector, No. 4 cyl.

Fuse box

white fuse: 8 ampere

red fuses: 16 ampere

Cable adapter

Cable connector, s ingle

Cable connector, double

Cable connector, triple

Brake, turn s ignal and tail lights

Brake, turn s ignal and tail lights

Horn ring to steering coupling ground

connection

Wiper motor to body ground strap

E.

F.

G.

G 1.

H 1.

H 2.

J 1.

J 2.

J 3.

K 1.

K 2.

K 3.

K 4.

K 5.

O 1.

O 2.

P 1.

P 2.

P 3.

P 4.

S.

T.

T 1.

T 2.

T 3.

X 1.

X 2.

2.

4.

1,50,5

2,5

Horn

0,7

50,5

S

F

Wiper

motorS

Ignition/

starter switch

Sealed

beam unit

2,5

2,5

2,5

4,0

1,5

1,0 1,0

2,5

2,5

2,5

0,5

0,5

0,5

1,0

0,5

4,0

1,0

1,01,0

Antenna

connection

Radio

56a

5630

30 15

30

Battery

to frame

ground strap

Door

switch

Door

switch

VLVR BI 49a S

0,5

0,5

0,5

1,01,5 2,5

0,5

0,5

15/5

4 50

1,0

1,0

1,5

0,5

1,5

2,5

58 30

F

56

57

30

T

T

1,51,0

S

R 54

L

0,5

5431b

54d

T

Generator/

regulator

1,5

0,5

0,5

0,5

6,0

4,0

4,0

6,0

6,0

0,5

1,0 1,0

T3

P3

P2

1,5

DistributorSpark plugs Spark plugs

P1

P4

25,

0

Ignition

coil

1,0

1,0

0,5

Starter30

50

O 1

O 2

Oil pressure

switch

X 1

0,7

51,01,0

1,5

1,51,5

X 2

1,5

0,5 © 1972 VWoA – 509

T21,5

1,5

14

15

61

B+

License

plate

light

Page 5: The data defined-vehicle_architecture

As early as the beginning of the 2000s, there were 45 connected Electronic Control Units (ECUs) made by different manufacturers in the Volkswagen Phaeton

Electronic components (blue) and wiring system (brown) (Photo: Volkswagen)

Cabling in the Phaeton has a total wire length of 3,860 m with a cable harness weighing 64 kg.

The bill of materials of the electricsconsist of 11,136 parts.

Only embedded software defined by hardware!

Page 6: The data defined-vehicle_architecture

In 2005, high variation of possible ECUs in the BMW 7 series (E65)

Source: S 400 HYBRID - own photo, Attribution, https://commons.wikimedia.org/w/index.php?cur id=11526833

BMW 7 series from 2005 contained around 65 ECUs, connected via five bus systems with an embedded software scope of around 115 megabytes.

Every car gets an own fingerprint just by ECUs and software for standard equipment (green) and optional equipment (blue).

Source: BMW

Anti-theftalarm

Tyrepressurecheck

Rain sensor

Lightswitchmodule

Heatingcontrolpanel

Heatingcontrolpanel

(back)

1-axis-air suspension

Control centreCentreconsole

Trailermodule

Instrumentcluster

Safetyandinformationmodule

Vehiclecentre

Human-machineinterface

ParkdistanceControl

Digital Diesel/ Motor

Electronics1

AdaptiveCruiseControl

SwitchcentreSteeringcolumn

Acolumn left

Bcolumn left

Acolumnright

Bcolumn left

Door frontleft

Driver’s seat

AudiosystemController

Door frontright

Backseat

Activerollstabilisation

Dynamicstabilitycontrol

Electronicgearboxcontrol

Passenger seat

SeatmoduleDriver

SeatmodulePassenger

Aerial tuner MultimediaChanger

AudioCDChangerVideomodule

Control centreCentreconsole

Rear

AdaptiveLightControl

ElectronicDampercontrol

Electromech.Parkingbrake

Ratesensor

(noswitchgear)

SeatmodulePassengerbehind

Power module

Digital Diesel/ Motor

Electronics2

Tilt andslideroof

ChassisIntegrationModules

Amplifier

Navigationsystem

Telephoneinterface

Speechrecognitionsystem

Headphoneinterface

Tailgatelift

SeatmoduleBehind driver

Auxiliaryheating /

Booster heating

Controller

Windscreenwiper module

DiagnosisAccess

CentralGatewayModule

CarAccessSystem

DoormodulePassenger

DoormoduleDriver’sdoor

DoormoduleDriver’s sidebehind

DoormodulePassenger’s side

behind

Bodywork

Multimedia

Drivesystem

Passivesecurity

Periphery

Diagnosis

Page 7: The data defined-vehicle_architecture

Today, the share of software is already higher than that of mechanics

Source: ITQ GmbH (2014) Kompetenz in Mechatronik. München https://www.itq.de/files/itq_unternehmensbrosch_r e_onl ine.pdf

1970 1980

Functio

ns

SoftwareElectronics

Mechanics

1990 2000 2010 2020

0%

10%

20%30%

40%

50%

60%70%

80%

90%

100%

Page 8: The data defined-vehicle_architecture

AUTOSAR (AUTomotive Open System ARchitecture)Electrical/Electronic architecture concept towards software-defined hardware

Source: AUTOSAR

ApplicationLayer

RuntimeEnvironment

Onboard DeviceAbstraction

MemoryHardwareAbstraction

CommunicationHardwareAbstraction

I/OHardwareAbstraction

ComplexDrivers

MicrocontrollerDrivers

MemoryDrivers

I/ODrivers

CommunicationDrivers

SystemServices MemoryServices CommunicationServices

Microcontroller

SWComponents

MiddleWareBasicSoftware

ECUResources

Over the past 20 years, there have been a number of efforts to standardize operational systems, bus systems, basic software and functional interfaces for the architecture of embedded systems.

Aim to decouple the software in the embedded systems from the underlying hardware!

Similarly to AUTOSAR, the JasPar is a consortium run primarily by Japanese companies, which also has other focuses

Page 9: The data defined-vehicle_architecture

Short summary…Growing importance of Information Technology in Automotive

1886Benz Patent Motor Car

2016New Mercedes-Benz E-Class

Product 0% IT

Research & Development

Calculation support

Production 0%

Marketing & Sales 0%

Aftersales 0%

Administration Calculation support

Connected Product >60% (Software)

Research & Development

>70% (Computer-Aided Engineering)

Production >60% (Computer-Aided Manufacturing)

Marketing & Sales >40% (Internet)

Aftersales >30% (Diagnostics)

Administration >70% (HR, Finance, Procurement)

Photos: Daimler AG

Digital Transformation

of the product and supporting processes

Vehi

cle

Arch

itect

ure

Ente

rpris

e Ar

chite

ctur

e

Page 10: The data defined-vehicle_architecture

Agenda

Ø Software-defined vehicles surrounded by historical structuresØ The mobility revolution shifts the vehicle to a software-defined serviceØ Critical business competencies in a globally transforming digital ageØ Fundamental challenges to master data-defined vehiclesØ Outlook of a data-driven architecture for mobility as a service

Page 11: The data defined-vehicle_architecture

How has the car changed in a full development cycle since 2007?Too many improvements to summarize all…

Is now really software or still hardware driving the new vehicle design?

Source: ITQ GmbH (2014) Kompetenz in Mechatronik. München https://www.itq.de/files/itq_unternehmensbrosch_r e_onl ine.pdf

1970 1980

Functio

ns

SoftwareElectronics

Mechanics

1990 2000 2010 2020

0%

10%

20%30%

40%

50%

60%70%

80%

90%

100%

Page 12: The data defined-vehicle_architecture

How has the mobile, mobility and IoT changed since 2007?The smartphone is a software-defined key to mobility!

iPhone (1st generation)first released June 29, 2007

iPhone 6first released Sept 19, 2014

Creating new products and business models

Driving engagement and customer experience

Accelerating advances in technology…are transforming every part of business

AdvancedanalyticsProductlifecycleCloudPervasiveconnectivityEmbeddedsensors

New hardware landscape defined completely by software! The automotive industry is still not there.

Page 13: The data defined-vehicle_architecture

…because the nature of the consumer is changingGeneration 2010 2020 Grown up Defines Invent

Traditionalist(born <1946)Silent Generation

4% 1% Books Fax

Baby Boomers(1946-1964)Growth Economies Generation

38% 22% TV PC

Generation-X(1965-1976)Tales for an Accelerated Culture

21% 20% PC Mobile Phone

Millennials(1977-1997)Digital Natives (Gen-Y)

37% 50% PC & Internet Google & Facebook

Gen-2020(born > 1997)Hyper connected

0% 7% Mobile Media iPhone Apps

Closed InnovationInnovation Network with

the whole Business Eco SystemOpen Innovation with

Business Partners

Hardware-defined Innovation

Traditionalist

Baby Boomers

Generation-X

Millennials

Gen-2020

Software-defined Innovation

Page 14: The data defined-vehicle_architecture

A new value network is evolving that is defined by software and data

Consumer

OEM

The HistoryHistorically the Dealer-to-Consumer

relationship, supported by the Business-to-Dealer relationship

have been the key relationships in the automotive industry.

The Opportunity1.Digital technologies will enable OEMs to establish a much closer customer relationship.

2.In addition the “Connected Car” opens up new “Vehicle to Consumer” (V2C) and “Vehicle to Business” (B2V) relationships.

DealerVehicle

B2D

D2CV2C

V2D

B2V

B2C

Tier 1B2B

B2B2C

Makeandsell g SellandmakeProduct-centricity g Customer-centricityOutput g PerformancesTransaction g RelationshipValuedelivery g Valueco-creationCompetition g Co-supplyValuechain g Valuenetwork

MiragliaandDavies2009

Page 15: The data defined-vehicle_architecture

Example Tier 1 Supplier is changing their position in the value chain

Source: Bosch

Page 16: The data defined-vehicle_architecture
Page 17: The data defined-vehicle_architecture

Short summary...Short term aim is to enable services in the vehicle as a deviceLong term aim is to enable the vehicle as a personalized service space

The internet is an institutionof the connected vehicle

Vehicle is an integral part of thecustomer’s personal network

Differentbusiness competences

Differentbusiness models

Hardware-drivenAUTOmobile Software-driven autoMOBILE

Page 18: The data defined-vehicle_architecture

Agenda

Ø Software-defined vehicles surrounded by historical structuresØ The mobility revolution shifts the vehicle to a software-defined serviceØ Critical business competencies in a globally transforming autoMOBILEØ Fundamental challenges to master data-defined vehiclesØ Outlook of a data-driven architecture for mobility as a service

Page 19: The data defined-vehicle_architecture

Five Key Challenges

Incompatible Standards3Fundamental Shifts in

Business Models2Unprecedented Data Volumes1

New Privacy Landscape5Entirely New Security

Threats4

• Sensors generating new kinds of data, as well as volumes 1000’s of times higher than not connected vehicles.

• Big data and machine learning required to complement traditional reporting and analytics.

• One-time purchases being transformed into ‘pay as you grow’ long term revenue streams.

• Traditional manufacturing and place-based businesses must become digital-centric organizations.

• Proliferation in competing platforms and incompatible standards raises costs and complexity, security risks, and time-to-market for data-driven innovators.

• Collecting physical world data on people and objects.

• Market is slow grasping implications - stiffer regulations are likely.

• Unknown devices connecting vehicles.

• Automobiles and connected plants are under growing attack.

Page 20: The data defined-vehicle_architecture

New and emerging technologies will combine to transform industries

Industries will converge

Ecosystems will emerge

Value chains will fragment Margin

Consumer experience

Marketing and sales

Outbound logistics

Design and operations

Inbound logistics

Consumer experience

Marketing and sales

Outbound logistics

Inbound logistics

Outbound logistics

Operations Specialist

Inbound logistics

Outbound logistics

Inbound logistics

Healthcare

Distribution

Electronics

Retail Outbound logistics

Operations Inbound logistics

Marketing and sales

Operations M

Operations

M Consumer experience

Marketing and sales

Marketing and sales

M

M

Consumer experience

Consumer experience

Source: IBM Institute for Business Value – Digital Reinvention

Page 21: The data defined-vehicle_architecture

The value chain is changing

Development Production Sales After-salessupport

Digitalizationoftheindustry:AmovefromtheAUTOmobile totheautoMOBILE

Core processes of the classic business model in the automotive industry

Procurement& production

Salesanddigitalaccess

Digitalproduct

integrationValue-addedservices

Core processes of the business model in the mobility industry

AUTOmobile in order to emphasize ‘Auto’ – the German word for car

autoMOBILE to emphasize the mobility of travelling from one place to another

Page 22: The data defined-vehicle_architecture

Today, 89 business competencies in the automotive industry

Corporateleadership

Research &development

Procurement&inboundlogistics Production Marketing &

communicationSales &

outboundlogistics Financial service After-salessupport Humanresources Quality Finance &controlling Infrastructure Corporate

supportservice

Leadershipdomain

Corebusinessdomains

Administrationdomains

Supportdomains

Planning&managementsystem

Internalcontrolsystem

Reporting&indicators

Accounting,f inancialstatement

Treasury

Financial marketcommunication

Goals, values,principles

Corporatestrategy

Business&processstructure

Integrity& law

Risks& f inance

Safety &security

Corporatedocumentation

Environment

HRmanagement& process

Humanresourcepolicy

HRplanning&organisation

Operationcontrol

Evaluation

Entry&exit

Operation&development

Administration&remuneration

Understandingof quality

Quality planning

Qualityimprovement

Qualityevaluation

Performanceevaluation

Quality assurance

Problem and error processing

Qualitydocumentation

Planning,requirement,change

Research &pre- liminarydevelop.

Standard,method,process

Testing &validation

Concept,design,constructionspace

Development &engineering

Productdata&documentation

Procurementstrategy

Logisticsplanning&management

Supplierrelationship

Supplierevaluation

Purchaseawarding& contract

Productionsupply

Procurementoptimisation

Productionplanning&management

Equipmentplanning

Productionassurance

Series preparation

Manufacturing

Assembly &intralogistics

Corporatecommunication

Corporate&brandidentity

Marketingconcept

Execute

Control

Direct

Market analysis &success evaluation

Marketingmeasures

Editing&Proofreading

Media archive

Productionprocess&simulation

Sales strategy& client

Sales, demand,stock

Distributionsystem

Sales performance

Qualif ication,quote,contract

Order&distribution

Acceptance &documentation

Distributionoptimisation

Financial servicestrategy

Guideline, process,risk

Evaluation&sustainability

Performancemeasurement

Financial servicescontract

Bank& credit

Insurance

Customervoice

Connectedvehicle

Customer&vehicle data

Productmonitoring

Warranty&goodwill

Standard,equip-ment,information

Locationplanning

Facility &sitesafety

Equipment&supply

IT operations

Knowledge&ideas

Law& regulations

IT development&documentation

Assistance

IT planning

Project,portfolio,process

Page 23: The data defined-vehicle_architecture

Business competencies of the changing business architecture for the autoMOBILE value chainPrimary focus on building up digital and mobility competencies

Corporateleadership

Procurement&inboundlogistics

Phy.production&outboundlogistics

Marketing &communication

Sales &digital access Financial service Digital productintgr.&

value addedservic Humanresources Quality Finance &Controlling CorporatesupportserviceInfrastructure

Leadershipdomain

Corebusinessdomains

Administrationdomains

Supportdomains

Planning&managementsystem

Internalcontrolsystem

Reporting&indicators

Accounting,f inancialstatement

Treasury

Financial marketcommunication

Goals, values,principles

Corporatestrategy

Business&processstructure

Integrity& law

Risks& f inance

Safety &security

Corporatedocumentation

Environment

HRmanagement& process

Humanresourcepolicy

HRplanning&organisation

Operationcontrol

Evaluation

Entry&exit

Operation&development

Administration&remuneration

Understandingof quality

Quality planning

Qualityimprovement

Qualityevaluation

Performanceevaluation

Qualityassurance

Problem and error processing

Qualitydocumentation

Planning,requirement,change

Procurementstrategy

Logisticsplanning&management

Supplierrelationship

Supplierevaluation

Purchaseawarding& contract

Productionsupply

Procurementoptimisation

Productionplanning&management

Equipmentplanning

Productionassurance

Engineering, seriespreparation

Manufacturing

Assembly &intralogistics

Corporatecommunication

Corporate&brandidentity

Marketingconcept

Execute

Control

Direct

Market analysis &success evaluation

Marketingmeasures

Editing&proofreading

Media archive

Productionprocess&simulation

Sales strategy& client

Sales, demand,stock

Distributionsystem

Sales performance

Qualif ication,quote,contract

Order& personalisation

Acceptance &documentation

Distributionoptimisation

Financial servicestrategy

Guideline, process,risk

Evaluation&sustainability

Performancemeasurement

Financial servicescontract

Bank,credit, paymentportal

Insurance

Customervoice&contact

NetworkEcosystem

Customer&vehicle data

Productmonitoring

Warranty&goodwill

Standard,equip-ment,information

Locationplanning

Facility &sitesafety

Equipment&supply

IT operation

Knowledge&ideas

Law& regulations

IT development&documentation

Assistance

IT planning

Project,portfolio,process

Vehicle f leet& mobilityservice

Technology&development

Research &pre- liminarydevelop.

Standard,method,process

Testing &validation

Concept,design,constructionspace

Development

Productdata&documentation

Page 24: The data defined-vehicle_architecture

…further detailsThe Mobility Revolution in the Automotive Industry: How not to miss the digital turnpike!

The Internet of Things, Cloud Computing, Connected Vehicles, Big Data, Analytics – what does this have to do with the automotive industry? This book provides information about the future of mobility trends resulting from digitization, connectedness, personalization and data insights. The automotive industry is on the verge of undergoing a fundamental transformation. Large, traditional companies in particular will have to adapt, develop new business models and implement flexibility with the aid of appropriate enterprise architectures. Transforming critical business competencies is the key concept. The vehicle of the digital future is already here –who will shape it?

http://www.amazon.co.jp/dp/4627486316http://www.amazon.com/dp/3662477874http://www.amazon.com/dp/3662447827http://www.springer.com/us/book/9783662477878http://www.springer.com/de/book/9783662447826

Page 25: The data defined-vehicle_architecture

Agenda

Ø Software-defined vehicles surrounded by historical structuresØ The mobility revolution shifts the vehicle to a software-defined serviceØ Critical business competencies in a globally transforming autoMOBILEØ Fundamental challenges to master data-defined vehiclesØ Outlook of a data-driven architecture for mobility as a service

Page 26: The data defined-vehicle_architecture

Potential Mercedes services defined 2009 – Common is data

Source: IBM Academy of Technology and Daimler AG

•GPSauge (Apple)•FloatingCarData•Route-Optimization•“Genius” Navigation

Consumer- Business-Platforms

Auto Mobility Platform

defined bydata

Smart-(Home & Business) Workplace

•Mail, Message•Business-Office Connect•Video-Conference•Private Storage•Music, Photos

• Face-Book• Twitter• Apple

(Trapster)• Skype• ….

• Internet Search• Maps• Entertainment (Music, Books,

Videos)• Video-Conference• Lexica, Travel-Guide

Social Networks

Automotive Services

Navigation Services

•Down-Stream data•Upstream data•Device-Integration•Secure connect

Apple

• CarBook (FaceBook)

• Driver-Services• Owner-Services• eHandBook• Diagnose-Service• Taxi/Bus-Services• Fleet-Services

Open Development Architecture• Apple, Google,

Microsoft• Mobile Device Support• Open Auto Architecture• Test & Dev Environment

Communication• Stable Internet-Connect• Car2Car Network• Voice2Text• Mobile Devices (iPhone)• WiFi Home Connect

Commercial• Accounting Service• Billing on Demand• Advertising• Marketing (Genius)

Mercedes Vehicle Connect

Page 27: The data defined-vehicle_architecture

Technologies & data trends which were NOT discussed in 2009

Source: IBM Institute of Business Value

Provides an understanding of the interest, attitudes and expectations consumers will have for future mobility solutions

Page 28: The data defined-vehicle_architecture

June 9th, 2016 – Daimler Chief Executive Dieter Zetsche andUber Chief Executive Travis Kalanick were interviewed together

Photo: dpa

The challenge: How is Uber organized? How is Daimler organized?Where is the Chief Digital Officer aligning the product integration to a data-defined vehicle?

Now roughly equal in value (stock market capitalization):German luxury car maker Daimler $70BSilicon Valley ride-sharing firm Uber $62.5B

Daimler AG (Karl Benz) invented the first automobileUber disrupted taxi business through new mobility services

Uber founded 2009Daimler predecessor Daimler-Benz founded 1926(1883-1926 Benz & Company, 1890-1926 Daimler Motoren Gesellschaft AG)

Page 29: The data defined-vehicle_architecture

Relevance of digital experiences is continuously increasing

Source: BMW

The challenge:Where is the Chief Digital Officer aligning the product integration to a data-defined vehicle?

Page 30: The data defined-vehicle_architecture

Short summary…The Chief Digital Officer aligns the digital product integrationto a data-defined vehicle

The Chief Data Officer playbookCreating a game plan to sharpen your digital edge IBM Institute for Business Value

IBM Institute for Business Value, “The New Hero of Big Data and Analytics, The Chief Data Officer”, June 2014

Page 31: The data defined-vehicle_architecture

Agenda

Ø Software-defined vehicles surrounded by historical structuresØ The mobility revolution shifts the vehicle to a software-defined serviceØ Critical business competencies in a globally transforming autoMOBILEØ Fundamental challenges to master data-defined vehiclesØ Outlook of a data-driven architecture for mobility as a service

Page 32: The data defined-vehicle_architecture

Computers and the brain are different and complementary

10 Hz, parallel, high fan-out

10 mW/cm2

Integrates memory, computation, communication

~5 GHz, sequential, linear

100 W/cm2

Separates memory, computation, communication

Page 33: The data defined-vehicle_architecture

Eras of computing

SystemIntelligence

1900 1950 2011

Tabulating

Programmable

Cognitive

PunchcardsTimecardreaders

DiscoveryProbabilisticBigDataNaturallanguageIntelligentoptions

SearchDeterministicEnterprisedataMachinelanguageSimpleoutputs

© 2015 International Business Machines Corporation

Page 34: The data defined-vehicle_architecture

The digitalization is changing the product architecture in 3 different data areas to make it more intelligent

Drive architecture

Ecosystem

Photos: BMW, Daimler

Life architecture

iPhone

iCloud

Source: IBM Academy of Technology and Daimler AG

•GPSauge (Apple)

•FloatingCarData

•Route-Optimization

•“Genius” Navigation

Consumer- Business-Platforms

Auto Mobility Platform

defined bydata

Smart-(Home & Business)

Workplace

•Mail, Message

•Business-Office Connect

•Video-Conference

•Private Storage

•Music, Photos

• Face-Book

• Twitter

• Apple

(Trapster)

• Skype

• ….

• Internet Search

• Maps

• Entertainment (Music, Books,

Videos)

• Video-Conference

• Lexica, Travel-Guide

Social Networks

Automotive Services

Navigation Services

•Down-Stream data

•Upstream data

•Device-Integration

•Secure connect

Apple

• CarBook

(FaceBook)

• Driver-Services

• Owner-Services

• eHandBook

• Diagnose-Service

• Taxi/Bus-Services

• Fleet-Services

Open Development Architecture

• Apple, Google,

Microsoft

• Mobile Device Support

• Open Auto Architecture

• Test & Dev Environment

Communication

• Stable Internet-Connect

• Car2Car Network

• Voice2Text

• Mobile Devices (iPhone)

• WiFi Home Connect

Commercial

• Accounting Service

• Billing on Demand

• Advertising

• Marketing (Genius)

Mercedes Vehicle Connect

Apps

Page 35: The data defined-vehicle_architecture

Data-defined Vehicle: Risks regarding endangering reputation / brand valueGoogle Executive Chairman Eric Schmidt said:“Google’s policy is to get right up to the creepy line but not to cross it”

Photos: BMW

PRODUCT INSIGHTS

CONSUMER DATA INSIGHTS

Traditional brand values: comfort, safety, longevity, reliability, …

Source: BMW – Redefining Premium Brand IdentityPhotos: Google

Vehicle data

Customer data

Drivers

Vehicle as a personalized space

Patent 8.630.897Transportation-aware physical advertising conversations

Why do I need to own a car?

Why do I need parking?

Why do I need a separate vehicle insurance?

Getting from A to B might be free of charge

Can I change the individualization of the car per ride?

Driving as a service

Safety is critical

Driving remains with the carEngineering challenge

Advanced Driver Assistance Systems

Durable & reliableengines

Page 36: The data defined-vehicle_architecture

How will a data-defined vehicle be produced?“Road Ready 3D-Printed Car”

Photo: Local Motors

Page 37: The data defined-vehicle_architecture

OEM need to create the data-defined vehicle themselves or together with new types of partners

AggregatedDataSharedDataManagementPlatform

Vehicle Insights Driver Insights Environment Insights Infrastructure Insights

SharedAnalyticandFunctionalServices

Offering1 Offering2 Offering3 Offering4 Offering6 Offering7

OEMs Ecosystem GovernmentOffering5

Annonymized &Opt-InData

Connected VehicleDataOEM1

Annonymized &Opt-InData Annonymized &Opt-InData

Connected VehicleDataOEM2

Connected VehicleDataOEM3

Offering1 Offering2

OEM

DedicatedDataManagementPlatform

Connected VehicleDataOEM

DedicatedAnalyticandFunctionalServices

Customer Experience(Convenience, seamless

interaction, usability, emotions)

Mobility Services(Car sharing, parking, taxi, ride sharing, public transport, etc.)

Connected Vehicle(Location, connectivity, information,

personalization)

Ecosystem(Notifications, road enforcement, variable speed limits, toll, etc.)

Page 38: The data defined-vehicle_architecture

Short summary…Guiding principles of a data-driven architecture to providemobility as a service in a cognitive era

AUTOmobile autoMOBILE

business rely on selling an integrated product business designed for relationship to consumer

designed by market designed to be globally available

build as an integrated system continuously integrate services

one product lifecycle three separate lifecycles

defined by the mechanical engine defined by the personal space to overcome spatial distances

capture data for engineers to improve product data designed to serve consumers

real vehicle bill of material virtual vehicle bill of material

components and systems programming machines are learning

Page 39: The data defined-vehicle_architecture

Dr. Sebastian Wedeniwski

IBM Distinguished EngineerCTO Global Industrial Sector

[email protected]