Autonomous Vehicle Ecosystem Analysis & Opportunities€¦ · Autonomous Vehicle Ecosystem Analysis & Opportunities April 2019. 2 01 Autonomous Vehicle Overview ... • Intel acquired

Source : DRAUP

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1

Autonomous Vehicle

Ecosystem Analysis &

OpportunitiesApril 2019

2

Autonomous Vehicle Overview01

Technology Spend Analysis02

Autonomous Vehicle Adoption03

This section provides an overview of :

AGENDA

Bay Area–Deep Dive04

Autonomous vehicle overview and its

potential

Disruption in Autonomous Vehicles:

o Tech Giants

o Partnerships & Consortiums

o Acquisitions & Start-ups

Impact of AV on different industries

Future of AV

Growth Drivers of AV

New Emerging business models

Top Companies Deep Dive05

Partnership Opportunities06

Source : DRAUP

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3

Overview: Autonomous Vehicles (AV) have huge potential to impact global economies, markets and industries

$7 Trillion Potential savings in the areas of fuel efficiency, cost of life and productivity

gains enabled through AV based business models in US by 2025

$250 Billion Estimated worth of Autonomous Vehicle Industry by 2025

8 MillionEstimated Level 3 and higher AV by 2025

3 MillionPotential Job loss in US by 2025

17%Expected AV market share as percentage of total worth of Auto industry, in 2025

Note : DRAUP- The platform tracks engineering insights in the automotive ecosystem using our proprietary machine learning algorithms along with human curation. The

platform is updated in real time and analysis is updated on a quarterly basis

Source : DRAUP

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Disruption in AV: Penetration of Tech giants in AV space has created an intense competition for traditional automotive players that enables multiple disruptions in the ecosystem

Tech Giants

Penetration

in AV

Consortium &

Partnerships

Acquisitions of

Start-ups

Case Studies

1

Disruption in AV

2

3

Note : The platform tracks real time insights and developments in the Autonomous Vehicle Ecosystem such as global engineering footprint, product launch,

Leadership Announcements, M&A, among other essential insights

Above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April, 2019

Tech giants are penetrating the AV ecosystem due to its prominent potential and impact. Tech giants are investing with OEMs, Tier-1 suppliers and start-ups to offer services and solutions

Autonomous vehicle development has disrupted the traditional partnership trends in auto industry and has brought in multiple industry giants together working in consortiums

AV based ML and Sensor startups have attracted phenomenal investments from the giants who are looking to win the Autonomous vehicle race

• GM acquired Cruise to use the technology and talent to accelerate the process of developing AV. GM Cruise is also partnering with other startups and companies to deploy autonomous vehicles. It has collaborated with DoorDash which offers food delivery service

• Intel acquired Mobileye which develops computer vision and machine learning, data localization, localization and mapping for ADAS and autonomous driving.

• BMW collaborated with Intel and Mobileye to position itself in AV ecosystem. Followed by BMW, tier 1 suppliers and other OEMs like Delphi, Valeo, Magna, Toyota, Aptiv, Continental, Jaguar, and Audi have also joined the coalition.

• Google’s Waymo, self driving vehicle technology company has partnered with Tier-1 and OEMs like Magna, FCA, and Jaguar to offer full-stack autonomous vehicles.

• It is also setting up a factory in Detroit to build autonomous vehicles and is working with American Axle & Manufacturing to convert the existing factory

Source : DRAUP

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Penetration of industries in AV: New age solution providers in the areas of Semicon giants, Telecom, Cloud, and Mobility are bolstering the evolution of vehicle autonomy

Silicon

Evolution

Internet

Age

Smart

Mobility

Automotive 1.0

Automotive Ecosystem has been disrupted through digital mega innovations

0

1

2

3

4

5

6

7

8

9

10

2003 2006 2009 2012 2015 2019

Note: Each unit on Y-Axis represents a

single type of ecosystem player

• Traditional suppliers such as

Bosch and TomTom have enabled

advanced vehicle navigation and

monitoring through specialised

telematics equipment

• Semiconductor giants such as Intel

and Nvidia have developed

specialised SoCs for processing

and computing large amount of

vehicle datasets

• Tech Mafia have transformed the

vehicle into a software computing

system with capabilities to take

autonomous decisions

• New age suppliers have built

capability into Advanced vehicle

control using deep learning,

sensor systems and connectivity

services

• The current Autonomous Vehicle

ecosystem has been rapidly growing

through a rich infrastructure of

network, cloud & insurance

providers enabling new age

business models

Ecosystem maturity trend during last 15 years

Note: The timeline above is illustrative of landmark events in the autonomous vehicle ecosystem during the last 15 years. The list above is non exhaustive

DRAUP Engineering Module: The platform tracks real time insights and developments in the Autonomous Vehicle Ecosystem such as global engineering footprint, product

launch, Leadership Announcements, M&A, among other essential insights

Num

ber

of

pla

yers

in t

he A

uto

motive E

cosyste

m

Insurance Providers: Usage based Insurance

Cloud Platforms: Data Management & Security

New Age Suppliers: ADAS Systems & Components

Data Services: Connected Car

Mobility Services: Alternative Ownership

Tech Mafia: Car OS, HMI

Consumer Electronics: Infotainment OS

Semiconductor Giants: SoC Processors

Traditional Suppliers: Telematics equipment

Telecom: 5G Infrastructure

Source : DRAUP

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6

Future of AV: Companies are accelerating commercialization of level 3 & 4 autonomy to lead the technology race

The league of 5 are well

positioned and future-ready, basis

their current R&D investment or

via virtue of their acquisitions

and/or partnerships

GM, Ford, and Waymo have

committed to attain Level 5

automation capabilities whereas

Intel, Tesla and Bosch have

envisioned Level 4 automation by

2021

These players have been

exploring a diverse set of GTM

strategies such as partnerships

with mobility providers, fleet

management and personal

ownership model to launch their

first commercial Autonomous

Vehicles by 2021

Note : 1-2021 AV Readiness Index: Function of % R&D Talent in Autonomous Vehicle technology, External Acquisitions and Investment, patents and partnerships;

2- Function of current leadership Outlook and commitments for autonomous vehicle launch in 2021. Automation Levels as outlined by SAE updated as of 2019;

The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019

Partial automated

Parking Traffic jam

assistance

Fully automated

vehicle

2

Partial

Automation

Highway chauffeur

Traffic jam chauffeur 3

Conditional

Automation

Highway autopilot

Including highway

Convoy Parking

garage pilot

4

High

Automation

5

Full

Automation

Targeted Levels of automation by

20212

Intel

WaymoGeneral Motors Ford

Volkswagen

Daimler

BMW

Nvidia

Argo.ai

Baidu

Tesla

Nissan-Renault Toyota

Bosch

Continental

Volvo

Delphi

Zoox Automation

nuTonomy

Uber

Apple

PSA

Autoliv Valeo

Nauto

2021 AV Readiness Index1

Source : DRAUP

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AV Growth Drivers: Liberal government policies, technology advancement and ecosystem openness to co-innovate are the key enablers driving autonomous vehicle innovations

Open Ecosystem

Decline in cost of computing and advancement

in processing power have enabled processing

large volume and variety of data such as image,

voice, text, etc.

Advances in machine learning have allowed

computer vision to compute unstructured data

and distinguish objects on the road and build 3-D

maps of the surrounding area

Deep learning and artificial intelligence have

led to better algorithms for pedestrian detection,

traffic control and other automation features.• Collaborative and open innovation- Top player Tesla

open-sourced its patents while Baidu and Lyft have

open software platforms

• Competitive landscape- Entrance of technology

mafias which are building a competitive environment in

AV through their strong capability in software platforms

• R&D partnerships between universities and

automakers- Toyota partnered with University of

Michigan for autonomous innovation.

Drivers for Autonomous

Vehicle

Technology advancement1

3

Political, legal and social drivers

State legislations related to autonomous vehicles

have gradually liberalised . In 2019, 29 states

have introduced legislation related to autonomous

vehicles in USA, allowing testing of autonomous

fleets under certain specified conditions

Extensive government investment in key

countries- US and UK governments plan to invest

$4Bn and £38Mn over the next 5 years, on

driverless cars technology

Projected 20% overall reduction in road

accidents- Elimination of drivers is expected to

reduce driving accidents caused by human error.

2

Note: Autonomous Vehicle regulations have been verified from reports published by Department of Motor Vehicle, California and other state regulatory bodies in respective geographies

The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on Feb, 2018

Source : DRAUP

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New Business Models: Shared service model and fleet owned taxis would be the first level of AV integration globally

Business Model Description Examples Intensity of Autonomy

Individual Owned Shared Service

Models

Privately owned vehicles provide

ride hailing/sharing service when

owner is not currently using it.

Uber, Lyft

Fleet Owned Taxis

Service company operates fleet of

autonomous vehicles to provide

mobility services

Waymo, NuTonomy, Lyft

Vehicle LicensingConsumers pay owner for the use

of vehicleCustomizable rental programs

AV–enabled software packagesServices and software that unlock

full autonomous capabilitiesProductive software suites

Retrofit

Package of Hardware and Software

to retrofit fully autonomous

capabilities on selected vehicles

Comma One

Emerging

Models

Potential

Models

Service and public utilization based models to dominate while traditional ownership model to diminish

Note: Autonomous Vehicle models have been verified from reports published by Department of Motor Vehicle, California and other state regulatory bodies in respective geographies.

The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on Feb, 2018

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AGENDA


Technology Spend Analysis:

o In-house Engineering Spend

o External Technology Spend

Engineering Spend Analysis:

o Top Companies

o Industry

o Geography

o Technology Segments

Geographical Talent Analysis

AV Ecosystem Analysis and Top 25

Companies mapping

Analysis of acquisitions and investments by

top companies Top Companies Deep Dive05


Source : DRAUP

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AV Technology Spend: AV ecosystem players are fuelling the technology spend by making investment in-house or externally for faster development and deployment of AV capabilities

Total AV Technology Spend

by top 25 players (2018):

$32–34 Bn

Autonomous Vehicle In-house1

engineering spend

$10-11 Bn Engineering spend

globally on

autonomous

technologies as of

2018

Autonomous Vehicle External2

technology spend

$22-23 Bn AV –Acquisition

,Corporate VC Spend

& Partnership as of

2018

• Engineering spend by autonomous vehicles includes in-house investments like talent, solutions, platforms, and services made by the OEMs, Tier-1suppleirs, tech giants to enhance the autonomous technologies for faster deployment of vehicles

• Major players investing in engineering spend include:

• Semicon giants, OEMs, tech giants are investing or acquiring in start-ups to leverage AV innovations. For example, Google acquired Waze, GM acquired Cruise, Intel acquired Mobileye to develop AV solutions and capabilities

• Major players include acquiring or building consortiums:

Note: AV In-house Technology spend: includes salaries and compensation along with spend on software, platforms and hardware tools required to develop In-house capability;

External Technology Spend: Consists of investment in Autonomous Vehicle and related technology areas through Acquisitions, Partnerships and Corporate Venture Arms;


Source : DRAUP

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11

$10–11

BnIn-house

Engineering

Spend by top

25 companies

~31%

~13%

R&D spend

by top 5

players

~56%

AV In-house Engineering spending analysis (2018) Key Insights

R&D spend

by next 10

players

Note: The numbers above are rounded-off, so they might not add up to 100%

R&D spend

by next 10

players

Note: 1-Technology spend includes employee compensation and related expenses along with spend on software, platforms and hardware tools required to develop In-house

capability; The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019

Engg Spend by Top Companies: Engineering spend by the top 5 players is largely focused on developing full stack solutions, robust sensor systems and advanced computing platforms for vehicle control

• Majority of the in-house engineering spend by players is

being invested in Autonomy. Top companies have already

invested billions in development of autonomous vehicles

like Ford is investing $5.4 billion in driverless cars and GM

has already invested $1.5 billion.

• GM, Tesla, Ford, Waymo, and Uber are the top players in

the autonomous vehicles ecosystem and are highly

investing to deploy the AV. Companies like GM and

Waymo are building R&D centres and assembly plants to

build AV

• Primarily, the companies are focusing on ride-sharing and

delivery over individual ownerships.

• Top players are majorly focusing on Electric vehicle AV as

compared to gasoline EV due to less moving parts and

maintenance costs

Source : DRAUP

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AV In-house Engg Spend by Industry: Tech Mafia and the Semiconductor giants are spending heavily alongside Automakers to develop strong Autonomous Vehicle capability

Others* include Telecom, Data Services, Insurance and other AV related infrastructure providers

Note: 1 Include investments on In-house R&D spend on engineering salaries and infrastructure support in AV and related technology areas;

DRAUP Engineering Module – Include AV companies across major geographies such as US, Canada, Israel, Europe, China and India.

Coverage may be limited in China and other south east APAC regions

AV In-house Engineering Spend by Industry Verticals (2018)

<5%

7-8%

10-12%

14-16%

25-27%

34-36%

Others*

Automotive Start-ups

Tier-1 Suppliers

Semiconductor

Tech Mafia

Traditional OEMs

In-house

Engineering

spend1 on AV as of

2018

$10–11

Bn

• OEMs have strategic focus on developing critical

safety and driving systems in-house. OEMs such

as Daimler, BMW and Ford are establishing

partnerships with technology providers to

collaboratively develop software capability for vision

and perception systems

• Semiconductor giants such as Intel and Nvidia have

developed specialised Autonomous Vehicle SoCs

for processing and computing using ML algorithms

• Tech Mafia giants are differentiating through strong

AI capability leveraging deep learning algorithms

required to make advanced driving systems safe

and predictable

• Tier-1 suppliers such as Bosch, Delphi and

Continental are major players providing Sensor

Systems such as Lidar, Radar, Cameras, and

Ultrasonic sensors

• Full stack ADAS providers is the most funded

segment . Nauto, Argo AI and Drive.ai are the top

players investing in full stack-Autonomous Vehicle

solutions

Note: The numbers above are rounded-off, so they might not add up to 100%

Source : DRAUP

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AV In-house Engg spend by geography: Majority of engineering investment in AV ecosystem is consolidated in US due to the supporting regulations by NHTSA

USD 10-11 BnGlobal AV In-house Engineering Spend by Top 25 players (2018)

Americas

~49% Europe

~30%

APAC

~21%

OEMs, Tech giants, Tier-1 providers

have chosen US, UK, Germany,

China and India as major hotspots

for engineering centres

Majority of the players are focusing

in US for the development of AV

solutions due to support from the

NHTSA and technological

advancement. US have also

introduced regulations for self-driving

vehicles on public roads and issued

autonomous testing permits.

California has allowed operation of

fully autonomous vehicles with no

driver on public roads

Autonomous Vehicles spend in

APAC region is growing due to high

autonomy activities by Chinese

players like Baidu and SAIC.

Shanghai has issued its first self-

driving licenses in China

Investment focus by Geography

Note: Geographical split indicates only the prime Autonomous Vehicle R&D locations. Primary locations include US, Europe, India and China; The above analysis is based on the

DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019

Source : DRAUP

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14

~3%

~6%

~7%

~9%

~13%

~15%

~47%

Singapore

Canada

Israel

UK

China

Europe

USA

Geographical split by AV Engineering Headcount

Note: Geographical split indicates only the prime Autonomous Vehicle R&D locations. Primary locations include US, Germany, France, Canada, China, UK, and Singapore ; The

above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019

40,000–45,000

Global Autonomous Vehicle Engineering Headcount

Note: The numbers above are estimated R&D headcounts in respective locations updated as of 4th quarter of financial year 2018

Geographical Talent Split: While the AV talent footprint is distributed across global locations, US and Europe are the hotspots with nearly 60% of talent consolidated between these two regions

Source : DRAUP

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15

20 %Sensors

Vision based perception

30 %

Computing & Vehicle Control

10 %HMI/ UI-UX

Network, Connectivity & Security

USD $ 10-11 Bn

Technology Segments

3D Mapping/ Localization

Lidar, Radar, Odometry and Ultrasonic sensor

systems for lane centering, path planning and V2V

communications

Using Neural Networks, the vehicle brain analyses all

sensor input and operates steering, accelerator and

brakes for critical driving decisions such as collision

warning, cruise control and advanced safety

HMI is crucial to optimally support the driver in the

monitoring and remotely control autonomous cars and

to give access to live sensor data and useful data about

the car state, such as current speed, engine and gear state

24 %

11 %

5 %

High resolution HD Maps enable precise lateral and

longitudinal positioning for vehicle localization

INSIGHTSTotal AV Engineering Spend1

Computer Vision systems use advanced deep learning

to aggregate, classify and identify critical

environment data such as obstacles, pedestrians, traffic

signs etc.

Advanced vehicle connectivity infrastructure to enable

communication between vehicles and environment

(V2V, V2X)

In-house Engg Spend by Technology Segments: R&D is focussed on developing core software capabilities, leveraging deep learning for computing, vehicle control and vision-based perception



Source : DRAUP

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AV Ecosystem: Two type of organisations are accelerating Autonomous Vehicle Ecosystem -In-house Innovators vs Collaborative Developers

Total R&D headcount in autonomous technology

Note: 1 Inorganic Growth Index: Function of investment in AV and related technology areas through Acquisitions, Partnerships and investment through Corporate Venture Arms;

2 Technology maturity Index: Function of maturity of technology across the AV stack of components, sub-systems and full-stack autonomous systems required to develop AV capability


• Start-ups and Tech Mafias have

been investing in Autonomous

Vehicle platforms and Vehicle

Operating Systems, leveraging their

strong software capability

• Key technology focus areas of

these companies are Deep

learning for vehicle control and

Computer Vision for environment

perception and sensing

• Semiconductor giants such as

Intel and OEMs such as BMW,

Toyota and GM have established

strong consortium to co-innovate

• These players have also acquired

many companies which offer full

stack Autonomous Vehicle

solutions. Some of the significant

acquisitions being Mobileye (by

Intel) and Cruise (by GM)

Collaborative Developers2

In-house Innovators1

Intel

Google- Waymo

GM-Cruise

FordVolkswagen

Daimler

BMW

Nvidia

Uber

Baidu

Tesla

Nissan-RenaultBosch

Continental

VolvoDelphi

Zoox Automation

nuTonomy

Argo.AI

OEMS Tier 1s Tech Mafias Semiconductor Auto Start-ups

AppleAutoliv

PSAValeo

Nauto

Low

High

High

Tech

no

logy

Mat

uri

ty I

nd

ex2

----

----

->

Inorganic Growth Index1 --------->

In-house Innovators

Autonomous Vehicle Capability & Investment Analysis

Toyota

1 Collaborative Developers 2

Source : DRAUP

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17

SEMICONDUCTOR OEM TECH MAFIA

~$18 Bn ~$3 Bn ~$1 Bn

$22–23 Bn

Total External investment spend to acquire AV capability

Top Acquisitions

AcquisitionCorporate VC Spend

Acquisitions and investments: Semiconductor giants and OEMs have been leveraging collaborative AV innovations and acquiring highly mature solutions to develop AV capability



Source : DRAUP

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18

Automakers

Mobility Services

Network, Security

and cloud

3D Mapping/

LocalizationHMI/UI-UX

Computing &

Vehicle Control

Network,

Connectivity Sensors

Vision based

perception

Software

Platforms

Hardware/

Processors

Technology

Suppliers

Services/

Operators

Tier-1s

Cloud based open

location platform;

provides mapping,

and traffic data Provides full stack

ADAS systems

Customized algorithms

of computer vision,

machine learning

Intel-Mobileye will provide computing

platform, sensing & localization expertise

Provides full stack ADAS system

Provides data processing, and

computing SoCs along with

Sensors and connectivity

Formed the Automotive

Edge Computing

Consortium with Toyota

to boost creation of maps

and ADAS technology

Ericsson and Toyota have

partnered for developing 5G

infrastructure for enabling

V2V, V2X communications

Connected car

application to connect

mobile to car

dashboard

BMW and Ford have collaborated with

ride sharing giants such as Lyft and

Uber respectively largely to mine

vehicle driving data

Bosch is co-innovating with

Nvidia for the AI based

software systems for its

sensor technology

Microsoft, Valeo & Renault

Nissan group partnered to

leverage Azure cloud platform

customization for data security,

connectivity and privacy

Acquisitions and investments: Automakers are thinking ahead and collaborating with Technology providers and disrupters to move beyond their traditional business segments

Note: The infographic above shows analysis done on specific companies. There are several other companies working towards Autonomous Vehicles


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AGENDA


Global and US AV adoption analysis

Miles driven by top companies in California



Source : DRAUP

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Autonomous Vehicles regulations by State and Central government organisations

Note: Autonomous Vehicle regulations have been verified from reports published by Department of Motor Vehicle, California and other state regulatory bodies in respective

geographies; The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019

Michigan

Japan

Israel

Legal for testing

prototype with

driver

Legal for testing

prototype on public

roads with driver

Legal for testing

prototype without

driver

Legal for testing

prototype on public

roads without driver

Semi autonomous

fleet services

allowed

Regulations

Passed

LOW HIGHAV* Adoption Index

AV*: Autonomous Vehicle

Michigan being a traditional automotive

engineering hub became the first state to

approve the latest autonomous technology

allowing automakers to test their

autonomous prototypes on public roads

even without a driver.

Governments of UK, Japan and Germany

are cautious about the safety of current

autonomous technology. Thus they have

taken proactive regulatory measures by

allowing testing only in the presence of

a driver.

Governments in geographies such as

Germany, UK and other European

countries are not able to develop a

concrete regulatory framework for

testing and assessing autonomous driving

because they face challenges in defining

ethical laws relating to responsibility in

accidents caused by fully autonomous

vehicles.

The Netherlands’ Council of Ministers

recently updated its bill to allow tests

without a driver. Shanghai issued its first

self-driving license, allowing automakers to

test their AVs on public rods.

California

China

Germany

Singapore

Netherlands

Florida

UK

Arizona

AV Adoption across globe: US states and several other nations are relieving the regulations around Autonomous Vehicle testing on public roads

Source : DRAUP

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21

Daimler

NVIDIA

Drive.ai

Renault…

Pony.Ai

Baidu

Nuro

Uber

Zoox

Aurora

Apple

GM Cruise

Waymo

Autonomous Test Miles Driven In California (2018)1

AV Miles Driven: Level 5 Autonomous Vehicles have Millions of Test Miles to complete before they can be Consumer Ready; Companies are investing in Simulation platforms

• Waymo and GM seem to be way ahead

of the competition when it comes to real

world tests but are way behind the

Industry Standard

• On-Road testing is a very lengthy

process that could take years to

complete. Hence, companies are shifting

their focus towards simulated testing

which can simulate all aspects of the

autonomous drive without posing any risk

to pedestrians or other motorists

• OEMs are still figuring out the right

balance of testing AVs in real world

scenarios and simulated environments

• Companies like Tesla, Apple and BMW

rely mostly on simulated testing of AVs

• Companies like NVIDIA, Electrobit,

Cognata currently provide Simulation

solutions for AV testing

• Testing through simulations also gives

the ability to test countless variations in

road conditions, scale and cost.

• Research done by RAND Corporation

suggests that autonomous vehicles need

to drive 11 billion miles in testing before

being ready for consumers while the

company with the highest autonomous

miles, Waymo has only completed 7

million miles in 10 years.

Note: 1-The data retrieved from the website of California DMV. The data reflects the number of test miles covered by AVs in the state of California from December 2017 to

December 2018.

Industry Standard

11 Billion Miles(to reach required safety levels as per industry consensus)

Miles to Go

10 Million of Autonomous

Test Miles since 2009

3 Million Autonomous

Test Miles driven since

2016

Miles of Autonomous Test Driving driven in 2018

AV Simulation

Testing Providers

Number of Autonomous

vehicles on road in California

• GM Cruise: 163

• Waymo: 125

• Apple:69

Note: Ford, Lyft and Tesla are top players in AV but have disengaged from California DMV Autonomous Vehicles

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AGENDA




Source : DRAUP

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23

55% 30% 15%

Innovators Followers Emerging Players

To invest $1 Bn in San Francisco over next

five years in AI and self-driving cars R&D

Invested $1 Billion in AI startup Argo AI;

Developed aDRIVE gaming environment for

autonomous test driving

6.5–7KBay Area

Google’s Core R&D team of ~1,000 engineers, located

in the Bay Area, is largely focused on developing deep

learning software capability for advanced vehicle control

and automation

Bosch has an autonomous driving solutions

center in Palo Alto. It partnered with Daimler to

launch automated valet parking system

Acquired HERE maps for 3D mapping

technology

VW works in partnership with Stanford

University for autonomous driving. Its

research lab -Volkswagen Automotive

Innovation Lab is located within the Stanford

University campus

Invested $14 Mn on the new expanded R&D facility

in California and plans to add 1,100 workers to it’s

new acquisition team at Cruise Automation

Uber poached around 50 researchers and engineers

from Carnegie Melon University’s Robotics Institute

to build its autonomous capability

Opened a new Automated Driving Group in

Silicon Valley and plans to invest $250 Mn on

self-driving tech via its Intel Capital investment

arm. Intel also has 3 other autonomous R&D

labs in Arizona, Germany and Oregon.

Tesla is building critical ADAS systems in-house and

leveraging partner network with Nvidia and Bosch for

autonomous hardware capabilities.

Note: Includes recent R&D initiatives and collaboration announcements/activities of the above mentioned players. List of emerging players non-exhaustive;


Autonomous Vehicle Engineering

Headcount in Bay Area

Bay Area Deep Dive: In Bay Area, Automakers have established AV innovation labs to collaborate with Tech Mafias and disrupters, and explore new AV enabled mobility solutions

24





AGENDA


Top leaders in the AV Ecosystem

Analysis of top leaders by:

o Positioning Strategy

o EV focus for AV

o Commercialization Roadmap

o Capability and prime acquisitions

across segments

Deep Dive analysiss of top leaders:

o Waymo

o GM

o Ford

o Uber

o Tesla



Source : DRAUP

25

25

• GM realised that to attain technology leadership in the industry EV focus is not enough.

• Failing to build AV expertise will create a technology dependence in future towards giants like Waymo (Google), Uber etc.

• GM’s out-of-the-box AV efforts are evident in their deployment strategy trying to monetize each level of Autonomy

Level 1Driver Assistance

Level 2Partial

Automation

Level 4High Automation

Level 5Full Automation

2012 2014 2016 2018 20202010 2022

Level 3Conditional Automation

Capitalize Level 5 capabilities to integrate

level 3 SuperCruise in Cadillac

Deploy Fleet of self-driving Bolt EVs for

ride-hailing service in US by 2019

Launched Semi-autonomous Cadillac CT6

equipped with self-driving system ‘SuperCruise’

Waymo & Uber skipped semi-autonomous levels

to focus on level 5 integration with OEMs

GM Tesla Ford Waymo Uber

Product focus Integration focus

Level 0No Automation

AV Positioning Strategy: OEMs like GM, Ford and tesla are trying to master each level of automation whereas, Waymo and Uber are working towards level 5 leadership



Source : DRAUP

26

26

AV focus in EV: Electric Autonomous Cars such as Hybrid, Plug-ins and Plug-in hybrids autonomous cars to cover the urban transportation landscape by the next decade

2016 2018 2020 2022 2025

Level 2 integration with Cadillac CT6

hybrid

Deploy Level 5 Bolt EV Fleets

Level 3 integrated Cadillacs

Test Level 5 in Jaguar I-Pace

Test Level 5 in Chrysler Pacifica

Partner with OEMs to deploy AV technology.

Test self-driving with a fleet of ford

fusion

Test Self-driving with fleet of Volvo

XC90

Partner with OEMs to deploy AV technology

Testing self-driving with a fleet of ford

fusion hybrids

Deploy self-driving with a fleet of ford

fusion hybrids

Integrated level 2 in tesla model S & X

Integrated level 5 capable hardware in Tesla Lineup

Activate Level5 in all models

through over-the-air updates (OTA)

58% of autonomous light-duty

vehicle models are currently

built over an electric powertrain

while a further 21% utilize a

hybrid powertrain, according to a

testimony submitted at the House

Energy & Commerce Committee.

Top drivers for Electric

Autonomous Vehicle adoption :

Regulatory restrictions

relating to gas-mileage

requirements.

Electric cars are easier for

computers to drive due to

fewer moving parts and

low maintenance.

Wireless charging

integrates seamlessly with

autonomy

Self driving cars to populate urban

areas first due to better availability

of charging stations. The US

Department of Energy lists around

48,000 such charging stations

across America.

Note: The infographic above shows analysis done on specific companies. There are several other companies working towards the automation of electric vehicles.


Source : DRAUP

27

27

Launch Level 5

and then establish

Level 3 dominance

Focus on Level 5

to establish AV

integration

leadership

Focus on Level 5

to establish AV

integration

leadership

Embed vehicles

with AV

capabilities and

deploy through

OTA updates

Skip Level-3 and

focus only on

level-5

2016 2018 2020 2023 2025

Deploy Fleet of Level-5 Bolt EVS

Level 2 Level 3 Level 4 or above

Level-2 “SuperCruise”

Integrate advanced “SuperCruise” in GM Lineup

Deploy Fleet of robot axis

Partner with automakers to deploy full stack AV solution

Achieve 7.0 million test miles to prove AV domination

Deploy Fleet of AV ride-hailing services

Partner with OEMs to deploy full stack AV

Test phase: Uber’s Self-driving ford fusion and Volvo XC90

Rollout Level-5 in Autopilot-2 embedded vehicles through OTA updates

Level-2 Auto-Pilot Model S & X

Level-5 hardware Embedded in to “AutoPilot-2” Tesla lineup

Level-2 integration Rollout Level-5 Self-driving Ford fusion for ride-hailing and door delivery services

AV Commercialization Roadmap: Companies like Tesla are planning to offer OTA updates that will transform existing models towards self-driving capabilities



• Waymo has driven nearly 7 million miles and is leading the competition of AV

• GM is planning to prove technology expertise by deploying Level-5 ride-hailing service and by integrating the expertise in SuperCruise System to achieve Level-3

• Ford visions to have a level 5 self-driving vehicles for ride-hailing and door delivery services with

Source : DRAUP

28

28

Google Cybersecurity Android Auto Waze

Lumedyne Technologies 510 Systems

Security Connectivity HD Mapping Sensor FusionAutomation

control systemFull Stack AV

Solution

OnStar StrobeCruise

AutomationUshr

Ford Sync Civil Maps Velodyne Argo AI

Acquisition Investment Partnership Inhouse

Overall Stack Rating

High Medium Low

Otto & Geometric IntelligenceDecartaUber Technologies

IntelBoschMapBox

AV Capability Deep-dive: Mapping, Sensors, and automation control systems based start-ups are prime acquisition targets



• GM’s acquire and invest AV strategy is a contrast to their traditional initiatives of spending minimal on acquisitions

• Ford is one of the top leaders who have invested $1 bn in Argo.AI to deploy full autonomous vehicles for commercial purposes

• Tesla is building in-house systems and services for AV capabilities

29Source : DRAUP

Location

Mountain View,

California

Autonomous

Headcount

250-300

Center R&D Spend

$ 1.1 Bn

Center Level

HQ & Hub

Key Influencers

John KrafcikCEO

Dmitri DolgovCTO, VP Engineering

Daniel ChuDirector of Product

Waymo LLC Key Autonomous vehicle Activities

Key Profiles

• Hardware Design Engineer

• Hardware Engineer, LIDAR Validation

• Audio Systems Engineer

• Robotics Software Engineer, Behavior Prediction

• Software Engineer, Machine Learning Infrastructure

• Software Engineer, Mapping

• Software Engineer, Computer vision system

• Develop and test high performance LIDAR systems• Develop insightful tests that span the range of radar integration stages, including individual snapshot evaluation, fully integrated on self-driving

vehicles, and fleet wide data mining• Design and execute LIDAR field measurements and structured tests• Build motion planning and decision-making systems for the self-driving vehicles, ensuring that the behavior of our vehicles is safe, smooth, and

predictable to other road users• Building backend infrastructure for storing and processing many forms of map data• Research new machine learning problems, models and algorithms• Design and manufacture of LiDAR systems• Develop car’s computer vision system that processes billions of pixels per second with very low latency• Develop autonomous vehicle system including optical modelling, camera hardware design, image quality, ISP pipeline, deep nets for detection and

classification, and high level perception evaluation

Waymo: Engineering Center Deep Dive

Note: Includes recent R&D initiatives and collaboration announcements/activities of the above mentioned player. List of AV activities and profiles are non-exhaustive;

Global Footprint data curated by DRAUP and updated in April, 2019

30Source : DRAUP

Location

Warren, Michigan

Greater Detroit Area

Autonomous

Headcount

2100-2200

Total Center Spend

$ 728 Mn

Center Level

HQ & Hub

Key Influencers

Dan AmmannPresident

Pamela FletcherVP, Autonomous & EV

Aaron SullivanEngineering ManagerAutonomous system

GM Warren Technical Centre

Key Influencers

Kyle VogtCEO

Daniel KanCOO

Cruise Automation

Location

San Francisco Bay

Area

Autonomous

Headcount

1,300-1,400

Total Center Spend

$ 1 Bn

Center Level

Hub

Key Autonomous vehicle Activities

Key Profiles

• Autonomous Driving Software Engineer

• Autonomous Driving Controls Engineer

• Autonomous Vehicle System Safety Engineer

• Autonomous Validation Engineer

• Autonomous Performance Engineer

• Algorithm Design and Development Engineer

• Development and integration of analytical algorithms and tools for autonomous vehicles.

• Development of Simulation platform for testing and simulating autonomous cars

• Autonomous system integration with hardware and software redundancy, fault-tolerant focus

• Driver modeling/machine learning development/integration

• Functional safety, hazard analysis, risk assessment

Key Profiles

• Autonomous Driving Software Engineer

• GIS Mapping Technician

• Autonomous Security Engineer

• Self-driving systems Engineer

• Computer Vision Engineer

• Network Engineer

Key Autonomous vehicle Activities• Computer vision and LIDAR-based solutions for

robotic perception• Design, implementation and support of network

monitoring and alerting systems• System and sub-system level requirements for

perception and localization software• System and subsystem level validation planning

and execution• Safety analysis and gaps coverage• Drawing and semantic annotation of road maps• Inspecting map labeling to ensure compliance for

organizational standards

GM: Engineering Center Deep Dive



31Source : DRAUP

Location

Dearborn, Michigan

Greater Detroit Area

Autonomous

Headcount

1350-1400

Center Spend

$ 900 Mn

Center Level

HQ & Hub

Key Influencers

Sherif Marakby CEO, Ford Autonomous

Vehicles LLC

Robert WalkerAV Product &

Experience Design Chief

Chris Brewer Chief Engineer,

Autonomous Vehicles

Ford Autonomous Vehicle LLC


Key Profiles

• Autonomous Vehicle Embedded Platform Software Architect

• AV Sensor and Module D&R Engineer

• AV - Systems Validation Engineer

• AV- Software Engineer

• Autonomous Vehicle Product Innovation Engineer

• Advanced Driver Assistance Systems and Controls Testing and Development

• Automated Driving Feature Development Engineer

• Development and design of autonomous vehicle sensing components

• Architecturall design, execution and development of infotainment platform

• Provide quality assurance for both hardware and software components

• Conduct performance design verification tests on prototype vehicles and constituent systems\

• Write production quality code to deploy as Transport-as-a-Service solutions

• Develop Remote sensing technologies

Ford: Engineering Center Deep Dive



32Source : DRAUP

Location

San Francisco Bay

Area

Autonomous

Headcount

250-300

Center Spend

$ 232 Mn

Center Level

HQ & Hub

Key Influencers

Eric HansonHead of Product, Advanced

Technologies Group

Steven ChoiProduct & Strategy

Key Influencers

Carl WellingtonDirector, Self Driving Cars

Jon ThomasonVP, Software Engineering

Advanced Technology Group Center

Location

Greater Pittsburgh

Area

Autonomous

Headcount

500-700

Center Level

Hub

Brian ZajacHead, Systems

Engineering & Testing

Advanced Technology Group Center


Key Profiles

• AI Research Scientist

• ATG Manufacturing Test Engineer

• AV Maps Quality Analyst

• Autonomous Vehicle Program Manager

• Android Engineer, Self-Driving Experience

• Design, implement and optimize novel algorithms that run at extremely low latency on autonomous vehicles

• Define, develop, implement and maintain the manufacturing requirements and test specifications

• Carry out root/cause analysis • Manage Autonomous Vehicle Integration

program delivery

Key Profiles

• Embedded Software Engineer

• Autonomous Vehicles-Embedded

Verification and Test Engineering

• Autonomous Vehicle Program Manager

• Computer Vision Engineer

• Backend Engineer, Self-Driving

Key Autonomous vehicle Activities• Create android applications for self-driving

systems • Manage Autonomous Vehicle Integration program

delivery, including milestones, prototype builds, and launch

• Establish process to manage changes for all component builds and vehicle builds

• Interface with Vehicle OEMs and Tier1 suppliers to align technology and vehicle delivery

• Work with lidar sensor firmware and low level signal processing

Uber: Engineering Center Deep Dive

Sameer KSupply Chain Director,

Advanced Technologies

Group

Center Spend

$ 77 Mn



33Source : DRAUP

Location

Palo Alto, California

Autonomous

Headcount

300-400

Center Spend

$ 392 Mn

Center Level

HQ & Hub

Key Influencers

Andrej KarpathySenior Director of Artificial

Intelligence

Neeraj Parik Architecture and Design

(Autopilot Hardware) Lead

Mitchell Heschke Sr. Product Design

Engineer- Autopilot

Tesla


Key Profiles

• Computer Vision Scientist/Engineer, Autopilot

• Firmware Engineer, Autopilot

• Autopilot Systems Design/Functional Safety Engineer

• Autopilot Software Engineer, Computer Vision and AI

• Autopilot - AI Technical Lead

• Architect, IoT Technology

• Work on the Camera software pipeline running on the target product platform to deliver high resolution images at high framerate to a range of consuming devices (CPU, GPU, hardware compressors and image processors)

• Optimize and integrate embedded code to introduce new features and capabilities to Tesla’s vehicles.

• Develop state-of-the-art algorithms in multi-sensor fusion, visual-inertial odometry, GPS, IMU and radar processing, intrinsic/extrinsic camera calibration, structure from motion, etc.

• Develop software platform and tools for AI algorithms in self driving cars.

• Define system reliability and robustness requirements for the autopilot ECU

Tesla: Engineering Center Deep Dive



34




AGENDA





Partnership opportunities across AV areas

Outsourcing intensity across AV areas

35Source : DRAUP

System Engineering & Functional Safety

Feature

Development

System Integration (Middleware)

SoC Testing, Physical Design

Sensor Fusion

Sensor Testing & Validation Sensor Design Software

• RADAR• LIDAR• Ultrasonic• Camera

• Camera Module Reference Design• Radar Module Design• Multi-Sensor Hub Reference

Design

Physical Design & FPGA/ SoC Testing

• SoC Verification• SoC Validation• Burn-in stress testing

ECU platforms Maps & Navigation

Sensor Perception

• Night time Pedestrian detection• Distance and Angle Estimation• Pedestrian, cyclist detection• Path planning & object tracking

Vehicle Control Systems Data Analytics & Cyber Security

GPS/INS-based vehicle state estimation, 3D mapping and localisation

• Driver Assist Systems• Emergency Breaking• Steering Control

• OTA Software Management

ADAS Algorithms Computer Vision/ML Virtual Environment Simulation & Testing

Prototype Testing & Validation

System Safety System Modelling

System validation including performance validation

Validation of autonomous features against diverse road scenarios

System Architecture alignment to the autonomous vehicle’s mission

• Image Processing and Machine Vision

• Traffic Incident readiness and ML

• Virtual environment development and data collection

• Integration software platform

• Platform testing

Algorithm development and calibration, validation, and functional safety.

Outsourcing Intensity

Co

mp

on

ents

& H

ard

war

eFu

ll St

ack

Pla

tfo

rms

Partnership Opportunities: High partnership opportunities in System Engineering, System integration & Feature development.

Note: The above analysis is based on the outsourcing done by the OEMs, Tier-1 Suppliers, Tech Giants and Start-ups in the AV ecosystem. There are several other companies

working towards Autonomous Vehicles. The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April

2019

Source : DRAUP

36

36

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