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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
3
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
4
4
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
5
5
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
6
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
7
7
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
8
8
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
9
Autonomous Vehicle Overview01
Technology Spend Analysis02
Autonomous Vehicle Adoption03
This section provides an overview of :
AGENDA
Bay Area–Deep Dive04
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
Partnership Opportunities06
Source : DRAUP
10
10
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;
The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019
Source : DRAUP
11
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
12
12
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
13
13
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
14
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
15
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
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
Source : DRAUP
16
16
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
The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019
• 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
17
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
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
Source : DRAUP
18
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
The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019
19
Autonomous Vehicle Overview01
Technology Spend Analysis02
Autonomous Vehicle Adoption03
This section provides an overview of :
AGENDA
Bay Area–Deep Dive04
Global and US AV adoption analysis
Miles driven by top companies in California
Top Companies Deep Dive05
Partnership Opportunities06
Source : DRAUP
20
20
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
21
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
22
Autonomous Vehicle Overview01
Technology Spend Analysis02
Autonomous Vehicle Adoption03
AGENDA
Bay Area–Deep Dive04
Top Companies Deep Dive05
Partnership Opportunities06
Source : DRAUP
23
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;
The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019
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
Autonomous Vehicle Overview01
Technology Spend Analysis02
Autonomous Vehicle Adoption03
This section provides an overview of :
AGENDA
Bay Area–Deep Dive04
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
Top Companies Deep Dive05
Partnership Opportunities06
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
Note: The infographic above shows analysis done on specific companies. 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
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.
The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on April 2019
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
Note: The infographic above shows analysis done on specific companies. 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
• 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
Note: The infographic above shows analysis done on specific companies. 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
• 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
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
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 Autonomous vehicle Activities
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
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
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 Autonomous vehicle Activities
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
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
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 Autonomous vehicle Activities
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
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
34
Autonomous Vehicle Overview01
Technology Spend Analysis02
Autonomous Vehicle Adoption03
AGENDA
Bay Area–Deep Dive04
Top Companies Deep Dive05
Partnership Opportunities06
This section provides an overview of :
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
www.draup.com