For the full video of this presentation, please visit: https://www.embedded-vision.com/platinum-members/aimotive/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-kishonti For more information about embedded vision, please visit: http://www.embedded-vision.com László Kishonti, CEO of AImotive, presents the "Shifts in the Automated Driving Industry" tutorial at the May 2019 Embedded Vision Summit. 2018 will have a lasting effect on the self-driving industry, as key stakeholders have turned from the unattainable goal of full autonomy by 2021 to more realistic development and productization roadmaps. This will in turn result in consolidation in the automated driving industry, which is currently too fragmented. To realize self- driving and gain regulatory, consumer and (in the case of startups) investor trust, Kishonti suggests in this presentation, the walled-garden approaches of the industry must change to a more collaborative approach. To support collaboration, cooperation and standardization, companies must adapt the way they create their software solutions and move to more modular designs. The companies with the most effective and meaningful collaborations will be the ones that survive the inevitable consolidation of the automated driving industry.

1. © 2019 AImotive
Shift in the Automated Driving Industry:
From Walled Gardens to Collaboration
Laszlo Kishonti
AImotive
May 2019

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A paradigm shift in 2018

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The road forward
• Automotive market flattening or shrinking in 2019 after growth in 2017,
2018
• Consumers may be holding off for more affordable next generation EVs
• Global trade situation less stable than before
• R&D budgets lower, less funding for costly experiments
3

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The industry reactions
OEMs putting less emphasis on far-out technologies (L4/L5)
4
Immediate
mass market
revenue
Compelling
product for
consumer
Additional
safety vs today:
will save many
lives
Simpler
to regulate
Shift in focus to L2 --> affordable and scalable sensor solutions
Solutions are sold to consumers as L2+ products:
Leading to corporate restructuring at OEMs
vsCamera- and radar-based LiDAR- and HD-map-based

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A turning point in founding AV companies
4 5 2
6 3 5 7
12 9
14 16 17
23
33
48
74
93
70
23
3
0
10
20
30
40
50
60
70
80
90
100
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Number of companies founded by year
5
Source: Crunchbase. Includes all companies tagged in ”Autonomous Vehicles” category.
Total number of companies: 467

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Funding remains strong with fewer but larger rounds
6
0
20
40
60
80
100
120
140
0
500
1000
1500
2000
2500
3000
3500
4000
4500
2015 2016 2017 2018 2019
MillionsUSD
Funding in Autonomous Driving - related companies
Total Money Raised(in USD) Number of rounds
Companies founded later
need more capital
to catch up
#ofrounds
Source: Crunchbase. Includes all companies tagged in ”Autonomous Vehicles” category. Only funding rounds less than 1B$ included.
Total number of founding rounds: 388, total number of companies included: 233

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Internal industry trends in line with VC trends
• Industry trends slowing investment in automated driving technology
• Chinese auto market has dropped 20%
• Industry less stable globally
• Instability leading to smaller R&D budgets for self-driving
• Limited internal and external investment pushing companies to monetize
existing technologies quickly
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The AV challenge: too complex to solve
by a single company
Validation and
verification
Robotics,
drones, other
airborne
Road Vehicles
Other electronic components
In-car
compute
Connected car, OTA, security
Mapping, navigation, positioning,
traffic management tools
Data, training,
simulation tools
Cloud platform
Systems
Integration
Mobility services & Fleet
management
Sensors
Middleware / OS
Autonomous driving & ADAS
software modules
UI / HMI
In-vehicle On-premise System services

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The AV challenge: too complex to solve
by a single company
Validation and
verification
Robotics,
drones,
other
airborne
Road
Vehicles
Other electronic components
In-car
compute
Connected car, OTA, security
Mapping, navigation, positioning,
traffic management tools
Data, training,
simulation tools
Cloud platform
Systems
Integration
Mobility services & Fleet
management
Sensors
Middleware / OS
Autonomous driving & ADAS
software modules
UI / HMI
In-vehicle On-premise System services
100+
80+ 50+
100+ 60+
50+
60+
80+

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Consolidation drives collaboration
• Self-driving has many technical challenges
• Too many companies are working on each challenge
• Current market trends cannot sustain so many stakeholders
• As technology matures consolidation is inevitable (see e.g., mobile
phone industry)
Companies must begin to collaborate and focus on their strengths,
or become victims of consolidation

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Strategies to survive
11
1. Industry needs to find short-term revenue streams
a) OEMs and Tier 1s need to collaborate
b) Tech providers must move to modular software design
2. Validation and verification will become standardized
3. Companies to begin partnering on non-core activities

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OEMs and Tier 1s must collaborate
• Automotive companies have internal R&D efforts
• Several have hit the wall, or are not providing expected return
• Shrinking industry means smaller budgets for R&D teams
• Strong competition to deploy increasingly advanced ADAS functions
• Looking for ways to quickly monetize their internal efforts
12
• Must collaborate to complete offerings and deploy automated driving
• Very few players building everything internally: e.g. Tesla

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Industry shifting towards collaboration
13
• Passenger car
• Robotaxi
• Trucking
With increased collaboration product
differentiation will shift to areas directly
visible to customers:
• UX/UI
• Design
• Interior
Differentiation based on market
segment is viable:

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Self-driving software must be modular
• Deployment of L4/5 delayed self-driving companies have no clear
business model
• No one has production full-stack different pieces of the
technology
• Survival: short-term monetization of technology
14
• Parts of self-driving software implemented in automated driving
systems
• Software stacks should be adapted to support this
• Modular design eases implementation in various solutions

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Standardization to drive safety in autonomy
• Industry efforts for standardizing automated
driving solutions increasing
• Basic standard for Functional Safety (ISO
26262) not prepared for all aspects of AD
• Safety of the Intended Functionality (SOTIF)
working group developing standard for
verification and validation of AD systems
• OpenGenesis working group to examine
questions of standardizing AI for self-driving
• Further standardization efforts in simulation
for self-driving
15

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Stricter regulations
• Accidents have led to increased scrutiny of automated driving solutions
• Regulatory approval will become harder to achieve
• EURO NCAP and NHTSA adding automated driving functionalities to
safety ratings and regulatory requirements
16
• Simulation the only way to verify and validate these solutions efficiently
• Standardization likely to affect simulator software and scenarios
• OpenScenario and OpenDrive standards
• Aviation a key example of this approach

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Simulation for continuous integration
New
Function
Request
Requirement
Definition*
Real and Simulated
Data
Package Unit
Test
Module
Test
Scenario
Test
Vehicle
Integration
Test
Iterative test-driven
developement
Closed loop
Validation process
Closed loop
training process
Worldwide
Robustness
Testing
Automated TestingDevelopment Deployment
*Functional, Performance, Safety Requirements and Test Scenarios
Code
Development
Simulation Aided

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Companies must partner on non-core activities
• No one has the resources to solve all the challenges of self-driving
• HD maps are a good example
• Maps are centuries-old standard for sharing geographic data
• Current HD maps limited, proprietary, and created on-demand,
• Current maps often kept up-to-date by self-driving companies – too
resource heavy for long-term solution
• Specialized providers with resources to keep maps updated
• Standardization should ensure accessibility and compatibility with
different solutions
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Conclusions
1. Auto Industry shrinking following growth in past years
2. Next big challenge for self-driving companies is to survive
3. To survive consolidation automotive companies must…
a) generate revenue in the short-term
b) enter collaborations
c) deploy modules as part of automated driving solutions
d) support standardization efforts in automated driving
e) rely on simulation for validation and verification
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AImotive Factsheet
20
Partners
Reference Customers
COMPANY
• Founded in 2015 by CEO Laszlo Kishonti
• Incorporated in Germany, headquartered
in Budapest
GLOBAL
GROWTH
• 4 licensed testing locations: Hungary, Finland,
California, Nevada
• Autonomous driving test cars from 4
manufacturers: Ford, Toyota, Volvo, Citroen, SAIC
TEAM &
EXPERTISE
• 200+ passionate team, including 150+ highly
skilled engineers
• In-house developed AI algorithms and framework
• 10+ years in high-performance embedded
programming
STRONG
TRACTION
• Track record of delivering customer projects
since 2015
• Running autonomous driving projects across 3
continents (Europe, USA, Asia)
INVESTORS
• Over $50 million raised
• Robert Bosch VC, Nvidia, Inventure VC, Draper
Associates, B Capital, Prime Ventures, Cisco
Investments, Samsung Catalyst Fund, Day One
Capital, Private investors

21. © 2019 AImotive
Thank you
for listening
Laszlo Kishonti