- What drives the progress of autonomous driving? - How far is the technology? - How far has legislation come? - How is autonomous driving perceived by the end consumer? We look at the state of play concerning autonomous driving, reviewing major development of 2017 and provide an outlook for 2018.

1. A member of
h&z Autonomous Driving Roadmap
Recap 2017 – Outlook 2018

2. Slide 2h&z Autonomous Driving Roadmap 2017_2018.pptx
h&z Autonomous Driving Roadmap Recap 2017
2017 was marked by significant progress in legal framework and technology, as well as
dynamic M&A activity – consumer acceptance has room for improvement
Area
Some rapid advancements
brought Autonomous Driving a
step closer to reality but there
are still several obstacles
More than double the
investment of 2016 and some
significant deals – the market
is heating up
People are increasingly aware
of Autonomous Driving but we
are far from large scale
support and acceptance
Once the technology is ready
there are major opportunities
to create value from a range
of new business models
Many governments are still
reluctant to allow large scale
public testing. Firms complain
about unclear and fragmented
legislative landscape
All presented milestones are exclusively from 2017
Comments
Testing
Stage
III
Early Stage Ready for
Implement
action
Proven
Scalability
I II IV
Legal
Framework
Technology
M&A and
Start-ups
The Human
Factor
Potential
Business
Models
 HD Map based simulations support the global testing efforts
 Audi A8 uses advanced autonomous features in traffic jams
 Waymo conducts first tests without any driver present
 Nauto raises US$ 159m
 Argo AI raises US$ 1bn from Ford
 Intel acquires Mobileye for around US$ 15bn
 Negative publicity: News of accidents and flawed testing spark skepticism
 Ethics and autonomous driving: The debate is ongoing
but still far from advancing practical problems
 First simulations of mixed traffic: Human interaction with
autonomous vehicles is still problematic
 Original design manufacturing (ODM) firms invest heavily into
Autonomous Driving
 Smart city: early-mover governments trial AD in urban areas
 Many OEMs prepare for monetizing Autonomous Driving features
Source: h&z research
 U.S. Self-Driving Car Council: Meetings and progress stalled
 U.S. Highly Automated Vehicle (AV) Testing and Deployment Act:
Shift of AV oversight to National Highway Traffic and Safety Administration
 UK Automated and Electric Vehicles Bill 2017–19: clear regulation on
insurance for AV and option for drivers to turn attention away from driving
Milestones

3. Slide 3h&z Autonomous Driving Roadmap 2017_2018.pptx
Autonomous Technologies on water, land and in the air
Sea-, land-, and –air-based autonomous technologies are developing in parallel, however,
land-based applications are the toughest to solve
On sea In the air
Advantages
 Traffic fatalities could be reduced by up to 90% –
one of the biggest impacts on public health ever
 Value of a new economy based on different AD
applications is expected to reach
US$ 800bn by 20351)
 Maneuvers by vessels are generally slow,
therefore reaction time is of little importance
 Vessels encounter a very stable environment
without interference from other objects
 3 dimensions offer more room to maneuver
 Once in the air, the environment is
less complex than on land
Disadvantages
 Particularly in urban environments, autonomous
vehicles need to manage complex interactions with
a variety of uncontrollable objects
 The potential savings and efficiency increases
are limited compared to land-based Autonomous
Driving technology
 There is no fail-safe state in stopping
 Regulations are often very strict when
a certain size of flying vehicle is reached
Cooperation between Google and Rolls Royce
 Google’s Cloud Machine Learning Engine will be
used to further train the company’s artificial
intelligence based object classification system for
detecting, identifying and tracking the objects a
vessel might encounter while at sea
Pizza in the Sky
 The world‘s first commercial usage of autonomous
delivery drones for food in Reykjavik, Iceland with a
60% reduction in transportation costs
Autonomous air taxis
• Firms like Ehang, Lilium,
and Volocopter work on vertical
take-off and landing
solutions – the race is on
Examples
On land In the air
Source: h&z research 1) Intel
 There are several hundred projects currently
working on testing and early applications –
See next slide

4. Slide 4h&z Autonomous Driving Roadmap 2017_2018.pptx
Hot spots and projects worldwide in 2017
Most current autonomous driving applications are used in commercial context, passenger-
oriented applications are undergoing intense testing worldwide
Haul truck
Company
Komatsu
Testing site
Private industrial ground
Excavator
Company
Built Robotics Inc.
Testing site
Private construction sites
Impact protection vehicle
Company
 Royal Truck & Equipment
 Kratos Defense &
Security Solutions
 Colas UK
Testing site
Public highways
and construction sites
Transportation cranes1)
Company
TraPac
Testing site
Private harbor area
Google’s test cars
Company
Waymo
Testing site
Public roads
Uber’s test cars
Company
Uber
Testing site
Public roads
Police cart
Company
OTSAW Digital
Testing site
Public streets
Refuse truck
Company
Volvo & Renova
Testing site
Public neighborhood
Baidu’s test cars
Company
Baidu
Testing site
Private & Public areas
Easy mile shuttle*
Company
EasyMile and DeutscheBahn
Testing site
Public roads
of commercial
industrial vehicles:
>10,000*
#
of test
vehicles: >400*
#
of commercial
passenger
vehicles: >100*
#
Source: h&z research 1) Indicative

5. Slide 5h&z Autonomous Driving Roadmap 2017_2018.pptx
Legal framework
Legislation needs to enable public testing of autonomous fleets while at the same time
maintaining high levels of road safety
UK’s effort to regulate
Autonomous Driving
The Automated and Electric Vehicles
Bill 2017 is an important step towards
a comprehensive Autonomous Driving legislation.
The bill states that:
“A vehicle is ‘driving itself’ if it is operating in a mode in which it is not being
controlled, and does not need to be monitored, by an individual.”
The bill thus acknowledges the technical difference between lower level autonomy
(like Tesla’s autopilot) and higher level autonomy designed to let the driver shift
attention elsewhere (like the recently proposed Audi Traffic Jam Pilot). This legal
differentiation is the basis for the driver legally being able to shift attention
away from steering the vehicle.
The legislative “trade-off”
Legislators have to balance the need for
public testing of a not entirely safe
technology and the desire to protect the
people in public spaces
Source: h&z research
USA as the leader in the Americas
California, Nevada, Michigan & Florida
posses reasonable regulated testing
frameworks. Arizona is the first state ever to
allow for testing without any driver present in
the car. Nonetheless, some states still do not
fully embrace AD technology testing
Singapore & Dubai as key in Middle
East and Asia
The two city states see Autonomous
technology as a key technology of their future.
Both have very open legislation for testing
and heavily subsidize different projects.
Diverse legislation in Europe
Although some governments are still skeptical
about AD (Italy for instance), others have
made great steps to position themselves as a
future hot spot for this technology. Among
these are The Netherlands, UK, Sweden, and
Germany.
New Zealand as hidden champion
While there is a limited number of testing
efforts, New Zealand has established a
variety of pro-active regulations allowing for
safe, yet applicable testing.

6. Slide 6h&z Autonomous Driving Roadmap 2017_2018.pptx
Technology – overview of modules and main players
Data processing, analysis and storage have been a dynamic area in 2017, some sensor
technologies are maturing, leading to a push for scale and standards
Technological Maturity Market attractiveness
LiDAR Cloud
and Live Data
Microelectro-
mechanical system
sensors
Motion SensorsUltrasonic HD Maps and
Stationary Data
Radar CPU
and GPU
Cameras
and image sensors
AI and
Deep Learning
5
1 2 3 4
6 7 8 9 10
1
4
3
5
2
8
7
6
10
9
Source: h&z research

7. Slide 7h&z Autonomous Driving Roadmap 2017_2018.pptx
Technology – current roadblocks
All of the players involved in AD technology are currently trying to tackle a number of
potential roadblocks
Weather conditions Cybersecurity
Isolated
R&D efforts Lane markings Hardware & Sensors
Scene
understanding
Human interaction
Complex
environment Cliffs and mountains
Interaction with law
enforcement Local idiosyncrasies Broken traffic lights
Any water from rain, snow or
fog fragments laser-based
sensors, leading to “noise” in
the system
Several incidents show that
connected cars are vulnerable
for attacks. It is still to be seen
how hacker-safe AVs will be
Given the different hardware
set-ups of the different test
vehicles, the software is
hardly transferable across
different models.
Consequently, scalability of
testing results remains limited
Unclear, dirty or missing lane
markings still cause trouble for
the Autonomous Driving AIs.
AD requires a flawless street
infrastructure in order to avoid
malfunctioning
There currently is no ideal
hardware set-up for sensors.
Some sensors, such as
LiDAR are still too expensive
for volume production
While object detection works
quite well already, making
sense of objects and
supporting decisions is still
difficult
Certain crossroads or merging
into rapidly flowing traffic often
requires humans to establish
eye contact; the search for
machine audio-visual
alternatives is still difficult
The environment of (urban)
public roads is extremely
complex; programming for
every possible scenario is a
tedious task. Any incident that
has not been anticipated in
the code can have severe
consequences
Cliffs are sometimes hard to
detect leading to risks
of falling off or coming too
close to the edge
Correctly understanding
spoken word or signs from law
enforcement or highway
safety employees is still
difficult
Volvo admits its self-driving
cars are still confused by
Kangaroos. The world is full of
local contingencies which
need to be managed
Distinguishing broken traffic
lights from working ones is
some-times hard to do. But
this is mostly a question of
training the AI adequately
Source: h&z research

8. Slide 8h&z Autonomous Driving Roadmap 2017_2018.pptx
M&A and Start-ups
2017 saw a further increase in M&A investment, around a quarter of deals was centered
on AI and Deep Learning
Mobileye
Mobileye, a key player in computer vision,
machine learning and mapping, was acquired
by Intel in 2017 for approximately US$ 10 bn
2017
AI, Deep Learning and
Connected Car applications were
the hottest M&A topics
Year
Investmentreceived
Zoox
Zoox offers autonomous taxi services
Nauto
Nauto is an autonomous vehicle
technology system that offers an artificial
intelligence-powered connected camera
network and smart cloud system
Quanergy
Another key provider of sensors such as
LiDAR. Among others, the key investors
thus far are Daimler, Delphi, and Samsung
Brain Corp
Focuses on robots and autonomous
machines for use in a number of
consumer-focused applications. The
investment was led by Softbank’s Vision
Fund
Velodyne
Another key provider of sensors such as
LiDAR. Key investors include Daimler,
Delphi, and Samsung
Split of clusters 2017
AI and Deep Learning 24%
Connected Car/ V2V
& V2X
16%
Autonomous Vehicle
Manufacturers
10%
Drones and UAVs 9%
Various Sensors 8.5%
LiDAR 7.9%
Robotics and
Automation
7.6%
Simulation and Data
Processing
5.9%
Cybersecurity 5.4%
Signal processing 3.4%
Mapping 1.1%
Source: Quid, h&z analysis

9. Slide 9h&z Autonomous Driving Roadmap 2017_2018.pptx
The Human Factor
Consumer acceptance and adoption of autonomous driving is in early stages, a concerted
push is necessary to speed up the process
Human interaction with autonomous vehicles
Simulation tests conducted by the UK-based Transport
Research Laboratory show that drivers are more likely
to conduct risky maneuvers if they know the other car is
controlled by a computer. The research found that drivers
may “adapt their behavior as autonomous vehicles
become more prevalent”
How can we speed up consumer acceptance and push adoption of
autonomous driving?
In order to push the adoption of
the new technology, consumers
can be influenced using these 9
levers:
Source: h&z research
Current adoption stage
2.5% 13.5%
Early
Majority
Late
Majority
Laggards
Innovators
EarlyAdopters
34% 34% 16% 1. Stress advantages and benefits of AD
2. Make sure benefits materialize immediately
3. Minimize the risk of purchasing AD cars/features
4. Optimize ease of use
5. Ensure benefits are observable to others
6. Provide ample opportunity for trialing AD cars/features
7. Adjust prices to prevent barriers to purchasing
8. Minimize the need for customer behavioral change
9. Promote return on investment

10. Slide 10h&z Autonomous Driving Roadmap 2017_2018.pptx
General technology
Future urban mobility and society
Uber, Lyft, Waymo and GM
Sensors & Software
Levels of Autonomy & Autonomous
Features
Apple
Insurance
Nvidia
Tencent and other
Chinese efforts
Consumer readiness
TomTom HD Maps
BMW, Intel
& Mobileye
Impact
Sentiment
Combined
Score
(Mean)
US legislation
The Human Factor – press coverage in 2017
The currently low consumer acceptance is fueled by mixed coverage in the media – future
fatal accidents could have a significant negative impact on public opinion
“There are huge unknowns in the technology,
vehicle safety, driver capability, application of
state laws, insurance, public acceptance and how
many lives might be saved.”
Market forecasts
Positive coverage Negative coverage
Intel acquires Mobileye
UK efforts and legislation
Baidu’s efforts
Fiat Chrysler
Korean firms & legislation
Impact: LargeMediumSmallSource: Quid; h&z analysis

11. Slide 11h&z Autonomous Driving Roadmap 2017_2018.pptx
Potential business models
Initial business models have already been implemented or are undergoing intensive
testing, many future business models are difficult to predict but could be groundbreaking
Short lead time
Uber, Didi Chuxing, Lyft and co.
are planning on providing mobility-as-a-
service, moving millions of people with
autonomous, efficiently managed fleets
The luxury option
Autonomous driving features are
going to be subsequently rolled out in
the premium car segments, for
instance Audi’s traffic jam function
which has been deployed in the new
A8
Commercial and
private delivery services
E.g. automated food/goods delivery
The “buses” of the future
Governmental public transport might
incentivize the usage of autonomous
transport options instead of existing public
transport options
First tests in Dubai
have proven the technical
feasibility of autonomous flying
vehicles. Several players are
currently trying to scale up the
technology
Extension of existing business model
Radical new mobility model
Autonomous
MoD fleets
Autonomous
features in
privately owned cars
Long lead time
Use case in
special vehicles
Public
Transportation
Air-based
personal
transport
GROUNDBREAKING DISRUPTIVE
CONSERVATIVE LOW ENTRY BARRIER
A privately owned
car stands still 23h
a day on average1)
We could generate
the biggest value-
add by reducing this
time and by using
cars more efficiently
– This is what most
current disruptive
mobility models
build on
Source: h&z research, 1) Wissenschaftszentrum Berlin für Sozialforschung (WZB) Market size: LargeMediumSmall
Amusement parks,
University campuses,
large corporate venues
Several companies
offer such services today
Warehouse and
back-end logistic
services, agricultural
tasks, construction sites
Hamburg Port logistics
Private area
fixed route
operations
Industrial area
applications

12. Slide 12h&z Autonomous Driving Roadmap 2017_2018.pptx
h&z Autonomous Driving Roadmap Outlook 2018
2018 will see incremental progress in all relevant areas, with a potential leap in the human
factor due to large-scale tests and roll-out of features in luxury cars
Area
Testing
Stage
III
Early Stage Ready for
Implement
action
Proven
Scalability
I II IV
Legal
Framework
Technology
M&A and
Start-ups
The Human
Factor
Potential
Business
Models
It is too early in the year to anticipate, which technological roadblock
will be removed first. Solid state LiDAR technology is receiving
substantial research funding and could lead to a dramatic drop in
cost
There are no signs of start-up activity and M&A by various old and
new players to abate. It is worthwhile watching out for new, surprising
business models to emerge
Large scale tests with potential end users will give a wider audience
access and understanding of autonomous driving, new features in
luxury cars will be rolled out which will also help to promote the
benefits of the new technology
New business models will emerge at the intersection of different,
currently separated, spheres, such as connected cars and smart
cities
Source: h&z research
It is highly likely, that additional governments will draft legislation
furthering autonomous driving, potentially creating a ripple effect
globally
Milestones
2017 2018
2017 2018
2017 2018
2017 2018
2017 2018

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Benjamin Scher | Strategy & Innovation Consultant Dr. Alexander Stern | Head of Automotive Practice Group
+49 89 242969 - 293 | benjamin.scher@huz.de +49 89 242969 - 833 | alexander.stern@huz.de
Business Intelligence Unit Automotive Practice Group