#815

L4 Autonomous Forecast

AUT

TABLE OF CONTENTS

AutonomousVehicles

When it rolls out, the automotive landscape at large will already be greatly impacted by level 4 autonomy. This
impact can be already felt across multiple sectors – with autonomous services being piloted, or launched, indifferent regions and more OEMs fitting more L4 features and systems onto their latest vehicles. Likewise, this levelof autonomy will pave the way for new players while providing new opportunities for additional industry sectors –such as mobility and trucking.

Introduction
Executive Summary
Segment – Robotaxis

Despite the prosperity of L4 autonomy, its evolution and eventual release relies heavily on a number of factors. Forinstance, any OEM, supplier, or company wishing to benefit from it will face a series of legal and regulatory
challenges across several regions to ensure their systems are safe for use on public roads. At the same time, theseplayers must also consider the best commercial practices for these systems to secure and maintain revenue as theecosystem becomes more competitive.

Segment – AV Public Transport
Segment – AV last-mile delivery
Segment – AV Truck

The L4 Autonomy Forecast delivers comprehensive insights into the expected growth of fully autonomous vehicles
and services across different regions and segments. It assesses which segments within L4 autonomy will generate
the most opportunities over time, while understanding how it is expected to be deployed over the next decade.

Forecast Data
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#815/L4 Autonomous Forecast

Key questions answered> How many L4 vehicles will
be deployed acrossdifferent cities and regionsin the next 10 years?

> Which segments (robotaxi,shuttles, last mile delivery,trucks, etc.) will lead the way
in L4 adoption?

> How much revenue will
the L4 market generate
as a proportion of alltransportation revenues?

> Which L4 autonomy
segments will generate thehighest opportunities?

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L4 Autonomous Forecastdelivers comprehensive insights into the expected growth of fully autonomousvehicles and services>640 Datapoints
All major segments

DashboardL4 Autonomy Forecast
GlobalContents
815 - L4 Autonomy forecast
Introduction ≫Birds-eye view ≫Executive Summary ≫4713Analysis ≫19Segment - Robotaxis ≫32▪ News▪ Segment analysis▪ China▪ USA▪ Europe▪ Other notable regions▪ Technology trends

Segment - AV public transport≫

55

Segment - AV Truck≫▪ News▪ News▪ Segment analysis▪ Segment analysis▪ China▪ China

▪ USA

▪ USA

▪ Europe▪ Europe▪ Technology trends▪ Other notable regions▪ News▪ Technology trends

Segment - AV last-mile delivery≫

76

97

Forecast data ≫118

Next Steps ≫125Contact us ≫129

▪ News▪ Segment analysis▪ China▪ USA▪ Europe▪ Other notable regions

Data Deep Dive

▪ Technology trends

View and analyze deep
data in your own way

Total number of pages - 129

Introduction

Introduction

Introduction
Ever since Alfred Vacheron invented the steering wheel in 1894, the steering wheel is one of theindispensable components in vehicles. However, it is being challenged today as L4 autonomousvehicle services are deploying, and humans are now being prepared to give up control.
Although the transformation to automation has some promised socioeconomic merits such asenhancing safety, efficiency, etc. in the long term. In the recent past there has also been ageneral recognition in the industry that the journey to delivering L4 is longer than anticipated.

SAE Level 4 (the focus of this report) refers toautonomous vehicles that can operate without any
driver interaction but within pre-defined parameters(geographical, weather conditions, etc).

The purpose of the report is to evaluate the affecting factors in the way to deploy L4autonomous vehicles in different regions and forecast the future market based on grounded
analysis, and answer the following questions:•How many L4 vehicles will be deployed across different regions by 2031?

•Which segments (robotaxi, shuttles, last-mile delivery, trucks, etc.) will lead the way in L4
adoption?
Which region will lead the way to deploying L4 vehicles and why?

•L4

HighAutomation

This report mainly focuses on three regions which are dominating this sector (USA, Europe andChina), analysing the technical, regulatory, user acceptance and commercial factors for major
segments. Some other notable regions and technology trends are also included in the report.
This report identifies the major drivers and barriers for the six key motivations for theAutonomous Vehicle.

6

IncreasedsafetyLoweroverheads

Increased
utilization

Overcomelabor shortages

Sustainability

Expandedcoverage

6Introduction

We Listened and Invested In Our L4 Report to Align to Your Goals

You Said...
“I sometimes struggle to relate conclusions from research reports
to the Outcomes and KPIs that we are working towards...”“I would like to see what has recently changed within a forecast or
domain to help decide if any changes to strategy need to be made...”We Did...
Added an Autonomy BIRDS-EYE VIEW chapter
with a high-level overview of all our Autonomous
reports.

Added dedicated ANALYSIS section to provide aninsight to the future of the industry“I can find it difficult to take actionable next steps on Guides
without assessing the future direction of the industry...”“It would be helpful to identify disruptive companies and startups to keep an eye for partnerships in the future...”“I would like the topics to be more ‘forward looking’ to help withfuture planning and take advantage of enabling technologies.”

More DATA-DRIVEN ANALYSIS through oursegment analysis and Executive Summary.

Pushed boundaries to launch the disruptive NEW
TITLE L4 Autonomy Forecast

77Example slides
from the reportBird’s Eye View

Autonomous Trucks

Large

L4 autonomy to support four key segments in transportation networks

Autonomous public transport are those which moving
large groups of people between transportation hubs oron the first/last-mile leg of their journey via Avs, it
includes campus microtransit, last mile microtransit, AVbus and AV rapid bus

Autonomous trucks are those conducting journeys between
freight hubs along pre-defined and pre-mapped routes,
including freight yard automation (private operating area),truck platooning and automated semi-trucks
Drivers• Cost savings• Driver shortages• High efficiency• Fewer accidents

Autonomous Public TransportBarriers• Road network• Crossing borders• Insurance/liability• Vehicle approval

Drivers• Cost savings• More coverage• Less congestion• Less emissions

Barriers• Vulnerable users• Managing liability• Low city budgets• Infrastructure

Goods

People*Robotaxis

Autonomous Last-Mile Delivery

Robotaxis are those transporting individuals directly totheir destination in automated taxis, it includes different
segments like Micro robotaxis, City robotaxis, large
robotaxis and premium robotaxis with different
operation domains and capacity

Drivers• Cost savings• Driver shortages• Expanded services• High productivityBarriers• User experience• Liability• Complex roads• Process/controls

Small

Autonomous last-mile delivery are those Delivering goods
from central hubs to homes and businesses, including
micro delivery robots and AV delivery vans

Drivers• Cost savings• Driver shortages• Fewer accidents• New experiences

Barriers• Low profitability• Difficult to scale• Liability concerns• User acceptance

L4 Autonomy Forecast
This slide provides an overview of thedifferent segments for L4 autonomy
considered in this report as well as thedrivers and barriers to deployment. Theoverall report considers these segments,drivers and barriers and provides aforecast in the USA, Europe and Chinamarkets.

99Analysis

The question to be answered: what’s in it for customers?
TestingStage
1.0

DemandGradually cultivate the customer
awareness

The automation of vehicles can give people:

10

Stage
2.0

Ramp-up

Improved customers acceptancewithin the operation zones

Stage
3.0

Full Deployment

Large-scale operations, L4 autonomybecome the favorable option for mobility
demandWithout adequate development/deployment, some hurdles include...

Safer journey

Human mistakes are still one of the biggest reasons
behind accidents and the autonomous vehicles will
operate at speed limits

Safety concern

While road fatalities are high now, every death in an
AV will face added scrutiny, and removing humandrivers will make some people feel less secure

Lower cost

Once the business model is clearer, the cost of L4
AV services should be lower than manual services

Lessaccessibility

Some people with disability may find that using L4 AV
services is harder, as no human drivers will offer help

Higher coverage

Some places that cannot be covered byconventional services (e.g. remote places) can bepotentially covered by L4 AVs

Constrainedroute

In the early stage, autonomous vehicles are moreconstrained in terms of drop-off and pick-up

Less efficient
service

Without human drivers, some inconvenientexperiences may occur. For example, AV delivery
services will require people to collect goods bythemselves from the vehicles

More efficient
service

L4 AV can provide more efficient service, including
24/7 services, etc.

New experience

New types of vehicle experiences and interiors,
making travel more enjoyable

Failure toachieve humanlike trajectory

Not making autonomous vehicles human-like has
mainly two drawbacks: 1) uncomfortable journeys forpassengers 2) making the AV unpredictable to otherhuman drivers.
10

AV Segments

Robotaxis

The journey of Robotaxis to achieve full deployment
Stage
1.0

Testing

Current

Stage
2.0

Stage 1.1

Stage 1.2

Stage 1.3

Robotaxi pilot
only

Small-scale commercial
operation with safetydrivers

Small-scale commercial
operations without safe
drivers

Technology

Developing and testing the various
technologies required for robotaxis tofunction safely and effectively

Pilots and early commercial operations
are granted in some regions

Regulation

Customers in certain areas havealready started using the service
mainly for the new experienceRamp-up>2030

Full Deployment>2040

Gradual performance increases. This
stage involves limited deployment ofrobotaxis in specific areas or under
specific conditions

Technologies have been fully tested andovercome most of the technical challenges

Most regions have established morecomprehensive regulations, coveringliability, data privacy, societal rules,traffic management, etc

Robotaxis regulations have been revised andbecome more comprehensive over time

Improved customers acceptancewithin the operation zones

Large-scale operation, robotaxis
represent a majority of all private
passenger journeys in major cities

Optimizing the operating andcommercial model, expanding theservice by scaling up the fleet incertain regions or entering moreregions

Achieved overall lower cost than
traditional services, attracting moreindustrial players to be in the robotaxis
marketDemandStart fee-paying services in specificregions, mainly for collecting
customer feedback and building
Commercialization customer confidence

Stage3.011

AV Segments

Autonomous public transport

Barriers in deploying autonomous public transport
Commercialization
Many campuses offer limited or no transit – so costs
would be incremental if they choose to deploy
autonomous transit. Also, The update of the current
public transport infrastructure requires hugeinvestment, e.g. bus stops, dedicated bus lanes,
V2X RSUs, etc.

TechnologyThe deployment of autonomous public transport
requires cooperation with intelligent infrastructure,such as traffic management systems, which brings
difficulties in data security, communication, etc.

To deliver the longer-term success of autonomous
public transport there needs to be greater levels of
integration across government, operators, OEMs andtechnology companies, which is a complex taskRegulation
Consumer demand
Operators currently depend on drivers to assist
passengers with special needs or manage any
situations that may occur between passengers, suchas conflicts. The removal of drivers may result in alack of support for these passengers, potentiallycausing them to feel more vulnerable andunsupported.
Due to the outbreak of pandemic, people would relyon the public transport less frequently, because of
the mixture of health concerns and a trend towards
work from home

Today the liability for accidents can be placed onhuman drivers, and that include bus or shuttledrivers. Operators of AV public transport will need toconsider carefully how to handle liability, particularly
if they are partnering with 3rd party tech players.
In addition, there is a concern that the sensors andcameras equipped on autonomous buses maygather personal data of passengers and pedestrians,
potentially leading to the use of such data for
purposes beyond those originally intended. As such,there may be a need for regulatory frameworks tosafeguard the privacy of individuals while utilizing
autonomous buses
12

AV Segments

Autonomous public transport

China – Analysis/overview

32,436Autonomous public
transport vehicles
Parc in 2031

Readiness forecast (to achieve “Full deployment level”)

Technology

10,226Autonomous public
transport newvehicles sales in2031

2Key pattern••

Commercial operations in some of theplaces
Led by commercial vehicle OEMs

Autonomous public
transport pilots inChina

Regulation

DemandCommercialization

2022

2030

2040

2050

SBD Viewpoint

China is one of the leading countries in terms of deploying autonomous buses and started the fee-paying service back in 2021. The industry in China isstrongly supported by China government from regulatory support to financial investment. One clear advantage China has in deploying autonomous public
transport services is that China is still building infrastructure at a rapid speed and expanding the tech zones. In addition, the public transport market size isconsiderably larger in China than in other countries, which provides great potential to scale up the fleet.

13

AV Segments

Autonomous last-mile delivery

AV last-mile delivery technology trend
1

Cheaper lidars bring bigger opportunity for the mass production ofautonomous delivery vehicle
Lidars, Chassis and CPU are the three most expensive components of autonomous
delivery vehicles, accounting for up to 70%+ of the total cost. Compared with othersegments, the vehicles in autonomous delivery are more cost-sensitive, one example
is that the GWM-backed HAOMO.AI announced the autonomous delivery vehicle“Xiao Moto 2.0” with the price of $18K. The price of lidars have reduced significantlyin the past few years, and it is expected as the widespread of autonomous vehicles
in the future, the price of short-range lidars (less sensing requirement than othersegments) might reach $500 in the future.

2Sensor technology count required for highrobustness levels:
Each circle represents an instance of sensor required

AV Delivery Van

Micro Delivery Robot

Teleoperations remains important for corner cases
Although safety drivers are not normally required in autonomous delivery
services, teleoperations keep playing a vital role in the operation ofautonomous delivery vehicles to deal with corner cases in cities. The
teleoperation centre must be considered in expanding the service and the cost
will also be increased as the fleet expands.

CamerasUltrasonics

HD mapsEnhanced GNSS

RadarsLidarsV2X

14

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