Study on the societal acceptanceof Urban Air Mobility in Europe
May 19, 2021

Confidential and proprietary. Any use of this material without specific permission of EASA is strictly prohibited.

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Further information and the full survey insights are available at easa.europa.eu/UAM

This study has been carried out for EASA by McKinsey & Company upon award of a specific contract implementing arunning multiple framework contract for the provision of consultancy services. Consequently, it does not necessarily
express the views of EASA itself, nor should it be relied upon as a statement, as any form of warranty, representation,
undertaking, contractual, or other binding commitment upon EASA. Ownership of all copyright and other IPR in thismaterial including any documentation, data and technical information, remains vested to EASA. All logo, copyrights,
trademarks, that may be contained within, are the property of their respective owners. Reproduction of this study,
in whole or in part, is permitted under the condition that this Disclaimer remains clearly and visibly affixed in full at all
times with such reproduced part. This study has measured the attitude of the EU society towards UAM early 2021, wellin advance of future deployment in EU cities foreseen around 2024-2025. The results have been generated with best
effort at this point in time, however public perception may change over time once citizens are exposed to actual UAM
operations.

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Executive Summary

New technologies such as the enhancement of battery technologies and electric propulsion as well as major investments
made into start-ups are enabling the development of new vertical take-off and landing Urban Air Mobility (UAM)
aircraft. Thus, Urban Air Mobility – defined as an air transportation system for passengers and cargo in and around urban
environments – may be deployed in Europe within three to five years, offering the potential for greener and faster mobility
solutions.
As several projects and demonstrations are under way, it is time for the European Union, and for national and local
authorities to prepare the framework that will enable this new mode of transport and give Europe the chance of
establishing itself as one of the first movers in this field at a global level.
Citizens’ and future UAM users’ confidence and acceptance will be critical to success. As part of the preparation ofan adequate regulatory framework, the European Union Aviation Safety Agency (EASA) therefore conducted thiscomprehensive study on the societal acceptance of UAM operations across the European Union. The study was carried out
together with the consulting firm McKinsey & Company between November 2020 and April 2021. Full details of the report
can be found on the EASA website.
Based on thorough research, literature review, local market analysis, surveys and interviews, the study examined
the attitudes, expectations and concerns of EU citizens with respect to UAM and revealed interesting insights, some
unexpected. The survey results were very homogeneous among all those surveyed across the EU and in all socio-economic
categories. They can be clustered into 10 key take-aways:
1. EU citizens initially and spontaneously express a positive attitude toward and interest in UAM; it is seen as a new andattractive means of mobility and a majority is ready to try it out;
2. The notion of general/public interest is a determining factor for acceptance: use cases for the benefit of thecommunity, such as medical or emergency transport or those connecting remote areas, are better supported thanuse cases satisfying individual/private needs;
3. The main benefits expected from UAM are faster, cleaner and extended connectivity;
4. However, when encouraged to reflect upon the concrete consequences of potential UAM operations in theircity, EU citizens want to limit their own exposure to risks, in particular when related to safety, noise, security andenvironmental impact;
5. Safety concerns come first, but the study also shows that citizens seem to trust the current aviation safety levels andwould be reassured if these levels were applied for UAM;
6. Noise is the second main concern expressed; the study indicates that the level of annoyance varies with thefamiliarity of the sound, with familiar city sounds at the same decibel levels being better accepted; it also confirmsthat the distance, duration and repetition of the sound impacts its acceptance;
7. UAM is seen as a good option to improve the local environmental footprint, through reduced urban traffic
congestion and better local air quality; but at the same time citizens express major concerns about UAM’s impact on
wildlife;
8. The results also demonstrate a limited trust in the security and cyber security of UAM, requiring threat-prevention
measures;
9. The integration of UAM into the existing air and ground infrastructure must respect residents’ quality of life and thecultural heritage of old European cities;
10. Finally, local residents and authorities feel directly affected by the deployment of UAM and want to engage and play
an active role in its implementation.

Executive Summary

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The study results show that EU citizens are calling for active and pre-emptive measures from competent authorities.
In addition to mitigating risks related to safety, security, noise and environmental impact, these measures are expected
to ensure that UAM will be a common benefit to all of society by offering affordable, integrated and complementary
mobility. By providing transparent and timely information and guidance, the authorities at all levels – local, national andEuropean – have the chance to consolidate public acceptance of UAM.
By 2024-25, UAM may be a lived reality in Europe. The EU has only a few years, and a unique opportunity, to prepare forthe smooth transition of European cities, and also of the European aviation system, towards the mobility of the future.

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Table of content

Table of content
Definitions
Introduction

56
7

1. Research and literature review
1.1 Literature review		
Methodology
Summary of insights		
1.1.1 UAM use cases found in literature		
1.1.2 Expected challenges identified in literature				
1.1.3 Societal acceptance factors identified in literature			

11
12
13
14
16
16
17

1.2 Industry status and projection						 Overview		
UAM vehicle types
		
1.2.1 Aircraft and Use Cases				
1.2.2 UAM stakeholder environment

21
21
22
22
27

1.3 UAM high level societal benefits and risks		
1.3.1 Benefits based on market models, literature and expert interviews		
		
1.3.2 Risks and acceptance based on literature and expert interviews

30
30
32

2. Assessment of urban European target markets
2.1 Use case prioritisation
2.2 Target market identification

35
36
42

3. Survey-based assessment of public acceptance of UAM in the EU
3.1 Survey methodology
		
3.1.1 Quantitative survey methodology
		
3.1.2 Qualitative survey methodology
		
3.1.3 Noise test methodology

49
50
50
57
58

3.2 Survey results (10 key findings)
		
3.2.1 A positive initial attitude to UAM throughout the EU		
3.2.2 Strong support for use cases in the public interest		
3.2.3 Top 3 expected benefits: faster, cleaner, extended connectivity
		
3.2.4 Top 3 concerns: safety, environment/noise and security		
3.2.5 Safety: existing aviation safety levels are the benchmark
		
3.2.6 Environment: priority is protection of wildlife		
3.2.7 Noise: acceptable at level of familiar city sounds				
3.2.8 Security: need to build confidence and trust in citizens
		
3.2.9 Ground infrastructure: must be integrated well				
3.2.10 Regulatory authorities: must work together at all levels

61
61
66
68
70
73
75
79
85
86
88

Table of contents

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4. Expectations and options for action

93

5. Conclusions

99

Appendix 1

101

Appendix 2

103

Detailed information on target market identification
Detailed information on questionnaire structure
Detailed information on methodology of quantitative survey question types and questionnaire

103
122
126

Appendix 3

154

Bibliography

154

Definitions
ANSP: air navigation service provider
BVLOS: beyond visual line of sight
EASA: European Union Aviation Safety Agency
EIS: entry into service
OEM: Original Equipment manufacturer
Transforming vehicle: a vehicle that can drive on the road and fly, e.g. a flying car
NASA: National Aeronautics and Space Administration
UAM: urban air mobility
VTOL: vertical takeoff and landing
Conjoint analysis: trade-off survey method to evaluate relevance and extend of decision factors
eVTOL: electric vertical takeoff and landing
UAS: Unmanned Aircraft System, i.e. an unmanned aircraft, i.e. without a pilot on board, and the equipment
to control it remotely
Manned / unmanned aircraft: an aircraft with a pilot/ without a pilot on board
Autonomous aircraft: an aircraft flying without the assistance of a dedicated pilot

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Introduction

Background and context of the study
Congested streets and pollution are already a reality in several European cities, as indicated by the TomTom Traffic Index
2020 and the Air quality in Europe 2020 report by the European Environment Agency. With the population of cities
in the European Union set to grow to more than 340 million citizens by 2030, there is a risk of increased pollution andcongestion. In this context, local authorities are looking at smarter, greener, more integrated and sustainable mobility
solutions.
Urban Air Mobility (UAM) has the potential to respond to these needs. Air transport of goods and people is no longer
science fiction and will become a reality in European Union cities soon. Adding a new dimension to urban transportation
will allow air transport of goods and people and may also help to make a leap towards smarter and more sustainable
cities. Urban Air Mobility is expected to bring environmental benefits as well as advantages for citizens and businesses –notably for commercial or emergency/medical purposes.
A key enabler for the development of Urban Air Mobility solutions was the significant reduction in lithium-ion battery
cell costs to 110€/kWh in 2020 from 1000€/kWh in 2010, as well as the increase of cell energy density to approximately
300 Wh/kg from approximately 150 Wh/kg in the same timeframe.1 The experiences gained with the development ofelectric vehicles in the automotive industry have also influenced the development of UAM globally and in Europe. The
European industry has played a leading role in the development of UAM since the first flight of a manned eVTOL proofof-concept by Volocopter in 2011. There are also several other European companies developing UAM aircraft at the
moment, for example Airbus, Ascendance, Lilium, Pipistrel, Quantum Systems, and Tecnalia.
Objective of the study
This breakthrough in urban mobility needs to be accompanied and supported by relevant measures, in particular anadequate regulatory environment, which would reflect the needs and aspirations of European society and provide astable and clear framework for the industry. The first step consists in measuring EU citizens’ willingness to accept thisnew mode of transport and collating their possible concerns and expectations, for instance related to safety, security,
privacy and environmental impact.
The European Union Aviation Safety Agency (EASA) launched a comprehensive study on the societal acceptance of
UAM across Europe in November 2020. The study included research work, literature review, as well as a survey witharound 4000 residents of six European cities. These survey cities – Barcelona, Budapest, Hamburg, Milan, Paris andthe cross-border region Öresund – were identified as potential target markets for the future deployment of Urban Air
Mobility. The quantitative survey was complemented by more than 40 qualitative interviews with focus groups of local,
national and European stakeholders as well as by a noise perception study with a group of 20 European residents.
EASA ambition
The study on societal acceptance is only one aspect of EASA’s work to support the deployment of UAM in the EU.
EASA’s ambition is to anticipate this new mode of transport and provide an enabling comprehensive regulatoryenvironment, allowing the EU to establish itself as one of the first global movers in this field.

1 Bloomberg NEF

Definitions / Introduction

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Work has started and initial actions have been taken. EASA has prepared a number of regulatory documents, the latest
one being the first worldwide regulation on U-Space recently adopted by the European Commission. The SESAR JU
defines U-space as follows: “U-space is a set of new services relying on a high level of digitalisation and automation offunctions and specific procedures designed to support safe, efficient and secure access to airspace for large numbersof drones. As such, U-space is an enabling framework designed to facilitate any kind of routine mission, in all classesof airspace and all types of environment - even the most congested - while addressing an appropriate interface withmanned aviation and air traffic control.” The full overview of these documents is provided in Appendix 1.
The results of the study will be considered by EASA in the preparatory work for a future regulatory proposal for the socalled high risk operations of the specific category of drones and for operations of the certified category of drones andmanned VTOLs in urban environments. They will also serve to raise awareness about UAM across the EU as a means offostering public adoption.
Scope of the study
The terms ‘Advanced Air Mobility (AAM)’ and ‘Urban Air Mobility (UAM)’ are both in common use. As can be seen in
Figure 1, AAM covers passenger and cargo transport as well as other aerial missions in urban, regional, and interregional
geographies. UAM can be understood as a subset of AAM, which covers transportation systems that move people or
cargo by air in and around urban environments.2 In the absence, as yet, of agreed standard definitions, the term “Urban
Air Mobility” is used in the context of this study, as it explicitly refers to the specific context of the operations, i.e. in cities
and densely populated environments, and is therefore more easily understood by the general public.
In this report, “urban” is defined according to the functional urban area concept used by Eurostat: “A functional urban
area consists of a city and its commuting zone. Functional urban areas therefore consist of a densely inhabited city and aless densely populated commuting zone whose labour market is highly integrated with the city (OECD, 2012)“.

2 https://www.easa.europa.eu/sites/default/files/dfu/easa_drones_section.pdf

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Advanced Air Mobility is a more inclusive
Figure 1: AAM covers a wider scope than UAM
deﬁnition of UAM
No explicit mention

Included scope in AAM and UAM deﬁnitions
Use cases
Passenger
AAM

Explicit mention

Geographic reach
Cargo

Operations

Urban

Regional

Interregional

FAA
NASA
NASA
Deakin Uni.

UAM

NASA
SESAR JUFAA
Deakin Uni.
Jonkoping Uni.
MITRE Corp
UC Berkley
TU MunichFurthermore, the scope of the study was intentionally limited to:• The transportation systems that move people or cargo by air in and around urban environments for commercial or
emergency service operations. Other use cases, such as infrastructure assessment, surveillance, 5G emissions orstate operations (e.g. military, police surveillance) were excluded. The transportation of goods or people is indeed
adding an additional risk that may require specific attention;• Drones and manned VTOL aircraft with electric propulsion systems were the focus for this study. Other vehicles suchas traditional helicopters or transforming vehicles (e.g. flying cars or motorcycles) were excluded as the focus should
remain on new types of vehicles intended for use in urban airspace;• A 10 year timeframe, i.e. until 2030: for this reason, the study focused on manned VTOL (i.e. with a pilot on board) for
the transport of people, as it appears unlikely that unmanned transport of people in urban environments may takeplace within that timeframe;• The European Union, although global developments were taken into account for information purposes.
This report was created based on the best knowledge of the involved parties at the time of writing. However, due to thefast pace of this emerging industry the stated content might be subject to change in the future.

Introduction

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1. Research andliterature review
This first chapter contains information on the literature reviewed and the research done to set up the study on societal
acceptance in general. This preparatory work ensured that the starting point was the most up-to-date state of science,research and market development.

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1.1 Literature review
To lay the foundations for the study on societal acceptance of Urban Air Mobility (UAM) as well as to collectinitial data and information to build the quantitative and qualitative survey, a thorough literature review
from two different perspectives was carried out:
1) The UAM market and UAM-related societal acceptance factors
2) Insights about relevant societal acceptance factors from adjacent technologies, such as autonomous
driving, smart home and other emerging technologies.
The review focused on the UAM market and related societal acceptance factors, as core objectives of thisstudy. Literature reviewed included recent publications, i.e. not older than three years, in English and other
European languages, from academia or other publicly-accessible sources.

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Methodology
The methodology used to filter publications was the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) framework. This framework is a systematic process for filtering publications for duplicates,
relevance, and eligibility.
Figure 2 shows that this process was applied to all UAM 130 publications identified through search terms (n=60) as
well as publications identified through other sources (n=70). As a first step, 19 duplicates were removed from further
consideration. The next step involved a check for relevance: here 20 publications were excluded, as they were either
published before 2017, did not cover the UAM space at least partially, or did not mention UAM use cases or societal
acceptance factors. In the last step only publicly available publications, which are available free of charge, passed theeligibility filter; the others (n=15) were excluded. This left a total of 76 publications for consideration during the detailed
UAM literature review (see Bibliography).
16 publications were identified for the review on societal acceptance factors for adjacent technologies, such as
autonomous driving and smart home. There were no duplicates, but three publications did not pass the relevance test
as they were either published before 2017 or did not cover societal acceptance factors. Another three publications did
not pass the eligibility test as they were not publicly available. This left a total of ten publications for the comparison ofsocietal acceptance factors for smart homes and autonomous driving with UAM.

Figure 2: Application of PRISMA framework for UAM literature review
Publications
identified

Articles identified through search terms(n=60)

Additional research findings identified
through other sources (n=70)

Articles and research findings after
duplicates removed (n=111)

Relevance

Articles and research findings screened on
basis of title and abstract (n=111)

Articles and research findings excluded(n=20)

Eligible

Full-text articles and research findings
assessed for eligibility (n=91)

Full-text articles and research findings
excluded, with reasons (n=15)

Included

Articles and research findings included inqualitative synthesis (n=76)

Source: Adapted from The PRISMA Group (2009)

1.1 Literature review

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Summary of insights
As shown in Figure 3, a considerable increase in the frequency of UAM-related publications can be observed between
the years of 2017 and 2020.
Figure 3: Origin and timing of publications

HQ region of publishing entity, %Origin of publications, %Asia Africa

Other

Governments

9

7

1

Academia

Industrygroups8

Manufacturers

North
America 30

43

62

13

Europe18
Consultancies

Publications increasing significantly in recent years
%

47%

25
18
8
1%
2017

18

19

20

2021

It can also be seen in Figure 3 that:• More than a third of the publications included are from academia, with contributions from leading entities such as TU
Munich, Fraunhofer, Massachusetts Institute of Technology (MIT) and the National Aeronautics and Space Administration(NASA). Consultancies and manufacturers within UAM are the other main contributors of recent publications.
• More than half of the included publications originate from entities with their headquarters in Europe, indicating thatleading authorities in the emerging UAM industry tend to be based in Europe. The region with the second highest numberof publications was North America. However, the relatively small number of publications from Asia and Africa could be
related to the focus on publications in English and other European languages.

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In order to gain an understanding of the UAM market, literature contributions were evaluated in terms of:
•
•
•
•
•
•

use cases,
challenges,
societal acceptance factors,
stakeholders,timelines,
target markets.
The key results of this evaluation are summarised in Figure 4 and moredetailed in the following Figures. The use cases most frequently mentioned
in publications are air taxis, drone delivery and rescue drones. The main
challenges raised are infrastructure and safety. Noise and safety were listed
as the major societal acceptance barriers. Entry into service (EIS) timelines
differ significantly between piloted and autonomous vehicles, with mostcertification or EIS for piloted operations being planned for around 2025.
Unmanned or autonomous operations are expected to start entering themarket not before 2030, according to statements made by the OEMs in theInterest in UAM increased
in recent years
Initially, 130 publications were identified
and still 76 of them – published since 2017
– were analysed and considered in the
study. More than half of them originate
from entities with their headquarters in
Europe. The frequency of publications
increased recently, showing a growinginterest in the topic.

reviewed literature.

Figure 4: Key insights from the literature review

Most often named …
…use cases
Taxi

Air Taxi
Drone delivery…challenges 2…societal acceptance barriers3

11% Infrastructure

18% Noise

9% Safety

17% Safety

Rescue drone1

Number of mentions with regard to expected start of entering the market
Piloted

6

Autonomous

4
2
0
2022

2023

2025

~2025

~2030

2030+

~2035

~2040

1. Transporting a first responder to the location of an accident
2. Share of the 173 mentions regarding challenges (multiple per publication possible)
3. Share of the 188 mentions regarding societal acceptance (multiple per publication possible)
Source: Literature review

1.1 Literature review

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1.1.1 UAM use cases found in literature
Cases that were found during the literature review can be grouped into five functionally distinct groups.
1) Passenger transport
The most frequently mentioned passenger transport use case is the air taxi. Here, passengers will initially use UAM
aircraft to travel from one vertiport to another. Eventually it may be possible to hire an air taxi in a street or park close
to the starting point and land in a street or park next to the destination. Quickly flying an emergency doctor to thesite of an accident is the application mentioned second most frequently.
2) Delivery
The most often described use cases are package and food delivery by drones into private gardens or properties, andpackage delivery by drones into a central delivery hub. A number of publications also describe the usage of drones
for time-critical medical applications, such as the delivery of organs or stored blood.
3) Civil surveillance and other operations
The autonomous inspection and/or maintenance of bridges and other infrastructure is expected to be the major
operations use case. Other operations use cases include precision agriculture and the preliminary visual assessmentof incident sites, such as assessing the extent of fires and accidents.
4) Sovereign functions
The top-ranking application of UAM aircraft in this group is police surveillance.
5) Signal emitting
Emitting signals for multimedia applications or internet access was only mentioned in two publications.

1.1.2 Expected challenges identified in literature
Figure 5 provides details on the expected challenges for UAM. 50of the 76 reviewed publications mentioned challenges, where theInfrastructure named
leading challenges are related to infrastructure, safety and noise.
as leading challenge inIn this categorisation, while technology covers a large variety ofexisting literaturetechnological solutions, it mostly refers to battery electric propulsion
Based on literature, biggest challen-ges
systems and their current limitations in terms of energy density andfor UAM are expected to be related tooverall weight. Environmental impact is a term used generically ininfrastructure, safety and noise. Namely:
the reviewed literature and can include a plethora of topics such as• Finding suitable locations / buildings
noise, visual pollution, air pollution, land use, protection of species andfor Vertiports
biotopes, climate, natural resources, water and soil.
• Aiming for safety level similar/equal
to commercial aircraft• Achieving low noise level for bettersocial acceptance16

Societal acceptance, the focus of this study, is not listed among theoverall top five challenges for UAM, but is an important dimension for
EASA as its role is to serve the general public in its actions.

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Figure 5: Challenges for UAM

Challenges for UAM1%
Infrastructure
SafetyNoiseTechnology
Environmental impact
Regulations
Air Traffic Management
Certification
Communications
Cost
Economics
Societal acceptance
Public acceptance
Legal framework

11.0

2.3

Operations
Public perception
Security

2.3
2.3
2.3

8.7
8.7
8.1
7.5
6.9
4.0
4.0
4.0
3.5
3.5
3.5
2.9

Generic term used inliterature – may include
noise, visual pollution, air
pollution, land use,
protection of species &biotopes, protection ofwater & soil, climate, andnatural resources.

1. Share of the 173 mentions regarding challenges (multiple per publication possible);

1.1.3 Societal acceptance factors identified in literature
Although most publications do not mention societal acceptance asa main challenge, 61 of the 76 reviewed publications mention social
Main societal acceptanceacceptance factors. Figure 6 summarises the main insights fromfactors are comparable
literature. Noise and safety are the leading factors mentioned by ato those of other smart
technologies
large margin. Combined, they constitute 35 percent of all 188 mentionsof an acceptance factor within the publications reviewed. Most of the
If comparing acceptance barriers fortime, safety refers to the safety of an occupant of an air taxi, but it does
Urban Air Mobility with those of otheralso include people on the ground. Environmental impact has the same
smart technologies, it is noticeable thatwide definition in literature as for UAM challenges. Increased travel
they are similar. Safety is the leading
options refer to the provision of an additional mode of transport for
acceptance factor for autonomousa certain route. This metric has diminishing returns as it provides thedriving – which is in line with the findings
highest benefit if there is no other option to travel an intended routefor UAM. Probably because bothwithout UAM, but only contributes a small benefit if there are, forsolutions carry goods and passengers.
example, four other modes of transport available.
Privacy on the other hand is also a top
concern in the smart home space.

1.1 Literature review

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Figure 6: Societal acceptance factors

Societal acceptance factors1%
Noise
SafetyPrivacy
Benefits for self or community
Visual annoyance
Environmental impact
Increased travel options
SecurityAffinity to automation
Data concerns
Perceived usefulness
Trust
Willingness to share (ride)
EthicsJob loss concerns
Lack of experience
Misuse
Price

18
17
6
5
5
4
3
3
3

Generic term used in literature and may
include noise, visual pollution, air
pollution, land use, protection of
species & biotopes, protection of water& soil, climate, and natural resources.

2
2
2
2
2
2
2
2
2

1. Share of the 188 mentions regarding societal acceptance (multiple per publication possible)

Comparison with societal acceptance factors for smart home and autonomous driving
As explained at the beginning of this section, literature for adjacent technologies, such as smart home and autonomous
driving, was also reviewed for societal acceptance factors. The literature reviewed is indicated in the Bibliography andthe findings are displayed in Figure 7.
Safety was a leading acceptance factor for autonomous driving. This is in line with the findings for UAM and could be
explained by both topics being mobility solutions carrying goods or passengers. Noise, on the other hand, does notappear as a major topic for autonomous driving, as a level of noise comparable to current passenger cars seems to be
acceptable.
Privacy is also a top-ranking concern in the smart home space, which potentially explains the lower usage rate for thistechnology in Western Europe compared to the United States.
In the reviewed surveys for the acceptance of autonomous driving, the survey participant’s openness to and interestin new technologies has a stronger influence than their sociodemographic background, such as age, gender, or
employment status. With both autonomous vehicles and smart homes, participants with a positive attitude towards
the technology were more likely to use it.

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Figure 7: Societal acceptance barriers for smart homes and autonomous driving

Privacy

Noise

Noise
Privacy Privacy
Noise15%
No major concerns about noise of cars or busses in
Smart Home penetration rate in West Europe
No major
concernsof cars or busses in
Smart
Home penetration
ratein WestSmart Home
penetration
rate in West
Europe15%Europe
No15%
major concerns aboutnoisecarsidentified.
or aboutbussesnoise
in
the
EU of
were
The level of noiselower
incomparison
to
the
USA.
Major
adoption
Noise theNoise
Privacy lower
PrivacyEU
wereidentified.
The
level
of noisein comparison
toMajorthe USA.
Major adoption
lower in comparison
to
the
USA.
adoption
the EU were identified. The
level of noisecomparable
comparable
to anaveragepassenger
seemsinto
barriersin theEU areprivacy,interoperability,No
major
concerns
No
major
about
concerns
noise
about
of
cars
noise
or
bussesofcars
inorcarbusses
Smart
Home
Smart
penetrationHome
penetration
rate
in
West
rate
EuropeinWest
15%Europe15%
comparable
toanaveragepassenger
car
seems
to
barriers
in
the
EU
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1.2. Industry status and projection

This section of the report provides an overview of the industry status, including UAM aircraft types, use caseapplications for these UAM aircraft and the UAM stakeholder environment.

Overview
As of 2021, the UAM market is still in an early stage, while showing increasing momentum. Many start-ups and companies
are emerging across the entire value chain. In particular, the eVTOL manufacturing and Original Equipment Manufacturer(OEM) sector is rapidly evolving. More than 200 eVTOL designs and concepts are currently being investigated anddeveloped with many prominent ones like Volocopter, Joby, Lilium, Airbus, or Kitty Hawk. Some of these air vehicle
systems are already in advanced certification stages. Europe is leading with many OEMs such as Volocopter, Airbus, Lilium,
Ascendance, and Pipistrel in advanced certification stages and a significant number of pilot regions and projects, forexample in Frankfurt, Paris, Cologne and Dusseldorf, Linz, Helsinki, and Ingolstadt (see Figure 8 and Figure 9).
Figure 8: Passenger vehicle certification announcements (non-exhaustive)
First manned flight

European

2016

2017

2018

Expected certification, i.e., commercial rollout possible

2019

2020

2021

2022

2023

Announcements
2024+ made for EU
Frankfurt, Paris in
2021 (test flights)

Public test flights in Stuttgart Helsinki and Singapore

N. a.
N. a.
Cologne andDusseldorf in 2025
Linz in 2021
(test flights),
Seville, and Llíria

No certification for current model in Western countries

N. a.

Currently manned test flights
in New ZealandN. a.

Design stage

N. a.
Design stage
N. a.

Test flight certification

N. a.
N. a.

Design stage

N. a.

Design stage
2024
Design stage

N. a.
2026
2024

Design stage

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8A0846_Report_Spreads_210518_Langversion.indd 21

N. a.

N. a.
Paris

2024

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Figure 9: Cargo vehicle announcements: (non-exhaustive)
European

2016

First manned flight

2017

2018

Expected certification, i.e., commercial rollout possible

2019

2020

2021

2022

Part 135 certified for in the US

2023

Announcements
2024+ made for EU
Helsinki in 2020
Testing in France andAustria
Ingolstadt in 2022
N. a.
N. a.

Design stage
N. a.
Design stage
N. a.

UAM vehicle types
In general, UAM aircraft layouts for vertical take-off and landing (VTOL) can be categorised into three archetypes:
i. Vectored thrust
The same propulsion units first provide lift during the hover and then swivel to create thrust in the cruise phase. During
the cruise phase, lift is generated by the wings. This layout is better suited to longer-distance flights, as the system ismore efficient but more complex than the other concepts. An example can be seen on the left side of Figure 10.
ii. Lift + cruiseThis layout has separate propulsion units for the hover and cruise phases. Wings create the necessary lift during thecruise phase. Lift + cruise is suited to shorter distance flights than vectored thrust, but to longer distances than wingless.
It is potentially easier to certify than vectored thrust because the propulsion systems are separate. An example can beseen in the middle of Figure 10.
iii. Wingless (multicopter)
Here the propulsion units are fixed in position and create lift all the time. This is the option that offers the shortest flight
distances and is overall the simplest concept, as it is avoiding any unnecessary movable parts (e.g. thrust vectoring). An
example can be seen on the right side of Figure 10.
1.2.1 Aircraft and Use Cases
In the following subchapters, the aircraft types and certification timelines of the main use case categories of this study(passenger transport, cargo transport, and emergency) are discussed. Detailed statements related to autonomy levels,

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Figure 10: UAM vehicle types

Vectored Thrust

Lift + Cruise

Wingless (Multicopter)

Thrusters used for lift
and cruise

Independent thrusters
used for cruise as for lift

Thrusters only for lift,
cruise via rotor pitch

ExampleHyundai SA1 eVTOL

Wisk (Kitty Hawk) Cora

Volocopter 2X

Benefits

Optimized for both hoverand cruise

Redundancy benefits ofmulticopter without collective or
cyclic actuation

High redundancy and simple
controls

Lift provided by wings for
cruise for highest efficiency
Highest cruising speeds

Wing configuration allows formore speed in cruise

Significantly quieter thanhelicopters
Lower maintenance andlightweight

Implications

Greater mechanical
Suboptimal for both hover
Slowest cruising speeds/least
complexityorcruiserange, energy consumption and required ground infrastructure are not presented in theefficient
following as these are kept

confidential by the relevant actors.
Passenger transport aircraft
The commercial transport of people by UAM aircraft is covered by this segment. This can be, for example, a flightbetween a city centre and an airport, flights within a metropolitan area, or flights within a city for sightseeing.
For the passenger transport use cases, vectored thrust (i) appears to be a preferred solution, with 7 out of 16 of theconcepts reviewed opting for this solution (e.g. Bell, Hyundai and Joby). This is followed by lift + cruise (5 out of 16, e.g.
EVE, BETA and Wisk), and finally wingless (4 out of 16, e.g. Airbus, Volocopter and EHang). Planned passenger numbers
range from one to five.
Source: Hyundai, Wisk, Volocopter, evtol.news, NASA.gov

Passenger, cargo and emergency use cases and potential vehicles
For passenger transport use cases, (i) vectored thrust
appears to be the preferred solution for OEMs. Mostof them plan to start operations with a pilot on board.
First certifications for passenger transport use cases
are estimated for 2022. To ensure infrastructureneeded, vehicle manufacturers, cities and infrastructurecompanies are cooperating. Most of this is happening inEurope right now.

Most concepts plan to fly autonomously from the
beginning and have a payload between 0.7 to 200 kg.
First operational certifications are already achieved.
For emergency use cases, (iii) wingless vehicles are
preferred, all planned to be remote controlled. They cancover transport of medical emergency personnel to an
accident site, patients to a hospital but also e.g. direct
firefighting.

For cargo transport use cases, (ii) lift + cruise is thepreferred archetype for OEMs, followed by wingless.

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Most OEMs plan to start operations with vehicles with a pilot on board (e.g. Volocopter, Lilium and Bell). Very few plan
to start operations with fully remote controlled or autonomous vehicles (e.g. EHang and Wisk). All concepts are poweredby a battery electric propulsion system, except for those from Moog and Ascendance Flight Technologies, which utilise ahybrid electric propulsion system.
The earliest estimated certification year for the companies reviewed within the passenger transport use case is 2022
(for Volocopter), followed in 2023 by Airbus and Joby. The bulk of players (e.g. Lilium, EHang, Wisk etc.) announced
they would expect certification in 2024 or later. The most ambitious timelines were four years from the start of thedesign phase to planned certification for Vertical Aerospace and Ascendance Flight Technologies. Both companies are
currently in the design phase. The European OEMs Lilium and Volocopter were among the first to start development ofpassenger transport aircraft.
UAM ground infrastructure
Dedicated infrastructure is required for the initial operation of UAM passenger transport. ‘Vertiports’ will probably
appear in different sizes and numbers in different cities, depending on expected traffic volumes. The largest vertiports
will be the fewest in number in a city, and the smallest ones will be the most numerous. Figure 11 indicates potential
numbers for different city archetypes in mature UAM network state. The number of landing pads is different for thethree vertiport types, with vertipads only having one or two, while a vertihub can have around ten landing pads. The
number of landing pads per vertiport multiplied by the respective number of vertiports in a city results in the total
landing pad number.

Figure 11: Urban Air Mobility infrastructure may come in scalable size types

24

Large cities

Medium cities

Large, dense, high-income urban city, e.g.,
Paris, Berlin, Madrid, Hamburg, Vienna,
BarcelonaMedium, less dense, medium income,urban/suburban city, Sevilla, Lisbon, Dusseldorf,
Riga, Athens

Outposts, areas of interest or
private use

3-5

Vertipads

3-5

Major suburban commuting stations,private use for high net worth
individuals, or in wealthy suburbs

Near concentrations of highorigin and destination points

5-10

Vertibases

3-7

Major corporate headquarters, major
retail districts, and major commuting
stations

Major airports, city centres,
and major commute corridors

2-3

Vertihubs

1-2Main airport, downtown, and major
work district

40-60

Total landing pads

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What are vertiports?
Vertiports are needed to enable take-off
and landing of air taxis. They are expected
to appear in different sizes. Depending on
the traffic of a city, number of vertiports willvary.
At the moment, the development ofvertiports seems to be mostly throughcollaborations between experienced infrastructure players and UAM vehicle manufactures.

Two important factors for locating vertiports will be the ease ofaccess to them, as well as the electricity infrastructure connection.
As the energy for the operations of most UAM aircraft will beelectricity stored in batteries, the recharging of the batteries
will probably happen at the vertiports and therefore a suitableconnection to the electricity grid will probably be required.

At the moment, the development of vertiports seems to be mostly
through collaborations between experienced infrastructure players
and UAM aircraft manufacturers, although manufacturers, havealso demonstrated development of some of their own concepts.
Some infrastructure players have also demonstrated concepts they
are developing on their own that would be compatible with various
UAM aircraft manufacturers. But at the moment the interoperability of these concepts is difficult to assess.
Europe seems to be a leading market for passenger transport, as demonstrated by the announcements of collaborations
between UAM aircraft manufacturers, cities, and infrastructure companies by the various regions, as can be seen in
Figure 12.
Figure 12: Vertiport announcements
Potentially open to all OEMs
Collaboration

EuropeNorth America

Asia

FranceUSA

Australia

Germany

Concepts for Joby (formerly UBER)

China

Italy

Singapore

OEMs without location

OEMs without location

OEMs without location

Cargo transport aircraft
This segment covers the transport of goods by UAM aircraft for commercial or industrial applications. This can include,for example, last-mile delivery, delivery to a hub, or rural delivery of supplies. The transport of emergency and medical
goods, such as organs and blood, is excluded from this category as it is covered by the emergency use case.

1.2 Industry status and projection

25
Source: Center for Future Mobility

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The delivery could be lowered via a winch on the UAM vehicle into the garden of the receiving person or organisation,or the vehicle could land on the roof of a multistorey building and the delivery could be picked up from there. Anotheroption is the delivery to a fixed station in the vicinity of the receiving person, similar to the self-service parcel terminals
already used today.
The lift+cruise aircraft is the preferred archetype in this category (with four out of eight OEMs using this concept),
followed by wingless (three out of eight) and vectored thrust (one out of eight). The stated payload of the concepts
ranges from 0.7 to 200.0 kg. Only two concepts will initially be remote controlled (EHang and Volodrone); the others are
already planned to be autonomous during initial operation. Six of the concepts use battery electric propulsion, while two
will use hybrid propulsion, which includes two or more sources of propulsion in one design (Pipistrel and AutoFlight).
Of the companies reviewed within the cargo use case, Wing and Amazon have already achieved operational certificationaccording to Part 135. From an aircraft point of view, Quantum-Systems is aiming for certification in 2022, while
Volodrone and Pipistrel are aiming for 2023. The other players did not state a definite target for aircraft certification andare mostly in the prototype stage.
From a European OEM point of view, quantum systems had already started development of a cargo vehicle with 0.7
kg payload in 2017, while Volocopter and Pipistrel announced plans for vehicles with a larger payload (200 and 460 kg
respectively) in 2019 and 2020.
Emergency aircraft
Aircraft for emergency-related use cases are summarised in this segment. These can cover applications such as thetransport of medical emergency personnel to an accident site, the transport of patients to a hospital, the evaluation of
emergency areas, direct firefighting, or the delivery of medical and emergency supplies.
The emergency UAM aircraft development does not seem to be a focus for European OEMs so far. Only Volocopter
collaborates with ADAC Luftrettung, a German non-profit air medical provider, on the use of Volocopter’s passenger
UAM for flying emergency doctors to accident sites. However, any passenger transport UAM could in principle beused for transport of a doctor, while for a patient transport a dedicated cabin modification would be needed. Thus,
aeromedical services are more dependent on the operations regulations.
Other aircraft reviewed in this category are all wingless since non-urban applications such as those by Zipline are out of
scope. Airobotics, DJI, IAI and Parrot plan to use vehicles for the visual assessment of emergency locations, while EHang
plans to use them for extinguishing fires in high-rise buildings. All concepts reviewed were remote controlled and will
have an electric propulsion system either powered by batteries or via a tether, for IAI.
No certification timelines were found for the five manufacturers reviewed (Airobotics, DJI, EHang, IAI and Parrot) in thissegment.

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1.2.2 UAM stakeholder environment
The emerging UAM industry and ecosystem is influenced by many stakeholders. The main UAM stakeholders can be
categorised into four groups along the value chain, as can be seen in Figure 13.
Figure 13: UAM vehicle types
UAM industry
Manufacturers, UAM operators, maintenance services, airport operators,
service providers, vertiports, communication providers, suppliers
Potential users
Urban residents, travellers, commuters, high wealth individuals, car users,
emergency services, public transport users
Potential
users
Governments,
publicinstitutions &regulators

UAM
industry

Indirectly
affected third
parties

Governments, public institutions & regulators
Supranational & national: EU institutions and bodies, EASA, air traffic control
organizations, EU member state governments, state authorities, military &policeLocal: Local authorities, municipalities, city officials, urban and city planners,
public institutions and organizations
Indirectly affected third parties
Private individuals: Residents, communities, real-estate owners, citizens
Professionals: Pilots, academia, innovators
Associations: Local environmental protection associations, local traveller's’associations, unions, lobbies, associations, environmental groups

Major influence on societal acceptance-

Stakeholders at all levelare important for societal
acceptance of UAM
Urban Air Mobility needs to meet expectationsof a wide variety of stakeholders. This involves
reconciling different social acceptanceperspectives.

Extended industry: Airports, aerospace & automotive industry, energy
providers, public transport providers, insurance providers, ticket brokers,
businesses in other industries potentially interested in entering UAM space

The following section covers the different stakeholder groups inmore detail and lists their motivation, expectations, and concerns.
The UAM industry stakeholder group includes all entities directly
involved in the development, manufacturing, operation, andservicing of UAM aircraft and services. The main motivation for thisgroup is generating a profit from their activities. They may also be
motivated by advancing technologies, keeping or increasing their
number of employees, or being a first mover.

While working on UAM topics, this group may hope for a stable regulatory framework, minimal levels of bureaucracy,
support for building up a new industry, access to a qualified workforce, and beneficial taxation. Their main concerns
could be the impact of regulation on the economics of UAM, excessive regulation, public opinion, nimbyism, andenvironmental issues.
For the potential user stakeholder group, time and cost savings, as well as comfort, are some of the main decision
criteria for selecting a mode of transport. The expectations of the potential user group for UAM will probably be safety,

1.2 Industry status and projection

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reliability, predictability, affordability, ease of use, and convenience. Topics they may have concerns about are noise,safety, environmental impact, benefit for self and/or the community, automation, and accessibility.
From the governments, public institutions, and regulators group viewpoint, three different levels of political structures
come into play: supranational, national, and local. The focus for this stakeholder group is the public good, safety of the
public, an efficient mobility system, limitation of congestion and pollution, the creation of jobs, supporting and building
up an industry in their respective jurisdictions, the environment, and public opinion.
The expectations regarding UAM are probably that it should generate a positive contribution to the community,
contribute income tax that finances governmental tasks, and that the industry complies with regulations. The mainconcerns are likely around public opinion, loss of life, impact on voters, prestige for their respective jurisdictions, underor over-regulation, and environmental issues.
Members of the indirectly-affected third-parties group may be impacted by an evolving UAM industry. They canbe further divided into private individuals, professionals, associations, extended industry, and potential competitors.
UAM will most likely be evaluated by this stakeholder group through the lens of the benefit for oneself and/or for society.
Opportunities for growth and development are the probable expectations from this group and becoming irrelevant or
losing job security may be some of their concerns.

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1.3 UAM high level societal benefits and risks
The introduction of new technologies comes with benefits and risks for the users, but also for the generalpublic. The following section reflects the high-level societal benefits and risks initially identified through theresearch and literature review. These elements were then used to build the survey questionnaires and werecompared ultimately with the results of the survey (see Conclusion).
1.3.1 Benefits based on market models, literature and expert interviews
UAM will have societal benefits for the EU and Europe. These benefits come in a variety of dimensions, as
shown in Figure 14.
The estimated market size of UAM in Europe, including R&D, vehicle manufacturing, operations andinfrastructure construction, will be approximately EUR 4.2 billion in 20303 , which represents almost
one third of the global market and hints at the opportunity that this industry may offer for Europe. The
estimated market size may create or sustain approximately 90,000 jobs in 2030, based on labour spendingfor constructing related infrastructure and operating the UAM. Manufacturing jobs are not included, as
the whole supply chain setup is still uncertain. If we visualise what this market size would mean for the Paris
metropolitan area in terms of UAM aircraft, the estimates range from approximately 3,000 to 3,500 UAM
aircraft for passenger and cargo transport in 2030. In this estimate, UAM passenger aircraft represent thesmallest part with numbers between 160 and 180, whereas the estimates for the UAM cargo aircraft anddelivery drones range from 2,840 to 3,300.
Local emissions by UAM, in the city environment, could be almost zero if battery electric propulsion
systems are used. Most of the reviewed UAM concepts already rely upon this propulsion type, with aminority working on hybrid electric propulsion systems.

3.

30

Source: McKinsey Center for Future Mobility UAM Market Model

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One of the major benefits of UAM for users will be time savings. For example, a city-to-airport transfer in Paris by air taxi
could 2 to 4 times faster compared to a car journey on a Thursday evening during rush hour. Also, medical transportationof equipment or organs could be performed approximately 73 percent faster by drone than by ambulance, taking theexample of a trip in Berlin on a Thursday evening, during rush hour.
If UAM passenger transport achieves the same level of safety as aviation did within the EU in 2018 (0.01 fatalities per
billion passenger kilometers), it would then be approximately 1,500 times safer on a passenger-kilometer basis than roadtransportation. This number is based on data for road transport and commercial air transport in the EU. As a first step000
the fatalities per million passenger kilometers for both modes of transport
and in a second~90
step these~4.2werebncalculated€
respective numbers were put in proportion.
jobs created in the Europe in 20303
1~4.2 bn €market size in Europe in 2030

15-40 min

~90 000

saved in average on travel time100%
by UAM for a city to airport
5transfer~31%
15-40 min
~90 000
reduction of local emissions forelectric propulsion4100%
3of global UAM market
besaved toin averageon travel timejobs created in the Europe in 2030
1
~73%
located in Europebyin
2030forUAM
a city to airport
reduction of local emissions for54transfer
electric propulsion
faster delivery of organs
between
1 500
times

jobs created in the Europe in 20303
Figure14: UAM benefits for the EU and Europe
market size in Europe in 20301~4.2 bn €~31%market size in Europe in 20301
of global UAM market to belocated in Europe in 20301~31%

of global UAM market to belocated in Europe in 20301

100%
reductionof local emissions for
1 500 times
4electric propulsion
less likely to be involved in a fatal
accident compared to road transporta passenger
kilometre basis2
1on500times

city hospitals possible5
less likely to be involved in a fatal~73%
accident compared to road transport
on abetween
passenger kilometre basis2
faster delivery of organs
5city hospitals possible

less likely to be involved in a fatal
accident compared to road transport
on a passenger kilometre basis2
1.
2.
3.

1.
2.
3.

Based on McKinsey VTOL market model
Assuming same safety level as commercial air transport in the EU
Based on direct, indirect and induced jobs created by CAPEX and OPEX spendof UAM industry in Europe in 2030
4.
Compared to a helicopter with conventional kerosene propulsion
Compared
to a car drivea Thursday
1.5. Basedon McKinsey
VTOLonmarketmodelat 5pm
2.Source:
AssumingsameEurostat,safety level
as commercial
air transport in the EU
VTOL team,
GoogleMaps
3.
Based on direct, indirect and induced jobs created by CAPEX and OPEX spend
1.3 UAM ofhighlevelindustry
societalin
benefits
risks
UAM
Europeandin 2030
4.
Compared to a helicopter with conventional kerosene propulsion
5.
Compared to a car drive on a Thursday at 5pm

4.
5.

Based on McKinsey VTOL market model
Assuming same safety level as commercial air transport in the EU
Based on direct, indirect and induced jobs created by CAPEX and OPEX spendof UAM industry in Europe in 2030
Compared to a helicopter with conventional kerosene propulsion
Compared to a car drive on a Thursday at 5pm

Source: VTOL team, Eurostat, Google Maps

31

Source: VTOL team, Eurostat, Google Maps
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1.3.2 Risks and acceptance based on literature and expert interviews
There are also a few risks associated with the implementation of UAM in Europe (see Figure 15). Amongst the top
concerns in the literature or stated by experts are:• Noise: is perceived as a prevalent risk of UAM. This includes the noise generated by the vehicles when they take-off
and land, as well as while they are in flight.
• Safety: Ranks high among the risks of UAM mentioned in the reviewed literature, as an unsafe system could havewidespread implications for public acceptance.
• Privacy: Society may also be concerned about privacy, as UAM aircraft like air taxis and drones may fly above or
close to places of residence.
• Visual pollution: Was mentioned as a potential nuisance, which may hamper public acceptance of UAM and istherefore a risk to its widespread rollout.
• Job losses: Some jobs may become obsolete due to the introduction of UAM, and this could lead to resentment
against it. Affected industries could include logistics and taxi services.
• Environmental issues: The environmental impact of UAM may be almost zero on a local emissions level forbattery electric vehicles, but the required electricity still has to be generated and the vehicle components have to be
manufactured, assembled and eventually disposed of. Focus should be placed on reducing the overall environmental
impact of UAM aircraft during the design phase.
• Affordability: Another risk for UAM is the affordability of the services for a large part of society. If the services
are only available to more affluent individuals but the disadvantages (like noise) are borne by everyone, this could
hamper the acceptance of UAM within society.

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Figure 15: UAM risks for the EU and Europe

Noise"..there are certain threats that could
impede the sustainable and thus
successful introduction of UAM to ourcities, with noise being a prominent
limitation." (26)
Safety"The key areas of discussion to move
forward will be to meet, or exceed, thecurrent safety parameters with thesenew vehicles." (87)

Privacy"Civil liberties groups have privacy
concerns with widespread UAM
adoption..." (20)
Source: Bibliography ID 20, 26, 52, 53, 61, 87

Visual pollution"The sensitive topic of visual and noise
pollution must also be addressed." (52)Affordability"Public acceptance of these new systems
and services is imperative, driven by ...
...and affordability." (61)Obsolete jobs
"There is concern that autonomous
technology will render jobs obsolete acrossmultiple industries" (20)Environmental impact"Air pollution caused by pollutants
such as particulate matter, nitrogenoxides and ozone, as well as odour
nuisance should be avoided." (53)33

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34

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2. Assessment ofurban European
target markets
An extensive market analysis was performed to identify a list of EU cities where the deployment of local UAM markets
appears plausible in the years to come, due to the local conditions and needs. A further objective was to identify six cities
from this list where the quantitative survey could be conducted. As respondents to the quantitative survey needed toinclude sufficient representatives of the cross-sections of the local population, only large cities with a minimum numberof inhabitants (300,000 for cities and 2,000,000 for cross-border regions) were pre-selected. This list is only indicativeand not exhaustive, and the absence of a city does not imply that UAM would not work well in that location.
Since the selection process was very comprehensive, only an overview and its methodology is given below, together
with the overall results. Further details can be found in the Appendix.

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2.1 Use case prioritisation
The review of international literature identified six categories of principal use cases for UAM deployment (see Figure 16):
Transportation (passenger transfer for commercial applications), delivery (transport of goods for commercial and industrial
applications), emergency services (response in case of an accident, fire, disaster etc.), civil surveillance and other operations(manual operations that physically interact with the environment), sovereign functions (surveillance and analytics of areas,
objects or people), and emitting (providing multimedia bandwidth by emitting signal/video/sound).
For each of these use case categories, societal risks and benefits were evaluated to identify those with the highest risks
and benefits, and a framework was created to break down benefits and risks into categories. This allowed us to understandwhich use cases are likely to be deployed in the EU in the next five to ten years and to include them in the survey.

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Figure 16: Transformation, emergency services and delivery are use cases with high risks and high benefits

Societal benefits
Low – Minimal or no benefits
for the majority of use cases
High – Implies
major risks
transporting
people, or
flying overpeople1 Transportation 2 Emergency(Passenger
transfer forcommercial
applications)34

Societalrisks

High – Significant benefits forthe majority of use cases

Operate(Manual operations
that physicallyinteract with theenvironment)

5 Sovereign functions(Surveillance andanalytics of areas,
objects or people)

services(Response incase of an
accident, fire,disaster, etc.)

Delivery(Transport of goods forcommercial and industrial
applications)6 Emitting(Providing multimedia
bandwidth by emitting
signal/video/sound)

Low – Minimal
or no new risks

The results indicate that three use cases have the highest risk and benefits, and are therefore very important candidates
for societal acceptance analysis: (1) commercial passenger transport by electric vertical take-off and landing (eVTOL) witha pilot onboard, (2) emergency services use cases (both medical equipment by drone and people transport by eVTOL witha pilot onboard), and (3) delivery transport by drones for commercial and industrial applications. These results also support
the request from the European Union Aviation Safety Agency (EASA) to include only people transport, goods delivery, andemergency services in the scope of the UAM target market analysis.
These three main use cases were analysed in detail and sub-use-cases were defined for each. The analysis centered on how
often sub-use-cases were mentioned in the literature review as well as during interviews with external and internal UAM
experts. For each sub-use-case, this analysis indicated whether it was a likely candidate for initial implementation in the EU,
its near-term viability for 2025 to 2030, and which benefits and risks it involved. Based on this evaluation, six priority subuse-cases were chosen for further analysis.

2.1 Use case prioritsation

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1. Passenger transfer use cases for commercial application
The sub-use-cases for commercial passenger transport were divided into three categories (see Figure 17 below):
intracity transport (under 40 km), suburb/region-to-city transport (under 100 km) and regional city-to-city transport(between 100 km and 300 km). Airport shuttle (A), sightseeing (C) and fixed metropolitan network (D) were identified
as the sub-use-cases with the highest benefits, lowest risks, and the highest viability for the initial UAM introduction in
2025 to 2030. They have therefore been chosen for the survey city-selection process (for more details see Appendix). As
can be seen in chapter 1.2 (UAM vehicle types), these operations will be piloted in the first years of introduction.

Figure 17: Airport shuttle, sight-seeing (loop) and fixed metropolitan network are most important passenger use cases
for the survey

3.Regional city-to-city(100-300km)

2.Suburb/ region-to-city(<100km)

1. Intracity transport(<40km)Category38

Use case

Description

Frequency of
publications andindications fromexperts interviews

In scope of city selection

2025
viability

Risks

High

Benefits

MediumLow

Alternatives

A Airport
shuttleRide from airport tovertiport located in city
centre (e.g., main rail
station)

Car, taxi,
subway, bus,
walking,bikingB Fixedurban
network

Aerial taxi for fastertravelling within dense
urban area

Car, taxi,
subway, bus

C Sightseeing(loop)

Pre-defined trip overiconic sights (e.g., Eiffel
Tower)

Bus, taxi,
walking

Fixed
Flights connections
D metropolitan within a metropolitan
networkover slow or often
congested routes

Train, public
transport

FlexibleE metropolitan
point topoint
transfer

Flexible routes, e.g., tocommute from residential
rural suburb to office in acity centre

Car,ridesharing,subway, bus,
walking,bikingF Fixedregional
network

Ferrying over slow oroften congested
routes withinregional span

Driving,ridesharing,train,
subway, bus

FlexibleG regional
point topoint
transfer

Flexibleintercity
network withinregional span

Helicopter,boat

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2.Emergency service use cases
The sub-use-cases for emergency services were divided into three categories: accident response, disaster management
and supplies delivery (see Figure 18 below).
First-aid and medical-supply delivery sub-use-cases were identified as the sub-use-cases with highest benefits, lowest
risks, and viability for initial UAM introduction in 2025. Therefore these have been chosen for the survey city-selection
process (for more details see appendix). For our purposes, first-aid (H) includes transport of medical emergency forces
to the site of an accident and these operations are expected to be piloted in the first years, as in the case of passenger
transport. Medical supply delivery (O) refers to the transport of blood or organs to an hospital (for example) and cansupport even faster delivery than existing modes of transport (see section “UAM vehicle types” for more information).

Figure 18: First aid and medical supplies are most important emergency use cases for the survey

3. Disaster management

2.Response in caseof an accident

Category

Use case

Description

In scope of city selection

2025
viability

Risks

High

Benefits

MediumLow

Alternatives

H First aid

Transport of medical
emergency forces to siteof accident, e.g., on
highways

Ambulance,car,helicopter

I Patienttransport

Transfer of injured orsick patient
to closest hospital

Ambulance,
helicopter, car

J Evaluationof adisaster/emergency
area

Drones with cameras
providing first responders
a real-time elevated viewof the situation, directing
emergency teams on
the ground

Helicopter,
Aircraft

K Observation Observation of a fireof a fireincident site drones withincident
thermal and visual cameras,siteenabling rapid and informed
decisions for firemen

Firefighting
team

L Firefighting

Firefighting
team

Firefighting with
firefighting
foams and extinguisher
bombs for high-risebuildings

M Emergency Rescue of people fromdisaster/emergency areas
rescue4.Supplies delivery

Frequency of
publications andindications fromexperts interviews

Helicopter

O Medical
supplies

Delivery of timecritical medical
supplies (blood,organs) to hospitals

Helicopter

P Emergency
supplies

Dropping of lifebuoys or
emergency supplies tocatastrophe regions

Helicopter

2.1 Use case prioritsation

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3. Goods delivery for commercial and industrial applications
The sub-use-cases for goods delivery were divided into two categories: last-mile delivery (e.g. the last section of the
supply chain, which delivers goods to their final destination) and long-distance delivery (see Figure 19 below).
The last-mile delivery category was identified as the priority sub-use-case having the highest benefits, lowest risk, andbest viability for the initial UAM introduction in 2025 to 2030 and has therefore been chosen for the survey city selection
process.
Figure 19: Last mile delivery holds the most important sub-use-case for the survey 2.2 Target market identification

6. Long distance delivery

5. Last mile1 delivery

Category

40

Frequency of
publications andindications fromexperts interviews2025
viability

In scope of city selection

High

Risks

Benefits

MediumLow

Use case

Description

R

Deliver to a
privateproperty(e.g.
garden)Fast delivery (e.g.
food or last minutegift) in urban area
to private residences

Car, bike,motorbikeS

Delivery toa hubGoods delivery (e.g.
retail goods) in urban
area to a hub along a
pre-defined route

Truck, car

U

Heavy
cargo

Forwarding ofcontainers
or bulk goods over aroutewith little
infrastructure

Ship, boat,
helicopter

V

Industrial
Transport ofapplications instantaneously
needed goods forindustrial applications,e.g., spare parts

Truck

W

Rural
deliveryof supplies

Truck

Grocery delivery tohome in area withlong travelling
distance to next shop

Alternatives

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2.2 Target market identification

Use cases most likely to be
deployed first (in the EU)
•
•
•
•
•
•

airport shuttlesightseeing
fixed metropolitan network
first aid
medical supplies
delivery to a private property

For each of the six prioritised sub-use-cases (airport shuttle,
sightseeing, fixed metropolitan network, first aid, medical supply
delivery and last-mile delivery), the project identified the most
attractive EU urban target markets – from a business perspective –for UAM OEMs and UAM operators. These target markets are likely
to see the first deployments of commercial UAM services in the EU
and were therefore deemed to be important candidates for societal
acceptance analysis.
To identify target markets for each use case, a four-stepmethodology was established:
1. European cities were pre-selected based on metrics relevant to the specific use case;
2. Pre-selected cities were ranked based on defined KPIs: the 15 cities with the highest ranking were selected for the
next step;
3. An infrastructure assessment, relevant to the specific use case, was performed for these 15 cities;
4. A timeline assessment (number of announced pilot projects, timelines of known pilot projects, implementation
feasibility by 2025) was performed for these 15 cities – this information was used for informative purposes only andnot for further selection.
Figure 20 shows the city selection process on the airport shuttle use case, as an example.

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Figure 20: City selection process for airport shuttle use caseI

Main steps

Selection of mostsuitable cities basedon identified
metrics

Proceeding

1

European cities
with highpopulation (>300 k)

2

Availability of an
airport)3

Number of
travellers between
the airport and thecity centre (>25k
passengers/ day)

4

High GDP/capita
level (>35k PPP in
EUR)

IIRanking of cities
based on KPIs

1

City size

2

Expected trip
volumes3

Distance between
airport and city
centre4

Travel time between
airport and city
centre with fastest
alternative travel
type in the rush hour5Congestion rate

6

Taxi price7

Suitable weather
conditions (% ofweather causes intotal arrival days,
precipitation inmm per year)

III
Infrastructure
feasibility
assessment

1

Availability of
inner-city spacefor heliports

2

Availability ofriver, highway or
corridor for noise
avoidance

3

Availability ofmobility offer for
onward journey(e.g., e-scooter,car-sharing)IV
Timing feasibility
assessment

1

Number ofannounced pilot
projects

2

Timeline of known
pilot projects

3

Implementation
feasibility
until 2025

Used for informative
purposes only and not for
selection

The detailed evaluation per use case is provided in the Appendix 2. Please find further information on the viability 1) for
airport shuttle use case, 2) for sightseeing use case, 3) for first aid use case, 4) for Last-mile delivery, 5) for Medical supply
delivery, 6) for fixed metropolitan/regional network.
After applying this process, a number of cities remained which were further prioritised according to a KPI system tailoredto the respective use case. Figure 21, on the example of the airport use case, shows how pre-selected cities were ranked
by KPIs to arrive at the 15 highest priority cities. The KPIs included: city size; expected number of trips; distance between
the airport and city centre; travel time between the airport and the city centre with the fastest alternative travel type (e.g.
taxi, car, or public transport) in rush hour; congestion rate; taxi cost for the journey to the airport; and suitable weather
conditions (percentage of weather causes in total arrival delays, precipitation in mm per year). A weighting factor was
assigned to each KPI to adjust that KPI’s impact on the overall ranking score.

2.2 Target market identification

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Figure 21: Target cities ranking process for the airport shuttle use caseRanking of cities based on further KPIs
KPI
1

2

3

4

5

6

7

Weighting
City size

25%

Expected trip volumes

25%

Distance between airport andcity centre

Travel time between airport andcity centre with fastest
alternative travel type in therush hourTimesaving 25%

Congestion rate

Taxi expenses for ride from airport tocity-centre

Suitable weather conditions (% ofweather causes in total arrival delays,
precipitation in mm
per year)

15%

10%

City

Ranking (100 =best suitability
for UAM)

Paris

88.2

Berlin

78.3

Rome

75.4

Munich75.3

Madrid74.8

Budapest

73.8

Prague

72.8

Milan

72.1

Barcelona

71.4

Dublin70.8

Vienna70.4

Brussels

67.8

Bucharest

67.4

Warsaw

66.8

Amsterdam

65.6

Stuttgart

63.9

Stockholm

63.0

Hamburg

62.8

Lyon

60.8

Frankfurt am
Main
Bologna

59.9

Bonn

59.6

Helsinki

58.2

Cologne57.8

Dusseldorf

56.8

Copenhagen

56.2

Toulouse

55.2

59.8

Based on this methodology, 90 potential target markets (15 cities x 6 use cases) were identified for initial OEM
introduction (‘long list’, see Figure 22 below).

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Figure 22: Potential target markets for the six prioritised use cases

People transportation
A
AirportshuttleCity
Parisshortlist Berlin
Rome
MunichMadridBudapest
PragueMilan
Barcelona
DublinViennaBrussels
Bucharest
WarsawAmsterdam

Cargo use cases

C

D
Fixed metropolitan
Sightseeing network (<120km)
Paris
Rome
Amsterdam
VenicePragueBarcelona
Florence
Budapest
BerlinFrankfurt am
Main
Stockholm
MadridAthensNice
LisbonBelgian central metro(Brussels)
Rhein-Ruhr region(Cologne, Düsseldorf, Duisburg,
etc.)
Rome metropolitan region
Milan metropolitan region
Barcelona metropolitan area
Rhein-Neckar region(Mannheim, Karlsruhe,
Heidelberg, Pforzheim, etc)
Stuttgart metropolitan region
Oresund region(Copenhagen, Hillerod, Malmo,
Lind)
Munich metropolitan region
Vienna metropolitan region
Paris metropolitan region
Rhein-Main region(Frankfurt, Darmstadt, Mainz,
etc.)
Warsaw metropolitan region
Stockholm metropolitan region
Noord-Brabant region(Eindhoven, Tilburg, Breda, etc.)

HFirst aid3
Last miledeliveryQ
Medicalsupplies

Paris
BerlinHamburg
Lyon
Marseille
Nice
GenovaPragueBrno
Budapest
Nurnberg
Stuttgart
Milan
Rome
DublinRotterdam
Hamburg
Helsinki
Tallinn
Bonn
Hanover
Cologne
DortmundDresdenDusseldorf
Essen
Leipzig
Bratislava
PragueMurciaCracow
Wroclaw
Bucharest
Warsaw
PoznanSofia
Budapest
DublinPraha
Brno
Vilnius
Hamburg
BerlinGdanskParis

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City selection for the survey
This long list was reduced to six major cities, taking into account the use cases with top rankings and city-average ranking
scores (across all use cases where the city was on the top 15 list). In addition, five guiding principles were established to help
ensure that the selected major cities were representative of different regions, cultures and city archetypes (see Figure 23).
Figure 23: Guiding principles for city selection
Aspiration

Guiding principle

Rationale

Different
regions

1. Our research focuses on different
regions of the European Union

Regional differences will influence thesocietal acceptance of UAM

Different
Culture2. We investigated regions with possibly
large cultural differences

Different cultural values will have an
impact on the societal acceptanceDifferentsizes

3. The focus of the research was on large
cities with the population >100 K
inhabitants

High traffic density, noise levels and UAM
risks will significantly influence the societal
acceptance in large cities

4. Medium and small size cities were
included, if they already announced
the attention to start pilot projects

Public awareness about upcoming pilot
projects will affect the societal
acceptance in small/medium cities

5. We analysed different cities
archetypes (dense/wide-spread,high/medium-income,urban/suburban city)

The societal acceptance will vary for
different city archetypes

Different
Archetypes

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-Cities selected for the survey• Barcelona• Budapest• Hamburg• Milan• Paris• Øresund cross-border region between
Denmark and Sweden

As a result of this process, Barcelona (Spain), Budapest (Hungary),
Hamburg (Germany), Milan (Italy), Paris (France) and Øresund(cross-border region of Denmark and Sweden) were chosen as sites
for the quantitative survey (see Figure 24). For further details on use
cases and the metrics used for the survey city-selection process, see
Appendix 2.

Figure 24: Final city selection and ranking
Target cities selection › Final cities

Our final cities selection covers all demographics, cultures andcities archetypes dimensions

X Top cities from KPI based evaluation
X City added to fulfil the guiding principles

City/Country

Country/Region

Ranking

Use case

City archetype1 ParisCentral Europe

100

Airport shuttle1
Sight-seeing, First aid

Large, very dense,
high–income city

2 RomeSouth Europe

87

Sight-seeing1
Airport shuttle, First aid

Large, medium dense,
medium-income city

3 Barcelona

South Europe

79

Sight-seeing1
Airport shuttle, First aid,
Medical supply

Large, very dense,
medium-income city

4 Hamburg

Central Europe

75

First aid1
Large size, medium dense,
Airport shuttle, Sight-seeing medium-income city

5 Budapest

East Europe

68

Medical supply1
Airport shuttle, First aid,
Sight-seeing

Large size, medium dense,
medium-income city

6 Oresund region

North Europe

20

Fixed metropolitan
network 1

Network of wide spread
medium size cities(Copenhagen,Hillerod, Helsingor,
Malmo, Lund)

1. Most relevant use case

5. Survey-based assessment of societal benefits and concerns for European citizens

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3. Survey-based
assessment ofpublic acceptanceof UAM in the EU
The stated goal of the survey was to assess and understand the most important societal-acceptance drivers for UAM
across cultures and regions in the European Union, including perceived benefits and concerns. This served both tocomplement available data from literature and to confirm this data for the specific EU environment. The results of thissurvey will further support the impact assessment and regulatory work of EASA.
The survey itself contained three parts:• A quantitative survey, with the participation of 3,690 citizens across six European cities, through a web-basedquestionnaire;• A qualitative survey, consisting of one-hour interviews with more than 40 stakeholders at local, national andEuropean level, informed by the results of the quantitative survey and aimed at better understanding theperspectives of different stakeholders;• A special noise perception survey with 20 participants was initiated to gain even more insights on how the noise of
UAM aircraft may be perceived by the public.
The following chapter describes the overall survey methodology (3.1) and provides the ten key survey results (3.2),
aggregating results from across three parts.
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3.1 Survey methodology
Advantages of an online
panel
Online samples are considered very
representative:• A broad section of the population
reacts to online surveys• Office workers are easier to reach(filling survey during the workday
and can participate at a time that’s
convenient for them)• Respondents provide more authentic
and detailed answers to open-ended
questions (as they may take the time
to reflect on their responses)• Various
visualisation
options(videos, logos, product images,
shelves, advertisements, TV spots,
radio spots, etc.) arise and survey
questions are better understood byparticipants.

Chapter 3.1 is divided into three parts: First, the methodology
for the quantitative survey is explained (3.1.1) in detail,including information on how participants were chosen, how
the survey was structured and how the questions were defined.
This section also provides a deep dive into the methodologyof the conjoint (or: trade-off) analyses. Then follows an
overview of the qualitative survey methodology (3.1.2) and themethodology for the noise acceptance study (3.1.3).
3.1.1 Quantitative survey methodology

Information on the panel of participants
The participant target for the quantitative survey was at least
600 individuals from each of the six cities being surveyed. To
ensure that participants were sufficiently representative of the
populations of the surveyed cities, nationally representative
distributions were chosen regarding gender, age, andemployment status. As a sample can never be perfectly
representative of a population’s distribution, technical criteria
were used to ensure the margin of error was kept as small as
possible. Screening questions were used at the beginning of thequestionnaire to ensure the fulfilment of quotas and to identify
other demographic features. These questions related to, forinstance, age, gender, type of household, place of residence, etc; More information on these screening questions canbe found in the Appendix (Questionnaire). The final demographic distribution of participants be seen in Figure 25.

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Figure 25: Panel selection across cities

Panel composition shows that representative distribution and quotas are met in total panel
Panel size = 3690 participantsAge, %

Gender, %
18-24

16

25-34

17

35-44

17

45-54

18

55-64
65-75

Family type, %

Male

49

Female51

Singles21

Couples46

Families

33

18
14

Education, %Employment status,%

Gross household income per year

Low (up to higher
schooling)

37

Full time (30+ h)incl. self-employed

53

Medium (up to finishedcollege or university)

44

Part time or student

19High (post-graduates orhigher)19

Not working, retired
and other29

Low(< 20k EUR)
Medium(20k - 60k EUR)
High(> 60k EUR)
Prefer not to say

21
45
23
11

To summarise the figures shown in Figure 25: :• Total numbers of participants across the six cities was 3,690;• Balanced gender distribution, as number of male and female participants were nearly the same (0.2 percent diverse,
other, or preferred not to answer). The shares of male and female participants had to be at least 48 percent each. As
women usually tend to be more responsive to online panels than men, it was important to maintain a balance between
the genders, but a margin of error of 1 to 2 percent is considered a statistically acceptable range;

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• Participant age was relatively evenly distributed between 16 and 75 years. At least 15 percent of participants wererequired to be in each of the age groups 18 to 24, 25 to 34, 35 to 44, 45 to 54 and 55 to 64, and 10 percent in the
65 to 75 age group. The age group 65 to 75 years was not required to be as large as other groups as this group is
generally less responsive to online panels and will be less affected by innovations in UAM, which are currently still in
their infancy and will take years to develop;• Most of the participants (46 percent) were employed full time (30 hours or more per week), 9 percent employedpart time (up to 30 hours per week), 7 percent were self-employed (business owners, freelancers), 9 percent werecollege or university students or apprentices, 4 percent were homemakers, 16 percent were retired, 8 percent were
jobseekers or other, and 1 percent preferred not to say;• 99 percent of participants had EU citizenship; participants had to reside in the city or region where the survey was
conducted, as the aim was to reflect the perceived benefits and concerns of residents potentially affected by the riseof UAM;• The type of household was diverse as well: singles (24 percent), participants with two persons in household (51percent), with three (16 percent), four (7 percent), five or more persons in the household (2 percent) participated;• On the level of education, 2 percent had no school-leaving certificate, 9 percent finished basic schooling, 27 percent
finished higher schooling (10 or more years), 13 percent had college or university education (no degree), 29 percent
have a college or university degree (e.g. diploma or bachelor’s degree), 19 percent have a postgraduate degree orhigher (e.g. master’s degree, PhD), 1 percent preferred not to say;
• The total gross household income per year shows that 21 percent of the participants receive less than EUR 20,000,
26 percent EUR 20,000 to 39,999, 19 percent receive EUR 40,000 to 59,999, 9 percent receive EUR 60,000 to
79,999, 5 percent receive EUR 80,000 to 99,999, 4 percent receive EUR 100,000 to 119,999, 2 percent receive
EUR 120,000 to 139,999, 1 percent receive EUR 140,000 to 160,000, 2 percent receive over EUR 160,000, while 11
percent preferred not to say;
• The replies on employment industry show that participants work in: grocery or other food retail or manufacturing(3 percent), automotive and transport (4 percent), public sector and administration (6 percent), banking and finance(7 percent), clothing manufacturing or retail (2 percent), education (7 percent), healthcare (7 percent), computerscience or IT (9 percent), in another field (25 percent) or are unemployed (30 percent). The maximum allowed shareof the non-working population was 35 percent, to avoid a skewed distribution towards this very responsive group;• To make sure we compiled a solid database on potential users of UAM, special attention was paid on ensuring to get aminimum number of respondents with generally positive attitudes towards UAM and who were identified classified
as potential users. A minimum of 120 participants per city were identified as potential users of drone delivery – samefor air taxis. A minimum of 200 participants per city were identified as potential users of either drone delivery or air
taxis. And a minimum of 240 participants per city were not identified as potential users of UAM;
• People working in advertising, media, PR and marketing may typically encounter surveys and statistical models intheir day-to-day work. They understand the underlying methodology and levers and this could have an influenceon their responses and thus the outcome of the survey. Therefore, these professional groups were categorically
excluded.
The survey was translated into the local languages of the participants (Spanish, Hungarian, German, Italian and French)
to ensure understanding across the different cities and regions. The exception was for participants in the Øresund
region where the survey was conducted in English, as non-native English skills are very good in Scandinavian countries
according to the Education First English Proficiency Index 4.

4 https://www.ef.com/wwen/epi/

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Information on the questionnaire structure and question types
The questionnaire was designed to assess, understand, and measure the most important societal-acceptance drivers
for UAM, including perceived benefits and concerns and what it would take to increase societal acceptance. The
questionnaire included 36 questions; the response time was estimated at twenty-five minutes.
Two use cases that are considered easy to imagine and self-explanatory for non-experts were used in the quantitative
survey to determine levels of acceptance: the delivery of goods in the low single digit kilogram range by drone andthe transport of passengers by air taxi. An in-depth analysis was conducted to measure the relative acceptance levels
across cultures of three key concerns identified through the literature review: the perceptions of safety, noise, and visual
annoyance in an urban environment. Finally, the questionnaire addressed the general attitude and expectations ofrespondents towards regulatory authorities. For an English version of the questionnaire that was distributed online tothe participants, please refer to the Appendix.
The first part of the survey ensured that participants met the predefined criteria (see the predefined quotas above). An
informational video of 1 minute and 36 seconds was presented to give participants’ prior information as well as generaland common understanding of UAM. The use cases shown in the video were passenger transport by air taxi, expressdelivery of food by drone, transport of emergency medical services to the scene of an accident, and delivery of medical
supplies to a hospital. The selection aimed for a balanced representation of commercial and public service use cases,
drone and passenger use cases, as well as use cases both with a pilot on board and remotely piloted. The vehicles
depicted in the video were invented and did not correspond to any industrial product existing or in development. The
objective was to give a general feeling and idea, rather than to reflect actual technical accuracy. The video concluded
with the message that Urban Air Mobility is coming soon to Europe. The video did not include any sound other thanmusic, as noise perception was evaluated in a separate survey.
Subsequently, this section checked whether participants could be considered a potential user for either or both ofdelivery of goods by drone and/or transport of passengers by air taxi.

The online questionnaire wasdivided into 6 areas:
1. Making participants familiar with what
UAM means and assessing participants’general attitude towards new technology and UAM use cases
2. Testing acceptance of delivery drones,
3. Testing acceptance of passenger transport (air taxis)
4. Understanding their attitude towards
regulators and their expectations
5. Understanding security and environmental aspects and concerns
6. Asking for additional demographic data

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8A0846_Report_Spreads_210518_Langversion.indd 53

The subsequent parts of the survey focused on collecting insights about
the following topics (in order):
•
•
•
•
•
•

General attitude towards UAM
Delivery by drone
Passenger transport (air taxi)
Regulators and their role
Further understanding of security and environmental aspects
Additional demographic questions

For more information on the structure of the questionnaire, see
Appendix 2.

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Deep dive into choice-based conjoint (trade-off) analysis
Conjoint analysis is a statistical technique that models the behaviour of survey participants in choice / trade-off
situations. Among other things, it helps to explain and forecast the level of readiness for new technologies where tradeoffs between objectives need to be made. In a survey situation, participants are asked to indicate their preferences when
faced with different alternatives. The aim is to find out which factors are relevant to a decision and to what extent they
influence that decision.
A conjoint setting is characterised by its attributes and the levels of those attributes. Attributes are characteristic properties
of, e.g. products, services, or scenarios. In product design, typical attributes may be price, brand, and durability. Attributes
should be relevant to decision making, consist of at least two levels with varying values, and are expected to influence
preferences between products, services or scenarios. In product design, typical attributes may be price, brand anddurability. Levels are expressions of the attributes, i.e. unambiguous, mutually exclusive and realistic possibilities of how an
attribute could materialise. Levels for, e.g. the attribute price would simply be the different price points.
Participants are offered a choice between different bundles, in which each attribute is assigned one level only. To
continue the above example, a bundle would be a theoretical product described by its price, brand and expected
durability. As the number of attributes and levels to be assessed significantly influences the sample size and number ofchoices to be made, the number of distinct attributes and levels should be limited to keep the scope of the choice-based
conjoint analysis manageable.
In a survey setting, the process for conducting a choice-based conjoint analysis is as follows: participants are shown asmall number of different bundles represented by choice cards (see Figure 26), and are asked to choose their preferredbundle. This step is repeated several times.
Figure 26: Example of a choice in choice-based conjoint analysis

54

SafetyOne drone has the same
likelihood of hitting apedestrian as one car

One drone has 1/10th
the likelihood of hitting apedestrian as one car

One drone has 1/100th
the likelihood of hitting apedestrian as one car

Noise

One drone Is as loud as aleaf blower (~90-r dB,
unbearable)

One drone is as loud as aleaf blower (-90+ dB.
unbearable)

One drone is as loud as a
car driving by at city
speed (~65 dB,
noticeable)

Visuals

1 or 2 drones per hour in
one's ﬁeld of view when
walking down a street~5 drones per hour in
one's ﬁeld of view when
walking down a street

20+ drones per hour in
one's ﬁeld of view when
walking down a street

SelectSelectSelectA study on the societal acceptance of Urban Air Mobility in Europe

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Due to the high number of possible combinations of attribute levels into bundles, participants will not see every possible
bundle, and will not be asked to compare every bundle to every other bundle. However, preferences can be extrapolated
based on a few choices.
A specific two-stage process is used to estimate valid/stable utilities for each respondent: a latent class (LC)segmentation is followed by a hierarchical Bayes (HB) utility estimation within each latent class analysis (LCA) segment.
The model assigns a utility to each level (the expressions of the attribute). The utility describes numerically how(negative for rejection, positive for approval) and to what extent a level impacts decision making (small absolute value
for little influence, large absolute value for great influence).
The greatest increase in utility within an attribute is equivalent to the greatest gain in approval rating (i.e. from the lefthand side to right-hand side of a number scale).
Arranging the utilities on a scale from -3 to 3 gives an overview of which levels lead to rejection and which to approval,e.g. level A.4 in Figure 27 has the greatest approval rating for attribute A. The ideal bundle would consist of levels A.4,
B.4, C.4 and D.4. However, in a real-world setting this particular bundle might be unrealistic, and trade-offs may need
to be made. This raises the question about which levels are still considered acceptable, i.e. what is the lower boundary.
For example, a bundle composed from the levels to the right of the respective greatest increases, i.e. A.4, B.3, C.2 andD.1 in Figure 27, might provide an acceptable approval rate. However, this logic should be applied with caution to real-life
applications and bundles should always be chosen with care.

Figure 27: Schematic illustration of utilities in choice-based conjoint analysis
Utilities of attributes

-3.0

3.0

0.0

Attribute A
Level A.1

Level A.2

Level B.1

Level B.2

Level A.3

Level A.4

Attribute B
Level B.3

Level B.4

Level C.2

Level C.3

Level C.4

Level D.2

Level D.3

Level D.4

Attribute C
Level C.1

Attribute D
Level D.1

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Conjoint analysis was chosen for the joint assessment of concerns regarding safety, noise, and visual annoyance in two
settings: the operation of drones and the operation of air taxis. The aim was to avoid participants choosing the optionthat indicated the least change from the status quo when asked about desirable levels. In the conjoint analysis they areforced to make trade-offs between three scenarios, thereby indicating real preferences and acceptable levels. The
questions used can be found under B7 and C7 in the Appendix.
The bundle of levels accepted by the majority will serve as a basis for future regulatory projects. The initial setting oflevels is therefore of particular importance. On the one hand, levels need to be specific enough to form a solid basis for
specifications in regulatory projects; their formulations, on the other hand, need to be graspable for non-experts andrelatable in a survey situation.
SafetyTwo different scales for the safety attribute were selected because the air taxi use case poses risks to both passengers
and pedestrians, whereas the drone use case poses risk solely to pedestrians.
The following levels were selected for the operation of drones: five-times higher likelihood of one drone hitting apedestrian as one car; the same likelihood; one-tenth of the likelihood; and one-hundredth of the likelihood. The safety
standard for the first level would translate to about 200 fatalities per year in Europe by 2025, compared to 22,800
fatalities caused by cars in the 27 EU member states in 20195 (i.e. 200 fatalities from drones would lie in a range of
1 percent of the fatalities from car accidents). The best level for the drone safety standard (a hundredfold improvementcompared to passenger cars) lies within a factor of two of today’s commercial aircraft safety standard (calculated on apassenger-kilometre basis and assigning a theoretical passenger to a drone).
The following levels were selected for the operation of air taxis: safety standards comparable to motorcycles (approximately 5 fatalities per billion passenger kilometres), cars (approximately 2)6, buses (approximately 0.05) 7, andcom-mercial aircraft (approximately 0.01)8. Motorcycles are widely regarded as an unsafe mode of transport, andcommercial aircraft as one of the safest.
Noise
For the noise attribute, the following levels were selected to cover both the operation of drones and the operation of
air taxis: volume of a leaf blower (over 90 dB, unbearable), volume of a truck driving by at city speed (roughly 82 dB,disturbing), volume of a car driving by at city speed (approximately 65 dB, noticeable), and volume of a bicycle riding by
at city speed (around 57 dB, barely noticeable). By comparing scenarios to an example from everyday life, participants
can imagine the background noise; moreover, the decibel indication can be used to inform a noise specification. For
the first and loudest level, a noise was selected that is quite common in urban environments but not permanently
conceivable as background noise. For the last level, a noise was selected that is not disturbing but still realistic for drones
and air taxis.

5
6
7
8

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https://ec.europa.eu/commission/presscorner/detail/de/qanda_20_1004
EurostatEurostatEurostatA study on the societal acceptance of Urban Air Mobility in Europe

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Visuals
For the visuals attribute, the following levels were selected for both the operation of drones and the operation of air
taxis: more than 20 flying vehicles per hour in one’s field of vision when walking down a street; around 10 vehicles; around
5 vehicles; and 1 or 2 vehicles. On a typical day and in a typical residential area, roughly 1 to 2 aircraft per hour are visible
in the sky today. Helicopters, too, can be seen flying above cities in Europe and hospital pads are estimated to be busy at
1 to 2 landings per hour. The last level is chosen as a realistic lower limit. Multiplying this number by 20 for the first levelamounts to a massive change from today but is in the range of the projected number of drones in urban areas in 2025.
Questions B8 and C8 in the Appendix ultimately serve to find upper and lower limits for the overall acceptance rate. For
this purpose, the acceptance rate (without comparison or choice) for the bundle of consistently best levels is queried, as
well as the acceptance rate for the bundle of consistently worst levels. The results from the conjoint analysis can then be
fit into these boundaries.
3.1.2 Qualitative survey methodology
After there was a clear picture on the results from the quantitative survey, further qualitative interviews with morethan 40 local, national, and European stakeholders took place (see Figure 28). To prioritise and select the stakeholders
for these interviews, the long list of identified stakeholders from the literature review was taken and assessed along
the three dimensions of concerns, level of influence and level of support for UAM. The stakeholders with the highest
concerns and level of influence, as well as the lowest level of support for UAM, were ranked highest. The objective
was to get their differentiated and specialised point of view on benefits and concerns around UAM. Around half of the
stakeholders interviewed were local, covering all cities in which the survey took place and all stakeholder groups. In
most cases, interviews with representatives of at least two of the cities were done in order to capture potential local
differences.
Figure 28: Stakeholder interviewee overview

Stakeholders interviewed
Stakeholders interviewed

Local level

Mayor
Local andlevelmunicipalities services
Local environmental protection associations
Local
traffic
and transport authority
Mayorand municipalities
services
Local
resident
association/Real-estate
ownersLocal environmental
protection associations
Emergency
responseorganization
Local traffic and transport authority
Local
local
ATC
Localairport,
resident
association/Real-estate
owners
Local
urban
and
city
planners
Emergency responseorganization
Local
of commerce
Localchamber
airport, local
ATC
Local
Localpolice
urban and city planners
Local chamber of commerce
Local police

National and European level
Airports
CouncilInternational
Nationaland European
level(ACI)National governmental authorities for aviation(e.g.,
DCGA)
Airports
Council International (ACI)Europeanenvironmentalauthorities
protectionfor
associations
National governmental
aviation
Alliancefor new mobility Europe (ANME)(e.g., DCGA)
An
insuranceenvironmental
providerEuropeanprotection associations
EuropeanCommission
Alliance fornew mobility Europe (ANME)TheAn European
insurance helicoptersprovider association
Europeanaviation association
EuropeanbusinessCommission
CANSO
The European helicopters association
Smart
City Initiative
Europeanbusiness aviation association
The
European Cockpit Association
CANSO
Smart City Initiative
The European Cockpit Association

57

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3.1.3 Noise test methodology
Both the qualitative and quantitative surveys identified noise as one of the major concerns for societal acceptance ofurban/advanced air mobility. UAM aircraft have a variety of noise profiles that differ from those of traditional aircraft.
Characteristics of their noise signature such as tonality could potentially increase annoyance. Other health impacts
associated with introducing this entirely new sound source into urban and suburban environments are not widely known.
UAM aircraft pose another layer of complexity since, compared with other types of aircraft, they will fly closer to where
people live and work.
Understanding how noise from UAM aircraft is perceived will therefore be essential to the introduction of this newtechnology. Designs of aircraft, legislation and planning for UAM infrastructure and routes will all be dependent uponunderstanding reaction to the sound.
To begin to understand people’s response to UAM sound and investigate how a more comprehensive study would operate,a pilot study was undertaken with Arup featuring listening tests leveraging the Arup Soundlab. This is described in thefollowing section.
Use of sound demonstrations for understanding environmental soundOriginally, Arup Soundlab was conceived and developed to inform the design of some of the world’s best arts andculture venues. More recently, SoundLab has been used to enable clients and stakeholders to experience the impactsof major infrastructure projects during the design and planning process, helping to shape better outcomes. Throughthe process of continuous development, SoundLab pairs advanced visualisation with novel aircraft noise synthetisation
tools to enable noise assessment in the early stages of aircraft design. SoundLab has also developed methods andtransportable facilities for engaging people in their local areas, delivering sound demonstrations for schemes including
aviation, railways, highways and windfarms. Compared with traditional methods of engagement on environmental
sound issues, sound demonstrations have many advantages:
•
•
•
•
•
•

helping identify stakeholders’ needs and concerns;
facilitating dialogue on implications of noise on public health and wellbeing;
increasing transparency on how stakeholders could be affected by a proposed development or new noise source;building trust through impartial advice and integrity;
ensuring proposals are inclusive and accessible; andsupporting data-driven decision making.

The pilot study
The pilot study aimed to:• Investigate whether sound demonstrations would be an appropriate way to engage with and understand people’s
responses to UAM sound;• Test and develop approaches to undertake the tests, with a view to carrying out a larger study; and• Gain initial insight into people’s perceptions of UAM sound, noting that the sample would be far too small to yieldstatistically reliable results.
• Due to travel restrictions in place at the time as a consequence of the COVID-19 pandemic, the study was carried out
using a transportable facility (MLab) currently installed in Arup’s office in Amsterdam. As in SoundLab, MLab uses
3D ambisonic sound, focused at the listener’s head height, from an array of 12 loudspeakers, four each at floor level,
head height and overhead (plus bass loudspeakers) – see Figure 29 below.

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Figure 29: Noise auralization setup in Arup MLAB in Amsterdam

A total of 20 listeners took part over a period of two days in April 2021. Each test was carried out with one listener at a time.
Listeners were guided through the tests in the following way:
• The purpose of the tests and how they were being undertaken was explained. The listeners were told that the
•

•
•

•

research was to gauge responses to different transportation sounds; drones and air taxis were not mentioned;
The listener was settled into the listening environment by hearing background sounds of an outdoors urban location;
A recording made in Dam Square, Amsterdam was used, to reflect the soundscape in the city in which the tests wereconducted. This background sound contained no transportation sound and was reproduced at a level of 55dBL Aeq. It
was played continuously as a backdrop to the transportation sounds;
An image of Dam Square was presented on a display screen to help localise the listener. No visual representation of
the sound sources was included in the test to avoid objectivity bias;
Sounds from the following sources were each reproduced at a level of 80dBL Amax,F: jet aircraft, helicopter, bus,
motorbike, large multicopter drone, smaller multicopter drone, air taxi and synthesised air taxi with different
acoustic characteristics to the others. Additionally, the air taxi sound was reproduced at two lower sound levels(60 and 70 dBL Amax,F ). Each sound source recording was played forpage
30s. Normalisation of the sound levels to the
maximum level may have resulted in the sound levels for each source being different, if they had been quantified
using a different metric, such as the L Aeq, due to the different durations and rise and decay times of the sounds;
The listeners were asked to rank each sound according to how much the sound would bother, annoy or disturb themon a scale of 0 (not at all) to 10 (extremely) as Figure 30 shows. They were asked to consider their responses assuming
the sound occurred five times in one hour. In addition to the annoyance scale, they were also asked to provide
comments on the aspects of the sound that had contributed to their rating. Thirty seconds were allowed for each
response before playing the next sound.

Figure 30: Scale to determine if sound was found to be bothering, annoying or disturbing

On scale of 0 (not at all) to 10 (extremely), how much would the sound bother, annoy or
disturb you?
Noise 10

1

Not at all

2

3

4

5

6

7

8

9

10
Extremely

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3.2 Survey results (10 key findings)

The overall objective of the survey was to generate new insights on societal acceptance of UAM by European citizens
and so support the future impact assessment and further regulatory work by EASA.
The following sections summarise the 10 key findings from the survey conducted between January and April 2021. For
each key finding, the combined insights from the quantitative survey, the qualitative interviews and the noise test arepresented. For the detailed survey results, please go to the EASA website.
3.2.1 A positive initial attitude to UAM throughout the EU
Homogeneous results
The survey was designed to capture potential divergence of opinion within various sub-groups, notably through screening
questions covering age, household composition, affinity to new technologies, geographical/cultural differences, etc. (seeInformation on the panel of participants above). Unexpectedly, the results demonstrated homogeneous replies: a levelplaying field throughout Europe, with no major deviation between the respondents of the six cities (see Figure 31), and nomajor deviations according to age, household composition or affinity to new technologies or other differentiating criteria(see Figure 32). This was confirmed by the qualitative interviews.
Figure 31: Cities surveyed indicated a similar likelihood of using the services
X%

Sum

Positive difference to avg+X%

Not at all likely

Likelihood to try out…

Negative difference to avg-X%

Rather unlikely

Rather likely

Very likely… delivery drones
Total

36%

11%

25%

Barcelona

32%

7%

25%

46%

Budapest

33%

8%

26%

43%

Hamburg

43%

Milan

28%

Öresund

41%

Paris

39%

Total

51%

18%

33%

35%

15%

49%

Barcelona

49%

16%

33%

35%

16%

51%

Budapest

46%

11%

35%

Hamburg

53%

Milan

46%

Öresund

59%

Paris

50%

14%

29%
7%

12%

22%
23%

31%

41%
18%

41%

28%

17%

44%

22%

64%
68%
67%
57%

19%

38%

21%

17%

22%

42%

72%
59%
61%

… air taxis

17%

36%
14%

24%

32%
35%

23%

27%

14%

40%
14%

33%

18%

36%
29%
36%

54%
47%
54%
41%

12%
14%

50%

Source: EASA UAM societal acceptance survey questions S6. How likely are you to make use of delivery of goods by drone (i.e.,delivery of parcels from an online
shopping platform to a nearby delivery hub, your garden or private property or a publicly accessible area), if it were offered in your city? Please assume that delivery
by drone would cost about double today’s standard shipping fees and ensured guaranteed delivery within 2 hours from the time you place your order. S7. How likely
would you be to use an air taxi (i.e., a flying vehicle that transports passengers from A to B) for a 25-50% higher price than current road passenger transport options
like conventional (road) taxis or Uber-like offerings, if you assume the trip could be made in half the time in the air taxi?

3.2 Survey results (10 key findings)

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Only small differences were noticed:• In general, respondents from the South of Europe (Milan, Barcelona) demonstrated a more positive attitude across
all question types than those from the Northern part of Europe (Hamburg, Oresund region);• On the readiness to use drone services: respondents from Milan (+8 percent) and Barcelona (+4 percent) had morepositive attitude compared with the average, while Hamburg (-7 percent) and Oresund region (-5 percent) were morecritical;• On the readiness to use air taxi services: respondents from Milan (+5 percent) and Barcelona (+2 percent) wereamongst those declaring a more positive attitude, and citizens from Budapest were more likely to try an air taxi
service (+5 percent compared to average). Citizens from Oresund (-8 percent) and Hamburg (-2 percent) showed
lowest interest in air taxi services.
The deviations in demographic groups and defined subgroups followed expectations:• The positive demographic groups included younger people, such as the age group 25-34 (+7 percent more likely to
try out drones, and +10 percent more likely to try air taxis compared to the average), men (+5 percent, +7 percent),

Figure 32: Overall interest in UAM services by subgroups deviating significantly from average
X%

Sum

Positive difference to avg+X%

Not at all likely

Likelihood to try out…

Negative difference to avg-X%

Rather unlikely

Rather likely

Very likely… delivery drones
36%

Total

25%

11%

Families

7%

Digital adopters

+10%

46%

15%

46%

34%

+16%

18%

47%

30%

+13%

6%

28%

Age group 65-75

-11%

16%

31%

37%

16%

Singles

-10%

16%

30%

40%

14%

Digital laggards

-22%

23%

64%

22%

19%
5%

Target group for express delivery by drone

42%

35%

33%

33%

35%

9%

… air taxis

Total

51%

18%

Age group 25-34

29%

12%

Target group for airport shuttle
Digital adopters

9%

Age group 65-75-10%Digital laggards

-20%

24%
34%

41%

19%

5%

37%

33%

40%

25%

30%
24%

+10%

18%

43%

26%
37%

49%

15%

+27%
+15%

9%
5%

Source: EASA UAM societal acceptance survey questions S6. How likely are you to make use of delivery of goods by drone (i.e., delivery of parcels from an online
shopping platform to a nearby delivery hub, your garden or private property or a publicly accessible area), if it were offered in your city? Please assume that delivery
by drone would cost about double today’s standard shipping fees and ensured guaranteed delivery within 2 hours from the time you place your order. S7. How likely
would you be to use an air taxi (i.e., a flying vehicle that transports passengers from A to B) for a 25-50% higher price than current road passenger transport options
like… conventional (road) taxis or Uber-like offerings, if you assume the trip could be made in half the time in the air taxi?
…

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the high income group (+6 percent, +7 percent) as well as digital adopters as participants accustomed to using other
innovative services (+16 percent, +15 percent). It is possible that families (+10 percent each) were more positive thansingles because the perceived advantages of UAM services (e.g. time saving) are felt to be more critical for a couple
with a double burden of work and educational activities for their children;• As expected, the subgroup defined to be the target group for services of delivery drones and air taxis were amongst thosewith the most positive attitude when asked how likely they were to use available services (+13 percent, + 27 percent).
On the other hand, the slightly more reluctant groups included singles (-10 percent, -8 percent), older people such as the agegroup 65-75 (-11 percent, -10 percent), women (-5 percent and -6 percent) and digital laggards (-9 percent and -5 percent).
Positive initial perception
Early in the survey, participants were asked to indicate what their overall perception would be if Urban Air Mobility solutions
were introduced in their cities.
Overall, the perception of UAM was positive: most (83 percent) of the respondents felt (very or rather) positive about the
introduction of UAM overall. Across the surveyed cities, only 3 percent of the respondents had a negative perception of
Urban Air Mobility and will probably be hard to win round to the introduction of UAM (Figure 32a).
Figure 32a: Vast majority of respondents were positive on UAM

Overall, 83% of respondents have a very positive or
rather positive attitude towards UAM…

xx% Sum
Very negative

General attitude towards urban air mobility, %Rather negative
Rather positive
Very positive

17%
3

14

83%

54

29

The qualitative interviews also indicated that the general attitude towards UAM is mostly positive. Surprisingly, this waseven true for participants who could have been expected to have most concerns – for instance, those involved in security
or environmental matters. The interviews indicated that UAM is seen as an exciting innovative development and the factthat Europe may be playing a leading role in this domain is triggering positive consideration and goodwill. However, thesurvey revealed that most stakeholders have not yet been exposed to UAM matters so far, except for those cities withpilot projects (e.g. Hamburg or Paris), and generally lack information on the topic.
Readiness to use UAM
As shown in Figure 32b, the results showed that a large share of the population would be interested to use UAM
services. 64 percent would be interested in using drone delivery and 49 percent would be interested in using an air taxi.
43 percent would be interested in using both, 71 percent are likely to make use of at least one service. Only 29 percent
would not use either of these services if they were available in their respective cities.

63

3.2 Survey results (10 key findings)
Source: EASA UAM societal acceptance survey question S5. What would be your overall perception if urban air
mobility solutions (such as those shown in the video) were to be introduced in your city? Please select one answer.

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Figure 32b: Vast majority is positive on UAM
Likelihood to use air taxis

A
Broad users: 43% likely to become users ofboth services

Likelihood to use delivery drones

10%

7%

4%

A

B
22%

4%

A

1%

13%

71%
3%

+

B

Potential drone delivery users: 64% likely to try
out delivery of goods by drone (defines subgroup)

A

+

C

Potential air taxi users: 49% likely to make useof at least one service (defines subgroup)
1%

5%

C
0%

D
1%

2%

A

5%

14%

29%
8%

+

B

+

C

Potential UAM users: 71% likely to make use ofat least one service (defines subgroup)D
UAM rejecters: 29% not likely to become usersof either use case (defines subgroup)

Level of comfort
The questionnaire also verified participants’ basic comfort level with the idea of delivery drones and of manned
and unmanned air taxis. To this effect, participants were asked to rank their level of comfort with respect to different
scenarios (see question C4, Appendix).
57

Air taxis pose a potential safety threat not only to the passengers using them. Pedestrians will be affected by drones andair taxis, despite not necessarily choosing to use them themselves, and so the hypothesis was that the perceived safetyof pedestrians will have a significant impact on the societal acceptance of drones and air taxi operations.
Overall, the results from the questionnaire were positive. The majority of respondents indicated that, as pedestrians,
they would feel safe with drones and manned air taxis flying above their heads.
However, the results also showed that pedestrians always felt safer considering manned aircraft than considering
unmanned ones, no matter the size or the characteristics of the aircraft. Therefore, the share of people feeling safe as
pedestrians with manned air taxis (70 percent) flying above their heads was much greater than with unmanned ones
(44 percent) – and still higher than those who feel comfortable with unmanned delivery drones (56 percent), as Figure 33
shows. As expected, the number that would be likely to try a manned air taxi (75 percent) was higher than those who
would try an unmanned one (43 percent). It is also no surprise that those participants identified to be potential air taxi
users had a higher level of comfort with manned air taxis (+13 percent) than the average.

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The qualitative interviews also showed that trust in manned services was higher, and that respondents felt more
comfortable with initial manned operations of air taxis.
The high level of comfort of EU citizens with manned air taxis, either as pedestrians on the street or as passengers, may
be explained by the fact that the aircraft and their operations may look to non-specialists very similar to traditional
aviation vehicles and operations, and by the fact that traditional aviation is perceived as very safe by citizens, at least in
Europe.
Figure 33: Participants feel more comfortable with manned than with unmanned aircraft systems
Respondents feel safer as a pedestrian with manned air taxis than with delivery drones
Level of comfort with manned & unmanned aircraft systems
Strongly disagree

DisagreeSomewhat disagree

Somewhat agree

Agree

Strongly agree

As a pedestrian on the ground, I would feel safe with unmanned delivery drones potentially flying above me.
DeliveryDrones

44%

12%

11%

21%

20%

30%

56%

7%

As a pedestrian, I accept the fact that manned air taxis could fly above my head.
Pedestrian
view

30%
Air taxis

10%

8%

13%

27%

32%

10%

70%

As a pedestrian, I accept the fact that unmanned air taxis could fly above my head.
56%

20%

15%

21%

23%

16%

44%

5%

I would be interested in trying out a manned air taxi myself.

25%
Passengerview

9% 7% 10%

30%

29%

15%

75%

Air taxis
I would be interested in trying out an unmanned air taxi myself.
57%

20%

16%

21%

23%

14%

6%

43%

Source: EASA UAM societal acceptance survey questions B3. Drones intended for the delivery of goods are remotely piloted aircraft systems with no pilots on board.
Assume that they have an average wingspan of 3 metres, would fly at between 120 and 150 metres altitude, and are certified by competent authorities. Please rate howmuch you agree or disagree with the following statement. C4. Recent studies extend the prospect of aircraft soon transporting passengers, either with a pilot on board orwith a remote pilot. You will now see several statements that people might make about such air taxis. Assuming that all of the aircraft are certified by competentauthorities, please rate how much you agree or disagree with each statement for each type of air taxi.

3.2 Survey results (10 key findings)

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Some sub-groups were more comfortable with unmanned air taxis than others. This is true for: the target group for airport
shuttle (+17 percent), digital adopters (+11 percent), potential air taxi users and men (both +10 percent), families and thosewith higher incomes (both +7 percent) and the younger age group of participants between 18 and 44 years (+6 percent).
Those with a lower level of comfort compared to the average were: air taxi user rejecters (-16 percent), digital laggards(-15 percent), women (-10 percent), the older age group between 55 and 75 years (-8 percent) and singles (-6 percent).
In general, participants expressed slightly more concern about unmanned services when they thought of it as passengers(32 percent) than when they thought of it as pedestrians (26 percent), as can be seen in Figure 34. There was only small
deviation in cities: citizens in Budapest and Milan felt safer (~ +6 percent) while Hamburg, Oresund and Paris felt less safe
compared
tocomfort
average with(~ -4 percent).
C4. Level ofmanned & unmanned vehicles – air taxis (3/5)
Figure 34:Pedestrians are slightly more concerned about unmanned operations than passengers

Pedestrians are slightly less concerned about unmanned operations than passengers themselves
Unmanned

Passengers

Pedestrians

Share of respondents that feel safe

Share of respondents that feel safe

30%

Total

40%

50%

60%

70%

80%

90%

30%

32 %

40%

50%

60%

70%

Manned

80%

90%

26 %

Barcelona
Budapest
Hamburg
MilanÖresund
Paris

Source: EASA UAM societal acceptance survey question C4. Recent studies extend the prospect of aircraft soon transporting passengers, either with a pilot on board or witha remote pilot. You will now see several statements that people might make about such air taxis. Assuming that all of the aircraft are certified by competent authorities,
please rate how much you agree or disagree with each statement for each type of air taxi.

In addition, the results of each question were compared between the cities.
3.2.2 Strong support for use cases in the public interest
Several survey questions helped to identify use cases that respondents expected to be most useful and these, therefore,
will probably receive highest acceptance by citizens.

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As a first step, each participant’s affinity to the new technologies was assessed. This was intended to help understandtheir attitude towards innovation in general, as this was assumed to impact their openness towards use cases.
Participants were then asked to rank the usefulness of fourteen UAM use cases. In this way, the use cases considered
the most important for the population were identified. Participants also received an overview of several conceivable use
cases that go beyond those shown in the video.
As illustrated in Figure 35, the use cases related to medical and/or
emergency transport were voted most often amongst the three as
most valuable ones and therefore ranked highest: transport of injured
persons to hospital (41 percent), drone delivery of medical supplies
to hospitals (41 percent), transport of emergency medical personnel(36 percent), and using drones for disaster management (28 percent).
Use cases related to the transport of individual passengers, such as sightseeing by air taxi or a flight from one point in thecity to another, were considered to be less useful.
Medical/emergency uses cases are seenas the most useful, whether consisting indrone delivery of medical equipment or
urgent transport of persons.

Figure 35: Emergency use cases are expected to be most useful
1

Perceived usefulness of UAM use cases, %Emergency
use cases

Drone
deliveryuse cases

Top 5 use caseRanked #1
Ranked #2

X% SumRanked #3

2

Drone delivery of medical
supplies to hospitals

18

15

8

41%

1

Transport of injured person to hospital

18

19

4

41%

3

Transport of emergency
medical personnel

16

4Disaster management using drones

12

Drone delivery of medical
supplies to home

5

Drone delivery of groceries andGoods in remote areas

6

Drone delivery of goods fromonline shopping in urban area
5

Long-distance forwardingof heavy cargo

4
5

9

17

2 3
7

Shuttle service to airport

7

4

3

36%
28%

4

18%

14

24%

9

23%
25%
18%
10%

Regional air mobility

5Commute from a suburb
to the city centre

4

Point to point travel within a city2

5%

Sightseeing by air taxi

3

5%

None1

3.2 Survey results (10 key findings)

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129Drone delivery of meals in urban areas

Passenger
transport
use cases

17

8%
6%

2

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Passenger transport: highinterest but less useful
Qualitative interviews showed that themain reason is the assumption that will
only be accessible by a few and probably
much more expensive than other modes oftransport.

These figures indicate that use cases that are in general public interest,
notably in the health and safety domains, would be better accepted
than use cases fulfilling private and individual needs.
These results from the quantitative survey were confirmed by thequalitative interviews. Interviewees on local, national, and European
level saw benefits in UAM preferably when it contributes to public
services and interest. Those use cases expected to be most beneficial
are linked to emergency and medical transport.

The qualitative interviews, however, also indicated that the emergency or medical character of an operation would notjustify any deviation from the safety or security standards. In contrast, higher noise levels could be acceptable if thenumber of operations for emergency purposes was limited.
3.2.3 Top 3 expected benefits: faster, cleaner, extended connectivity
Through a multiple-select question, survey participants were asked to select up to three benefits and opportunities
that the development of UAM could bring for the EU and its citizens. A list of seven possible selections was given (seequestion A4). This list was not use-case specific. Additionally, participants were invited to name up to three more
benefits that did not appear in the survey and may not have been covered by the literature so far.
Again, the use of UAM in emergency situations was perceived to generate the greatest added value: 71 percent
of participants expected an improved response time in case of an emergency (see Figure 36). It was also foundthat, compared to other participants, the age group between 55 and 75 years perceived this to be a more significant
advantage on average.
The reduction of traffic jams ranked second (51 percent) on average, closely followed by an expected reduction of
local emissions (48 percent). Better connection to remote areas (41 percent), and the creation of new jobs (32 percent)represented other perceived benefits. The latter was on average more often mentioned as an expected benefit bypeople younger than 24 years and participants in Barcelona expected this advantage more often than the average
respondent (+9 percent). No additional benefits were proposed by respondents in the open question.

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Figure 36: Improved response time is clearly perceived as top benefit

Perceived UAM benefits
Total

Barcelona

Budapest

Hamburg

MilanÖresundParis(absolute %, +/- difference to avg % in total)

Improved response time is clearly perceived as top benefit with all cities ranking it first
Share of respondents that selected benefit
out of 3 possible•

Similar perception in all
cities as suggested by low
spread and steepness oftrend curve•

Hamburg and Öresundwith similar opinions•

Reduction of local
emissions with highest
spread between Paris(37%, -11%) on lower andBudapest (56%, +8%) and
Milan (55%, +7%) on upper
end•

Creation of new jobs more
important in Barcelona(41%, +9%)

0% 10% 20% 30% 40% 50% 60% 70% 80%
Improved emergency
response time
Reduction of traffic jams
Reduction of
local emissions
Development of
remote areas
Creation of new jobs
Market-leading
position for Europe
None

Source: EASA UAM societal acceptance survey questions A4. What benefits and opportunities can the development of urban air mobility bring for the EU and EU citizens?
Please select up to 3 answers.

Overall, the replies indicated that participants attach a higher value to perceived positive impacts of UAM on their own
security, health, and quality of life, than to other potential benefits – notably the economic ones.
These results from the quantitative survey were confirmed by the qualitative interviews. Interviewees saw and preferredbenefits in UAM when it was perceived to be contributed to public services/public interest, such as emergency and medicaltransport. Connecting remote areas or areas that are currently not sufficiently connected by ground transport systems was alsopart of this public interest.
Most interviewees spontaneously and immediately referred to the reduction of congestion and emissions as a key benefit, butalso at the same time requested that UAM would be integrated into local strategies on multi-modality.
Some of the interviewees considered UAM to have the potential to reduce noise in the city, for instance by replacing
the noise of ground ambulances or of some helicopter flights. UAM was also perceived to potentially help citizens gainback green areas, as a result of ‘moving’ the traffic into the air and building less ground infrastructures (roads, bridges,
tunnels, etc.). Finally, UAM was seen as a showcase for innovation and for the transition to smart and green mobility.

3.2 Survey results (10 key findings)

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3.2.4 Top 3 concerns: safety, environment/noise and security
Through a multiple-select question, participants were invited to rank the six most important concerns, in theirview, regarding the operation of drones in an urban environment, out of a list of nine potential negative effects (seeAppendix). This indicative list of concerns was derived from the literature review. Participants were also free to add theirown concerns in a free text field.
To avoid confusion, the notions of safety and security were clarified
in the questions: safety mainly referred to incidents resulting from atechnical or human failure, while security related to incidents causedby harmful deliberate or intentional actions, such as cyber-attacks or
Dronesthe failure of mobile networks. The qualitative interviews confirmed• safety (44 percent)that participants indeed see a clear difference in safety and security,• security (39 percent)although the translation in some European languages leads to the• environment (36 percent)same wording (e.g. in Hungarian). Individually-stated definitions
Air Taxis
by participants were very close to each other and in line with the• environment (38 percent)understanding and description in the quantitative survey. Noise was• safety (37 percent)listed as a distinct concern, although it is sometimes included under the• security (29 precent)wide category of ‘environmental concerns’ in the reviewed literature.
The reading of the results should take this element into account, forinstance by adding or not the noise results to the results on environmental impact.

Survey results: Concerns
on drones and air taxis arenearly the same

The overall results indicated that safety, security, and environmental issues were the top concerns of respondents –as can be seen in Figure 37, with noise ranking second for air taxis. The results showed that these concerns increase withage, education, and income. Four percent of the respondents expressed no concerns. Participants also had the option to
add concerns in a free text field. However, no significant mentions were added.
The ranking of concerns for drones and air taxis was relatively similar – only two primary differences can be seen:• Noise in the case of air taxis ranked second, but was significantly lower for drones coming in 6th place;• Security ranked 10 percent higher for drones. Most likely, this is because drones are unmanned while air taxis are
expected to be manned initially and thus might be less prone to security threats in the eyes of the general public. It
can be assumed that air taxis operated by remote pilots or flying autonomously would increase the public concern forsafety. In general, slightly more than half of the participants trusted security and cyber-security regarding drones,
with men demonstrating more trust than women (+7 percent). See details in Appendix.
Concerns regarding drones
The main concerns for drones also related to safety, security, and environmental impact. Relative to the results for air
taxis, the security threat was perceived to be around 10 percentage points higher, which might correlate with the factthat in the scope of this study air taxis were framed to be piloted for initial operation. In addition to Figure 38 it is worth
mentioning that a notable demographic difference showed up: concerns related to safety and security increased withthe age of participants, while privacy concerns decreased with age.
Concerns regarding the local environmental impact (named by 28 percent as a top-three concern) ranked much higher thanthose linked to the global environment. Younger participants expressed more concerns regarding the global environment
than older respondents. Participants who feared job losses were most likely to be participants with lower incomes and level of
education.
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Figure 37: Respondents had similar concerns about delivery drones and air taxis
Concerns regarding delivery drones and air taxis ranked
by % of respondents under top 3
Local2 & global3
environmental
concern
Noise related
concerns4

Delivery drones

Air taxis
38%

36%

38%

28%

Safety37%

44%

Security5

29%

39%

Privacy30%

Job loss

30%

Affordability

19%
16%
16%

21%
19%

Visual pollution
None

Part of trade-off analysis (conjoint)

16%
4%

4%

1. Incident due to technical or human failure
2. Local environmental impact includes air pollution, negative impact on bird life and insects, decreasing biodiversity
3. Global environmental impact covers climate change
4. Covers noise pollution for delivery drones, and noise related to flying aircraft and noise related to vertiports for air taxis
5. Incident due to deliberate harmful action, e.g. by criminal organization or terrorists

Figure 38: Safety is the leading concerns for drone delivery
Concerns on drone delivery use cases ranked by % of respondents under top 3

X% SumRanked #1
Ranked #2
Ranked #3

22

Safety1

17

Security2

12
9

13

Job loss
Local environmental
impact3

911

Noise pollution

7

Affordability

6

Visual pollution

5

Global environmental
impact4

5

8
11

10
7

7
8

6
5

4

9
9

12

9

Privacy

44%
39%

9

30%

7

30%
28%
28%
21%

36%5

19%
14%
1%

Other
None

13

4

1. Incident due to technical or human failure 2. Incident due to deliberate harmful action, e.g. by criminal organization or terrorists 3. Local environmental impact includes air pollution, negative impact on bird life and insects, decreasing biodiversity 4. Global environmental impact covers climatechange 5. Share of respondents that ranked any environmental concern among top 3 answers
Source: EASA UAM societal acceptance survey questions B4. What are you most concerned about regarding drone delivery, both fo r the delivery of
day-to-day goods as well as medical supplies? Please consider your own usage of such a service as well as other people using it (e.g. your family orneighbours), which may affect you as well. Please select up to 6 answers. B5. Please sort your main concerns (selected in B4.) from ‘most concerning’
to ‘least concerning’.

3.2 Survey results (10 key findings)

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Concerns regarding air taxis
Additional concerns were considered in the ranking question for air taxis, including those around the infrastructure thatenables air taxis to take-off and land, called vertiports. The main concerns related to air taxis as perceived by respondents
were noise and environmental impact (both 38 percent, when combining mentions on air taxis and vertiports for the
category of noise). These concerns were followed by safety (37 percent), security (29 percent) and privacy (19 percent), as
can be seen in Figure 39. Job losses, affordability, and visual pollution (all 16 percent) were raised as well but appear to havea much lower importance to survey participants. Again, demographical differences can be found: concerns around safety
and noise related to flying aircraft slightly increase with age, education, and income. Fear of job losses on the other handdecreased with age, education, and income. The results also show that women expressed slightly more concern aroundenvironmental issues. A large share of respondents (81 percent) assumed that shuttle services would only be accessible toa few – this is likely to be one of the highest barriers to societal acceptance of air taxis.
Figure 39: Noise produced by air taxis is expected to be much higher than that produced by drones
X% SumConcerns on air taxi use cases ranked by % of
respondents under top 3

Ranked #1
Ranked #2
Ranked #3

SafetySecurity
8

Local environmental impact

10

7

10

13

Noise related to flying aircraft

8

10

19

10
9

37%
29%

10

29%

7

27%

Privacy67

619% 38%5

Global environmental impact

7

7

5

18%

Job loss

7

5

5

16%

Affordability

5

5

6

16%

Visual pollution

4

5

6

16%

Squandering of public money

5

5

6

15%

7

5

Noise related to vertiports

3

Inner-city space occupation

3

Downwash

2

4

4

10%

Additional traffic from/to vertiports

3

3

4

9%

Flight shame

1 2 2

15%
12%

5%

Other
None

4

4

38%6

0%
4

1. Incident due to technical or human failure 2. Incident due to deliberate harmful action, e.g. by criminal organization or terrorists 3. Local environmental impact includes air pollution, negative impact
on bird life and insects, decreasing biodiversity 4. Global environmental impact covers climate change 5. Share of respondents that ranked any environmental concern among top 3 answers 6. Shareof respondents that ranked any noise related concern among top 3 answers
Source: EASA UAM societal acceptance survey questions C5. What are you most concerned about with respect to air taxis? Please consider your own usage of such a service as well as other people using it (e.g.
your family or neighbours), which may affect you as well. Please select up to 6 answers. C6. Please sort your main concerns from ‘most concerning’ to ‘least concerning’.

The qualitative interview revealed that noise was the concern most mentioned by stakeholders as they expected noise
to be the greatest reason for citizens to complain. Security was also mentioned frequently as a major concern, related for
instance to the risk of hacking into the control link and equipping drones with dangerous or explosive goods.

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Respondents often took for granted that safety would be guaranteed by authorities that authorise them to fly.
Therefore, safety was not mentioned very often as a key concern. Privacy, such as potentially taking pictures of private
areas was frequently mentioned in qualitative interviews, but not in the quantitative survey. In this regard, harassment
was mentioned as a potential concern from drones operated by private users (e.g. stalking), particularly if more flights
take place in densely populated areas.
Stakeholders also mentioned in interviews additional concerns that had not ranked high in the quantitative survey:
insufficient public acceptance, problems of integration of airspace between drones and aircraft, lack of space
availability for vertiports and integration into cityscape as well as insufficient integration into the existing transportecosystem of the city (i.e. UAM just adding another layer of transport congestion, “moving traffic jams into the air”).
Some respondents were also concerned by: the affordability of the services, the pressure on the electricity demand, theenergy efficiency of transporting through the air, the visual impact on of cultural heritage in old European cities (visualpollution of flights and ground infrastructure), the compatibility of UAM with the “slow mobility” concepts adopted bymore and more European cities. Finally, local stakeholders, in particular local authorities, were concerned by a potential
lack of involvement in decision making and deployment of UAM in their city/region, especially with regard to topics that
impact the local city, such as definition of routes and traffic frequencies.
3.2.5 Safety: existing aviation safety levels are the benchmark
With the help of a comprehensive survey-based trade-off analysis (conjoint methodology as explained in chapter 3.1),
the relative importance of different levels of safety, noise, and visual pollution on the acceptance level of the survey
respondents was assessed. While these results can give an indication of how different improvements in safety, noiseand visual pollution are perceived by the public – and what measures could enhance public acceptance – the analysis
cannot directly indicate precise regulatory measures, which must also be influenced by other considerations. One
reason for this is that the perception of the safety dimension might be underrated in this survey as people are used to andexpect high safety standards when it comes to aircraft. This particular fact was highlighted many times in the qualitativeinterviews performed after the quantitative survey.
A separate analysis was done for drones and for manned air taxis as different responses were expected due to thedifferent size and application of the aircraft. The details are shown in the following differentiated results both for drones
and air taxis.
Detailed trade-off analysis for drones
When it comes to delivery drones, 24 percent of participants indicated that they would accept delivery drones in any presented
scenario, given the worst safety, noise, and visual pollution level. In contrast, one out of five participants (20 percent) indicatedthey would not accept delivery drones at all, despite the best level of safety, noise, and visual pollution (see Figure 40).
The results from this simplified trade-off analysis indicated that citizens’ acceptance could be improved by 56 percent
by implementing the highest levels for the safety, noise and visual pollution dimensions. Within these 56 percent, thesafety dimension is the main influencing factor (increasing acceptance by 23 percent). The results for delivery drones
imply that a change of safety from level 1 (one drone has five times the likelihood of hitting a pedestrian as one car) tolevel 2 (one drone has the same likelihood of hitting a pedestrian as one car) could increase the public acceptance by
12 percent, which is also the highest incremental increase for all three dimensions and almost as much as the complete
visual-pollution dimension. A change in the safety dimension from level 2 to level 3 (one drone has 1/10th the likelihood

3.2 Survey results (10 key findings)

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Figure 40: Trade-off analysis results for drones

Example: Levels regarding safety standard forcommercial drones: different acceptance rates
of up to 80% may be achieved

A

Secured acceptance

Increase in accepancefrom level 1 to 2

Increase in accepancefrom level 3 to 4

Influenceable range by setting
attributes from level 1 to 4

Increase in accepancefrom level 2 to 3

Non-addressable acceptance

Sum

Good

20
Level 4: Ø utility = 1.51
One drone has 1/100th thelikelihood of hitting apedestrian as one car
Level 3: Ø utility = 0.86
One drone has 1/10th thelikelihood of hitting apedestrian as one car

13

Bad

7

9
56%

Level 2: Ø utility = -0.06
One drone has the same
likelihood of hitting apedestrian as one car
Level 1: Ø utility = -2.31
One drone has 5x thelikelihood of hitting apedestrian as one car

20

A

3
3

23
5
5

7
4

100
80

12

24

Acceptdeliverydrones inany form

SafetyNoiseVisualpollution

Would Accept noaccept delivery
best case drones at
scenario
all

Total

1. Figures may be used to assess different scenarios for regulation; however, survey participants are not expert in regulation efforts and may havemisleading expectations (too low and too high); answers are always a snapshot
Source: EASA UAM societal acceptance survey questions B7. Put yourself in the year 2030: drones with about 3-metre wingspans, certified by competentauthorities, are flying at altitudes of up to 150 metres. In the following section, you will be asked which scenario out of three alternatives is most acceptablefrom your perspective. Please choose your most preferred option out of the three alternatives shown. B8. Again, put yourself in the year 2030. How
acceptable would you find the following scenarios for the future? Please rate each scenario based on the scale shown below.

of hitting a pedestrian as one car), or from level 3 to level 4 (one drone has 1/100th the likelihood of hitting a pedestrian as
one car) could increase societal acceptance by 5 percent each.
Detailed trade-off analysis for air taxis
Taking a closer look at air taxis (see Figure 41), the maximum achievable acceptance rate is 82 percent, as 18 percent ofrespondents said they would never accept an air taxi as part of urban transport system even if the best level of safety, noiseand visual pollution could be achieved. However, nearly one third indicated that they would accept air taxis in any presented
scenario, given the worst safety, noise and visual pollution level. This means the range of influence by different levels for thedimensions of safety, noise and visual pollution is 49 percent in the given simplified scenario.
Within these 49 percent, the noise dimension is the main influencing factor (increasing acceptance by 18 percent),
followed by safety (16 percent) and visual pollution with (15 percent). In general, as well as for drones, visual pollution is
the least important factor for citizens. Noise on the other hand moved to the first place for air taxis. The results for air
taxis imply that a change of safety from level 1 (~5 fatalities per 10^9 PAX km) to level 2 (~2 fatalities per 10^9 PAX km)
could increase the public acceptance by 8 percent. A change in the safety dimension from level 2 to level 3 (~0.05 fatalities

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per 10^9 PAX km), or from level 3 to level 4 (~0.01 fatalities per 10^9 PAX km) could increase societal acceptance by ~5
percent each. A reason why noise is perceived more important in relation to safety for air taxis could on the one handbe that vehicles are larger and thus more associated in respondents’ minds to today’s helicopters flying in cities, which
are very noisy, and on the other hand that the safety of currently flying vehicles is already perceived as very high andthus is not a top concern for most citizens. The results on safety imply that a change of noise from level 1 (one air taxi
is as loud as a leaf blower) to level 2 (one air taxi is as loud as a truck driving by at city speed) could increase the public
acceptance by 5 percent. A change in the noise dimension from level 2 to level 3 (one air taxi is as loud as a car driving by
at city speed), or from level 3 to level 4 (one air taxi is as loud as a bicycle riding by at city speed) could increase societal
acceptance by 6-7 percent each.
Figure 41: Trade-off analysis results for air taxis
Secured acceptance

Trade-off analysis via conjoint question for air taxis:
different acceptance rates of up to 82% may beachieved, but results are less differentiatedrange by setting
A Influenceable
attributes from level 1 to 4
Increase in accepancefrom level 1 to 2

18
7

49%
A

16%
5
8

8

Increase in accepancefrom level 3 to 4
Non-addressable acceptance

18

15
A

4
3

6

5

Sum

Increase in accepancefrom level 2 to 3

100

4

82%

33
Accept delivery
drones in any
form

SafetyNoiseVisual pollution

Would
accept bestcase scenario

Accept nodeliverydrones at all

Total

Source: EASA UAM societal acceptance survey questions C7. Put yourself in the year 2030: air taxis with wingspans of up to 12 metres, certified bycompetent authorities, are flying at altitudes of about 150 metres. In the following section, you will be asked which scenario out of three alternatives ismost acceptable from your perspective. Please choose your most preferred option out of the three alternatives shown. C8. Again, put yourself in the year
2030. How acceptable would you find the following scenarios for the future? Please rate each scenario, based on the scale shown below.

3.2.6 Environment: priority is protection of wildlife
As indicated above, environmental impact was the second highest concern of citizens. In order to get a better
understanding of the exact nature of this concern, the quantitative survey invited participants to separately rank
detailed environmental concerns they have with regard to drones and air taxis. They were given a list of seven concerns
each to rank from “most concerning” to “least concerning”. Also, they had the chance to choose “none of these”.

The main environmental concerns relate to
the risk of negative impact on wildlife (birds,
insects, bats, etc). The results are identicalacross the six cities.

3.2 Survey results (10 key findings)

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As the results in Figure 42 show, the top-three environmental risks
that survey participants expected to see with delivery drones andair taxis were the same: nearly two out of three participants feared anegative impact on animals from drones, while 56 percent feared
the same for air taxis. Negative impact on animals was more often
mentioned as a concern by the age group older than 65. This age

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group was concerned, for example, that animals could be disturbed and that this could lead to a reduction of birds inurban areas. Noise pollution is also an environmental concern: for both delivery drones and air taxis more than halfof participants named noise as one of their top-three-concerns. The third concern related to the environmental andclimate impact of the manufacturing and production of the vehicles and of their batteries.
Environmental concerns on drones
When taking a closer look at the expected environmental impact of drones, three concerns clearly stood out: negative
impact on animals (62 percent), noise pollution (52 percent) and environment and climate impact from production
including batteries (43 percent). This last concern was significantly higher than climate impact from operation, with only
one third of participants being concerned about the latter.
Figure 42: Details on environmental concerns

Environmental concerns ranked by % of respondents
under top 3%
Delivery drones
Negative impact on animals

Ranked under top 3

Air taxis

62

Noise pollution

56

52

Environmental and climate impact fromproduction (incl. battery production)
Climate impact from operation(incl. energy expenditure)

53

43

42

33

40

Environmental impact from disposal

29

30

Sealed surfaces

28

33

Emissions

28

31

None

8

5

Source: EASA UAM societal acceptance survey questions B9. What are your greatest concerns when it comes to the possible envir onmental
consequences of drone delivery? Please sort the following answers from 1 being ‘most concerning’ to 7 being ‘least concerning’ or select ‘noneof these’. C9. What are your greatest concerns when it comes to the possible environmental consequences of air taxis? Please sort thefollowing answers from 1 being ‘most concerning’ to 7 being ‘least concerning’ or select ‘none of these’.

At the end of the list, participants ranked lowest the concerns around disposal, sealed surfaces, and emissions (~28
percent). The concern about emissions decreased by age: the age group 55 to 65 years expressed less concern on this
topic (-8 percent), while the youngest age group 18 to 25 year expressed higher concern (+12 percent).
The results demonstrate an amazing homogeneity across the cities, with responses and the rankings closely aligned
when it comes to environmental concerns on drones (see Figure 43). It is to be noted however, that the largest
differences in concerns between cities relate to the environmental impact of local emissions, likely driven by differencesin perceived current air quality in the respective cities.

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Concerns for delivery drones
Figure 43: There is a major difference between cities on concerns around delivery drones and emissions
Cities very aligned in opinion, especially for highly ranked environmental concerns
Total

Barcelona

Budapest

Hamburg

MilanÖresundParis

Share of respondents that rank concern under top 3
8.5

0%

10%

20%

30%

40%

50%

60%

70%

Negative impact on animals
7.5
Noise pollution
6.5
Environmental and climate impact
from production (incl. battery production)
Climate impact from operation(incl. energy expenditure)

5.5
4.5

Environmental impact from disposal
3.5
Sealed surfaces
2.5
Emissions
1.5
None
0.5

Source: EASA UAM societal acceptance survey questions B4. What are you most concerned about regarding drone delivery, both for the delivery of day-to-day
goods as well as medical supplies? Please consider your own usage of such a service as well as other people using it (e.g. your family or neighbors), which may
affect you as well. Please select up to 6 answers. B5. Please sort your main concerns (selected in B4.) from ‘most concerning’ to ‘least concerning’.

Environmental concerns on air taxis
When it comes to air taxis, two concerns ranked significantly higher than others: the negative impact on animals (56percent) and noise pollution (53 percent). Again, environmental and climate impact for production (incl. battery) andoperations ranked third and fourth, but these concerns were mentioned nearly the same number of times (42 percent
for air taxis vs. 40 percent for drones). While younger people were more concerned with climate change, they were lessconcerned by noise (-10 percent).

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Environmental concerns for air-taxis
Figure 44: Concerns on air taxis are nearly the same across survey cities
Impact on animals and noise are highest ranked environmental concerns regarding air taxi use case
Total

Barcelona

Budapest

Hamburg

MilanÖresund

Paris

60%

70%

Share of respondents that rank concern under top 3
8.5

0%

10%

20%

30%

40%

50%

Negative impact on animals
7.5
Noise pollution
Environmental and climate impact
from production (incl. battery production)

6.5
5.5
Climate impact from operation(incl. energy expenditure)
4.5
Environmental impact from disposal
3.5
Sealed surfaces
2.5
Emissions
1.5
None
0.5

Source: EASA UAM societal acceptance survey questions B4. What are you most concerned about regarding drone delivery, both for the delivery of day-today goods as well as medical supplies? Please consider your own usage of such a service as well as other people using it (e.g. your family or neighbors), which
may affect you as well. Please select up to 6 answers. B5. Please sort your main concerns (selected in B4.) from ‘most concerning’ to ‘least concerning’.

Just as for drones, participants were aligned across geographies on the top environmental concerns. However, thelargest spread in opinion across cities showed up when considering environmental impacts both from disposal of air
taxis and emissions (see Figure 44).
The risk to wildlife was repeated during the qualitative interviews, principally by local stakeholders. Examples mentioned
were birds disturbed by noise, or bats and other animals disturbed by lights if aircraft was flying at night.
Possible mitigation option: the eco-label
As part of understanding potential solutions to societal acceptance andbuy-in in relation to environmental impact, the questionnaire invited
respondents to indicate whether, in their view, the environmental impact
of Urban Air Mobility operations should be evaluated by the authorities andmade public, e.g. via an eco-label, such as the one being developed by EASA
for traditional aviation:

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Figure 45

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As illustrated by Figure 45, a large majority (74 percent) of survey participants saw advantages in introducing an ecolabel for commercial Urban Air Mobility vehicles and operations.
Figure 45: An eco-label for commercial VTOL can increase societal acceptance
A vast majority of 74% in favor for introducing an eco -label for commercial VTOL
No

Total

3%

23%

Maybe, don’t know

Yes, certainly

74%

Source: EASA UAM societal acceptance survey question D4. Should the environmental impact of urban air mobility operations be evaluated by theauthorities and made public, e.g., via an eco-label such as the one shown below (picture included in back-up)? Please select one answer.

Again, the responses were similar across all surveyed cities. Participants from Barcelona showed a slightly morepositive attitude towards such an eco-label (+8 percent) compared to others. Oresund (-8 percent) showed the lowest
enthusiasm.
3.2.7 Noise: acceptable at level of familiar city sounds
The findings of the noise perception study described in the survey methodology section (see § 3.1.3) are presented in thissection.

Citizens’ acceptance of noise
expected to increase overtime
At the same sound level, participants of anoise test felt more annoyed by UAM
vehicle sounds than by sounds that they
already know.

Figure 46 below presents a summary of the results in which theaverage ratings as well as the minimum and maximum ratings areshown. It must be noted that the worst ranking level was largely
driven by two listeners, as their responses to most sources appears
to have been much more adverse than the responses from others.
These differences in responses were not due to any difference inthe test methodology, such as listening at different sound levels: theconditions were identical for each listener.

Therefore, it can be expected that thelevel of annoyance will decrease as
citizens become familiar with soundsof UAM vehicles, and provided that thesound level and character.

The volume values presented in dBA units in Figure 47 below
correspond to maximum A-weighted noise levels and are notintegrated over time. Consequently, they correspond to the loudest
instant in the sound sample, but do not capture that noise events
may be significantly different in duration from one another, andthus result in very different perceptions by the listeners. This aspect should be accounted for and soften the following
conclusions.

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Figure 46: Result overview of noise perception study

Sample size n=20

1. UAM noise is more annoying at same noise level…

Average

How annoying sound was perceived

Sound type

VolumeHelicopter

80 dBA

Aircraft

80 dBA

Motorbike

80 dBABus

80 dBA

Light Drone

80 dBA

Large Drone

80 dBA

Air Taxi 1

80 dBA

Air Taxi 2, Position 1

80 dBA

Air Taxi 2, Position 2

70 dBA

Air Taxi 2, Position 3

60 dBA

Not at all annoying
012Extremely annoying
3

4

5

6

7

8

9

10

Although this is a small sample of results, the responses have also been analysed statistically. Figure 47 @VG:
below showsform…
mean response and the 95 percent confidence intervals for each source. A repeated measures ANOVA (analysis oftemplate ofvariance) shows that there is a statistically significant effect of vehicle type on annoyance (F(9, 180) = 24.17, p < 0.001).

page

Figure 47: Statistical analysis of responses
53

AverageAnnoyance
Not at all annoying

Sound type

0

1

2

Extremely annoying
3

4

5

6

7

8

9

10

Helicopter
Aircraft
MotorbikeBus
Light Drone
Large Drone
Air Taxi 1
Air Taxi 2 Position 1
Air Taxi 2 Position 2
Air Taxi 2 Position 3

56

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Some important information can be inferred from Figure 46 and Figure 47. Figure 48 shows the comparison between
familiar sounds and UAM aircraft played at same maximum noise level. Figure 46 shows the noise perception rating forsources at different distances.
Observations of sounds played at the same noise level (see Figure 48):
• Responses showed a clear separation between the drone/air taxi sources and the others, at the same sound level;• This separation is particularly marked between the drone/air taxis and the road vehicles;• The air taxi and large drone scored the highest mean average result of 7.8. The synthesised air taxi at 80dBL Amax,F(Air Taxi Position 1) scored only slightly lower (mean of 7.7) but had the most instances of the highest score of 10@VG: form(5 times).

template ofpage
This could lead to conclusions that unfamiliar sounds, in this case UAM sounds, are perceived more negatively
or that thesound characteristics of these aircraft lead to a more negative rating at the same maximum noise level compared to theother sounds to which the participants were exposed.
Sample size n=20

Figure48: Result
between familiar
soundandlevel…
Urban Air Mobility vehicle sounds at same maximum noise level
1. UAM
noisecomparison
is more annoying
at samenoise
Average

How annoying sound was perceived
Not at all annoying

KnownSoundsUAM
SoundsSound type

VolumeHelicopter

80 dBA

Aircraft

80 dBA

Motorbike

80 dBABus

80 dBA

Light Drone

80 dBA

Large Drone

80 dBA

Air Taxi 1

80 dBA

Air Taxi 2

80 dBA0

1

2

Extremely annoying
3

4

5

6

7

8

9

10

54

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Observations with respect to different distances (see Figure 49):
• As expected, the synthesised air taxi score dropped with distance/sound level, both in terms of individual ratings andthe mean average. The difference in responses between Position 2 and Position 3 was greater than the difference inrating between Positions 1 and 2;• As expected, the synthesised air taxi at the furthest distance (and 20dB quieter than the other sounds) scored thelowest ranking, with an average score of 3.2;
• It can be seen that at a distance equivalent to 60dBL Amax,F the annoyance level was below the annoyancefor the@VG:
form
familiar reference sounds at 80dBL Amax,F. The level of 60dBL Amax,F on top of a background noise of 55dBL Aeq seemedtemplate of
to be largely acceptable for the 20 test participants.

page

Figure 49: Noise perception at different distances

2. Annoyance levels significantly decline with noise levels
Average

How annoying sound was perceived
Not at all annoying

Sound type

VolumeAir Taxi 2, Position 1

80 dBA

Air Taxi 2, Position 2

70 dBA

Air Taxi 2, Position 3

60 dBA0

1

2

Extremely annoying
3

4

5

6

7

8

9

10

Additional response comments
The following summarises the main themes that were noted in the listeners’ comments or mentioned after the listening
tests to the Arup staff:• Familiarity: Most comments featured recognition of or familiarity with the sounds being linked to lower (relative)
annoyance scores (e.g. the aircraft and motorbike), with one commenting that these sounds were ‘part of everyday
life’. One listener linked the familiarity of the sound with perceived frequency of occurrence, i.e. ‘I only hear anaircraft a few times a day, so I don’t find the sound too annoying’. Similarly, some respondents said they owned a
motorbike so were not annoyed by that sound.
• Unfamiliarity: In several cases participants did not understand what they were listening to or could not imagine
the source of the noise sample, as evidenced by descriptors including ‘lawnmower’,‘swarm of bees’or ‘boat’. The
listeners had not been asked to try to identify the sources but several attempted to do so.
• A difference in response between familiar and unfamiliar sounds was also reflected in the response ratings, shownby Figure 49. No visualisation was provided during the tests that could have helped people understand the soundsources. It is not known whether this had a positive or negative effect on responses to UAM sounds.
• The relationship between familiarity and response should be investigated in any future tests, since it may be that
responses would become more aligned with current transportation sources if such aircraft were to become acommon feature of the urban soundscape.
• Whilst not intentionally part of the pilot study, the speed of the pass-by was also commented on by several
participants. i.e. a slow pass by was more annoying than a quick one, possibly because of the amount of time exposedto the Lmax level or because the L Aeq would have been higher for the longer exposure. This could be investigatedfurther in a larger study, to consider the relationship with rise-time and startle, as well as duration of the sound.
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Sound character and response
Spectrograms have been calculated for each sound source, to enable a preliminary assessment of the effect of soundcharacteristics on responses and show the change in the magnitude and frequency content of the sound with time.
Examples are shown below. Time is plotted along the horizontal axis and frequency on the vertical axis. The colours
indicate the sound pressure level: blues are the lower levels, with increasing levels being reflected in magenta, throughred to white.

Air taxi

Large drone

HelicopterBus

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There are elements of tonality at frequencies where they might be expected, such as low frequencies for the bus. Thereis generally a clear tonal component at around 3kHz for most drones/air taxis, which would correspond to frequencies
where humans are most sensitive. However, the tonality is much more distinct with the air taxis than with the drones,
which may be a factor in their higher annoyance rating.
The drones and helicopter exhibit a series of vertical transients with higher magnitude darker lines occurring in quick
succession in their spectrograms. This characteristic is not evident in the other samples.
Conclusions of noise study
Initially it must be emphasised that this study was only meant to provide initial takeaways and insights. Results are notsufficiently significant and would have to be done at larger scale to draw conclusions. Nevertheless, the results provide
insights that can support the design of further and more detailed studies.
It is apparent from this small study that there was a difference between reaction to sounds of drones/air taxis (at thesame sound level) and reaction to other sound sources. This may be due to differences in sound character or differencesin familiarity with the sounds. Participants more easily accepted sounds they were familiar with (even helicopters or
motorbikes) and expressed annoyance towards unfamiliar sounds at the same maximum noise level.
This conclusion must be weighed alongside the fact that, despite being played at the same maximum noise levels,the noise samples exhibited very different time durations or rise-and-fall dynamics. This introduces a clear bias in theperception, as longer noise events are always perceived more negatively than shorter ones.
This consideration would benefit from further investigation through a larger set of tests. It may follow that sound level
limits for these types of aircraft may need to be assessed and treated differently to other sources. Conversely, increased
familiarity with such sound may lead to a greater acceptability in future.
A larger study would also allow the relationship between annoyance and other acoustic characteristics to beinvestigated.
As expected, people reported lower annoyance to sounds at lower sound levels. A statistically significant sample to test
this in relation to unfamiliar sounds would be a beneficial part of a future study. For this pilot study, the tests adjusted
only the level across three different sound levels, and not any other acoustic characteristics that would arise from thesame source being at increasing distances: at a greater distance, the same noise source is attenuated, but its rise-andfall dynamic (perceived duration) can increase.
The duration for which the sound was at a high level appears to have affected the responses. This should be assessed
further to establish whether there is any relation between the duration of the sound and potential ‘startle’ effects ofsteep rise times. These issues could be particularly important when defining and assessing the potential locations ofvertiports.
Further consideration should be given to whether visual representation of the sound sources should be included in any
future wider study and how this might affect the outcomes.

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3.2.8 Security: need to build confidence and trust in citizens
As indicated by the results to the generic concerns questions, security was the third highest concern of respondents.
The survey looked into more detail at the trust level of citizens regarding the security and cyber-security of UAM, bothfor drones and air taxis. Participants were invited to indicate to what extent they trust that advanced aircraft flying in an
urban environment will be technologically secure and protected against malicious threats and actions. The participants
could then indicate different levels of trust ranging from fully trust to fully mistrust.
The results can be seen in Figure 50: The level of trust for delivery drones as well as for air taxis is just above 50 percent
and therefore could be improved.
Figure 50: Trust levels in VTOL technology incl. security and cybersecurity
Trust levels show similar trends for drones and passenger transport
X%

Sum

Fully mistrust

Mistrust

Somewhat mistrust

Somewhat trust

Trust

Fully trust

Deliverydrones

46%

10%

12%

23%

31%

19%

4%

54%

Passenger
Transport

47%

10%

12%

25%

32%

17%

3%

53%

A minor difference can be seen between the demographics: while men were more likely to trust UAM services(~+7 percent), women (~-7 percent) and the older age group between 65 and 75 years (~-8 percent) were more likely to
Source: EASA UAM societal acceptance survey question D2. To what extent do you trust that advanced aircraft flying in an urban environment will be technologicallyshow
It is threatsno surprisethattheones thatduringhacktivists
the survey
answered
to becases?
rejectersof delivery
and/orsecuremistrust.
and armed against
from hackers(such
as criminalorganisations,or terrorists)in the following
Please selectone answer per
row. air taxi
usage as well as digital laggards are amongst those with lowest trust level towards UAM (-16 to -27 percent less trust).
Some small local differences in trust were observable: The highest level of trust showed up in Milan (+10 percent
for drones, +7 percent for air taxis) and Budapest (+7 percent, +10 percent). The lowest trust level showed up in Paris(-10 percent, -8 percent).
Another question tested whether the trust level of respondents would increase if the regulators were to develop
regulations to manage cybersecurity risks (certification and operation of aerial vehicles). Figure 51 shows that on
average 37 percent indicated that cybersecurity regulations would not influence their trust in vehicles. Also it can be seenthat the public has no preference if these topics are regulated on European, national or regional level.

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Numbers wrong?

Figure 51: Impact on trust level due to regulation by authorities

On average, 37% indicate cybersecurity regulations by authorities would not influence their trust
X%

Sum

Decrease a lot

Stay the same

Increase

Decrease slightly

Increase slightly

Increase a lot

52%
European12%
authorities

6% 7%

35%

25%

21%

7%

20%

6%

18%

5%

51 %
National 13%
authorities

6% 7%

37%

25%

48 %

Figure 52: Impact on trust level due to regulation by authorities

Regional or
local
14%
authorities

5%

8%

39%

25%

Source: EASA UAM societal acceptance survey question D3. Would your trust increase if the following regulators were to develop regulations to manage cybersecurity
risks (certification and operation of aerial vehicles)? Please select one answer per row.

On the contrary, the survey results regarding concerns related to vertiports (see below, Figure 53) showed that security
issues linked to the vertiport operations are not a major concern of respondents (ranking 5th). This could be explainedby the fact that vertiports are still at the conceptual stage and that very few representations are available to the generalpublic at present.
Interview respondents on local and national level indicated that they would prefer a regulation on European level thatthey can rely on.
3.2.9 Ground infrastructure: must be integrated well
The survey also looked at the attitude of citizens towards emerging UAM ground infrastructure for drones and air taxis.

Integration into thecity and local transport
network
UAM services need to be integrated into
the existing local mobility system. Visual
impact of aircraft and infrastructure
should be limited and preserve city
landscape.

86

Infrastructure for delivery drones
To get insights on drone delivery, participants were asked how
comfortable they would be with different modes of drone delivery
for medium-sized parcels (max. 120 x 60 x 60 cm, up to 5 kg). Overall,participants said that the closer to a private area that a drone candeliver, the more comfortable they would feel (see Figure 52). Some
68 percent would prefer delivery to their own garden or private space,
67 percent delivery to a station within the neighborhood, 52 percent
on walkway in front of the house, 45 percent would like a delivery on

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the top of the house or to their office. Still 39 percent said they would be satisfied with delivery to a nearby park. The
option of delivery to garden was especially popular in Budapest (+16 percent) and Milan (+11 percent) and least popular in
Oresund (-13 percent). The option of delivery in front of the house and on the roof of the house were in the midfield – butshowed high deviations: The approval was for example higher within the groups of participants aged 25 to 44 (+2 percent
for delivery on walkway, +8 percent for delivery on top of house) and families (+7 percent, +6 percent), while it was lower
within the older age group aged 55 to 75 (-6 percent, -10 percent) and within the group of singles (-7 percent, -4 percent).
Figure 52: The closer to the house the better is what counts for drone delivery
Very uncomfortable

Somewhat uncomfortable

Comfortable

Uncomfortable

Somewhat comfortable

Very comfortable

X%

Sum
comfortable

Preferred drop-off locations for parcels delivered by drones are garden / private area and delivery station in neighbourhood
Low level of comfort

High level of comfort
68%

67%

10%

10%

9%

9%

14%

14%

52%

14%

45%

39%

22%

24%

13%
16%

17%

21%
30%

17%

33%

20%
28%
23%

23%

22%
22%
18%

15%

12%

Garden or private area

Delivery stationin neighbourhood

15%

12%

6%

7%

5%

Walkway in frontof my house

Roof on top ofhouse or office

Nearby park

Source: EASA UAM societal acceptance survey question B6. How comfortable would you be with the following modes of drone delivery for medium-sized parcels (max. 120
x 60 x 60 cm, up to 5 kg) at places near your home? Please select one answer in each row.

Infrastructure for air taxis
It is assumed that air taxis will need specific infrastructure on the ground to embark and disembark passengers, as wellas to recharge their batteries, as their autonomy will be limited. Assuming that a take-off and landing-station would beclose to them, i.e. close to their living or working place (under 50 metres), the respondents to the questionnaire wererequested to indicate what they would be most concerned about. They replied that (Figure 53), noise from take-off
and landing (48 percent) and safety (41 percent) are their main concerns. In line with the concerns on drones and air taxis
in general, the fear of noise pollution increased with age and education. The third concern mentioned most often forvertiports is on visual pollution (32 percent). Participants also feared that vertiports close to where they are living could
negatively influence their privacy (31 percent).

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Concerns regarding vertiports ranked by % of
Figure53: Concerns
respondents
underrelated
top 3 to vertiports
Noise from take-off
and landing
17

14

8

Visual pollution
Privacy

13
15

8

12

Security2More road traffic inneighbourhoodSpace occupation needed
for living or recreation

10

6

4

5

Space occupation needed
for retail4

5

Ranked #3

10

48%
41%

12

32%

8

31%

9

31%

11

11

29%

8

11

28%

9

More people walking by

Ranked #2

12

15

21

Safety1

None

Ranked #1

6
5

15%
14%

0

1. Incident due to technical or human failure
2. Incident due to deliberate harmful action, e.g. by criminal organization or terrorists
Source: EASA UAM societal acceptance survey questions C11. Assuming that a take-off and landing-station is close by (under 50 metres), what are
you most concerned about? Please select up to 6 answers. C12. Please sort your main concerns from ‘most concerning’ to ‘least concerning’.

These results are to put in parallel with the notion of “not in my backyard” regularly expressed during the qualitativeinterviews. UAM was seen as positive and attractive as long as the impact does not affect specifically and negatively an
individual or a group of individuals.
3.2.10 Regulatory authorities: must work together at all levels
As one objective of the study was to support future regulatory work on UAM, participants’ expectations towards European,national, regional or local authorities were assessed. The survey polled participants’ trust levels towards local, national andEuropean authorities to handle the risks associated with UAM and to adopt adequate regulations (see questions D1 to D3).
As results in Figure 44 indicate, the participants’ trust towards local, national, regional and European authorities came withnearly the same proportion, with a slightly higher level of trust overall towards European regulatory authorities.
A closer look at the results in each of the six cities reveals local differences. As demonstrated by in Figure 55. participants
form Budapest, Italy and Spain expressed better trust towards
Public acceptance will most likely
European authorities, while participants from Germany and Oresund
increase if authorities on all levels work
trusts better national and local authorities. It is to be noted thattogether. This will also allow to link the
respondents from Paris were the most sceptical and express a low trust
UAM operations to the different local
level towards all authorities, below 50 percent in all cases.
conditions.
Qualitative interviews with local stakeholders reinforced this finding.
Most of them, except those coming from cities where pilot projects or demonstrators are taking place, had morequestions than answers to the interview questions, as UAM is new and information on it has not yet reached the local
decision-making level. Many of them are concerned by potentially insufficient information to take informed decisions as

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Figure 54: Overall, participants trust European authorities a bit more than national, regional or local ones
X%

Sum

Europeanauthorities

43%

National
authorities

46%

Fully mistrust

Mistrust

Somewhat mistrust

Somewhat trust

Trust(absolute %, +/- difference to avg % in total)

Fully trust

20

11%

22%

30%

21%

11%

14%

22%

30%

20%

6%

Reference page

Regional or
46%
24%
9%
13%
local authorities
D1. Trust levels in regulation authorities – per city (2/3)

30%

20%

57%

4%

54%

4%

54%

Source: EASA UAM societal acceptance survey question D1. To what extent do you trust the following authorities to handle the risks and adopt regulations needed
to manage urban air mobility (including safety, noise control, environmental protection, security, cybersecurity, etc.)? Please select one answer per row.

Figure 55: Whom citizens trust most depends on where they come from

Budapest with highest trust in European authorities, Oresund with higher trust in local andnational authorities
X%

Sum

Fully mistrust

Mistrust

Somewhat mistrust

67%
57%

6%
21%

59%

21%

2%

61%

5%

5%

25%

21%

17%
26%

4%
16%

31%

35%

4%

27%

22% 22% 21%

47%

5%
20%
18%

30%

50%

55%

3%

3%

5%
18%

18%

10%

12%

7%

(+/- difference to avg % in total)

26%
21%

4%

4%
20%

18%

34%

31%

24% 28%

35%
26%

18%

21%

51%

5%

56%

54%

4%

2%

19%

18%

12%

8%

6%

European authorities

10%

15%

14%

17%
17%

12%

7%
16%

11%
13%

Total

15%

9%

10%
7%

National authorities

6%

18%

33%

35%

20%
24% 24%
26%

13%

13%
9%

Total

14%
12%

49%

27%

21%

18%

30% 28%

50%

2%

5%

27%

19%

34%

25%

20% 23%
9%

14%
11%
10%

5%

32%

8%
10%

14%

Total

54%
48%

17%

25% 28%22% 23%

55%

9%
11%

Fully trust

65%

7%
54%
48%

17%

30% 29% 29% 29%

22% 21%

61%

48%

28%

Trust

68%

9%

8%

Somewhat trust

8%

5%

17%

11%
7%

11%

Regional or local authorities

Source: EASA UAM societal acceptance survey question D1. To what extent do you trust the following authorities to handle the risks and adopt regulations needed to
manage urban air mobility (including safety, noise control, environmental protection, security, cybersecurity, etc.)? Please select one answer per row.

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well as on insufficient involvement of local authorities in the deployment of UAM locally. They did not see easily how therole of local authorities would be articulated with that of national and European authorities.
Overall, the study highlighted the expectations by respondents and stakeholders that all levels of authorities play a rolein the deployment of UAM. The very specific nature of UAM operations, closely linked to the local conditions, needs andconstraints can explain this expectation.

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4.Expectations andoptions for action
This chapter considers possible actions and measures that could be taken to address stakeholder concerns and increasesocial acceptability levels of UAM. Preliminary qualitative assessments of costs and benefits for some measures are
considered.

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4.1 Citizens’ and stakeholders’ expectations
The cumulated results of the quantitative survey, qualitative interviews and noise simulation reveal some general trends
in public acceptance in the EU.
EU citizens initially and spontaneously expressed a positive attitude toward and interest in UAM, seeing it as a newand attractive means of mobility able to offer faster, cleaner and extended connectivity. However, they also expressedsignificant concerns. When prompted to reflect upon the concrete consequences of potential UAM operations intheir city, EU citizens want to limit their own exposure to risks and expect authorities to pro-actively respond to theseconcerns.
Public acceptance is a critical success factor of the future deployment of UAM, and it must be secured by a number of
preventive actions. Some of these actions fall under the competence of regulatory authorities :• Address safety, ensuring that UAM has a safety level equivalent to that of current aviation operations for passengers
and for people on the ground;• Ensure local environment protection by less local emissions, less congestion and sufficient protection of wild life;• Ensure global environmental protection from a life-cycle point of view;• Ensure birds and insects are not affected by the production of the aircraft and their operations;• Address UAM noise, ensuring that the level, frequency and duration of the related sounds is kept at acceptable levels,
notably when first UAM operations start, as unfamiliar sounds are perceived as more annoying than familiar ones; tothis effect, further research should be conducted to confirm the survey results with larger panels;• Prevent security and cyber security risks, particularly for drones, as manned aircraft are perceived as more secure,probably due to the presence of a pilot onboard;• Ensure coordinated actions between all authority levels (European, national and local); EU citizens trust them equallyand expect all levels to be involved in decision-making. Local authorities expect more information and guidance, andwant to be involved at an early stage in the decision-making, concerning the roll out of UAM in their territory. This
association will be key for buy-in and acceptance;• Conduct prior studies, for example measuring local noise and wild-life impact and defining quiet zones and times;
this could help reduce affected stakeholders’ uncertainty or fear regarding the introduction of UAM;
• Ensure that UAM fits with the notion of “public interest” by making it affordable to all, and integrating it into the local(multimodal) mobility system/network accessible to all;• Support the deployment of UAM supported by timely, sufficient and transparent information and dialogue with tocitizens and local stakeholders groups;• Encourage demonstration and pilot projects in order to show that UAM can actually work and is safe. Gradually
introducing use cases with the highest benefit for the general public, e.g. transporting medical goods with manned
eVTOLs could also reinforce societal acceptance;• Regulate airspace/aviation and aircraft design dimensions carefully. The integration of airspace should also be
clarified, as this can provide a framework for the operation of conventional and UAM aircraft in the same airspace,e.g. around airports.

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4.2 High level cost-benefit analysis of options
Some of these possible actions, notably the first four, fall at least partly under the competence of the EU regulator, inparticular EASA.
A qualitative cost benefit analysis was therefore conducted to assess the options available to act on the safety, security,
noise and environment dimensions. The following assessment, which was not the core subject of the study, is provided
as a high level indication of the options available to EASA to address these four specific concerns.
Possible safety measures
For safety, two different levels were evaluated: A high safety bar for UAM, similar to the one established in commercial
aviation today and a slightly lower safety bar similar to the highest requirements in the automotive industry.
If the high safety bar were adopted for UAM, it could lead to significant higher costs for the business cases of thecompanies in this field, but it could result in a very low number of injured people and damaged property. This in turn
may facilitate a higher societal acceptance of UAM, as can be seen in the results of the survey. Indeed, the societal
acceptance increases by 10 percent for the drone delivery use case and 9 percent for air taxi use case, if a safety bar
similar to commercial aviation was implemented instead of one similar to the highest automotive one. Among theassessed cost dimensions were extensive redundancy requirements in the UAM system, longer duration of UAM
introduction due to extended design and testing periods, as well as shorter intervals between maintenance checks of
UAM aircraft and infrastructures. This was then qualitatively assessed to have a high impact on UAM system costs.
For the slightly lower safety bar, the associated increased risk to the population could be unacceptably high, andincidents or accidents could severely hamper the emerging UAM market. From a potential benefits point of view, thisapproach could offer a faster introduction of UAM services and therefore also provide faster assistance in battling
ground-based traffic congestion. The cost impact was assessed as medium, due to a lower redundancy requirement,
faster introduction of UAM services, and longer maintenance intervals for UAM aircraft and systems.
However safety is not a dimension where a business trade-off is acceptable in our society. Even a low number ofaccidents such as seen for autonomous cars can quickly cause a deterioration of public perception, thus the highest
standards should be applied to UAM to foster its acceptance.
Possible security measures
In the security domain, possible measures on cyber security, security checks of passengers and counter UAM systems
were assessed.
Cyber security should prevent the hacking of UAM communication and therefore avoid the malicious use or control of
UAM. This could be done by encrypting the communication signals in the UAM system through hardware and softwarebased encryption. The cost impact could be medium and would potentially come from securing and monitoring thecommunications network and/or establishing a private command and control (C2) communication link.

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Secondly, security checks of passengers similar to those carried out at airports could reduce the risk of malicious UAM
use by the passengers. Equivalent checks could also offer the potential for passengers to directly connect to commercial
aircraft at an airport gate. Measures could potentially include scanning of luggage and passengers, as well as limiting
the carrying of liquids. The capital expenditure for the security technology, the increased personnel requirements atvertiports, and the potentially reduced competitiveness of UAM from the point of view of passenger time saving weresome of the evaluated cost points which could result in a medium to high overall cost impact for UAM.
Finally, counter UAM systems, such as geofencing, might be needed to protect no-go areas from access by UAM. The
acquisition and operation of counter UAM systems comes at a cost, but this was assessed to be low for the overall UAM
system.
Possible measures on noise
The strength of focus on reducing the noise footprint of UAM will affect the overall cost impact on the UAM system.
The strong focus on reducing the noise footprint could risk significantly impacting the UAM business case due to highaircraft costs, but might bring the benefits of higher societal acceptance. This is indicated by the survey results, wherea strong, rather than low, focus on reducing noise footprint increases public acceptance by 11 percent for the dronedelivery and air taxi use cases. A strong focus on noise production could include measures like limiting aircraft noise to
the level of a car at city speed and limiting the maximum aircraft on flight routes. Limiting the maximum number ofaircraft on flight routes could also aid the societal acceptance of visual pollution. This would result in high aircraft costs,
but could result in lower operating costs on defined routes due to a lower possible flight altitude and therefore shorter
flight time for a set noise footprint on the ground. The overall cost impact of a strong focus on the UAM system could be
medium to high.
A low focus on reducing noise footprint could severely reduce societal acceptance, but would make UAM more quickly
available and could reduce the aircraft complexity. If the aircraft noise were limited to the level of a leaf blower or an old
motorcycle, the aircraft costs could be lower. However, the operating cost might be higher, due to a higher flight altitude
in order to achieve a set noise footprint on the ground. There could also be more noise-related complaints or law suits
than for the strong focus on the noise footprint. This cumulates in a medium overall UAM system cost impact.
Possible measures on environment
From an environmental point of view two dimensions, wildlife protection and lifecycle sustainability, were each
evaluated in a stronger and weaker form.
Strong environmental wildlife protection could help counteract a general reduction in biodiversity by increasingprotection of local wildlife, but it could risk an economic impact on the UAM system. Potential measures in this domain
could be the establishment of wildlife protection areas with no overflights, the implementation of bird avoidancesystems, or specific onboard equipment like lights. This could lead to longer flight routes in order to avoid the wildlife
protection areas, and the installation of bird avoidance systems either on the ground or in the UAM aircraft. For theoverall UAM system, the implied costs of these potential measures were assessed as medium.
Weaker environmental wildlife protection could help local wildlife by simply establishing protection areas with limited or
no overflights. The implied smaller restrictions to flight routes would result in an overall low-cost impact on the overall
UAM system.

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A high lifecycle sustainability of UAM could reduce the risk of accelerating global warming and might bring create
additional jobs in the value chain, while lowering the indirect cost of climate change. Possible measures could forexample be a mandate for only using renewable power for the operations of UAM and requiring a recycling rate of morethan 90 percent for the UAM aircraft and infrastructure. This could lead to higher costs for aircraft manufacturing andoperations of the system, therefore the overall cost impact could be high.
A lower lifecycle sustainability of UAM could still somewhat reduce the risk of accelerating global warming, while
maintaining a potentially low UAM system cost impact. A potential measure for this would be a mandate for some useof renewable power for operations and this could result in a lower cost impact for vehicle manufacturing and operations.

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5. Conclusions
This comprehensive study is the first of its kind and scope to measure the societal acceptance of UAM in the EU. New
modes of transportation rarely appear, a recent example being autonomous cars, and their broad acceptance by society
is typically linked to a series of factors. These include the maturity of certain technologies and how they are perceived interms of threats or benefits by the public. The case of autonomous cars has demonstrated how difficult it is to predict
exactly how a technical innovation will be adopted by users and by society in general.
For instance, as it was indeed difficult at this stage to provide real noise simulations or to quantify with certainty the
number or frequency of UAM aircraft flying in a given city on a given day, it was also difficult to fully appreciate theannoyance this could cause.
It must therefore be kept in mind that this study has measured the attitude of the EU society towards the UAM at a given
moment, i.e. early 2021, well in advance of future deployment in EU cities foreseen around 2024-2025. At this stage,
information on UAM has been mostly reserved to specialised press and media and has not really reached the generalpublic. Citizens therefore variously still perceive Urban Air Mobility as “science fiction” or “an exciting new concept”, buthave not yet been exposed to actual operations and therefore lack tangible experience and feelings.
Globally, the study results tend to show that Urban Air Mobility concepts and operations benefit from a positive image
and could be accepted by EU citizens, who are open to solutions improving the quality of life in the city and offering
benefits for the common good. The acceptance would however be subject to respecting a number of guarantees andconditions to ensure that adequate levels of safety, security and environmental protection will be granted and that no
citizen will suffer an undue and unbalanced nuisance from UAM.
It is now up to the UAM actors concerned, and in particular the regulatory authorities at all levels, to build on thisinitial positive premise and take measures to meet citizens’ expectations, so as to ensure that this initial open attitudetranslates into actual adoption by future users and acceptance from city residents.
For this reason, more specific studies, demonstrations and early implementation projects will likely be necessary
as the concept further develops. Further information for the general public and guidance to national and local actors
concerned will also be useful.

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Appendix
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Appendix 1: EASA’s UAM enabling activities

Aircraft airworthinesscertification of aircraft that are going to be flying in UAM environment on the basis of special Conditiona. For airworthiness certification for Manned VTOLs for operation in urban environment: SPECIAL CONDITION
Vertical Take-Off and Landing (VTOL) Aircraft, Doc.Sc-VTOL-01, issue 1, 2 July 2019 Publication 2nd July 2019 Special Condition for small-category VTOL aircraft;b. For airworthiness certification of Light UAs medium risk that can also be operated in an urban environment:
Special Condition Light Unmanned Aircraft Systems - Medium Risk, Doc. SC Light-UAS Medium Risk 01, Issue 1, 17
December 2020 Special Condition Light UAS Medium Risk ;c. Guidelines on Design verification of UAS operated in the ‘specific’ category and classified in SAIL III and IV, Issue 1,
31 March 2021 Publication 8th April 2021 - Guidelines for the design verification of drones operated in the ‘specific’category.
Operations
Launch of the regulatory developments aimed at introducing requirements for pilots/remote pilots/operators of thesevehicles, operational requirements for operators, infrastructure such as vertiports, airspace integration aspects.
a. Open and Specific category: ED Decision 2020/022/R of 15 December 2020: Amendment 1 to the Acceptable Meansof Compliance and Guidance Material to Commission Implementing Regulation (EU) 2019/947 and to theAnnex (Part-UAS) thereto ‘AMC and GM to Commission Implementing Regulation (EU) 2019/947 — Issue 1,
Amendment 1’ ‘AMC and GM to Part-UAS — Issue 1, Amendment 1 ED Decision 2020/022/R
b. Certified Category: Terms of reference for rulemaking task RTM.0230; Introduction of a regulatory framework forthe operation of unmanned aircraft systems and for Urban Air Mobility in the European Union aviation system,
Issue 2 — 04.06.2018; Introduction of a regulatory framework for the operation of unmanned aircraft systems andfor Urban Air Mobility in the European Union aviation system, Issue 3 — DD.MM.YYYY ( not yet published)
Airspace integration
Adoption by the European Commission of the U-space regulatory package based on EASA technical Opinion (Opinion
No 01/2020, High-level regulatory framework for the U-space, 13 March 2020 Publication on 13th March 2020 - Opinion
01/2020 ).
The U-space regulatory package is due to enter into force in autumn and applicable as from January 2023. The
implementation of U-space will enable UAS operations in urban environment in safer and efficient manner and having
due regard to other societal acceptance aspects such as environment and privacy and security.
Commission Implementing Regulation, amending Commission Implementing Regulation (EU) 2017/373 as regards
requirements for providers of air traffic management/air navigation services and other air traffic management network
functions in the U-space airspace designated in controlled airspace (publication expected in Autumn 2021)

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In addition, EASA has signed the Manifesto of the UAM initiatives by European cities under the UAM Initiative Cities
Community (UIC2) of the EU’s Smart Cities Marketplace – formerly known as EIP-SCC Urban Air Mobility (UAM)
Initiative 30th May 2018 - European Innovation Partnership in Smart Cities and Communities (EIP-SCC).
Finally, EASA is also engaged in a number of European research and demonstration projects, providing guidance andadvice on the regulatory aspects.

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Appendix 2

In addition to chapter 2.2 (Target market identification), this chapter holds further information on identification of target
markets. It also hols more detailed information on the surveys structure and on the methodology of quantitative survey
question types (additions to chapter 3.1.1). Last but not east, the survey questions are attached in this Appendix.
Detailed information on target market identification
As explained in 2.2, for each of the six prioritised sub-use-cases defined in 2.1, the project identified the most attractive
EU urban target markets for UAM OEMs and UAM operators from a business perspective. These target markets arelikely to see initial deployment of commercial UAM services in the European Union and were therefore deemed to beimportant candidates for societal acceptance analysis.
The 4-step-methodology, explained in 2.2, led to an identification of 90 potential target markets (15 cities x 6 use cases)
for initial OEM introduction.
Results of city selection
The following pages hold additional information to chapter 2.2 on use cases and metrics used to decide for the most
relevant cities within the survey.
1. City viability for airport shuttle use casePre-selection for the airport shuttle use case was based on the following metrics:• Availability of an international airport. An airport is required for an airport shuttle service.
• Population size. A large population of minimum 300,000 citizens is needed to ensure sufficient route utilisation.
• Amount of non-transit passengers travelling between the airport and the city centre. An estimation of atleast 25,000 passengers are required for efficient utilisation of a route from an operator’s perspective.
• GDP per capita level. Higher route utilisation rates are expected in cities with higher GDP per capita levels.
This led to a shortlist of 27 cities (see Figure 56).

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Figure 56: Target cities pre-selection process for the airport shuttle use case

Metrics

Selection criteria

City
Availability populationof an airport (Thousand
inhabitants)>300k# cities

yes

Rationale

Shortlist of cities

389

172

Airportrequired for
airportshuttleservice

Number of
non-transit
passengers
per day(Thousand)GDP per
capita (PPPin EUR)

>25k

>35k

75

Large city
population
to ensureefficientutilization
for route36

Estimation
requiresat least
25k
passengers toefficiently utilize
route for
operator

27

Higherutilization
expected
withhigher
GDP per
capitaAustria

ViennaBelgium

Brussels

Czech
Republic

PragueDenmark

Copenhagen

FinlandHelsinkiFranceLyon, Paris,
Toulouse

Germany

Berlin, Bonn,
Cologne,Dusseldorf,
Frankfurt am Main,
Hamburg, Munich,Stuttgart

Hungary

Budapest

IrelandDublinItaly

Bologna, Milan,
Rome

Netherlands

Amsterdam

PolandWarsaw

Romania

Bucharest

Spain

Barcelona, Madrid

SwedenStockholm

These 27 cities were then ranked through a process based on the following KPIs: city size; expected number of trips;
distance between the airport and city centre; travel time between the airport and the city centre with the fastest
alternative travel type (e.g. taxi, car, or public transport) in rush hour; congestion rate; taxi cost for the journey to the
airport; and suitable weather conditions (percentage of weather causes in total arrival delays, precipitation in mm
per year). A weighting factor was assigned to each KPI to indicate how significant that KPI’s impact was on the overall
ranking score (see Figure 57):

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Remaining cities were ranked based on KPIs and top cities were pre-selected for next step

Airport shuttle use case example

Figure 57: Target cities ranking process for the airport shuttle use caseRanking of cities based on further KPIs
KPI

1

2

3

4

5

6

7

Weighting

City size

25%

Expected trip volumes

25%

Distance between airport andcity centre

Travel time between airport andcity centre with fastest
alternative travel type in therush hourTimesaving 25%

Congestion rate

Taxi expenses for ride from airport tocity-centre

Suitable weather conditions (% ofweather causes in total arrival delays,
precipitation in mm
per year)

15%

10%

City

Country

Ranking (100 =best suitability
for UAM)

Paris

88.2

Berlin

78.3

Rome

75.4

Munich75.3

Madrid74.8

Budapest

73.8

Prague

72.8

Milan

72.1

Barcelona

71.4

Dublin70.8

Vienna70.4

Brussels

67.8

Bucharest

67.4

Warsaw

66.8

Amsterdam

65.6

Stuttgart

63.9

Stockholm

63.0

Hamburg

62.8

Lyon

60.8

Frankfurt am Main

59.9

Bologna

59.8

Bonn

59.6

Helsinki

58.2

Cologne57.8

Dusseldorf

56.8

Copenhagen

56.2

Toulouse

55.2

The 15 top-ranking cities were further analysed in terms of the infrastructure available for UAM operations: availabilityof inner-city space for a heliport and availability of a river, motorway or corridor for noise avoidance; availabilityof mobility options for onward journeys (e-scooter, car-sharing etc.), as Figure 58 shows. All 15 cities passed theinfrastructure assessment and entered consideration for final selection as a survey city.

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As final step a cities infrastructure assessment for UAM operations and check of implementation timelines was
conducted
Airport shuttle use case example
PRE-READ
Figure58: Cities infrastructure assessment for the airport shuttle use case

Preselectedcity

Ranking fromprevious steps Availability of(100 = best
inner city space
suited)for heliport

Paris

88.2

Berlin

78.3

Rome

75.4

Munich75.3

Madrid74.8

Budapest

73.8

Prague

72.8

Milan

72.1

Barcelona

71.4

Dublin70.8

Vienna70.4

Brussels

67.8

Bucharest

67.4

Warsaw

66.8

Amsterdam

65.6

Availability ofriver, highway
or corridor fornoise avoidance

Availability ofmobility offer for
onward journey(e-scooter, car- Information fortimeline assessment
sharing, etc.)
Volocopter pilot in
2021

Not feasible until 2025 as
distance to airport too long

Not feasible until 2025 as
distance to airport too long

2. City viability for sightseeing use casePre-selection for the sightseeing use case was based on the following metrics:• Number of international visitors per year. A leading position in terms of number of visitors per year is required asa signal for sufficient demand for potential UAM operators.
• EU membership. Only EU cities were in scope.
From 389 EU cities, 100 were identified as having a large amount of international visitors per year (over 2.4 million), as
Figure 59 shows.

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Figure 59: Target cities pre-selection process for the sightseeing use case

Rationale# cities

Metrics

Selection criteria

Shortlist of cities

International
visitors per
year (Mn)Europeancountry

Member ofEuropean Union>2.4 Mn

Yes

Yes

389

Leading position(top 100
worldwide) in
number of visitors
per year isrequired as signal
for sufficientdemand towards
potential
operators

100Standard
preselection ofEuromonitor

32

26

In scope for EASA
and European
Commission

Austria

ViennaBelgium

Brussels

Czech
Republic

PragueDenmark

Copenhagen

FranceNice, Paris

Germany

Berlin, Frankfurt
am Main, Munich

GreeceAthens, Heraklion,
RhodesHungary

Budapest

IrelandDublinItaly

Florence, Milan,
Rome, Venice

Netherlands

Amsterdam

PolandCracow, Warsaw

Portugal

Lisbon, Porto

Spain

Barcelona, Madrid

SwedenStockholm

The 26 pre-selected cities were then ranked in accordance with the following KPIs: addressable market (number ofinternational visitors per year, expenditure on entertainment and sightseeing per visitor and per trip); number of similar
tourism offerings in terms of scope (e.g. architectural tour, towers and viewing platforms, helicopter trips) and budget(price over EUR 100) as found on getyourguide.com; suitable weather conditions, measured on the basis of ATFM delays
due to bad weather; and attractiveness (e.g. architecture) of city for aerial sightseeing according to expert opinion. A
weighting factor was assigned to each KPI to indicate how significant that KPI’s impact was on the overall ranking score(see Figure 60):

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Figure 60: Target cities ranking process for the sightseeing use caseRanking of cities based on further KPIs

KPI

1

2

WeightingNumber of international
visitors per year

Expenditure forentertainment & sightseeing
per visitor and per trip

Address 25%
ablemarket

City
Paris

93.75

Rome

87.50

Amsterdam

81.25

Venice

81.25
81.25
81.25
75.00
75.00
68.75
68.75

PragueBarcelona
Florence
Budapest

3

Number of similar touristicofferings1

25%

BerlinFrankfurt am
Main
Stockholm
Madrid4

Suitable weather conditions,
measured as annual
precipitation

25%

AthensNice
LisbonVienna5

Attractiveness (e.g.,architecture) of city for aerialsightseeing according toexpert opinion

25%

Country

Ranking (100 =best suitability
for UAM)

Warsaw
Porto
Cracow
MunichMilan
RhodesBrussels
DublinHeraklion
Copenhagen

68.75
68.75
68.75
62.50
62.50
56.25
56.25
56.25
50.00
43.75
43.75
43.75
37.50
37.50
37.50
31.25

The1.top-ranking
15regarding
cities were
finally
analysedtermsof theinfrastructure
available
for UAM operations: availability of
Similar offerings
scope (e.g.,architectural
tour,intowers& viewing
platforms,
helicopter trips)
andbudget (price >100 EUR) as found on getyourguide.com
space near tourist hotspots (see Figure 61). All 15 cities passed the infrastructure assessment and were selected for the
next step.

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Figure 61: City infrastructure assessment for the sightseeing use case

City

Country

Ranking from previous steps(100 = best suited)

Paris

93.75

Rome

87.50

Amsterdam

81.25

Venice81.25

Prague81.25

Barcelona

81.25

Florence

75.00

Budapest

75.00

Berlin68.75

Frankfurt am Main

68.75

Stockholm

68.75

Madrid68.75

Athens

68.75

Nice

62.50

Lisbon62.50

Availability of space near
tourist hotspots

3. City viability for first aid use casePre-selection for the first aid use case was based on the following metrics:• Availability of an emergency rendezvous system (emergency doctor arriving at an accident location
before and separately from an ambulance vehicle). This sub-use-case is most likely to be firstly implemented incountries with the rendezvous emergency system.
• City population. A high number of inhabitants (more than 300,000 citizens) is required as a signal for sufficientdemand for potential operators.
• Accident statistics. A high number of accidents per city inhabitant is a signal for sufficient demand for a first aid
service.
• Congestion rate. A high congestion rate indicates the added value of UAM first aid service.
From a long list of 389 EU cities, 316 were identified as being in countries that have a rendezvous emergency system, and 66 ofthese were further selected as having a large population (over 300,000 citizens). In the next step 64 of the 66 were identified ashaving a high number of accidents per city inhabitant (more than 1 accident/1,000 inhabitants). In the last step 19 of these 64
cities, which have a high congestion rate (over 30 percent), were pre-selected for the ranking process (see Figure 62).
Appendix

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Figure 62: Target cities pre-selection process for the first aid use case

Rationale# cities

Metrics

Selection criteria

Shortlist of cities

City
Availability populationof an airport (Thousand
inhabitants)

Number of
non-transit
passengers
per day(Thousand)GDP per
capita (PPPin EUR)

yes

>25k

>35k

389

>300k

316

The use casewill beimplementted firstly incountries
with therendezvous
emergency
system(emergency
doctorarriving
separately)

66

High
amount of
inhabitants
is required asa signal forsufficientdemandtowards
potential
operators

64

Highamountofaccidents
per city
inhabitant is asignal forsufficientdemandfor a firstaid
service

Belgium

Brussels

Czech
Republic

Prague, Brno

FranceLyon, Marseille,
Nice, Paris

Germany

Berlin, Hamburg,
Munch, Nurnberg,
Stuttgart

Italy

Genoa, Milan,
Naples, Palermo,
ROME

Hungary

Budapest

IrelandDublin19

Highcongestion rate
indicates
a necessity for a
UAM first
aid
service

The 19 pre-selected cities were ranked in accordance with the following KPIs: number of accidents per 1,000 inhabitants
and number of hospitals per 100,000 inhabitants. A weighting factor was assigned to each KPI to indicate how
significant that KPI’s impact was on the overall ranking score (see Figure 63). Cities with the highest number of accidents
and lowest number of hospitals obtained the highest ranking score.

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Figure 63: Target cities ranking process for the first aid use caseRanking of cities based on further KPIs
City
KPI

1

2

WeightingNumber of accidents per 1K
inhabitants

Number of hospitals per 100K
inhabitants

50%

50%

Country

Ranking (100 =best suitability
for UAM)

Paris

83,3

Berlin75

Hamburg

75

Lyon

66,7

Marseille

66,7

Nice

66,7

Genova62,5Prague

62,5

Brno

62,5

Budapest

62,5

Nurnberg

58,3

Stuttgart

58,3

Milan

45,8

Rome

45,8

Dublin45,8München45,8

Brussels

45,8Napoli

45,8Palermo45,8

The 15 top-ranking cities were analysed in terms of the infrastructure available for UAM operations: availability of innercity space for a heliport and availability of a river, motorway or corridor for noise avoidance (see Figure 64). All 15 cities
passed the infrastructure assessment and were selected for the next step.

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Figure 64: Cities infrastructure assessment for the first aid use caseMetropolitan
area

Ranking from previous
steps (100 = best
suited)

Paris

83,3

Berlin75

Hamburg

75

Lyon

66,7

Marseille

66,7

Nice

66,7

Genova62,5Prague

62,5

Brno

62,5

Budapest

62,5

Nurnberg

58,3

Stuttgart

58,3

Milano

45,8

Roma

45,8

Dublin45,8München

45,8

Availability of
innercity space forheliport

Availability of river,highway or corridor
for noise avoidance

4. City viability for Last-mile delivery
Pre-selection for the last-mile delivery use case was based on the following metrics:• City population. A high number of potential customers is required as a signal for sufficient demand for potential
operators.
• Percentage of online ordering. A high number of inhabitants ordering online is required as a signal for sufficientdemand for potential operators.
• Population density. Low population density is required to enable a ‘garden delivery’ option and build delivery
stations for a ‘pre-defined route’ option.
• Availability of same day delivery. Availability of same day delivery is an indicator for sufficient demand fordelivery services in the city.

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From a long list of 389 EU cities, 236 were identified as having a large population (over 300,000 citizens). 56 of thesewere further selected as having a high percentage of online ordering (over 63 percent, which is the average percentage
of online ordering in the EU). In the next step, 31 of these 56 cities were identified as having low population density (lessthan 3,000 inhabitants/km2). In the last step, 26 of these 31 cities that have a same day delivery option were pre-selected(see Figure 65).
Figure 65: Target cities pre-selection process for the last-mile use case

Rationale# cities

Metrics

Selection criteria

Shortlist of cities

City
Availability populationof an airport (Thousand
inhabitants)

Number of
non-transit
passengers
per day(Thousand)GDP per
capita (PPPin EUR)

>300

<3

Yes

389

>631

236

High
amount ofpotential
customers is
required as asignal forsufficientdemandtowards
potential
operators

56

Highamount of
inhabitants
ordering
online isrequired as asignal forsufficientdemandtowards
potential
operators

31

Low populartion density
is required toenable a“gardendelivery”
option andbuild delivery
stations for“pre-definedroute” option

Netherlands

Rotterdam

FinlandHelsinkiGermany

Hamburg,
Nurnberg, Bonn,
Bremen, Bochum,
Düsseldorf,
Dresden,
Dortmund,Duisburg, Cologne,
Essen, Hannover,Leipzig,
Mannheim,
Münster,
Wuppertal

Czech
Republic

Prague, Brno

Denmark

AarhusEstonia

Tallinn

Spain

Saragossa, Murcia,
Palma de Mallorca

SwedenGothenburg

Slovakia

Bratislava

26

Availabilityof sameday
delivery is
an indicatorforsufficientdemand fordeliveryservices

7.4.2 The 26 pre-selected cities were then ranked in accordance with the following KPIs: number of food delivery app
downloads per inhabitant, availability of Amazon delivery centres in the city and average congestion rate per city. A
weighting factor was assigned to each KPI to indicate how significant that KPI’s impact was on the overall ranking score(see Figure 66).

Appendix2
1. Averagevalue for EU

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Figure 66: Target cities ranking process for the last-mile delivery use caseRanking of cities based on further
KPIs
KPI

1

2

3

WeightingNumber of fooddelivery app
downloads
per inhabitant

Availability ofamazon delivery
centresin the city

Average congestion
per city

City

Ranking(100 = best
suitability
Country for UAM) City

Ranking(100 = best
suitability
Country for UAM)

Rotterdam

73,3

Aarhus50

Hamburg

73,3

Nuremberg

50

Helsinki69,2

Duisburg

50

Tallinn

69,2Bremen50

Mannheim

50

Münster(Westphalia)

50

Brno

45,8

35%

35%

30%

Bonn

69,2

Hanover

65,8

Cologne61,7

Dortmund61,7

Dresden61,7

Dusseldorf

61,7Bochum

42,5

Essen

61,7

Wuppertal

42,5

Leipzig

61,7Saragossa

42,5Bratislava

57,5Palma deMallorca

38,3

Gothenburg

30,8Prague50

Murcia50

7.4.3 The top-ranking 15 cities were analysed in terms of the infrastructure available for UAM operations: availability of
inner-city space for a heliport and availability of a river, motorway or corridor for noise avoidance (see Figure 67). All 15
cities passed the infrastructure assessment and were selected for the next step.

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Figure 67: Cities infrastructure assessment for the last-mile delivery use caseMetropolitan
area

Ranking from previous
steps (100 = best
suited)Rotterdam

73,3

Hamburg

73,3Helsinki

69,2Tallinn

69,2

Bonn

69,2

Hanover

65,8

Cologne61,7

Dortmund61,7

Dresden61,7

Dusseldorf

61,7

Essen

61,7

Leipzig

61,7

Bratislava

57,5Prague50

Murcia50

Availability of
innercity space forheliport

Availability of river,highway or corridor
for noise avoidance

5. City viability for Medical supply delivery
Pre-selection for the medical supply delivery use case was based on the following metrics:• City population. A high number of inhabitants is required as a signal for sufficient demand for potential operators.
• Congestion rate. A high congestion rate indicates the need for UAM medical supply services.
From a long list of 389 EU cities, 89 were identified as having a large population (over 300,000 citizens); from these 32
were further selected as cities with a high congestion rate (over 30 percent), as Figure 68 shows.

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Figure 68: Target cities pre-selection process for the medical supply delivery use case389

Rationale# cities

Metrics

Selection criteria

Shortlist of cities

Cities population(Thousand)Congestion rate
(%)

>300

>30%

89

High amount of
inhabitants is required
as a signal forsufficient demand
towards potential
operators

Belgium

Brussels

Czech
Republic

Prague, Brno

FranceLyon, Marseille,
Nice, Paris

Germany

Berlin, Hamburg,
Munich, Nurnberg,
Stuttgart

Hungary

Budapest

Italy

Genoa, Milan,
Naples, Palermo,
Rome

Bulgaria

Sofia

PolandCracow, Poznan,
Szczecin, Warsaw,
Wroslaw, Gdansk

Estonia

Tallinn

GreeceAthens,
Thessaloniki

IrelandDublinLithuania

Vilnius

Portugal

LisbonRomania

Bucharest

Slovakia

Bratislava

Croatia

Zagreb32

High congestion rate
indicates a necessity
for UAM medical
supply services

The ranking process for the 32 pre-selected cities was based on the following KPIs: number of hospitals per 1,000
inhabitants and average congestion rate. A weighting factor was assigned to each KPI to indicate how significant that
KPI’s impact was on the overall ranking score (see Figure 69). Cities with the lowest density of hospitals and highest
congestion rate obtained the highest ranking.

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Figure 69: Target cities ranking process for the medical supply delivery use caseRanking of cities based on further KPIs
KPI

1

2

City
Weighting

Low number of hospitals per
1K inhabitants

50%

High average congestion rate

50%Country

Ranking (100 =best suitability
for UAM)

Cracow

100

Wroclaw

90

Bucharest85

Warsaw

85

Poznan

85

Sofia

75

Budapest

75

Bratislava

75

Dublin70

Prague70

Vilnius65

Hamburg

65

Berlin65

Gdansk

65

Paris

60

The 15 top-ranking cities were analysed in terms of the infrastructure available for UAM operations: availability of innercity space for a heliport and availability of a river, motorway or corridor for noise avoidance (see Figure 70). All 15 cities
passed the infrastructure assessment and were selected for the next step.

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Figure 70: Cities infrastructure assessment for the medical supply delivery use caseMetropolitan
area

Ranking from previous
steps (100 = best
suited)

Paris

83,3

Berlin75

Hamburg

75

Lyon

66,7

Marseille

66,7

Nice

66,7

Genova62,5Prague62,5Budapest

62,5

Nurnberg

58,3

Stuttgart

58,3

Milano

45,8

Roma

45,8

Dublin45,8München

45,8

Availability of
innercity space forheliport

Availability of river,highway or corridor
for noise avoidance

6. City viability for fixed metropolitan/regional network
Pre-selection for the metropolitan use case was based on the following metrics:• Number of medium- and high-income households. Higher utilisation is expected in regions with a higher
number of medium- and high-income households.
• Metropolitan size. The metropolitan/regional network would connect large and medium-size cities of a same
region, within a single Member State or cross border; A large metropolitan/regional population is required to enableefficient route utilisation (i.e. minimum 2 million citizens).
• Availability of at least two medium-size cities within a metropolitan area. At least two medium-size cites are
required to ensure sufficient route utilisation.

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Figure 71: Target cities pre-selection process for the fixed metropolitan network use case
Selection criteria
MetricMetropolitan regionswith high number ofhouseholds withmedium and highincome (%)

Metropolitan
size

>40%

>2 Mn
inhabitants#
91
citiesRationale

Shortlist of cities

Higher utilization
expected inregions withhigher number ofhouseholds withmedium and highincome(Mninhabitants)

52

Large
metropolitan
population
required to enableefficientutilization for
route

20

At least two
medium size
cities within ametropolitan
regionAustria

Vienna region

Belgium

Belgian central
metro region

Yes

Denmark

Oresun region(Copenhagen)FranceParis region

Germany

Rhein-Ruhr, RheinMain, RheinNeckar, Stuttgart
and Munich regions

Italy

Rome and Milan
regions

Spain

Barcelona region

PolandWarsaw region

Netherlands

Noord-Braband(Eindhoven,
Tilburg, Breda)

16

Estimation
requires at least
two medium size
cites to efficiently
utilize route for
operator

From 91 EU metropolitan areas, 52 were identified as having a high number of medium (over EUR 25,000) and high (overEUR 60,000) annual income households, and 20 of these were further selected as regions with a large population (over 2
million inhabitants). In the last step, 16 of these 20 metropolitan areas had at least two medium-size cities and were preselected (see Figure 71).
7.6.2 The 16 pre-selected metropolitan areas were ranked in accordance with the following KPIs: metropolitan size;
distance between cities; time saved when travelling with UAM instead of the fastest alternative method (train, taxi,
airport shuttle bus); GDP per capita; concentration of destination points within a metropolitan area; and suitable weather
conditions (percentage of weather causes in total arrival delays, precipitation in mm per year). A weighting factor was
assigned to each KPI to indicate how significant that KPI’s impact was on the overall ranking score (see Figure 72).

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Figure 72: Target cities ranking process for the metropolitan network use caseRanking of cities based on further KPIs

KPI

Weighting

1 Metropolitan size

25%

2 Distance between the cities

25%

3 Time saving when travelingwith UAM instead of fastest
alternative source (train,taxi, airport shuttle bus)

4 GDP per capita

25%

10%

5 Concentration of destination
10%
points with one metropolitan
region6 Suitable weather conditions 5%(% of weather causes in total
arrival delays, precipitationin mm per year)

Example route

Ranking (100 =best suitability
for UAM)

Belgian central
metroBrussels-Leuven

79.6

Rhein-Ruhr

Cologne-Bonn

79.2

Rome region

Rome-Ostia

78.8

Milan region

Milan-Monza

75.8

BarcelonaregionBarcelona-Mataro

73.8

Rhein-Neckar

MannheimHeidelberg

73.8

Stuttgart region

StuttgartReutlingen

72.5

Oresund

CopenhagenHillerod

68.3

Munich region

MunichHeidelberg

62.9

Vienna regions

Vienna-Baden

59.2

Paris region

Paris-Chantilly

58.8

Rhein-Main

FrankfurtAschaffenburg

58.8

Metropolitan
area

The 15 top-ranking cities were analysed in terms of the infrastructure available for UAM operations: availability of
inner-city space for a heliport and availability of a river, motorway or corridor for noise avoidance; availability ofmobility options for onward journeys (e-scooter, car-sharing etc.) (see Figure 73). All 15 metropolitan areas passed theinfrastructure assessment and were selected for the next step.

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Figure 73: Cities infrastructure assessment for the fixed metropolitan network use case
Selection criteria
MetricMetropolitan regionswith high number ofhouseholds withmedium and highincome (%)

Metropolitan
size

>40%

>2 Mn
inhabitants#
91
citiesRationale

Shortlist of cities

Higher utilization
expected inregions withhigher number ofhouseholds withmedium and highincome(Mninhabitants)

52

Large
metropolitan
population
required to enableefficientutilization for
route

20

At least two
medium size
cities within ametropolitan
regionAustria

Vienna region

Belgium

Belgian central
metro region

Yes

Denmark

Oresun region(Copenhagen)FranceParis region

Germany

Rhein-Ruhr, RheinMain, RheinNeckar, Stuttgart
and Munich regions

Italy

Rome and Milan
regions

Spain

Barcelona region

PolandWarsaw region

Netherlands

Noord-Braband(Eindhoven,
Tilburg, Breda)

16

Estimation
requires at least
two medium size
cites to efficiently
utilize route for
operator

Selection of the six cities or regions for the survey
The top 15 cities or regions across the discussed city selection use cases and the guiding principles were the basis for theselection of the six cities or regions, where the survey was to be conducted. The final selection of the survey cities wasmade during a meeting with the Executive Director of EASA and contained the cities of Barcelona, Budapest, Hamburg,
Milan, and Paris, as well as the Øresund region between Denmark and Sweden.

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Detailed information on questionnaire structure
The questionnaire was designed to assess, understand and measure the most important societal acceptance drivers for
UAM, including perceived benefits and concerns and what it takes to increase societal acceptance. The questionnaire
included 36 questions; the response time being estimated at twenty-five minutes.
Complementing the general attitude towards various use cases and the relative importance of them, two overarchinguse cases that are easy to imagine and self-explanatory for non-experts were identified in the quantitative survey
to determine the levels of acceptance: the delivery of goods by drone and the transport of passengers by air taxi. An
in-depth analysis was conducted to measure the relative acceptance levels of three key concerns, identified through theliterature review: of safety, noise and visual annoyance in an urban environment, possibly tinted by cultural differences.
Finally, the questionnaire addressed the general attitude and expectations of respondents towards regulatory
authorities. For an English version of the questionnaire that was distributed online to the participants, please refer to the
Appendix.
Part 1: Screener
Part 1 of the survey ensured that participants meet the predefined criteria (see the predefined quotas above). An
informational video of 1 minute and 36 seconds was presented to ensure the participants’ prior information as well as
general and common understanding of UAM. The use cases shown in the video were passenger transport by air taxi,
express delivery of food by drone, transport of emergency medical services to the scene of an accident, and deliveryof medical supplies to a hospital. The selection aimed for a balanced representation of commercial and public service
use cases, drone and passenger use cases, as well as use cases with a pilot on-board and remotely piloted. The vehicles
depicted in the video were invented and did not correspond to any industrial product existing or in development. The
objective was to give a general feeling and idea, rather than to reflect actual technical accuracy. The video concluded
with the message that Urban Air Mobility is coming soon to Europe. The video did not include any sound other thanmusic, as noise perception was evaluated in a separate survey.
Subsequently, this section checked whether participants fell into one of the pre-selected potential user groups, i.e.
delivery of goods by drone and/or transport of passengers by air taxi.
Part 2: General attitude towards UAM
In a first step, participants’ affinity to make use of new technologies was assessed. This was intended to help understandtheir attitude towards innovation. Participants were then asked to rank the usefulness of fourteen UAM use cases. In thisway, the use cases considered the most important for the population could be identified. Participants were also given an
overview of several conceivable use cases that go beyond those shown in the video.
In a second stage, participants were asked to evaluate the most important overarching perceived benefits andopportunities (not use-case specific) that UAM could entail. In addition, an open question invited them to name further
positive aspects that did not appear in the survey and may not have been covered by the literature so far.
Part 3: Delivery by drone
To ensure participants did not mix responses for different types of vehicles (drones and air taxis), questions on drones
were asked first, before questions on air taxis were asked separately in Part 4.

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In a first step, participants’ propensity to make use of current express delivery options was assessed. This was intended
to help classify their views on the potential usefulness of express delivery options by drones. In a second step, they wereasked to rank the most important perceived benefits of goods delivery by drones.
The core element of this section was the investigation into the public’s concerns for this type of use-case. In general,questions were phrased in such a way to understand the relative importance of concerns among the population –whereas an absolute question such as ‘How important is security to you?’ would have led to a potential selection
providing little to no insight (‘Everything is important’). The concerns were measured through six groups of questions.
• The first question addressed participants’ basic comfort level with the idea of unmanned air taxis. Air taxis pose apotential safety threat not only to the passengers using them, but also to pedestrians on the ground. As pedestrians
will be affected by air taxis despite not necessarily choosing to use air taxis themselves, the hypothesis was that theperceived safety of pedestrians will have a significant impact on the societal acceptance of air taxi operations.
• In a second question, participants were asked to rank the most important concerns, in their view, regarding theoperation of air taxis in an urban environment. This list of concerns was derived from the literature review.
• The third question was a deep dive into safety, noise and visual annoyance concerns using a conjoint analysis. The
question aimed to determine which levels of these issues came within an acceptable range for a broad population.
• In the fourth question, environmental concerns were compared to determine their relative importance among the
population.
• A sixth group of questions addressed affordability, privacy, job losses, allocation of inner-city space to take-off andlanding stations, and security threats for local residents. These were intended to elicit the participants’ expectations
and fears, both rational and irrational.
• Lastly, participants were asked to rank the most important concerns, in their view, related to take-off and landing
stations (‘vertiports’).
Part 4: Passenger transport (air taxi)
Part 4 was structured analogously to Part 3 and the same methodology and reasoning applied for most questions. Onlyin some points adjustments were made to fit the use case. In a first step, participants’ travel habits were evaluated toassess their general propensity to fly.
• The first question was on how often they travel by aeroplane for personal or business reasons in a typical year.
• The second question asked them how they typically get to and from the airport. This was intended to help classify
their openness to try out air taxis, specifically to airports.
• Next, they were asked to rank the most important perceived benefits of passenger transport by air taxi.
• The next set of questions were designed to measure concerns. First, participants were asked to rank different
statements that people might make about air taxis. Four statements for ranking were given to identify theparticipants’ basic comfort level with the idea of unmanned air taxis – for both passengers and pedestrians.
Air taxis pose a potential safety threat not only to the passengers using them, but also to pedestrians on the ground. As
pedestrians will be affected by air taxis despite not necessarily choosing to use air taxis themselves, the hypothesis wasthat the perceived safety of pedestrians will have a significant impact on the societal acceptance of air taxi operations.
• With the fifth question, participants were asked to choose their most important concerns.
• After that, in the sixth question they were ask to rank the most important concerns, in their view, regarding the

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operation of air taxis in an urban environment. This list of concerns was derived from the literature review.
• Participants were then asked to imagine themselves in three different situations in 2030, involving air taxis.
Participants were then asked to choose their preferred option out of the alternatives.
• This was followed by rating given scenarios in terms of their acceptance.
After this, there was a deep dive into safety, noise and visual annoyance concerns using a conjoint analysis. The question
aimed to determine which levels of these issues were deemed within an acceptable range for a broad population.
• Next, environmental concerns were compared to determine their relative importance among the population.
• Separate questions on affordability, privacy, job losses, allocation of inner-city space to take-off and landing
stations, and security threats for local residents were designed to elicit the participants’ expectations and fears, bothrational and irrational.
• Another question on vertiports helped to understand how pleased participants would feel to have a take-off station
close by.
• Lastly, participants are asked to rank their most important concerns related to take-off and landing stations.
Part 5: Regulators and their role
As the study was commissioned by EASA, for future regulatory work, participants’ attitudes towards European,national, regional or local authorities deserved special focus.
• Therefore, the survey polled participants’ trust levels in the aforementioned authorities to adopt regulations and tohandle the risks associated with UAM.
Part 6: Further understanding of security and environmental aspects
In order to find out more on environmental and cybersecurity concerns, the survey also polled participants’ trust levels inthe security and cyber security of drones and air taxis.
• First, participants were asked to what extent they trust that advanced aircraft flying in an urban environment will betechnologically secure and armed against threats from hackers.
• Secondly, participants were asked whether and to what extent their trust level would increase with measures andregulations to manage cyber security risks. They were asked to compare authorities.
• Furthermore, the desirability of an ecolabel for UAM was assessed. This question was visually illustrated by a sample ecolabel.
Part 7: Additional demographic questions
Before the end of the survey, a few additional demographic questions were asked, such as the number of people living in
the participant’s household, their level of education, total gross household income and current occupation in order to beable to assess potential differences in the respondents’ groups.
Methodological basis of survey question types
Different types of questions are suitable for different objectives and the choice of question type should be guided by
the aim of the question. Multiple-selection, rating as well as forced-ranking questions were used. In the following, therationales behind each are described briefly.

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Multiple-select questions
Multiple-select questions allow survey participants to choose one or more answers from a set of provided options.
The order of the options may be randomised to avoid bias, as survey respondents have a tendency to choose options
positioned higher on the list. The advantage of this question type is that it gives participants the freedom to selectseveral options and not feel restricted in their answers. Question A4 (see next Appendix section) is an example of thisquestion type, when participants are asked to pick their top three personal benefits related to UAM.
For example, it is suitable for enquiring about participants’ motivations for an attitude or decision. When evaluating thesurvey responses, the relative frequency of mentions of each option can be compared and their importance assessed.
A slight restriction can be imposed by introducing an upper limit on the number of choices that participants may select.
This forces participants to prioritise. The number of mentions of an answer among the top three, for example, can thus
be evaluated.
A special case is single-punch questions, where only one answer can be selected. These are suitable for asking about
extremes (e.g. ‘What is your top priority?’) or when options are mutually exclusive (yes or no).
Rating questions
Rating questions allow participants to weigh answers or statements via grades or numerical scales. They are often used
when participants are asked about their level of approval or acceptance.
The grades can be transferred into a numerical evaluation via a Likert scale, which allows, for example, the comparisonof approval rates for different statements or population batches such as age or gender groups.
An example of this question type is Question B6 (see next Appendix section). Here, the level of comfort with different
drop-off locations for drone parcel delivery is queried to ultimately understand which option leads to the highest
possible approval rate across the population.
Forced-ranking questions
Forced ranking questions enable participants to compare items and to rank them according to their preference. Again,
the items may be randomised to avoid bias for higher-positioned answers.
The advantage of this question type is that participants consciously sort the items and indicate each item’s relative
personal importance; whereas in multiple-select questions, items are either important or unimportant, and in rating
questions, items can be assigned the same absolute grade. Therefore, this type of question helps make relative
differences visible, providing critical insights into participants’ individual preferences and the preferences of thepanel overall. In this way, within a set of important issues, the most important ones can be identified. An example ofthis question type is Question B9 (see next Appendix section), where the aim is to get to know the most criticalenvironmental concerns for respondents among an overall set of key environmental concerns.
A special approach was taken in Questions B4 to B5 (see next Appendix section). Since forced-ranking questions are
only suitable for a limited number of items (six to seven items is considered the upper bound, as the process becomes
confusing beyond that), a combination of multiple-select questions followed by forced-ranking questions was chosen
In this way, participants had the opportunity to pre-select the concerns that they considered most important, before

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being asked to give a relative assessment for this subset. This way, the important concerns are separated from theunimportant ones, and the especially important ones are then ranked.
A similar approach was taken in Questions A2 to A3 (see next Appendix section). First, participants are asked to selectthe most useful use cases, in their view, in each of the following categories: delivery, medical emergency transportand passenger transport. In order to make the usefulness comparable across the categories, the top two from eachcategory are transferred to Question A3 and are then subject to forced ranking. In this way, the most useful use cases are
identified, and conclusions can be drawn about the categories that are perceived as fundamentally useful.

Detailed information on methodology of quantitative survey question types
and questionnaire
Different types of questions are suitable for different objectives and the choice of question type should be guided by theaim of the question. Multiple-selection, rating as well as forced-ranking questions were used. For more details on thequestion types used, see Appendix.
Multiple-select questions
Multiple-select questions allow survey participants to choose one or more answers from a set of provided options.
The order of the options may be randomised to avoid bias, as survey respondents have a tendency to choose options
positioned higher on the list. The advantage of this question type is that it gives participants the freedom to selectseveral options and not feel restricted in their answers. Question A4 (see the Appendix) is an example of this question
type; participants must pick their top three personal benefits related to UAM.
For example, it is suitable for enquiring about participants’ motivations for an attitude or decision. When evaluating thesurvey responses, the relative frequency of mentions of each option can be compared and their importance assessed.
A slight restriction can be imposed by introducing an upper limit on the number of choices that participants may select.
This forces participants to prioritise. The number of mentions of an answer among the top three, for example, can thus
be evaluated.
A special case is single-punch questions, where only one answer can be selected. These are suitable for asking about
extremes (e.g. ‘What is your top priority?’) or when options are mutually exclusive (yes or no).
Rating questions
Rating questions allow participants to weigh answers or statements via grades or numerical scales. They are often used
when participants are asked about their level of approval or acceptance.
The grades can be transferred into a numerical evaluation via a Likert scale, which allows, for example, the comparisonof approval rates for different statements or population batches such as age or gender groups.
An example of this question type is Question B6 (see Appendix). Here, the level of comfort with different drop-off
locations for drone parcel delivery is queried to ultimately understand which option leads to the highest possible
approval rate across the population.

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Forced-ranking questions
Forced ranking questions enable participants to compare items and to rank them according to their preference. Again,
the items may be randomised to avoid bias for higher-positioned answers.
The advantage of this question type is that participants consciously sort the items and indicate each item’s relative
personal importance; whereas in multiple-select questions, items are either important or unimportant, and in rating
questions, items can be assigned the same absolute grade. Therefore, this type of question helps make relative
differences visible, providing critical insights into participants’ individual preferences and the preferences of the panel
overall. In this way, within a set of important issues, the most important ones can be identified. An example of thisquestion type is Question B9 (see Appendix), where the aim is to get to know the most critical environmental concerns
for respondents among an overall set of key environmental concerns.
A special approach was taken in Questions B4 to B5 (see Appendix). Since forced-ranking questions are only suitable
for a limited number of items (six to seven items is considered the upper bound, as the process becomes confusing
beyond that), a combination of multiple-select questions followed by forced-ranking questions was chosen In this way,participants had the opportunity to pre-select the concerns that they considered most important, before being asked togive a relative assessment for this subset. This way, the important concerns are separated from the unimportant ones,
and the especially important ones are then identified.
A similar approach was taken in Questions A2 to A3 (see Appendix). First, participants are asked to select the mostuseful use cases, in their view, in each of the following categories: delivery, medical emergency transport and passenger
transport. In order to make the usefulness comparable across the categories, the top two from each category aretransferred to Question A3 and are then subject to forced ranking. In this way, the most useful use cases are identified,and conclusions can be drawn about the categories that are perceived as fundamentally useful.

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128

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1.

Only relevant providers in respective cities are shown

9. Flat fee or subscription model for the delivery of online orders(of groceries, consumer electronics, apparel, etc.), such as Amazon
Prime, OTTO UP, Zalando Plus, Cdiscount à volonté, Fnac+,
PcComponentes Premium1

8. Drones, e.g. for photos, videos or recreation

7. Video conferencing, e.g. Zoom, Microsoft Teams, Skype

6. Online booking or booking via app of mobility tickets, e.g. for trains,
flights, buses, other public transport

5. (E-)bikes, (e-)scooters or electric kick scooters from sharing
providers, such as Lime, Tier, emmy, Cityscoot, Dott, GoVolt, Bird,
Vaimoo, MOL bubi, ogre&co1

4. Ride sharing (i.e. sharing a taxi or similar with other people taking asimilar route), e.g. UberPool, Moia1

3. Car sharing, e.g. Share Now, Miles, Cambio, getaround, Ubeeqo,
enjoy, letsgo, GreenMobility, GreenGo, MOL Limo1

2. Ride hailing, i.e. ordering a car similar to a cab via a mobile app, suchas Free Now, Uber, Bolt, it Taxi, Uber, Cabify, Moove, Viggo1

1. Car rental, e.g. Sixt, Europcar, Avis

Technology or service

Have not used
Never used and yet, but would
not interested
consider it
A few times
a year6 to 10 times a
year
Once a month

Every 2 weeks

Every week ormore often

In a typical year, how often do you use the following technologies and services? Please consider a typical year, for instance 2019, before the Covid-19 pandemic started. Please select one answer in each row.

A1. Frequency of usage of new technologies, such as mobility services

A1. Affinity to new technologies

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Never used andnot interested

Have not used yet,but would considerit
A few times
a year6 to 10 times a
year
Once a month

Every 2 weeks

Every week ormore often

In a typical year, how often do you shop online for yourself or your family (such as for food, beverages, daily supplies, consumer electronics, fashion and apparel) and use express delivery for your purchases? Pleaseconsider a typical year, for instance, 2019, before the Covid-19 pandemic started.

B1. Frequency of usage of express delivery services

B1. Express delivery

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1-2 times a year

3-5 times a year1.

6-10 times a year

Only relevant providers in respective cities are shown

Other, please specify: _____________________________

Public transport, such as bus, metro, or train

Ridesharing, such as Uber Pool or Moia or other local rideshare option1

Carsharing, such as Share Now, Miles, Cambio, getaround, Ubeeqo, enjoy, letsgo, GreenMobility, MOL Limo, GreenGo1

Taxi or equivalent provider, such as Free Now, Uber, Bolt, it Taxi, Cabify, Moove, Viggo1

Private vehicle, such as a car or motorbike

By (e-)bike or (e-)scooter from a sharing provider, such as Lime, Tier, emmy, CityScoot, Dott, GoVolt, Bird, Vaimoo, MOL bubi, ogre&co1

By foot, own (e-)bike, or own (e-)scooter

When travelling by aeroplane, how do you typically get to and from the airport from your home and vice versa? Please select all that apply.

C2. Mode of transport to airport

Not at all

Every month or more often

In a typical year, how often do you travel by aeroplane for personal or business reasons? Please consider a typical year, for instance 2019, before the Covid-19 pandemic started. Please select one answer.

C1. Frequency of travelling by aeroplane

C1 & C2. Flight habits

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1.

rather negative

rather positive

very positive

To inform participants about urban air mobility, a video of length 1:34 minutes was shown prior to this question, showcasing the use cases passenger transport by air taxi (pointing out to the existence of manned andunmanned VTOLs), parcel delivery via drone (more precisely, instant food delivery), transport of emergency medical personnel to site of an accident, and delivery of medical supply to a hospital

negative

What would be your overall perception if urban air mobility solutions (such as those shown in the video1) were to be introduced in your city? Please select one answer.

S5. Rating of perception from very negative to very positive

S5. General attitude towards urban air mobility

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rather negative

rather positive

very positive

negative

rather negative

rather positive

very positive

How likely would you be to use an air taxi (i.e., a flying vehicle that transports passengers from A to B) for a 25-50% higher price than current road passenger transport options like conventional (road) taxis or
Uber-like offerings, if you assume the trip could be made in half the time in the air taxi?

S7. Likelihood to try out air taxis

negative

How likely are you to make use of delivery of goods by drone (i.e., delivery of parcels from an online shopping platform to a nearby delivery hub, your garden or private property or a publicly accessible area),
if it were offered in your city? Please assume that delivery by drone would cost about double today’s standard shipping fees and ensured guaranteed delivery within 2 hours from the time you place yourorder.

S6. Likelihood to try out drone delivery

S6.S7. Likelihood to try out urban air mobility services

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Emergency medical service to transfer an
injured person to a nearby hospital

Grocery and goods delivery to my home orworkplace in areas with long travel times tothe next shop (i.e., in the countryside or not
well connected with public transport)

None of these are usefulNone of these are useful

Regional air mobility, for instance, from one
city to another small city in the same region(like from Copenhagen to Malmö2)

Air taxi to travel from one point in the city
to another

Air taxi, for instance, to commute from asuburban area to the city centre

Air taxi, for instance, to get from the city
centre to the local airport and vice versa

Sightseeing by air in a city or region

Which of the below passenger transport use
cases for urban air mobility would you consider
the most useful? Please sort the following
applications from 1 being ‘most useful’ to 5 being‘least useful’ or select ‘none of these are useful’.1

A2.c Ranking of use cases in
category passenger transport

4<If not none, #2 ranked option from A2.c isdisplayed><If not none, #1 ranked option from A2.c isdisplayed><If not none, #2 ranked option from A2.b isdisplayed><If not none, #1 ranked option from A2.b isdisplayed><If not none, #2 ranked option from A2.a isdisplayed>

And which of the below use cases (that you
previously selected as the most useful in theircategories) are the most useful overall? Pleasesort the following applications from ‘most useful’to ‘least useful’ or select ‘none of these areuseful’.1<If not none, #1 ranked option from A2.a isdisplayed>

A3. Cross-category ranking of top
2 use cases from categories3

1. Example of regional air mobility only shown in Öresund, as only supra-urban area where survey was conducted 2. Answers were shuffled to avoid biases towards options with higher position 3. If “None of these are useful”
was selected in all three A2 questions, A3 is skipped 4. No “None” option in A3, as participant must have selected an option he conceived as useful in some A2 question, otherwise see 3.

None of these are useful

Emergency medical service to bring doctors
or first aid personnel to the scene of an
accident

Drone delivery of medical supplies for
personal need (such as pens for autoinjection of a vital substance, defibrillatorsand medications) from a central hub to aplace not far from your home such as yourown garden or a nearby park
Disaster management using drones (such as
drones with thermal cameras to evaluate
fire incidents, drones equipped with
firefighting foams and extinguisher bombs)

Drone delivery of meals in an urban area,for instance, from my preferred restaurantor food delivery siteLong-distance forwarding of heavy cargo,
for instance, to places with little
infrastructure such as islands or drilling rigs

Drone delivery of medical supplies (such as
blood donations, organs, medical
equipment) to a hospital

Which of the below medical emergency use
cases would you consider the most useful in an
urban environment? Please sort the following
applications from 1 being ‘most useful’ to 5 being‘least useful’ or select ‘none of these are useful’.1

Which of the below delivery use cases would you
consider the most useful? Please sort thefollowing applications from 1 being ‘most useful’to 4 being ‘least useful’ or select ‘none of these
are useful’.1

Drone delivery of goods in an urban area,for instance, from my preferred online
shopping portal or site

A2.b Ranking of use cases in
category medical emergency

A2.a Ranking of use cases in
category drone delivery

A3.A2. Perceived usefulness of urban air mobility use cases, among and across categories

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E. Central delivery station in my neighbourhood, such as a petrol
station, supermarket or a postal service station

D. In a nearby park

C. On the roof of my house/block of flats or office

B. In my garden or other private area (not publicly accessible)

A. Over the walkway in front of my house or main door of my blockof flats (publicly accessible)

very
uncomfortableuncomfortablesomewhat
uncomfortablesomewhatcomfortablecomfortablevery comfortable

How comfortable would you be with the following modes of drone delivery for medium-sized parcels (max. 120 x 60 x 60 cm, up to 5 kg) at places near your home? Please select one answer in each row

B6. Selection of level of comfort with drop-off locations for drone delivery

B6. Level of comfort with drop-off locations for drone delivery

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1.
2.

__________________________________________________________Creation of new jobs and growth opportunities for people in my country (for instance,
manufacturing, research and development, pilot projects)

Market-leading position of Europe in urban air mobility technology (such as drones, air taxis)

Three free text fields were shown to survey participants
The evaluation of free text boxes in question A5. did not show other significant benefits; an example can be found in respective evaluation for Paris

None of these are useful

Reduced response time for emergencies

Reduction of local emissions and pollution (most of the vehicles will have battery electric
propulsion)

Reduction of traffic jams_____________________________

What other benefits and opportunities can the development of urban air mobility bring for EU
citizens? Please add up to 3 ideas in the below text boxes.1,2What benefits and opportunities can the development of urban air mobility bring for the EU and EU
citizens? Please select up to 3 answers.

Improved development of and access to remote areas (for instance, the countryside, regions
outside of a metropolitan area)

A5. Further positive benefits mentioned by survey participants

A4. Selection of up to 3 benefits incurred by UAM

A4 & A5. Benefits incurred by UAM

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None of these are usefulLess pollution due to electric propulsion

Less-congested city centres due to fewer people out shoppingLess-congested streets (i.e. due to fewer delivery vehicles parked on the street)

Fewer interactions with other people (i.e. for better hygiene standards, especially during/after the pandemic)

Higher reliability

Exact time window for delivery

Faster delivery

What benefits and opportunities can the development of urban air mobility bring for the EU and EU citizens? Please select up to 3 answers.

B2. Selection of up to 3 benefits incurred by drone delivery

B2. Benefits of drone delivery

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1.
2.

Number of options is 8 if participants opts for filling the free text field
The evaluation of free text boxes did not show other significant benefits

None of these are useful

Other, please specify: _____________________________ 2

Creation of new jobs in running air taxi services

The feeling of behaving in a modern way, being an early adopter

Ability to connect and access remote areas (areas with current poor access to city centres)

Less noise for inner-city residents due to emergency medical services taking an aerial route

Reduction of traffic jams

Comfortable continuation of travel after arrival at an airport station to my personal accommodation

Significant time saving for passengers

In your view, what are the main benefits of air taxis? Please sort the following benefits from the 1 being the ‘most useful’ to 7 or 81 being the ‘least useful’ or select ‘none of these are useful’.

C3. Ranking of benefits incurred by passenger transport with air taxis

C3. Benefits of air taxis

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As a pedestrian on the ground, I would feel safe with unmanneddelivery drones potentially flying above me.

strongly disagree

disagreesomewhatdisagreesomewhat agree

agreestrongly agree

Drones intended for the delivery of goods are remotely piloted aircraft systems with no pilots on board. Assume that they have an average wingspan of 3 metres, would fly at between 120 and 150 metres altitude,
and are certified by competent authorities. Please rate how much you agree or disagree with the following statement.

B3. Perception of safety with unmanned delivery drones

B3. Level of comfort with unmanned delivery drones

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D. Unmanned air taxi (meaning no human pilot is on board to steer
the aircraft)

C. Manned air taxi (meaning with a human pilot on board steering
the aircraft)

As a pedestrian (not as a passenger), I am okay with accept the factthat the following vehicles could fly above my head

B. Unmanned air taxi (meaning no human pilot is on board to steer
the aircraft)

A. Manned air taxi (meaning with a human pilot on board steering
the aircraft)

I would be interested in trying out the following vehicles myself:

strongly disagree

disagreesomewhatdisagreesomewhat agree

agreestrongly agree

Recent studies extend the prospect of aircraft soon transporting passengers, either with a pilot on board or with a remote pilot. You will now see several statements that people might make about such air taxis.
Assuming that all of the aircraft are certified by competent authorities, please rate how much you agree or disagree with each statement for each type of air taxi.

C4. Level of comfort with air taxis by level of autonomy (present versus absent) and degree of interaction (active versus passive)

C4. Level of comfort with manned & unmanned air taxis for passengers & pedestrians

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1.
2.
3.

Answers were shuffled to eliminate bias related to positioning
Evaluation did not lead to significant other concern.
Only options chosen in B4 prompted in B5; if "None of these" was chosen in B4, question B5 is skipped<Concern chosen in B4 is displayed, if at least 1 was chosen><Concern chosen in B4 is displayed, if at least 2 were chosen><Concern chosen in B4 is displayed, if at least 3 were chosen><Concern chosen in B4 is displayed, if at least 4 were chosen><Concern chosen in B4 is displayed, if at least 5 were chosen><Concern chosen in B4 is displayed, if 6 were chosen>

Please sort your main concerns from ‘most concerning’ to ‘least concerning’.3

B5. Ranking of previously selected concerns

Noise pollution, such as loud and/or annoying sounds
Visual pollution, such as annoying air traffic
Safety concerns, such as drones crashing
Concerns regarding local environment, such as air pollution, negative impact on bird life and insects, or decreasing biodiver sity in general
Global environmental concerns, such as negative impact on climate change
Job losses, for instance within local delivery companies
Security threats, for instance, criminal organizations (for ransom), hacktivists, or terrorists hacking into the control system and hijacking or misdirecting drones
Privacy concerns, for instance, a drone flying close to my window or over my property
Affordability, i.e. the service being affordable only for rich or privileged people
Other, please specify: ________________ 2
None of these

What are you most concerned about regarding drone delivery, both for the delivery of day-to-day goods as well as medical supplies? Please consider your own usage of such a service as well as other people using it(e.g. your family or neighbours), which may affect you as well. Please select up to 6 answers.1

B4. Selection of up to 6 concerns

B4.B5. Absolute and relative importance of general concerns in drone delivery
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Other, please specify: ________________ 2
None of thesePrivacy concerns, for instance, an air taxi flying close to my window or over my property

Affordability, i.e. the service being affordable only for rich or privileged people

1. Answers were shuffled to eliminate bias related to positioning 2. Evaluation did not lead to significant other concern 3. Only options chosen in B4 prompted in B5; if "None of these" was chosen in B4, question B5 is skipped
4. "Other" option in B5 contains text input from B4, if filled by participant<Concern chosen in C5 is displayed, if at least 1 was chosen><Concern chosen in C5 is displayed, if at least 2 were chosen><Concern chosen in C5 is displayed, if at least 3 were chosen><Concern chosen in C5 is displayed, if at least 4 were chosen><Concern chosen in C5 is displayed, if at least 5 were chosen><Concern chosen in C5 is displayed, if at least 6 were chosen>

Please sort your main concerns from ‘most concerning’ to ‘least concerning’.3,4

C6. Ranking of previously selected concerns

Flight shame (i.e. my social reputation would suffer as a result of using air taxis)

Downwash, i.e. downward wind generated by the rotors of air taxis when flying or in hovermode
Squandering of public money to finance new infrastructure and air taxi technology, instead ofimproving existing public transport and infrastructure like roads and rail

Security threats, for instance, criminal organizations (for ransom), hacktivists, or terrorists hacking into
the control system and hijacking or misdirecting the air taxi

Job loss, for instance affecting taxi drivers

Global environmental concerns, such as negative impact on climate change

Concerns regarding the local environment, such as air pollution, negative impact on bird life and insects,
or decreasing biodiversity in general

Noise related to the operation of take-off stations

Additional traffic from/to take-off stations

Visual pollution, such as annoying air traffic

Safety concerns, such as flying vehicles possibly crashing

Inner-city space occupation due to infrastructure requirements (take-off and landing stations)

Noise pollution, such as loud and/or annoying sounds of flying aircraft

What are you most concerned about with respect to air taxis? Please consider your own usage of such a service as well as other people using it (e.g. your family or neighbours), which may affect you as well.
Please select up to 6 answers.1

C5. Selection of up to 6 concerns

C5.C6. Absolute and relative importance of general concerns in air taxi use case142

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19.05.2021 12:57:05<Concern chosen in C11 is displayed, if at least 2 were chosen><Concern chosen in C11 is displayed, if at least 2 were chosen>

Increased road traffic to and from the take-off and landing station

Visual pollution, i.e. too many aerial vehicles in my field of view, for instance, when I look outof my window<Concern chosen in C11 is displayed, if 6 were chosen>

1. Answers were shuffled to eliminate bias related to positioning 2. Evaluation did not lead to significant other concern 3. Only options chosen in C11 prompted in C12; if "None of these" was chosen in B4, question B5 is skipped
4. "Other" option in C12 contains text input from B4, if filled by participant

None of these

Other, please specify: ________________ 2

Take-off stations taking up space otherwise available for living or recreation, suchas parks

Take-off stations taking up space needed for retail

Safety issues (fear of an increased number of air taxis crashing)

Increased security threats (such as terrorists hijacking an air taxi and letting it crashon purpose)<Concern chosen in C11 is displayed, if at least 2 were chosen><Concern chosen in C11 is displayed, if at least 2 were chosen>

Increased number of people walking by

Breach of my privacy<Concern chosen in C11 is displayed, if at least 1 was chosen>

Please sort your main concerns from ‘most concerning’ to ‘least concerning’.3,4

Assuming that a take-off and landing-station is close by (under 50 metres), what are you mostconcerned about? Please select up to 6 answers.1

Noise originating from the take-off and landing manoeuvres of air taxis

C12. Ranking of previously selected concerns

C11. Selection of up to 6 concerns

C11.C12. Concerns regarding take-off and landing stations

Questionnaire

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None of these

Sealed surfaces, for example, covering soil with materials like concrete and stone, e.g. for take-off and landing pads, potentially reducing natural soil and ecosystem function in the area concernedHigh environmental impact from the disposal of drones

High environmental and climate impact from the manufacturing of drones, including battery production

High environmental and climate impact from drone operation, including power generation (e.g. electricity)

Negative impact on bird life, insects and other flying animals

Noise pollution, for example, regular exposure to elevated sound levels that potentially have adverse effects on humans or other living organisms

Air pollution

What are your greatest concerns when it comes to the possible environmental consequences of drone delivery? Please sort the following answers from 1 being ‘most concerning’ to 7 being ‘least concerning’ or
select ‘none of these’.

B9. Ranking of 7 environmental concerns potentially incurred by delivery drones

B9. Environmental concerns regarding delivery drones

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None of these

Sealed surfaces, for example, covering soil with materials like concrete and stone, e.g. for take-off and landing pads, potentially reducing natural soil and ecosystem function in the area concernedHigh environmental impact from the disposal of air taxis

High environmental and climate impact from the manufacturing of air taxis, including battery production

High environmental and climate impact from air taxi operation, including power generation (e.g. electricity)

Negative impact on bird life, insects and other flying animals

Noise pollution, for example, regular exposure to elevated sound levels that potentially have adverse effects on humans or other living organisms

Air pollution

What are your greatest concerns when it comes to the possible environmental consequences of air taxis? Please sort the following answers from 1 being ‘most concerning’ to 7 being ‘least concerning’ or
select ‘none of these’.

C9. Ranking of 7 environmental concerns potentially incurred by air taxis

C9. Environmental concerns regarding air taxis

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D

C

B

A

A+

A++

A+++

Yes, certainly

May, not sureNo

Should the environmental impact of urban air mobility operations be evaluated by the authorities and made public, e.g., via an eco-label such as the one shown below? Please select one answer.

D4. Opinion on certification of environmental impact of UAM

D4. Introduction of an eco-label

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One drone has the same likelihood of hitting apedestrian as one car

One drone is as loud as a truck driving by at city speed(~82 dB, disturbing)~10 drones per hour in one’s field of view when walking
down a street

SafetyNoiseVisual pollution

20+ drones per hour in one’s field of view when walking
down a street

One drone is as loud as a bicycle riding by at city speed(~57 dB, barely noticeable)

One drone has 1/100th the likelihood of hitting apedestrian as one car

Alternative 2

1.
2.

8 trade-offs per participant to be madeOther possible levels for safety, noise ad visual pollution on following slides

B. Urban air mobility where
1) the chance of a delivery drone crashing onto a pedestrian is 5
times higher than that of a car hitting a pedestrian,2) drones flying by have a similar noise level as a leaf blower, and3) more than 20 drones pass by per hour

A. Urban air mobility where
1) the chance of a delivery drone crashing onto a pedestrian is
1/100th that of a car hitting a pedestrian,2) drones flying by have a similar noise level as bicycles passing by atcity speed, and
3) one or two drones pass by per hour
Very unacceptable

Unacceptable

Somewhatunacceptable

Somewhatunacceptable

Acceptable

Very acceptable~5 drones per hour in one’s field of view when walking
down a street

One drone is as loud as a car driving by at city speed (~65dB, noticeable)

One drone has 1/100th the likelihood of hitting apedestrian as one car

Alternative 3

Again, put yourself in the year 2030. How acceptable would you find the following scenarios for the future? Please rate each scenario based on the scale shown below.

B8. Absolute acceptance of best case and worst case alternatives for delivery drone

Alternative 1

Example choice card2

Put yourself in the year 2030: drones with about 3-metre wingspans, certified by competent authorities, are flying at altitudes of up to 150 metres. In the following section, you will be asked which scenario out of
three alternatives is most acceptable from your perspective. Please choose your most preferred option out of the three alternatives shown.1

B7. Relative importance of attributes safety, noise and visual pollution in conjoint style question

B7.B8. Trading off concerns safety, noise and visual pollution regarding drone delivery

Questionnaire

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An air taxi is as safe for passengers and pedestrians as acar (i.e., ~2 fatalities per billion passenger km)

An air taxi is as loud as a car driving by at city speed (~65dB, noticeable)~10 air taxis per hour in one’s field of view when walking
down a street

SafetyNoiseVisual pollution
20+ air taxis per hour in one’s field of view when walking
down a street

An air taxi is as safe for passengers and pedestrians as acommercial aircraft (i.e., ~0.01 fatalities per billion
passenger km)
An air taxi is as loud as a bicycle driving by at city speed(~57 dB, barely noticeable)

Alternative 2

1.
2.

8 trade-offs per participant to be madeOther possible levels for safety, noise ad visual pollution on following slides

B. Urban air mobility where
1) the risk posed by air taxis for passengers and pedestrians iscomparable to that of motorcycles,2) air taxis flying by have a similar noise level as leaf blowers, and3) more than 20 air taxis pass by per hour

A. Urban air mobility where
1) the safety standard for air taxis is similar to the safety standard ofcommercial aircraft for passengers and pedestrians (highest safety
standard),
2) air taxis flying by have a similar noise level as bicycles passing by
at city speeds, and
3) one or two air taxis pass by per hour
Very unacceptable

Unacceptable

Somewhatunacceptable

Acceptable

Very acceptable~5 air taxis per hour in one’s field of view when walking
down a street

An air taxi is as loud as a truck driving by at city speed(~82 dB, disturbing)An air taxi is as safe for passengers and pedestrians as abus (i.e., ~0.05 fatalities per billion passenger km)

Alternative 3

Somewhatunacceptable

Again, put yourself in the year 2030. How acceptable would you find the following scenarios for the future? Please rate each scenario, based on the scale shown below.

C8. Absolute acceptance of best case and worst case alternatives for delivery drone

Alternative 1

Example choice card2

Put yourself in the year 2030: air taxis with wingspans of up to 12 metres, certified by competent authorities, are flying at altitudes of about 150 metres. In the following section, you will be asked which scenario outof three alternatives is most acceptable from your perspective. Please choose your most preferred option out of the three alternatives shown.1

C7. Relative importance of attributes safety, noise and visual pollution in conjoint style question

C7.C8. Trading off concerns safety, noise and visual pollution regarding air taxis

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DisagreeSomewhatdisagreeSomewhat agree

Source: EASA UAM social acceptance survey questions C5. What are you most concerned about with respect to air taxis? Please consider your own usage of such a
service as well as other people using it (e.g. your family or neighbours), which may affect you as well. Please select up to 6 answers. C6. Please sort your main concerns
from ‘most concerning’ to ‘least concerning’

D. I would be afraid that the drones could be misused and become asecurity threat.

C. I would be afraid that the use of drones for the delivery of goods
would significantly reduce the number of jobs, e.g. for parcel delivery
personnel.

B. I would be afraid that drones could massively invade my privacy,
for instance, by spying through my window and recording mypersonal life.

A. I suspect that I would find extra fees for express delivery by drone
much too expensive.

Strongly disagree

To what extent do you agree with the following statements about drone delivery? Please rate how much you agree or disagree with each of the following statements

B10. Agreement with statements about drone delivery potentially leading to poor acceptanceB10. Negative assumptions about drone delivery

Agree

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D. I am afraid that the introduction of air taxis significantly reduces
the number of jobs, affecting, for instance, taxi drivers.

C. As a resident of the city, I would be afraid that air taxis or theirpassengers could massively invade my privacy when flying over myhouse/flat, for instance, by spying through my window andrecording my personal life.

B. I suspect that only rich people will be able to afford taking air
taxis.

A. I suspect that taking an air taxi is much too expensive for me
personally.

strongly disagree

disagreesomewhatdisagreesomewhat agree

To what extent do you agree with the following statements about aerial vehicles? Please rate how much you agree or disagree with each of the following statements.

C10. Agreement with statements about air taxis potentially leading to poor acceptanceC10. Negative assumptions about air taxis & vertiports

agreestrongly agree

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G. I would feel comfortable living close to a take-off station foraerial vehicles, for instance, within a range of 50 metres.

F. I consider the allocation of inner-city space for take-off andlanding stations of aerial vehicles as completely unfair or
unnecessary.

E. Take-off and landing stations for air taxis operated by only one
provider (comparable to airports for a single airline or docks for asingle ferry line) would hamper competition and are therefore
extremely unfair from a societal perspective.

strongly disagree

disagreesomewhatdisagreesomewhat agree

To what extent do you agree with the following statements about aerial vehicles? Please rate how much you agree or disagree with each of the following statements.

C10. Agreement with statements about vertiports potentially leading to poor acceptanceC10. Negative assumptions about air taxis & vertiports

agreestrongly agreeQuestionnaire

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B. Air taxis

A. Drones (such as delivery drones)Security

Fully mistrust

Mistrust

Somewhat
mistrust
Somewhat trust

Trust

Fully trust

To what extent do you trust that advanced aircraft flying in an urban environment will be technologically secure and armed against threats from hackers (such as criminal organisations, hacktivists or
terrorists) in the following cases? Please select one answer per row.

D2. Level of trust in security systems of drones and air taxis

D2. Trust in VTOL security

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C. Regional or local authorities

B. National authorities

A. European authorities

Security

Fully mistrust

Mistrust

Somewhat
mistrust
Somewhat trust

Trust

Fully trust

To what extent do you trust the following authorities to handle the risks and adopt regulations needed to manage urban air mobility (including safety, noise control, environmental protection, security,
cybersecurity, etc.)? Please select one answer per row.

D1. Level of trust in regulatory authorities by level by area of influence

D1. Trust in regulatory authorities

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C. Regional or local authorities

B. National authorities

A. European authorities

Trust

Decrease a lot

Decrease slightly

Stay the same

Increaseslightly

Increase

Increase a lot

Would your trust increase if the following regulators were to develop regulations to manage cybersecurity risks (certification and operation of aerial vehicles)? Please select one answer per row.

D3. Direction and dimension of impact from regulatory measures on trust levels

D3. Impact of regulation on trust

Appendix 3
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Appendix 3

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Dietrich, A.M. (2020, January 1). Community benefits of urban air mobility (UAM). Retrieved from https://static1.squarespace.com/static/5d27bb3e330ac30001dc14fd/t/5e9cc83d4ee1eb456087402d/1587333191886/
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Golding, R. (2018, June 7). Metrics to characterize dense airspace traffic. Retrieved from https://storage.googleapis.
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