Acceptability and Acceptance of Connected Automated Vehicles: A

Literature Review and Focus Groups

Jorick M. M. Post

, Janna L. Veldstra

and A. Berfu Ünal

1,2 c

Faculty of Behavioural and Social Sciences, Rijksuniversiteit Groningen, Groningen, The Netherlands

Faculty of Campus Fryslan, Rijksuniversiteit Groningen, Groningen, The Netherlands

Keywords: Connected Automated Vehicles, Autonomous Driving, Acceptance, Acceptability.

Abstract: A lot of resources and manpower are being allocated to develop Connected Automated Vehicles (CAV). CAV

are Automated Vehicles (AV) with vehicle connectivity abilities to further increase road safety and user

convenience. For a successful implementation of CAV, the psychological factors that predict its acceptance

have to be researched. The present paper provides a literature review of the individual differences and

perceived characteristics that could influence CAV's acceptance. Additionally, we report the results of several

focus groups that were held in 4 European countries to highlight additional factors not reported in the literature

yet.

1 INTRODUCTION

In the near future Connected Automated Vehicles

(CAV) will be introduced to public roads. CAV are

fully self-driving vehicles, which can share data with

other vehicles and transportation systems. The

traditional driver will take the role of a passenger in

CAV. Major players in the automotive industry have

already invested in designing vehicles with full

automation, and many have started pilot testing these

vehicles in designated test areas (SAE International,

2018).

At present, Automated Vehicles (AV) already

exist and are allowed on public roads in some

countries. However, AV sensing technologies are

currently limited, and unreliable under extreme

weather or road conditions (He et al., 2019). To

illustrate, at least three Tesla drivers have died in

crashes in which autopilot failed to detect obstacles

on the road since 2016 (Boudette, 2021), with

several crashes still under investigation. CAV

improves upon existing AV by including vehicle

connectivity abilities to communicate with other

vehicles and transportation networks, enhancing the

situational awareness. For example, they can share

the vehicles speed, heading, and brake status to

https://orcid.org/0000-0001-9048-1423

https://orcid.org/0000-0002-1604-5321

https://orcid.org/0000-0002-0221-0656

increase road safety (Eskandarian, Wu, & Sun,

2019). Moreover, they could help in improving

traffic flow and plan the most efficient road,

enhancing the vehicle’s convenience. Lastly, more

efficient driving and CAV’s ability to platoon may

reduce traffic CO

emissions, potentially making it

more environmentally friendly than AV or

traditional cars.

A lot of resources and manpower are being

allocated to realize the goal of connected fully

automated vehicles. However, whether these efforts

will be successful depends on whether the public

would accept and adopt CAV. The addition of

vehicle connectivity may lead to improved safety

and convenience over AV, but could also increase

the public’s concerns about for example data sharing

and possible hacking of the vehicle. In this paper we

explore which psychological factors are important

for the acceptability and acceptance of CAV. We

first conducted a literature review to answer this

question. Additionally, we held several focus groups

to discover other factors that could influence the

acceptance of CAV that are missing or lacked

attention in the literature.

Post, J., Veldstra, J. and Ünal, A.

Acceptability and Acceptance of Connected Automated Vehicles: A Literature Review and Focus Groups.

DOI: 10.5220/0010719200003060

In Proceedings of the 5th International Conference on Computer-Human Interaction Research and Applications (CHIRA 2021), pages 223-231

ISBN: 978-989-758-538-8; ISSN: 2184-3244

223

2 LITERATURE REVIEW

In the literature acceptability and acceptance are

sometimes used interchangeably. However, in this

paper we disentangle the two constructs and reason,

in line with Schade & Schlag (2003), that

acceptability refers to one’s attitudes and evaluations

before one has experienced CAV, whereas

acceptance refers to one’s attitudes, evaluations, and

behaviour after having experienced CAV.

Acceptability could be expressed as an attitudinal

evaluation or intention (e.g. the willingness to ride

CAV), while acceptance could both be expressed as

an attitude, as well as actual behaviour (e.g.

purchasing CAV). As those people that have had

experience with CAV mostly had those experiences

in an experimental setting and not in real-life, the

present literature review will cover acceptability and

not acceptance in the majority of the reviewed

studies.

Few studies have researched the acceptance of

fully automated vehicles (e.g. Kyriakidis et al., 2015;

Distler et al., 2018). Previous studies have mainly

focused on Advanced Driver Assistance Systems

(ADAS), partially automated vehicles, public

exposure to automated vehicles in the media such as

Google car and Tesla, or slow-driving automated

public transport shuttles. As such, we will extrapolate

results from these studies to CAV.

2.1 Individual Differences

Innate demographic differences have often been

analysed in an attempt to see whether they affect the

acceptability of automated vehicles (AVs; e.g.

Howard & Dai, 2014; Becker & Axhausen, 2017).

Individual differences may be interesting to examine

to be able to tailor CAV to specific needs of different

user groups. However, previous research has shown

that effects of individual differences on acceptability

of CAV are often small, and sometimes contradictory

(e.g. Becker & Axhausen, 2017 and Rödel et al.,

2014).

2.1.1 Gender and Age

Most studies included gender and age in their

analyses and examined whether innate demographic

differences exist in acceptance of AV. Some gender

differences surfaced. In general male drivers are

reported to be less concerned to be a passenger in a

fully automated vehicle than women (Schoettle &

Sivak, 2014; Becker & Axhausen, 2017). Howard &

Dai (2014), for example, reported that women and

men differed in the concerns they have with regard to

being a passenger in a fully automated AV. Women

were more concerned with low control over the

vehicle, while men were more concerned with

potential liability issues. Differences between men

and women in willingness to use an automated

vehicle could be partially explained by emotions that

they assign to automated driving. Women tend to

assign more negative emotions to automated driving,

and anticipate both less pleasure and more anxiety

than men (Hohenberger, Spörrle, & Welpe, 2016).

Comparisons between age groups are less

equivocal in the literature. Some studies reported that

young people were more positive about automated

vehicles than older drivers (Becker & Axhausen,

2017), while other studies report that older people

were more interested in using an automated vehicle

than younger people (Rödel et al., 2014). Gold et al.

(2015) reported that older people tend to rate the

potential safety gains of automated driving higher

than younger people. Likewise, Regan at al. (2017)

reported that younger people have a higher level of

trust in CAV than older people, but they also have

higher levels of concerns about their performance

than older people have. Ease of technology use may

be a moderating factor in the relationship between age

and willingness to use CAV. For example, Schaefer

et al. (2014) reported that higher self-reported ease of

technology use among older people had positive

effects on willingness to use AVs, and expected

benefits from using AVs. Additionally, Souders &

Charness (2016) found that reduced concerns related

to AVs had positive effects on willingness to use

them. As such, instead of focusing on differences in

acceptance based on age, it may be better to focus on

the ease of technology use.

2.1.2 Experience with Technology

Having no experience with an innovation can trigger

a negative response to it, especially among people

who are not open to new technology. On the other

hand, having positive experiences with an innovation

can increase willingness to use it. To illustrate, in a

simulation study conducted by Gold et al. (2015), the

researchers found that perceived trust and intention to

use an AV increased after exposure to it (Gold et al.,

2015). This means that even a simulated experience

with the technology can benefit the relationship to it.

In another study initial perceptions of highly

automated vehicles were assessed, followed by letting

participants experience the AV in a driving simulator,

and finally letting them experience it on a test track.

Acceptance, trust, satisfaction, and perceived

SUaaVE 2021 - Special Session on Research Trends to Enhance the Acceptance of Automated Vehicles

224

usefulness of the AV increased significantly after

experiencing the driving simulator compared to the

initial attitudes (Hartwich et al., 2018). Moreover,

these positive ratings remained stable over time after

they had experienced the AV on a test track. Also, Qu

et al. (2019) reported that self-reported familiarity

with AVs is positively correlated with the expected

benefits of AVs, and negatively correlated with

concerns. These studies indicate that experience with

the technology, even in a simulator, can significantly

increase the acceptance of CAV.

However, direct experience with CAV may not be

necessary to increase acceptability. Positive

experiences with automated features in cars, such as

automatic lane keeping, automated parking, or

adaptive cruise control may enhance willingness to

make the step to fully automated driving. Indeed,

Sener, Zmud, & Williams (2019) found that intention

to use AVs was higher among people who had

experience with automated features in cars than

people who did not have experience with features like

this. These results indicate that having people

experience driving with some automated functions

could increase the acceptability of CAV and in turn

acceptance.

2.1.3 Motives

Aside from previous experience with technology,

examining people’s motives for using cars could

prove useful in determining which factors are

important for acceptance of CAV. Most people will

come up with all kinds of practical arguments when

asked why they drive a car. Innovators generally also

stress these commonly named instrumental

advantages of AVs to promote their use. However,

research into motives for private car use has shown

that a car is much more for people than just a means

of transportation (Steg, 2005). Aside from

instrumental motives, symbolic and affective motives

influence current private car use (Gatersleben, 2007;

Steg, 2005). Symbolic motives for private car use

include being able to express one’s high status or

identity by driving an expensive or luxurious car.

Affective motives for car use include the joy of

driving and seeing driving itself as a positive and

enjoyable activity.

Although to date no research has extrapolated the

motives for traditional private car use to intentions for

the use of CAV, these findings have been replicated

in the purchase intention of electric vehicles (Noppers

et al., 2014). Participants indicated that instrumental

aspects of electric vehicles were the most important

for their purchasing intention, but purchasing

intentions were actually better predicted by the

evaluation of the symbolic aspects of the vehicle.

More specifically, the purchase intention of an

electric vehicle was mostly associated with gaining

status. Especially the early adoption of new mobility

choices may be driven by the association of high

status (Egbue & Long, 2012). Extrapolating these

findings to the intention to use CAV, CAV may

benefit from being presented as a luxurious product at

its launch to enhance acceptance.

2.2 Perceived Characteristics

Several models that aim to explain acceptance of

technology or innovations include system and design

features as predictors of acceptance (e.g. the

Technology Acceptance Model; Davis, 1993),

indicating that perceived characteristics of CAV may

play a major role in its acceptance. We will, therefor,

discuss the perceived characteristics of CAV that are

mentioned the most often in the literature relating to

acceptance below, namely perceived safety, pleasure,

convenience, comfort, trust, and control.

2.2.1 Perceived Safety

A lot of individual variation exists when it comes to

perceptions regarding the safety of automated

vehicles. For instance, while some people associate

full automation with high safety (Brell et al., 2019),

others associate it with low safety (Zmud et al., 2016).

A large-scale survey by Schoettle & Sivak (2014)

with over 1500 participants revealed that a large

portion of the respondents believed that fewer

accidents will happen in the future thanks to

automated vehicles, indicating they expected a high

safety increase.

It seems people immediately think of safety when

discussing AVs. In one questionnaire, more than half

of the participants chose ‘highest possible level of

safety’ as their greatest priority for automated cars

(Lustgarten & Le Vine, 2018). The greatest concerns

regarding the safety of automated driving people

seem to have are about equipment failure, vehicle

performance in unexpected situations, software

hacking, and data misuse (Kryriakidis et al., 2015;

Schoettle & Sivak, 2014). In short, people expect both

safety gains, but are concerned about safety as well.

Additionally, Zoellick et al. (2019) reported that

perceived safety correlated strongly with acceptance

and was a solid predictor of intention to use

automated vehicles in a study where potential users

experienced a vehicle with high automation on the

road. This indicates perceived safety may be a

Acceptability and Acceptance of Connected Automated Vehicles: A Literature Review and Focus Groups

225

predictor of both acceptance of and intention to use

CAV. In a different study it was found that the more

driving experience respondents had, the more often

they drove, and subsequently the more likely they had

been involved in a conventional car-based crash,

which made them view automated vehicles as a safer

alternative (Montoro et al., 2019).

2.2.2 Perceived Pleasure

As said above, a significant percentage of drivers do

not view driving as just a means of transportation, but

enjoy the driving in itself, feeling it is thrilling,

pleasurable, and adventurous (Steg, 2005). Driving in

CAV could pose a threat to driving pleasure, in

particular for those who associate driving with fun as

it takes away the driving task of the driver. In turn this

could affect the acceptability and acceptance of CAV.

Indeed, Rödel et al. (2014) reported that the expected

fun of driving was lower for higher automation,

compared to lower automation. Intention to use these

vehicles was also lower for higher automation levels.

Certain aspects of driving in CAV could also

increase driving pleasure, though. For example,

engaging in manoeuvres that are seen as difficult,

such as reverse parking, could decrease the driving

pleasure of a traditional car. When driving in CAV

there is no need to deal with such hassles. In support

of this reasoning, Bjørner (2017) found that people

expect the highest pleasure with AVs in situations of

parallel parking or in a traffic jam. In short,

perceptions of pleasure regarding being a passenger

in CAV could both be positive or negative. Future

research needs to investigate if and how these

perceptions influence the acceptability and

acceptance of CAV.

2.2.3 Perceived Convenience and Comfort

Convenience appears to be an important factor

associated with fully automated driving (Howard &

Dai, 2014). The possibility of being able to work,

socialise, or relax despite being stuck in a traffic jam

is very appealing to some. Some benefits potential

users imagine are (1) the ability to multitask, such as

reading or working while travelling, (2) extended

comfort (e.g. the ability to adjust the seat to a relaxing

position; integrated multimedia applications)

compared to a traditional vehicle (Pfleging et al.,

2016), and (3) enhancing the mobility of those

currently unable to drive or in situations in which

driving manually is undesirable, such as after

drinking or when one is fatigued (Jeon et al., 2018).

In fact, in a study examining the prioritization of

benefits of AVs, more than half of the respondents

expressed willingness to pay more, as well as a

willingness to accept slower travel in exchange for

greater comfort while travelling in an AV (Lustgarten

& Le Vine, 2018). Perceived convenience has been

linked to acceptance of both partially automated

vehicles and fully automated vehicles (Lee et al.,

2018).

The level of automation seems to affect perceived

convenience, though. Potential users believe fully

autonomous driving would be easier for them than

manual driving, while partially autonomous driving is

seen as more difficult (Kyriakidis et al., 2015). The

higher the level of automation, the more potential

users would intend to rest, watch movies, or read

while travelling.

2.2.4 Perceived Trust

In an international survey almost half of the

respondents indicated that trust is the biggest barrier

for accepting AVs (Jeon et al., 2018). Perceived trust

can be defined as the belief that CAV will function as

intended and without posing any danger to its

passengers as well as to other road users. When one

does not believe CAV will function as intended, one

has low trust in CAV. Low trust may even lead to

physiological responses among users. For example, in

a simulation study participants with less trust in AVs

experienced an additional increase in

psychophysiological stress when the vehicle drove

autonomously, compared to when the participant was

in control of the vehicle (Morris et al., 2017). As such,

enhancing trust in CAV should be a priority to

enhance acceptance. Two factors may influence trust:

previous experiences, and system transparency.

To start with the first factor, a simulation

experiment with partially automated vehicles found

that positive experiences enhanced trust in the

vehicle, while negative experiences (such as a crash)

decreased trust (Gold et al., 2015). Likewise, false

alarms and errors might decrease trust in automated

systems (Schaefer et al., 2016). Possibly, as CAV

takes over all driving tasks, users may attribute the

negative experiences such as crashes to CAV’s

computer system, while in a traditional car they may

attribute a crash to other road users’ behaviour or their

own driving. The attribution of blame in case of

crashes or errors with CAV still needs further

research. It will be crucial to build CAV so that it can

operate as error-free as possible, as people will be less

forgiving of a machine than a human (Zhang et al.,

2021).

Secondly, system transparency (the degree to

which users can predict and understand the operating

SUaaVE 2021 - Special Session on Research Trends to Enhance the Acceptance of Automated Vehicles

226

of the vehicle), as well as the perception of the

vehicle’s performance have been found to have

positive effects on trust in AVs in a survey applying

the Technology Acceptance Model to AVs (Choi &

Ji, 2015). Moreover, greater trust is associated with a

greater intention to use AVs. Perhaps explaining

clearly and in an easy-to-understand manner how

CAV functions could improve its acceptance.

2.2.5 Perceived Control

Another potential barrier towards the acceptance of

CAV is the feeling of low control associated with

fully automated driving. The higher the automation

level of a vehicle, the less likely people are to prefer

that vehicle over a vehicle with lower automation

(Schoettle & Sivak, 2016). The majority of the

current drivers indicate that they still would like to

have some control over the pedals and the steering

wheel. Current drivers would like AVs to have the

option to be able to drive manually whenever they

desire to do so (Liljamo et al., 2018). Lack of control

is rated as the least attractive feature of fully

automated driving (Howard & Dai, 2014). Full

automation could pose a threat to the basic need of

feelings of control, especially for those who enjoy

car-use and value their car as a luxury possession.

On the other hand, when people believe that

CAVs are capable to drive safely by having external

control of the road situation at all times, they are also

more likely to be accepting of CAV. For example,

Dixon et al. (2020) reported that the more people

perceived that an AV itself had control over and could

avoid possible hazardous situations, the more they

supported AVs. However, where these beliefs stem

from is not clear. It could be that those who already

have positive experiences with automation assign

more external control to the car. For instance, drivers

who already use adaptive cruise control indicate to be

more comfortable about driving without a steering

wheel than those who do not currently use adaptive

cruise control (Kyriakidis et al., 2015). In short,

perceived control does appear to play a role in the

acceptance of CAV, but what the antecedents of

perceived control of CAV are remains unclear.

3 FOCUS GROUPS

The literature review highlighted some important

psychological factors that could influence the

acceptability of CAV. The aim of the focus groups

was to assess if other psychological factors could play

a role in the acceptability of CAV that were not found

or received little attention in the literature. To this end

we conducted a total of 8 focus groups in Spain, Italy,

France, and the Netherlands. They took place from

late 2019 to early 2020.

3.1 Sample

In each country the focus group(s) targeted middle

aged drivers (aged 31-55). Additionally, the focus

groups were held to target specific groups: (1)

cyclists, (2) pedestrians, (3) anxious drivers / low

frequency drivers, (4) high frequency drivers, (5)

older drivers (aged 56-75), (6) younger drivers (aged

18-30), and (7) persons with physical disabilities.

The total sample consisted of 70 participants, with

a mean age of 40.8. The majority was male (61.4%),

and held a university degree (47.1%). For an

overview of the total sample per category, please refer

to Table 1 below. Please note some participants may

fall into multiple categories.

Table 1: Sample overview focus groups.

Participant type N

Young drivers (18-30) 21

Middle aged drivers (31-55) 32

Older drivers

(

56-75

)

Low fre

uenc

drivers 26

h fre

uenc

drivers 32

Vulnerable road users (pedestrians, cyclists,

and

ersons with a disabilit

3.2 Procedure

A script and questionnaires were prepared beforehand

in English, and then translated to Spanish, Italian,

French, and Dutch by native speakers. The focus

groups followed the method of Focus Group based on

Collective Questionnaire Sessions developed by

Bellet et al. (2018), allowing for both qualitative and

quantitative data collection.

Participants were first given an information form,

which detailed the aims of the study and what was

expected of them, as well as an informed consent

form. After signing the informed consent form,

participants completed a short questionnaire about

demographics, driving behaviour, and interest in

technology individually. After everyone completed

the questionnaire, participants introduced themselves

and were asked what comes to mind when thinking

about CAV. They were then shown a short videoclip

(3 minutes) that showed what driving in CAV is like

and received a textual description of CAV. After this,

participants individually filled out short questionnaires

on various topics, alternated with rounds of discussion.

Acceptability and Acceptance of Connected Automated Vehicles: A Literature Review and Focus Groups

227

The topics discussed were: (1) acceptability, (2) safety,

risk, and trust, (3) convenience, pleasure, and comfort,

(4) perceived benefits and costs, and motives, and (5)

ethical and legal issues.

Qualitative results were obtained from the

recorded discussions, as well as any comments

participants left on the individual questionnaires after

each section. The group discussions were led by the

test leaders, who had received the script and several

discussion topics beforehand.

The focus group for the Dutch participants was

held online instead, due to the COVID-19 lockdown

in 2020. Dutch participants completed the same

questionnaires online, and discussion rounds were

omitted for this group.

3.3 Collective Questionnaire Sessions

We will discuss the outcome of the focus group

sessions for each separate section.

3.3.1 Acceptability and Demographics

Acceptability of CAV was assessed at three points:

(1) before participants watched the movie and read

the description of CAV, (2) right after watching the

movie and reading the description, and (3) after the

group discussion about acceptability.

We took the mean of all these measurement points

to assess their acceptability. We compared

acceptability based on participants’ gender, age group,

driving frequency, and interest in technology. To

compare low and high frequency drivers, we created

two subgroups in which low frequency drivers scored

below the average on driving frequency, while high

frequency drivers scored above the average. Likewise,

we created two subgroups for high and low interest in

technology, based on whether participants scored

above or below the average on interest in technology.

Overall, more than half of all participants viewed

CAV at least slightly positively. Men, younger and

older drivers, high frequency drivers, and those with a

high interest in technology were slightly more positive

than women, middle-aged drivers, low frequency

drivers, and those with low interest in technology.

Please refer to Figure 1 below for an overview.

3.3.2 Perceived Benefits and Costs, and

Motives

The two largest benefits participants expected from

CAV were reducing the traffic CO

emissions (70%

of participants), and reducing traffic congestion (65%

of participants). Only around half of the participants

thought CAV will facilitate their mobility, and around

60% of participants believed the introduction of CAV

could reduce car insurance rates.

3.3.3 Ethical and Legal Issues

Participants were separately asked who (the owner or

the manufacturer) would be morally and legally

responsible in case of an accident with CAV. Most

participants agreed that the manufacturer was morally

Figure 1: Acceptability of CAV in the focus groups.

0 102030405060708090100

Full sample

Men

Women

Ages 20-30

Ages 31-55

Ages 56-75

High driving frequency

Low driving frequency

High interest in technology

Low interest in technology

Acceptability of CAV

Strongly Disagree Disagree Slightly Disagree Neutral Slightly Agree Agree Strongly Agree

SUaaVE 2021 - Special Session on Research Trends to Enhance the Acceptance of Automated Vehicles

228

responsible (70% of participants), compared to the

owner (25% of participants). They also agreed that

the manufacturer would be legally responsible (70%

of participants), compared to the owner (25% of

participants). They were also asked who CAV should

protect in case of an accident. These questions proved

difficult, as participants agreed that CAV should both

protect the passengers at all costs (55% of

participants), as well as protect the other road users at

all costs (60% of participants).

Lastly, participants were asked some questions

about how the introduction of CAV could lead to

various changes. The majority of the participants

thought CAV cannot coexist with traditional vehicles

on public roads (55% of participants), and that both

the infrastructure has to change for CAV (70% of

participants), as well as that new legislation is needed

(70% of participants). Many participants were

worried that their privacy would not be protected in

CAV (55%). Finally, although CAV would be fully

automated, participants still thought a driving license

will be required to use it (60% of participants).

3.4 Focus Group Discussions

The greatest concerns participants had, as well as the

most intensely discussed topics will be reported

below.

There was no consensus on the safety of CAV.

Some participants believed CAV would be safer than

traditional vehicles under all conditions and will be

capable of detecting objects and other road users

sooner than a human could see them. After all, CAV

is never distracted or fatigued like a human driver.

Others were overconfident in their own driving skills.

For example, one participant commented that they

could see a pedestrian earlier than a sensor could

detect them. Some thought a human could react better

in uncommon situations, while CAV would drive

better in common situations. In common situations,

CAV's behaviour will always be similar and thus

CAV would be more predictable than a human driver.

This could help make other road users feel safe. This

indicates the predictability of CAV’s behaviour may

play a role in the perceived safety of CAV, as well as

in its acceptance.

Many other road users (cyclists and pedestrians)

wished to know which vehicle is driving

autonomously and which is driven manually. They

suggested a sticker or logo could be used for this.

Some participants indicated they want to receive

some sort of signal when CAV has detected them as

pedestrian or cyclist. Other participants disliked the

idea of being unable to communicate with the driver,

leading to feelings of unsafety. It seems some form of

communication between other road users and the

vehicle will be necessary to make CAV acceptable for

other road users.

Some drivers wanted to retain the option to drive

manually, even if the vehicle could drive

autonomously. Others pointed out a driving license

will be required if this option remains. This would

mean CAV cannot facilitate the mobility of those

currently unable to obtain a driving license. Others

also indicated to like the idea of CAV in cases they

normally would be unable to drive, such as when they

are fatigued or have been drinking. The discussion

showed a divide between current drivers who need

some degree of control over the vehicle for CAV to

be acceptable, while current non-drivers wanted CAV

to be as accessible as possible to enhance their

mobility. Drivers and current non-drivers may have

different requirements of CAV, potentially causing

differences in their acceptance of CAV.

In terms of legal issues, most participants thought

legislation has to drastically change to ensure legal

liability is clear. Without a clear legal framework,

CAV would not be acceptable. A few participants

suggested legal liability of the vehicle owner could

depend on maintenance. The owner would be legally

responsible if the vehicle was poorly maintained;

otherwise the manufacturer would be responsible.

One potential issue of CAV is the sharing of data.

Most participants believed that as long private data is

not shared, it will not be problematic. Only data

needed for the algorithms and anonymous data should

be shared. If privacy cannot be guaranteed, CAV may

not be acceptable to several participants.

In terms of environmental sustainability of CAV,

most participants did not know CAV may be able to

reduce CO

traffic emissions by platooning or by

reducing traffic jams through more efficient driving.

Electric cars would be more environmentally

friendly, they thought. Some feared an increase in

mobility will increase traffic and congestion, which

will in turn increase traffic CO

emissions. Several

participants suggested making all CAV electric. This

indicates that the perceived environmental

sustainability of CAV could influence its acceptance.

4 CONCLUSIONS

In the present paper we provide a literature review on

psychological factors that could influence CAV’s

acceptability and acceptance. Additionally, we

conducted several focus groups to uncover other

factors that could play a role in CAV’s acceptance

Acceptability and Acceptance of Connected Automated Vehicles: A Literature Review and Focus Groups

229

that were not mentioned or received little attention in

the literature.

In the literature review we found that individual

differences may play a role in the acceptability and

acceptance of CAV. Gender and age may have

limited effects, while experience with the technology

may be a more reliable predictor. Perceived

characteristics of CAV may be the most important

predictors of acceptance. We discussed perceived

safety, pleasure, convenience, comfort, trust, and

control as being particularly relevant.

The focus groups showed that the predictability of

CAV’s behaviour, perceived environmental

sustainability of CAV, existence of a clear legal

framework of liability, and capability of

communicating with other road users may be

additional factors that could influence CAV’s

acceptance. We also found that drivers and non-

drivers may have different requirements for CAV,

which could lead to differences in their acceptance

levels. The finding also points out that marketing

strategies should target different factors based on user

group characteristics and needs.

Future research should determine whether factors

influencing acceptance of AV can be extrapolated to

CAV. Additionally, what drives different perceptions

of CAV (for example whether one believes CAV is

safe or not) is currently unclear. If these questions

could be answered, we would have a better grasp on

what is needed to enhance CAV’s acceptance to

facilitate its implementation.

ACKNOWLEDGEMENTS

This project has received funding from the European

Union’s Horizon 2020 research and innovation

programme under grant agreement No. 814999. The

content of this publication is the sole responsibility of

the authors, and in no way represents the view of

CINEA or European Commission.

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