Content uploaded by Caroline Pigeon
Author content
All content in this area was uploaded by Caroline Pigeon on Aug 23, 2021
Content may be subject to copyright.
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
Title: Factors of acceptability, acceptance and usage for non-rail autonomous public transport
vehicles: a systematic literature review
Authors: Caroline Pigeon, Aline Alauzet, Laurence Paire-Ficout
Transportation Research – Part F: Traffic, Psychology and Behaviour
Abstract:
Non-rail autonomous public transport vehicles have emerged over the last few years. Technical
progress in automation has resulted in a growing number of autonomous shuttle pilot experiments.
Although these systems are technologically feasible, determining the extent to which they correspond
to users’ needs and expectations remains a major issue. In order to answer that question, we
conducted a systematic review which synthesizes the literature regarding the acceptability and
willingness to use this type of autonomous public transport. This literature review allowed us to
identify 39 documents addressing 70 factors of acceptability, acceptance and usage of non-rail
autonomous public transport vehicles. The most salient factors concern service characteristics (times,
schedules, fares) and safety issues (road-safety, on-board security). Factors related to automation
level, comfort and access to the vehicle feature to a lesser extent. Acceptation is also related to
personal factors, such as socio-demographics, travel habits, and personality. This review could be of
interest to designers and manufacturers of non-rail autonomous public transport vehicles, as well as
policy makers, and assist with the successful implementation of autonomous public transport services
which are better adapted and meet the needs of all potential users.
Keywords: autonomous vehicle; autonomous shuttle; public transit; willingness to use; user needs
1 Introduction
The development of autonomous vehicles is currently booming and has been the subject of a growing
number of scientific publications over the last fifteen years (Gandia et al., 2019). However, non-rail
autonomous public transport vehicles (APTV) have received less interest than the autonomous
personal automobile (Azad et al., 2019). Excessive use of autonomous personal automobiles may
increase traffic congestion and greenhouse gas emissions (Harb et al., 2018). APTVs are seen as a more
appropriate response to the challenges of global warming. They could improve mobility services, and
in doing so, lead to an increase in the use of public transport, and therefore decrease reliance on
personal automobiles (Millonig & Froehlich, 2018).
However, if APTVs are to be implemented on a large scale and adopted for future use in daily travel,
people need to have a positive attitude towards them. Attitude can be defined as a mental state of
readiness, positively or negatively associated with a particular object. It is acquired through experience
and is a precursor of behaviour related to the object. Several concepts are commonly used to study
general attitude towards a new technology. Acceptability refers to the prospective judgment of
potential users towards a technology to be introduced in the future (here the APTV). This implies that
the potential users have not yet experienced this new technology (Schade & Schlag, 2003). Acceptance
corresponds to judgements, attitudes and behavioural reactions of potential users towards a product
after they have tried it (Schade & Schlag, 2003, Schuitema, Steg & Forward, 2010). Potential users have
experience of the technological object in an experimental context, but have not used it regularly or
spontaneously. The usage of a technology refers to the appropriation of this technology by users after
its introduction into their daily life. In that case, the technology is available and people opt to use it.
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
In a recent review (Nordhoff, Kyriakidis, et al., 2019), acceptance of autonomous vehicles was found
to be the result of four decision-making steps: exposure to an automated vehicle, formation of a
positive attitude towards it, a decision to adopt it and actual use of it. These authors found that
acceptance was determined by 28 factors, such as socio-demographic characteristics, experience of
autonomous vehicles and personality. Other factors, related to personal perception of autonomous
vehicles, such as performance expectancy, effort expectancy or social influence, were found to
influence acceptance.
Performance expectancy, or perceived usefulness, can be defined as an individual’s personal
perception that using an innovation would improve his/her performance (Davis, 1989). Effort
expectancy, or perceived ease of use, can be described as the degree to which people think that a
technology can be used without effort (Davis, 1989). Social influence, also known as the subjective
social norm, can be defined as the perception that other significant relatives or influencers have a
positive or a negative attitude towards the new technology (Fishbein & Ajzen, 1977).
Most of the articles emerging from our review focused on autonomous vehicles in general, or on
private autonomous vehicles. The main aim of the present paper is to present how users and potential
users accept autonomous vehicles in the specific context of public transport. In particular, our aim was
to identify within the literature the APTV characteristics which users and potential users need or
require, and which therefore increase acceptability and acceptance, and encourage their use. In
documenting users’ needs and requirements for APTVs, we hope that our findings will provide insight
for APTV designers, manufacturers and policy makers, and will help to improve APTV design and in
doing so meet the needs of all potential users.
This article focuses on non-rail vehicles, which can operate in automated mode on limited sections of
road (level 4 according to the classification of the Society of Automotive Engineers; SAE International,
2018) or which can operate in automated mode on all publicly accessible roadways (SAE level 5).
2 Material and methods
2.1 Search strategy and databases
The literature search was conducted in April 2019 and updated in January 2020 for studies published
between 1999 and 2019. A request relating to APTVs and acceptance, in both English and French was
submitted with the search field title for the Web of Science, Scopus and PsychInfo databases, and with
the search fields title and keywords for Transport Research International Documentation (TRID). The
request was: ((Driverless OR "Self-driv*" OR "Self driv*" OR Automated OR Autonomous OR Intelligent)
AND (Shuttle* OR Minibus* OR "Bus" OR "Buses" OR "Busses" OR Autobus* OR Transit* OR Vehicule*
OR "Public transport*")) AND (Accept* OR Willing* OR Preference* OR Perception* OR Need* OR
Expectation* OR Attitude* OR Adoption OR Readiness OR Interest* OR Opinion* OR Usefulness OR
trust ((Decision OR Intention*) AND Use)). Additional searches were performed using Pubmed,
Springerlink and Sage for documents containing the same terms in the search field abstract or all, and
using Taylor & Francis Online content platform for terms relating to autonomous vehicles in the search
field keywords. CAIRN and Revue.org were also used, but no results relating to autonomous vehicles
were found. In order to retrieve the maximum number of relevant documents, we used backward
snowballing to investigate the reference lists of the studies we included, and forward snowballing on
articles citing these studies. This search, carried out in March 2020, yielded additional documents.
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
2.2 Document selection and data extraction
We retrieved journal publications, conference proceedings, theses, reports and books or book
chapters. 133 records from database research were reviewed for eligibility (Figure 1). Exclusion criteria
were as follows: unrelated to APTV or user perspectives, not in English or French, non-scientific
documents, related to on-track-vehicles or only on-demand services, no acceptability, acceptance or
use factors identified, data gathering method not sufficiently explicit, full-text unavailable, reviews or
meta-analyses. Thirty-six duplicate records were removed, and, based on title and abstract, 61
documents did not fulfil the search criteria, resulting in 36 initially reviewed documents. The three
authors of the present paper participated in the screening process, and each document was
independently screened by two of them. The independent reviewers initially agreed on 92/97
documents (95%; Cohen's kappa coefficient of 0.89) and then met to reach agreement on the
remaining five documents. Fifty-eight additional documents were reviewed with backward and
forward snowballing, leading to a total of 94 documents retrieved. Finally, after the removal of 49
documents which did not fulfil the inclusion criteria and 5 documents for which the full text was not
available, 39 studies were retained.
Figure 1. Review procedure flowchart
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
2.3 Analysis
Firstly, the 39 studies included in this review were described according to their type (journal
publications, conference proceedings, reports, theses, books or book chapters), the kind of vehicle
involved (autonomous shuttle, bus shuttle or APTV in general), the methods used (quantitative,
qualitative or mixed) and their focus (acceptability, acceptance or usage). Secondly, all acceptability,
acceptance or usage factors investigated in these studies were extracted and categorized. The factor
extraction was performed by one author, and a second author independently checked the data
extraction forms for accuracy in a sample of the documents.
3 Results
3.1 Description of included studies
The 39 documents included 19 journal publications, 16 conference proceedings, two master’s theses,
one doctoral thesis and one report. Thirty studies focused on autonomous shuttles, 4 on buses
(including one on school buses) and 5 on APTVs in general. There were 27 quantitative studies and 8
qualitative studies, including 5 with individual interviews, 3 with collective interviews or focus groups
and 1 study involving individual and collective interviews. Three studies combined several methods: 1
study used surveys and qualitative interviews, 2 studies combined surveys, focus groups and
observations.
3.2 Factor analysis
Seventy acceptability, acceptance or usage factors were extracted from the 39 studies included in the
present literature review. They were classified into two themes: user-oriented factors (47 factors) and
individual factors (23 factors).
3.2.1 User-oriented factors
The user-oriented factors category regroups factors corresponding to the characteristics of
autonomous vehicles and of mobility services that are needed, required or suggested by users or
potential users. These factors concern several aspects, and were categorized into five themes: Mobility
services, Safety, Automation characteristics, Comfort and Vehicle access. Each of these factors will be
presented below, and they are summarized in Erreur ! Source du renvoi introuvable..
3.2.1.1 Mobility service factors
Mobility services have been assessed in a number of APTV studies. High frequency services and short
waiting times emerge as positive factors for APTVs acceptability or acceptance (Alessandrini, Delle
Site, Gatta, et al., 2016; Alessandrini et al., 2014; Dekker, 2017; Papadima et al., 2020; Ramseyer et al.,
2018; Salonen & Haavisto, 2019; Stark et al., 2019; Vöge & McDonald, 2003; Wicki et al., 2019). A
median waiting time of 10 minutes was defined as acceptable in the study conducted by Hinderer et
al. (2018), and an average of 6.4 minutes for flexible services and 5.4 for fixed routes in the study by
Földes et al. (2018). A lengthy travel time on an autonomous shuttle results in a negative assessment
(Dekker, 2017). When travel time is shorter, an autonomous shuttle is more likely to be chosen over
an equivalent manual vehicle (Alessandrini, Delle Site, Gatta, et al., 2016; Alessandrini et al., 2014), or
over another means of transport (Wicki et al., 2019; Wintersberger et al., 2018). Similarly, long travel
time seems to be less acceptable for an autonomous shuttle than for a regular bus, but a long waiting
time has been found to be more acceptable for an autonomous shuttle than for a regular bus (Wien,
2019; K. Winter et al., 2019). In terms of service schedules, the participants in a study in which an
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
autonomous shuttle operated from 1:00 to 6:00 p.m. found that the service needed to be extended
(Eden et al., 2017), and another study suggested that autonomous mobility services should operate 24
hours a day (Salonen & Haavisto, 2019).
Studies indicated that attractiveness of APTVs can be improved when fares are lower than for other
means of transport (Alessandrini, Delle Site, Gatta, et al., 2016; Alessandrini et al., 2014; Dekker, 2017;
Herrenkind et al., 2019; Papadima et al., 2020; Piao et al., 2016; Stark et al., 2019; Wicki et al., 2019)
or when the service is free of charge (Hinderer et al., 2018; Vöge & McDonald, 2003). However, 54%
of respondents in another study were willing to pay the same price for an autonomous bus as for a
conventional bus, and 21.5% of respondents were prepared to pay 0.50 € more (Portouli et al., 2017).
Fares can also be customized in line with the service provided (Stark et al., 2019). Some studies have
addressed the importance of the integration of autonomous vehicles into the traditional public
transport offer, and intramodality with other means of transport (Madigan et al., 2017; Stark et al.,
2019; Vöge & McDonald, 2003). People are willing to pay higher fares for flexible services than for fixed
routes, in peak hours, and if they can select fellow passengers; they expect to pay lower fares for a
flexible service ordered 30 minutes in advance and for daily use (Földes et al., 2018). People are also
willing to pay higher fares on an autonomous shuttle when it reduces on-vehicle time (Wien, 2019; K.
Winter et al., 2019).
Travel information, for example about routes and connections (Földes et al., 2018; Nordhoff, de
Winter, et al., 2019), and about vehicle speed and congestion is seen to be important for potential
APTV users (Fröhlich et al., 2019), and its provision in real time on smartphone applications has been
promoted (Papadima et al., 2020; Stark et al., 2019). Provision of on-board information about the
current position of the vehicle is also necessary (Vöge & McDonald, 2003). Another study found that
information should be easily visible for passengers, and therefore two screens are preferable when
seating is bi-directional. These should not, however, obstruct passengers’ view from the vehicle
(Fröhlich et al., 2019). Reliability of service and information provided is also a requirement of users
and potential users (Nordhoff, de Winter, et al., 2019; Stark et al., 2019).
With regards to the vehicle location context, several studies (Alessandrini, Delle Site, Gatta, et al.,
2016; Alessandrini, Delle Site, Stam, et al., 2016; Alessandrini et al., 2015, 2014) found that preference
for autonomous shuttles over traditional shuttles was greater in major facility infrastructures
(technological park, university campus), than in city centers, at transport public nodes or in residential
areas. In one survey, 28.8 % of respondents stated that autonomous shuttles would be useful between
residential areas and public transport connections, while 12.3 % replied in favour of autonomous
shuttles between workplaces and public transport connections (Roche-Cerasi, 2019). Other studies
report that a service on a dedicated line (Dekker, 2017; Vöge & McDonald, 2003) and in a context of
calm traffic is preferred (Salonen & Haavisto, 2019). However, pedestrian areas are not seen as a
suitable context for autonomous shuttles, while autonomous shuttles for connections to places such
as railway stations or airports are perceived as being more useful (Eden et al., 2017). Autonomous
shuttle services in locations which currently have insufficient public transport links, for example rural
areas, have been promoted in several studies (Hinderer et al., 2018; Nordhoff, de Winter, et al., 2019;
Stark et al., 2019). The itinerary of the autonomous vehicle must meet the needs of users (Salonen &
Haavisto, 2019).
Flexibility of service has been identified as a positive factor of intention to use an autonomous shuttle
(Nordhoff, de Winter, et al., 2019; Salonen & Haavisto, 2019; Vöge & McDonald, 2003). However, there
is also a certain reluctance to use this type of service, because it involves actively ordering a vehicle,
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
and can therefore be perceived as being less spontaneous and independent than just going to a stop
and waiting for a vehicle (Stark et al., 2019; Wien, 2019; K. Winter et al., 2019).
3.2.1.2 Safety factors and concerns
Factors discussed here relate to safety issues, and to concerns about traffic safety, difficulties
introduced by the absence of a driver, fear of assault, incivilities or invasion of data privacy. In this
section, we present vehicle characteristics related to these themes, as well as suggested preventive
counter-measures.
Fears and concerns about automation have been found to negatively influence attitude towards
APTVs, although they do not modify their perceived benefits (Acheampong & Cugurullo, 2019).
Concerns about the safety of the vehicle and incivilities decrease willingness to use an autonomous
bus (Dong et al., 2017; Monéger, 2018). Before and after trying an autonomous shuttle, participants
reported that fear of a technology failure resulted in a negative opinion about autonomous vehicles
(Fernández Medina & Jenkins, 2017). Potential users require personal data protection (Stark et al.,
2019), and concerns about this have been found to negatively impact the perceived usefulness of
autonomous shuttles, but not attitude towards them (Herrenkind et al., 2019).
Dong et al. (2017) found that the absence of a driver leads to concerns about assistance to people with
disabilities and access to information. These concerns negatively impact willingness to use
autonomous buses. The absence of a driver also raises questions about the resolution of technical
problems, the provision of information to passengers, the prevention of incivilities and supervision of
compliance with regulations (López-Lambas & Alonso, 2019). It also emerged that public transport
drivers carry out tasks unrelated to driving, such as providing information, ensuring passenger safety
and handling unexpected situations (Fernández Medina & Jenkins, 2017). Fears associated with the
night service is another issue (Piao et al., 2016), and this seems to affect women more than men (Stark
et al., 2019). Women are also more worried than men about traffic safety, incivilities, assault, terrorism
and personal data protection (Roche-Cerasi, 2019). Concerns about the decision-making algorithm, in
situations where a collision is unavoidable have also been voiced (Salonen & Haavisto, 2019).
The issue of vehicle speed leads to contrasting appreciations, depending on whether safety or
efficiency is the priority. Low speed has been associated with a negative appreciation of autonomous
vehicles in a number of studies (Fernández Medina & Jenkins, 2017; Nordhoff, de Winter, et al., 2019;
Nordhoff et al., 2018; Ramseyer et al., 2018; Wintersberger et al., 2018), and has been both positively
and negatively assessed in others (Eden et al., 2017; Salonen & Haavisto, 2019; Vöge & McDonald,
2003). Abrupt and frequent braking was assessed negatively in some studies (Eden et al., 2017;
Fernández Medina & Jenkins, 2017; Nordhoff, de Winter, et al., 2019; Ramseyer et al., 2018). However,
participants’ opinion of autonomous shuttles improved after they experienced that vehicle stopped
when pedestrians or cyclists came too close to it (Fernández Medina & Jenkins, 2017).
In response to these concerns, and to improve safety, countermeasures have been proposed. The
presence of seat belts (Eden et al., 2017; Vöge & McDonald, 2003) and child safety seats (Stark et al.,
2019), and the prohibition of standing inside the vehicle (Vöge & McDonald, 2003) have all been cited
as ways of preventing falls during braking. Divergences were found on passenger registration and
video and audio surveillance to prevent incivilities and assaults, because they raised concerns about
personal data protection (Stark et al. 2019). Certain studies have identified the need for a stop button
(Nordhoff, de Winter, et al., 2019) or a means of communication in case of emergency, vehicle
dysfunction or incivility, in the form of an on-vehicle system application (Vöge & McDonald, 2003).
Autonomous medical emergency management has also been proposed (Vöge & McDonald, 2003).
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
More globally, the need to respect current security standards was expressed in a study by Stark et al.
(2019).
3.2.1.3 Automation factors
Some factors found in the present literature review relate to automation characteristics. These include
supervision of the vehicle, presence of a means of manual control, automation level and information
provided to users about automated driving.
Inconsistent results were found regarding vehicle supervision. Some studies reveal a preference for an
on-board supervisor (Dong et al., 2017; López-Lambas & Alonso, 2019; Piao et al., 2016; Salonen &
Haavisto, 2019). External supervision was preferred in others (Dekker, 2017; Nordhoff et al., 2018) and
no supervision in other studies (Papadima et al., 2020). The same discrepancies can also be found
within a single study. In several studies, some of the participants appreciated the presence of a
supervisor on the shuttle, while others would have preferred not to have a supervisor on board
(Ramseyer et al., 2018; Wien, 2019; K. Winter et al., 2019). The need for supervision (via an external
or an on-board supervisor) was expressed by 20 % of the sample in the study by Nordhoff, de Winter,
et al. (2019), and a lack of supervision was perceived as being a barrier to autonomous shuttle use by
18 % of participants in Monéger's study (2018). Finally, preference for an on-board supervisor on
shuttles was found to be more important for non-users than for regular users of an autonomous
shuttle (Portouli et al., 2017).
Four studies have highlighted the interest for users of having a means of manual control over the
vehicle. This should take the form of an emergency stop button (Nordhoff, de Winter, et al., 2019),
which also opens the doors when pressed (Vöge & McDonald, 2003), or of a joystick which allows the
supervisor to take control of the vehicle (Ramseyer et al., 2018). However, a user-operated horn to
warn other road users of the approach of the autonomous shuttle was rated less well than an
autonomous horn (Monéger, 2018).
The importance of providing passengers with information about the autonomous functioning of the
shuttle has been pointed out, in particular in relation to the vehicle’s ‘awareness’ of its surroundings
(obstacles) and its ‘intentions’ (turning, braking, avoiding obstacles). This information could be relayed
by an auditory warning signal (Vöge & McDonald, 2003), or displayed at eye-level on the windscreen
(Fröhlich et al., 2019). However, it has not been clearly demonstrated if visually-displayed information
should contain text, icons or come in an augmented reality format, although a combination of these
formats might be more comprehensible (Fröhlich et al., 2019).
Concerning the automation level, participants in one study preferred traditional buses, or buses with
a low level of autonomy to fully-autonomous buses (Roche-Cerasi, 2019). In other research, after trying
an autonomous shuttle, participants negatively assessed both the shuttle’s inability to automatically
bypass obstacles, and manual interventions by a supervisor (Nordhoff, de Winter, et al., 2019).
3.2.1.4 Comfort factors
Comfort factors, which refer to the physical and aesthetic characteristics of a vehicle, and options
aimed at improving passenger satisfaction, have been mentioned in several studies.
Good visibility of the exterior, via large windows is important for users (Eden et al., 2017; Ramseyer
et al., 2018), as are road-facing seats (Fernández Medina & Jenkins, 2017; Nordhoff, de Winter, et al.,
2019). Free internet access on the vehicle was perceived positively in three studies (Földes et al., 2018;
Nordhoff, de Winter, et al., 2019; Vöge & McDonald, 2003). Other studies have addressed the question
of seats, which have to be comfortable (Eden et al., 2017; Nordhoff, de Winter, et al., 2019) and in a
configuration which facilitates discussion between passengers (Ramseyer et al., 2018). A low noise
level inside the vehicle has also been requested: the hydraulic compressor noise of a shuttle (Eden et
al., 2017) and an audible warning device used to warn other road users of the electric vehicle’s
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
presence (Fernández Medina & Jenkins, 2017) were found by participants to be irritating. Shuttle
appearance has also been studied. Potential users require an attractive interior (Nordhoff, de Winter,
et al., 2019), and an external appearance similar to that of a traditional shuttle (Vöge & McDonald,
2003). Vehicle cleanliness is also a requirement (Vöge & McDonald, 2003). Users and potential users
have also suggested that air-conditioning should be a feature of the vehicle (Nordhoff, de Winter, et
al., 2019). Finally, for participants who tried an autonomous shuttle, the presence of an humanoid
voice decreased their willingness to use the vehicle, its perceived usefulness, its social influence and
their perceived pleasure (Monéger, 2018).
3.2.1.5 Access factors
Several factors relating to physical access to the vehicle were found to influence APTVs acceptability.
Firstly, vehicles need to be sufficiently large in size, with enough seats for users (Stark et al., 2019)
and with room for wheelchairs, strollers and luggage (Eden et al., 2017; Nordhoff, de Winter, et al.,
2019; Nordhoff et al., 2018; Vöge & McDonald, 2003). Secondly, access with no physical obstacles,
(for example with low floors, large sliding doors and access ramps) has been found to influence APTVs
acceptability, in particular for users with disabilities (Nordhoff, de Winter, et al., 2019; Stark et al.,
2019; Vöge & McDonald, 2003). A high vehicle occupancy rate decreases willingness to use an
autonomous shuttle (Wicki et al., 2019). Proposals aimed at preventing overloading of the vehicle via
an access control system have been put forward (Vöge & McDonald, 2003). Finally, participants have
stated that access to the vehicle with a bicycle or a dog should also be possible (Hinderer et al., 2018).
Access to shuttle stops and their characteristics have also been considered. Stops with a shelter,
lighting and seats are preferred to stops without these facilities. A short walking distance to and from
a bus stop (<200 m) was also declared to be an important attribute (Papadima et al., 2020).
Table 1. Factors of acceptability, acceptance or usage related to user-oriented factors and number of studies that investigated
them (n)
Themes
Factors
n
Mobility services
Times and schedules: frequency/waiting time, travel time,
schedules
20
Fares, integration with public transport and intramodality
18
Location context
13
Travel information and reliability
9
Flexibility
6
Safety
Concerns: road-safety of the vehicle, incivilities, technology
failures, personal data protection, absence of a driver, night
services, decision-making algorithm
14
Vehicle speed
8
Braking behaviour
5
Countermeasures: seat belts, child safety seats, prohibition of
standing, registration of passengers and audio and video
surveillance, emergency stop button, communication means,
medical emergency management, respect of current security
standards
11
Automation factors
Supervision
13
Manual control means
4
Automation level
2
Information about autonomous functioning
2
Comfort
Visibility of the outside
4
Free internet access
3
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
Seats (comfortable and with a configuration facilitating
discussion)
3
Noise
2
Internal and external appearance
2
Air-conditioning
1
Cleanliness
1
Humanoid voice
1
Access to the vehicle
Vehicle size
5
Obstacle-free access
3
Occupancy rate and overloading prevention
2
Access to the vehicle with a bicycle or a dog
1
Access and characteristics of stops
1
3.2.2 Individual factors
Several studies point out that individual factors, such as socio-demographic, cultural or psychological
factors, play a crucial role in the process of acceptability, acceptance or usage of APTVs.
The model proposed by (Acheampong & Cugurullo, 2019), based on confirmatory factor analyses
indicates that attitude towards public transport (environmental benefits and their effectiveness) is a
relevant predictor of intention to use APTVs. The authors also found that other factors, such as
attitudes to ecology and technology, behavioural control, social influence and the image associated
with using an autonomous car, concerns about autonomous vehicles, perceived benefits, effort
expectancy, age, gender and education level, were all also predictors of intention to use APTVs.
In their initial study based on the UTAUT model (Unified Theory of Acceptance and Use of technology
of Venkatesh et al., 2003), Madigan et al. (2016) looked at whether the variables performance
expectancy, social influence and effort expectancy predict the intention to use an autonomous shuttle.
These factors accounted for 22% of the variance, suggesting that they were predictors of intention to
use, but that other variables also have an influence. Age, gender and exposure to technology were not
found to be moderating variables of intention to use.
In a subsequent study, Madigan et al. (2017) found that perceived pleasure, usefulness, social influence
and facilitating conditions (i.e. having the resources and knowledge to use the shuttle) were predictors
of intention to use an autonomous bus, and accounted for 58.6% of the variance. Effort expectancy
did not predict intention to use, nor did age, gender or the number of times the autonomous shuttle
was used.
Motak et al. (2017) found that 55% of the variance of intention to use an autonomous shuttle was
accounted for by perceived usefulness, social influence, perceived pleasure, and prior experience.
Each of these factors can be classified into six categories: socio-demographics, travel behaviour,
personality, performance and effort expectancy, exposure to autonomous vehicles and symbolic-
affective system evaluation. They will be presented below and summarized in Erreur ! Source du
renvoi introuvable..
3.2.2.1 Socio-demographic factors
Several studies have measured the effects of socio-demographic variables such as age, gender,
education level and income, on acceptance of APTVs.
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
The effect of gender on acceptability and acceptance is unclear. Several studies have found that men
are more willing to use an autonomous bus (Dong et al., 2017; S. R. Winter et al., 2018). They are also
seen to be more prepared to use APTVs in general (Acheampong & Cugurullo, 2019), to choose an
autonomous shuttle over a traditional vehicle (Alessandrini, Delle Site, Gatta, et al., 2016; Alessandrini
et al., 2014; Wien, 2019; K. Winter et al., 2019), to use an autonomous bus with a high level of
automation (Roche-Cerasi, 2019) and have more trust in autonomous shuttles than women (Dekker,
2017). In addition, while parents are globally unwilling to let their children use a driverless school bus
in the United States, mothers are less likely to accept this than fathers (Anania et al., 2018). Men are
also less afraid of other passengers on autonomous vehicles than women, but no significant difference
has been found on concerns about traffic safety or managing an emergency (Salonen, 2018). Gender
was found to have a moderating role on several factors: the effects of perceived ease of use of an
autonomous shuttle on its perceived usefulness were found to be greater for females than for males.
The effects of perceived usefulness on attitude were found to be greater for males than for females,
and the effects of trust on attitude were found to be significant only for females (Chen, 2019). Women
are less likely to think that APTVs are useful, have more concerns about them, and subjective norms
and ecological values moderate their intention to use APTVs less (Acheampong & Cugurullo, 2019).
Finally, people might be more willing to use an autonomous bus than to let their partner or their child
use it, and this applies more to women than to men (S. R. Winter et al., 2018). However, other studies
did not find significant differences between men’s and women’s willingness to use an autonomous
shuttle (Madigan et al., 2017; Nordhoff et al., 2018, 2017), or APTVs in general (Pakusch & Bossauer,
2017), and there is also no significant difference between them for performance expectancy, effort
expectancy, and social influence (Nordhoff et al., 2017). No gender effect was found on the intention
to use public transport more if autonomous shuttles provided mobility services between public
transport and car parks, the workplace and residential areas (Roche-Cerasi, 2019).
The effect of age on acceptance is not consistent across the literature. Several studies found no
significant age effect on willingness to use an autonomous shuttle (Kostorz et al., 2019; Madigan et al.,
2017, 2016; Motak et al., 2017), or an APTV (Pakusch & Bossauer, 2017), on the probability of choosing
an autonomous shuttle over another means of transport (Alessandrini, Delle Site, Gatta, et al., 2016;
Wien, 2019), on feelings of safety onboard the vehicle, traffic safety or emergency management
(Salonen, 2018) or on trust in autonomous shuttles (Dekker, 2017). Age was not found to have any
effect on intention to use public transport more when autonomous shuttles provided mobility services
between public transport and car parks, or the workplace and residential areas. Younger people
appeared to be more willing to use autonomous buses with high levels of automation (Roche-Cerasi,
2019). Other studies also showed that acceptance was higher in younger people. A negative correlation
between age and a positive attitude towards technology, intention to use APTVs and the perceived
benefits of APTVs has been demonstrated (Acheampong & Cugurullo, 2019). Participants aged 18-35
were found to be more willing to use an autonomous bus than those aged 45 years or more (Dong et
al., 2017). 42% of students surveyed were prepared to use a fee-based APTV service, compared to 20%
of retired people surveyed (Hinderer et al., 2018). In addition, regular users of an autonomous shuttle
were found to be younger than non-users (Portouli et al., 2017), and perceived ease of use was found
to be higher in younger participants than in older ones (Nordhoff et al., 2017). However, in one study,
acceptance of an autonomous shuttle was found to be higher in older than in younger participants,
although the former viewed the autonomous shuttle as less efficient than their current mode of
transport (Nordhoff et al., 2018). Another study showed that social influence was more important for
older participants (Nordhoff et al., 2017). Age also has a moderating influence on some factors. The
effect of perceived ease of use of an autonomous shuttle on attitude was seen to be greater in
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
participants over 40, whereas the effect of trust on attitude was significant only in participants of 40
and under (Chen, 2019).
A high education level was associated positively with a preference for autonomous shuttles over
traditional ones in three out of twelve cities surveyed (Alessandrini, Delle Site, Gatta, et al., 2016;
Alessandrini et al., 2015, 2014). In these three cities, implementation of autonomous shuttles was
planned in city centers. An effect of education level was found on willingness to use an autonomous
bus (Roche-Cerasi, 2019) on intention to use an APTV, on perceived usefulness of APTVs and perceived
ease of use (Acheampong & Cugurullo, 2019). However, no effect of education appeared either on
feelings of traffic safety, on-vehicle security and emergency management (Salonen, 2018) or on trust
in autonomous shuttles (Dekker, 2017). No effect of education was found between regular users of
autonomous shuttles and participants who never used this means of transport (Portouli et al., 2017).
Regarding the place of residence, people living in India were more willing to let their children use a
driverless school bus than US residents (Anania et al., 2018). There was no difference in willingness to
use an autonomous shuttle between residents and visitors to La Rochelle (France) and residents and
visitors to Lausanne (Switzerland; Madigan et al., 2016). People living in highly populated areas are
more willing to use highly automated buses (Roche-Cerasi, 2019). Intention to use an autonomous
shuttle did not differ between Germans living in rural areas and Germans living in urban areas (Kostorz
et al., 2019). However, American participants stated that they were more willing to use an autonomous
bus in the USA than in Russia, China, India, Nigeria, Indonesia or Brazil (S. R. Winter et al., 2018). Trust
in, and willingness to use, an autonomous shuttle was found to be greater in participants living in
regions where autonomous shuttle services had been implemented than in regions where no
autonomous shuttles were in operation (Dekker, 2017). However, participants working on a German
campus rated an autonomous shuttle as less efficient than their current means of transport than
participants who did not work on the campus (Nordhoff et al., 2018).
Income was not found to have an effect on preference for autonomous shuttles over traditional
shuttles (Alessandrini, Delle Site, Gatta, et al., 2016), on the intention to use an autonomous shuttle
(Kostorz et al., 2019), on feelings about traffic safety, on-vehicle security and emergency management
(Salonen, 2018) or on trust in autonomous shuttles (Dekker, 2017). Another study stated that a higher
income increases willingness to use an autonomous bus, but this difference exists only between higher
and lower incomes, and only when knowledge about autonomous vehicles is not controlled (Dong et
al., 2017).
Employment was not found to have an effect on preference for autonomous shuttles over traditional
ones (Alessandrini, Delle Site, Gatta, et al., 2016) or on fears about traffic safety and emergency
management (Salonen, 2018). However, students were found to be more regular autonomous shuttle
users than employees, or unemployed and retired people (Portouli et al., 2017). This can also be
attributed to an age effect.
3.2.2.2 Travel behaviour factors
A number of studies have assessed the effects of travel behaviour, such as travel habits, purpose of
travel and weather, mobility difficulties and attitudes towards using public transport.
Regarding travel habits, K. Winter et al. (2019) showed that people who use public transport once a
month or more are more willing to use an autonomous shuttle instead of a traditional bus, than people
who use public transport less frequently. Another study states that car users and public transport users
might be more willing to change their travel habits to using autonomous transport for journeys to
work, than pedestrians and bicycle users (Földes et al., 2018). According to a study conducted by Motak
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
et al. (2017), walking, the belief that public transport comes with too many constraints and knowing
about autonomous technology all tend to explain intention to use an autonomous shuttle. Kostorz et
al. (2019) concluded that bicycle users, public transport users and people using at least three different
means of transport per week were more willing to use an autonomous shuttle than drivers. They also
showed a positive association between feeling at ease in a car and the intention to use an autonomous
shuttle. However, other studies do not reveal any effect of an individual’s current use of a car or public
transport on their willingness to use APTVs (Pakusch & Bossauer, 2017). Nor has any effect of
frequency of public transport use (Wien, 2019), or frequency of bus use been observed on willingness
to use APTVs (Dong et al., 2017). In addition, no association has emerged between public transport
use and trust in autonomous shuttles (Dekker, 2017). Moreover, neither possession of a monthly public
transport pass nor access to a car had any effect on preference for autonomous shuttles over manually-
operated shuttles (Alessandrini, Delle Site, Gatta, et al., 2016). Finally, people with the most flexible
travel habits (for example car drivers) preferred on-demand autonomous vehicles to autonomous
public transport with fixed schedules (Földes et al., 2018).
Studies have established that purpose of travel and the weather have an impact on acceptance.
Autonomous transport with fixed schedules appears to be better accepted for fixed travel purposes
(work, education) than for flexible travel purposes (for example leisure; Földes et al., 2018). However,
in another study, 56% of respondents stated that they were willing to use an autonomous shuttle for
leisure trips, and only 41% for business trips (Kostorz et al., 2019). In conditions of bad weather, people
would be more willing to use an autonomous shuttle rather than to walk or hire a bicycle (Nordhoff,
de Winter, et al., 2019; Wicki et al., 2019).
The presence or absence of mobility difficulties can also have an effect on acceptance. Faced with the
choice of an autonomous shuttle, a rented bicycle or walking, the ability to walk unaided and without
stopping for a distance of 200 m and to use a bicycle, increases the probability of choosing the most
useful means of transport in terms of cost and travel time (Wicki et al., 2019). This study also showed
that the presence of mobility difficulties increases the probability of choosing an autonomous shuttle
out of the same three means of transport. Temporary disability (Nordhoff, de Winter, et al., 2019),
walking problems, the after-effects of surgery and the need to carry luggage (Monéger, 2018) all
increased the use of autonomous shuttles in the context of a hospital campus. In addition, people with
impaired mobility seem to have a greater preference for an on-board supervisor than people with no
disabilities (Földes et al., 2018).
In addition, a positive attitude towards public transport was found to be associated with a willingness
to use APTVs (Acheampong & Cugurullo, 2019), in particular, autonomous shuttles (Kostorz et al.,
2019).
3.2.2.3 Personality factors
Interest in technology, trust in autonomous vehicle, ecological values, attitude towards autonomous
shuttles, behavioural control and the need for control are some of the personality factors which
feature in studies on APTV acceptance.
Numerous studies have observed that interest in technology is a factor of acceptance. Participants
who are more positive about technology are more willing to try an autonomous vehicle (Földes et al.,
2018), to choose an autonomous shuttle over a traditional bus (Wien, 2019; K. Winter et al., 2019) or
to choose an autonomous shuttle instead of walking or renting a bicycle (Wicki et al., 2019). However,
competence in technology or the feeling of having a high level of control over technology (i.e. a
person’s belief in their own ability to use technology) does not seem to have an effect on the choice
between an autonomous shuttle and walking or renting a bicycle (Wicki et al., 2019). Confidence in
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
technology also influences intention to use autonomous shuttles (Motak et al., 2017). Finally, a
significant association between attraction to innovation and perceived ease of use of autonomous
shuttles has been observed, but this is not the case for perceived utility (Herrenkind et al., 2019).
A high level of trust in autonomous vehicles has been found to be a factor in the choice of an
autonomous shuttle over a traditional bus (Wien, 2019; K. Winter et al., 2019) or other means of
transport (Dekker, 2017). Herrenkind et al. (2019) also revealed a positive association between trust
in autonomous shuttles and intention to use this type of vehicle. Attitudes towards technology have
been found to be positively associated with the perceived usefulness of APTVs, and perceived
behavioural control. These attitudes have been negatively associated with concerns about using APTVs
(Acheampong & Cugurullo, 2019). However, Chen's study (2019) indicates that trust in autonomous
shuttles positively modifies attitude towards them but does not have a significant direct effect on
intention to use this type of transport. A positive attitude towards autonomous shuttles is associated
with intention to use (Chen, 2019; Kostorz et al., 2019).
According to one study (Motak et al., 2017), ecological values are not a predictor of intention to use
an autonomous shuttle, and they were not significantly associated with perceived usefulness in
another (Herrenkind et al., 2019). They were, however, found to be positively associated with the
perceived usefulness of APTVs and with intention to use APTVs in a third study (Acheampong &
Cugurullo, 2019).
Perceived behavioural control, that is an individual’s confidence in his/her own ability to use an
autonomous shuttle, is another personality factor which has been shown to have an effect on intention
to use (Motak et al., 2017). However, a negative association between the need to control and attitudes
towards autonomous shuttles has also been observed (Herrenkind et al., 2019).
3.2.2.4 Performance and effort expectancy factors
Performance expectancy of APTVs is an important factor in their acceptance. Nordhoff et al. (2017)
revealed that both performance expectancy of an autonomous shuttle and the fact that autonomous
shuttles constitute an important part of the public transport system foster intention to use APTVs for
daily travel. Performance expectancy has also been found to be associated with positive attitudes
towards APTVs (Chen, 2019; Herrenkind et al., 2019) and intention to use this type of vehicle
(Acheampong & Cugurullo, 2019; Monéger, 2018; Motak et al., 2017). The perception that
autonomous shuttles are useful and more efficient than current transport modes also increases
intention to use them (Madigan et al., 2017, 2016). Attitudes towards autonomous shuttles and their
perceived utility depend on the perception that they have more advantages than other modes of
transport (Herrenkind et al., 2019; Nordhoff, de Winter, et al., 2019). Participants in the study by
Nordhoff, de Winter, et al. (2019) indicated that outwith the context of the experiment (in normal
circumstances), they would have made the journey on foot. This decreased acceptance and lowered
their intention to use the shuttle.
Effort expectancy has been found to be an acceptance factor in several studies. When expectancy that
the effort involved in using an autonomous shuttle is low, positive attitude towards this means of
transport increases, as does its perceived usefulness (Chen, 2019). Herrenkind et al. (2019) also
observed that effort expectancy had an effect on attitude towards using APTVs. This was, however,
less pronounced than the effect of performance expectancy. An association has been demonstrated
between APTV effort expectancy, attitude, performance expectancy and intention to use APTVs
(Acheampong & Cugurullo, 2019). Low effort expectancy (Kostorz et al., 2019; Monéger, 2018) and
ease of learning how to use an autonomous shuttle (Madigan et al., 2016) have been associated with
a greater intention to use APTVs. When effort expectancy for using an autonomous shuttle is lower
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
than for other current means of transport, willingness to use APTVs for everyday journeys increases
(Nordhoff et al., 2017). However, Madigan et al. (2017) did not find any significant effect of low effort
expectancy (described by the authors as human-machine interfaces which are clear and easily-
understandable on the shuttle), perceived ease of use, and ease of learning how to use an autonomous
shuttle) on intention to use the shuttle.
3.2.2.5 Factors of exposure to autonomous vehicles
Level of knowledge and experience of autonomous vehicles can have an impact on acceptance of
APTVs. For example, previous experience of autonomous vehicles raised willingness to use APTVs in
the future (Pakusch & Bossauer, 2017), enhanced the feeling that autonomous shuttles are safe
(Salonen & Haavisto, 2019) and increased the likelihood of choosing an autonomous shuttle over
several other means of transport (Wicki et al., 2019). Previous experience of APTVs, even on guided
tracks, can have a positive impact on feelings of safety prior to traveling by autonomous shuttle (Eden
et al., 2017). One study indicated that frequent users of autonomous shuttles have a more positive
attitude towards autonomous vehicles than non-users. They also have a greater preference for full
automation, and are more likely to think that autonomous shuttles are safer than manually-operated
vehicles than non-users (Portouli et al., 2017). Perception of ease of use of autonomous shuttles was
greater in participants who had previous experience of this mode of transport than in non-users
(Dekker, 2017), and their intention to use an autonomous shuttle was greater (Motak et al., 2017).
One study showed that traveling on an autonomous shuttle improved perceived ease of use,
confidence in, and attitude towards the vehicle, but did not modify its perceived usefulness or
intention to use (Wintersberger et al., 2018). However, in another study (Monéger, 2018), willingness
to use APTVs, perception of control and of the usefulness of the vehicle increased after traveling on an
autonomous shuttle. When people were offered the opportunity of trying an APTV, acceptance and
use were both seen to rise (Nordhoff, de Winter, et al., 2019). However, the number of times
participants used or interacted with autonomous shuttles was not seen to have any effect on their
degree of willingness to use this type of vehicle (Madigan et al., 2017, 2016). Prior knowledge of
autonomous vehicles also increases the probability of being willing to use an autonomous bus (Dong
et al., 2017; Kostorz et al., 2019). People who had never heard of autonomous shuttles were more
concerned about the interaction of these vehicles with other road-users, and perceived APTVs as being
more difficult to understand, than people with previous experience (ranging from one trial to regular
weekly use) of an autonomous shuttle (Dekker, 2017). However, in the same study, exposure was not
seen to have any significant effect on performance, security (in terms of data-hacking and fears about
other passengers), trust in APTVs or preference for this means of transport over another. Knowing
that an autonomous shuttle had caused an accident prior to trying an APTV has a negative impact on
willingness to use this type of vehicle (Salonen & Haavisto, 2019) and raises concerns about safety
(Eden et al., 2017). Media coverage of autonomous vehicles can improve familiarity and consequently,
feelings of confidence (Salonen & Haavisto, 2019). However, it can also give rise to unrealistic
expectations, therefore decreasing positive perception of an autonomous shuttle tried subsequently
(Nordhoff, de Winter, et al., 2019).
Exposure does therefore have an effect on acceptance, and it depends on whether the knowledge of,
and the experience in relation to the APTV was positive or negative.
3.2.2.6 Symbolic-affective factors
Social influence and perceived pleasure are symbolic-affective factors which can play a role in the
acceptance of autonomous vehicles. Studies on social influence, have indicated that an individual’s
intention to use an autonomous shuttle is affected by the opinion of significant relatives (Madigan et
al., 2017, 2016), or of people living in the same region (Motak et al., 2017). Intention to use an APTV is
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
also associated with significant others adopting the same behaviour (Acheampong & Cugurullo, 2019).
In this context, a study conducted by Herrenkind et al. (2019) indicates that the reputation of
autonomous shuttles has an impact on their perceived utility, and that social influence is associated
with the perceived utility of the shuttles, attitude towards them and intention to use them. Nordhoff
et al. (2017) showed that use of an autonomous shuttle by significant relatives had an effect on
willingness to use shuttles in a rural context, but not in an urban context. Perceived pleasure, also
referred to as hedonic motivation, was positively associated with the intention to use an autonomous
shuttle (Madigan et al., 2017; Motak et al., 2017), with perception of usefulness and a positive attitude
to autonomous shuttles (Herrenkind et al., 2019), and with positive attitude to autonomous shuttles
and the intention to use them (Chen, 2019).
Table 2. Factors of acceptance, acceptability or usage related to individual factors and the number of studies that investigated
them (n)
Themes
Factors
n
Socio-demographics
Gender
20
Age
19
Education
7
Place of residence or work place
7
Income
5
Employment
3
Travel behavior
Travel habits
10
Travel purpose and weather
4
Mobility difficulties
4
Attitude towards public transport
2
Personality
Technology interest
8
Trust in autonomous vehicles
8
Ecological values
3
Behavioural control
1
Need to control
1
Performance and effort
expectancy
Performance expectancy
11
Effort expectancy
8
Exposure to autonomous
vehicles
Previous experience
12
Previous knowledge
3
Awareness of an accident
2
Media coverage
2
Symbolic-affective system
evaluation
Social influence
6
Perceived pleasure
4
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
Table 3. overview of the studies selected in the present literature review
Reference
Vehicle
Methods
Participants
Exposure to autonomous
vehicle
Factors studied
Acheampong &
Cugurullo, 2019
Autonomous
vehicles
including APTV
Online survey (54
items; Likert scales)
507 adults living in the
Greater Dublin
Area of the Republic of
Ireland
Unspecified
Concerns
Age
Gender
Education
Attitude towards public
transport
Attitude towards environment
Interest in technology
Usefulness
Effort expectancy
Subjective Norm
Alessandrini, Delle
Site, Stam, et al.,
2016; Alessandrini
et al., 2015;
Alessandrini, Delle
Site, Gatta, et al.,
2016; Alessandrini
et al., 2014
Autonomous
shuttle
Stated preference
questionnaire (face-to-
face, online, or
telephone)
3326 potential users of
autonomous shuttles in
12 European cities (167-
742/city)
For the study of
Alessandrini, Delle Site,
Stam, et al. (2016): sub-
sample of 1714
potential users of
autonomous shuttles in
4 cities
No exposure (study conducted
before implementation of
autonomous shuttles)
Waiting time
Travel time
Location context
Fares
Age
Gender
Education
Income
Employment
Travel habits
Anania et al.,
2018
Autonomous
school bus
Online questionnaire
(7 items; Likert scales
+ an emotion
scale in study 2)
Study 1: 50 participants
(25 females) living in the
United States (within-
subjects design); Study
2: 610 participants (274
females) living in the
United States or in India
(between-subjects
Unspecified (probably no
exposure)
Gender
Place of residence
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
design). Convenience
sampling using
Amazon’s® Mechanical
Turk®
Chen, 2019
Autonomous
shuttle
Self-administered
questionnaire on
paper (21 items in
Likert scale +
questions about
respondent’s
characteristics)
Random selection of 700
questionnaires /1498
correctly completed /
1658 completed by
passengers of an
autonomous shuttle.
Convenience sampling
Data collection after a trial on
an autonomous shuttle in a
scooter-dominant urban
context
Age
Gender
Trust in autonomous vehicles
Usefulness
Effort perceived
Attitude towards autonomous
shuttles
Perceived pleasure
Dekker, 2017
Autonomous
shuttle
Online questionnaire
(12 Likert scales items
+ 6 state preference
questions + 9
questions about
respondent’s
characteristics; 5-10
min)
195 correctly completed
questionnaires/198
questionnaires
completed by
participants working in
three business areas
(including one area
served by an
autonomous shuttle).
Sample quite
representative of the
Dutch labour force, but
with a greater
proportion of men and a
higher income and
educational level
Exposure measured: 13.8% of
participants used the
autonomous shuttle weekly,
21.5% used it once or several
times, 44.6% had seen or read
something about it, 20% had
no experience of it
Waiting time
Travel time
Fares
Location context
Flexibility
Supervision
Age
Gender
Education
Place of residence
Income
Travel habits
Trust in autonomous vehicles
Previous experience of
autonomous vehicle
Dong et al., 2017
Autonomous
bus
Online state
preference
questionnaire (Likert
scales items +
questions explaining
891 correctly completed
questionnaires/930
respondents/3350
University of
Pennsylvania employees
Effect of prior knowledge of
autonomous vehicles
measured (sample proportion
not indicated)
Concerns: road-safety,
incivilities, absence of driver
Supervision
Age
Gender
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
previous responses +
questions about
respondent’s
characteristics)
who participated in a
pre-tax transit
commuter program
contacted. Compared to
transit users: under-
representation of 18-24-
olds and users 65 years
and above; and higher
income
Income
Travel habits
Prior knowledge of
autonomous vehicle
Eden et al., 2017
Autonomous
shuttle
Collective semi-
structured interviews
17 autonomous shuttle
passengers in the old
town of Sion
(Switzerland). Sample
characteristics and
recruitment methods
unspecified
Data collection before and
after a trial on an autonomous
shuttle
Schedules
Location context
Vehicle speed
Braking behaviour
Seat belt
Feeling of safety
Windows
Seat
Noise
Vehicle size
Previous exposure to other
APTVs
Knowledge of an accident
caused by an autonomous
vehicle
Fernández
Medina & Jenkins,
2017
Autonomous
shuttle
Two individual semi-
structured interviews
(2x60 min)
33 participants recruited
from people interested
in trying an autonomous
shuttle but who had no
professional interest in
autonomous
technology, mainly
living, working or
commuting through
Data collection before and
after a trial on an autonomous
shuttle
Concerns: technology failure,
absence of driver
Vehicle speed
Braking behaviour
Road-facing seats
Noise
Supervision
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
Greenwich, London.
Various ages, genders
and driving status
Földes et al., 2018
Autonomous
taxis and
shuttles with
on-demand
and fixed
services
Online questionnaire
with multiple choice
and Likert-scale
questions
(respondent’s
characteristics,
mobility habits and
expectations about
autonomous vehicles)
510 Hungarian
participants. Sample not
representative of the
population
Usage cases not available in
the region studied; 1/3 of the
respondents had heard about
autonomous vehicles
Waiting time
Fares
Travel information
Internet access
Travel habits
Travel purpose
Mobility difficulties
Interest in technology
Fröhlich et al.,
2019
Autonomous
shuttle
Study 1: paper
questionnaire
(illustration of
different designs of
dynamic information
displays, 2 open
questions, 2 Likert-
scale questions; 10
min). Study 2:
questionnaire after a
simulated shuttle ride
(2 Likert-scale
questions; 10 min)
Study 1: 56 participants,
without prior experience
of a shuttle, aged 15-55.
Study 2: 77 participants,
aged 17-90.
Participants in the 2
studies recruited during
a shuttle demonstration
on the site of a transport
research conference
Study 1: data collection after a
shuttle trial
Study 2: data collection after
simulated shuttle trial
Information about
autonomous functioning
Herrenkind et al.,
2019
Autonomous
shuttle
Study 1: phone
individual semi-
directed interviews (35
min)
Study 2: online and
paper survey
Study 1: 15 automotive
industry experts
(snowball sampling)
Study 2: 268 participants
recruited in a German
city, sample varied in
terms of gender, age,
income, place of
Study 1: participants with
professional experience of at
least 3 years in future mobility.
Study 2: participants recruited
after a shuttle trial
Fares
Concerns: personal data
protection
Trust in autonomous vehicle
Ecological values
Capacity for personal
innovation
Need to control
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
residence, familiarity
with public transport
(57% used this at least a
few times a month)
Usefulness
Effort expectancy
Social influence
Perceived pleasure
Hinderer et al.,
2018
APTV
Paper questionnaire
(17 questions): age
group (pupil/students,
employees, retired
people), distance to
the nearest bus stop,
satisfaction with
available mobility
service (6 Likert-scale
questions), attitudes
towards APTV (8
Likert-scale questions),
APTV requirements (6
questions) and
additional comment
sections)
178 participants living in
the village of
Buechenbronn
(suburban area)
recruited outside the
polling station during a
parliamentary election.
Sample composed of
2.87% of the village
population
Unspecified
Waiting time
Fares
Location context
Access to the vehicle with a
bicycle or a dog
Age
Performance expectancy
Kostorz et al.,
2019
Autonomous
shuttle
Online questionnaire
including Likert-scale
questions (15
minutes):
respondent’s
characteristics,
mobility habits and
attitudes, introduction
to autonomous
shuttles, attitudes
towards autonomous
shuttle, usage and
900 correctly completed
questionnaires out of
1078 adult Germans
surveyed.
Representative sample
of the German
population (age, gender,
rural-urban
distributions)
Prior knowledge of
autonomous vehicles
measured. No experience of
autonomous shuttles,
however, the majority of
participants knew of them
Age
Place
Income
Travel habits
Travel purpose
Attitude towards public
transport
interest in technology
Attitude towards autonomous
shuttles
Effort expectancy
Prior knowledge of APTVs
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
attitudes towards
technology
López-Lambas &
Alonso, 2019
Autonomous
vehicles in
general and
autonomous
bus in
particular
Two focus groups
(1h30-2h)
8 participants per focus
group, recruited in
Madrid and Malaga. Age
and gender diversity
Unspecified
Concerns: incivilities,
technology failures, absence
of driver
Supervision
Madigan et al.,
2016
Autonomous
shuttle
Questionnaire on
tablet (8-10 min), self-
administered on site:
respondent’s
characteristics,
mobility habits,
exposure to
autonomous shuttle,
attitude towards
technology and
attitudes towards
autonomous shuttles
349 participants
residents or visitors of
La Rochelle (France) and
Lausanne (Switzerland),
61.6% of males
Participants had already
interacted with the shuttle
Age
Gender
Place of residence
Usefulness
Effort expectancy
Previous experience
Social influence
Madigan et al.,
2017
Autonomous
shuttle
Questionnaire on
tablet (8-10 min), self-
administered on site:
respondent’s
characteristics and 20
Likert-scale questions
performance
expectancy, effort
expectancy, social
influence, facilitating
condition, hedonic
motivation and
315 participants aged 9-
65, recruited in Trikala
(Greece), 54.6% of
males
Participants who had used a
shuttle at least once
Integration into the public
transport offer
Age
Gender
Usefulness
Expected effort
Previous experience
Social influence
Pleasure
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
intention to use the
autonomous shuttle.
Motak et al.,
2017; Monéger,
2018
Autonomous
shuttle
Pilot study: 4 focus
groups for the creation
of the study
questionnaire (1h45).
Study 1: questionnaire
(25-30 min, around
200 items): personal
values,
sociodemographic
characteristics and
mobility habits,
introduction to
autonomous shuttle,
and perception and
attitudes towards
autonomous shuttle
Study 2: on-site
questionnaire,
abbreviated version
from the previous one
Additional study from
Monéger, 2018:
experiment on shuttle:
measure of
acceptance in different
conditions (with and
without a manual
horn; with or without
a humanoid voice)
Pilot study: 23
occasional visitors to a
hospital campus aged
19-67.
Study 1: 370 students
aged 18-25.
Study 2: occasional
visitors to the hospital
campus (108
autonomous shuttle
non-users of aged 16-87,
and 54 first-time users
aged 28-76)
Pilot study and study 1:
conducted before the
implementation of the
autonomous shuttle
Study 2: data gathering prior
to implementation of the
autonomous shuttle for 108
respondents, and after a trial
on autonomous shuttle for 54
respondents
Additional study: data
collection after a trial on
autonomous shuttle
Concerns: road-safety
Manual control means
Supervision
Humanoid voice
Age
Travel habits
Mobility difficulties
Technology interest
Ecological values
Behavioural control
Usefulness
Expected effort
Previous experience
Social influence
Perceived pleasure
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
Nordhoff et al.,
2018
Autonomous
shuttle
Online questionnaire
(68 items): respondent
characteristics and
impressions about the
autonomous shuttle
and the services,
attitudinal questions
and acceptance
questions
384 participants
recruited online, 274
included in the analyses
Participants had used an
autonomous shuttle
Vehicle speed
Supervision
Vehicle size
Age
Gender
Work location
Effort perceived
Nordhoff, de
Winter, et al.,
2019
Autonomous
shuttle
Face-to-face or phone
(2/30) semi-directed
interview (50 min)
about acceptance
factors of the
autonomous shuttle
30 participants recruited
from among former
participants in previous
studies, students or
campus employees and
people who expressed
interest in participating
in the study
Participants used the
autonomous shuttle just
before data collection
Location context
Travel information
Flexibility
Reliability
Vehicle speed
Braking behaviour
Stop button
Supervision
Manual control means
Automation level
Large windows
Free internet access
Comfortable seats
Internal appearance
Air conditioning
Vehicle size
Obstacle-free access
Weather
Mobility difficulties
Usefulness
Previous experience
Vehicle exposure
Media coverage
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
Nordhoff et al.,
2017
Autonomous
shuttle
Self-administered
questionnaire on
tablet (37 items):
intention to use an
autonomous shuttle,
perceived usefulness,
ease of use, social
influence, trust,
ecological norms,
pleasure; respondent’s
characteristics
326 participants
recruited on an
autonomous shuttle
demonstration site, on a
campus (31.9% male,
77.1% campus
employees)
Data collection after a trial on
the autonomous shuttle; first
ever trial for 95.7% of
participants
Integration into public
transport system
Age
Gender
Effort expectancy
Usefulness
Social influence
Pakusch &
Bossauer, 2017
APTV
Online questionnaire:
presentation of APTV,
mobility habits,
experience of
autonomous vehicles
and attitude towards
APTV (Likert scales and
open questions),
respondent’s
characteristics
201 participants (18-81
years, 49.3% female)
recruited online, mainly
students)
91% of participants already
knew about autonomous
vehicles, 37.1% had already
tried an autonomous vehicle
(train, tram, metro, car or
shuttle)
Age
Gender
Travel habits
Previous experience
Papadima et al.,
2020
Autonomous
shuttle
Study 1: online
questionnaire (21
items): respondents
characteristics,
exposure to
autonomous shuttle,
impressions of the
pilot implantation of
autonomous shuttle
Study 2: online
conjoint analysis;
attributes: information
Trikala citizens recruited
online
Study 1: 158 participants
(48.7% female, 70.3%
permanent Trikala
citizens)
Study 2: 43 participants
Study 1: 78% of participants
had never tried an
autonomous shuttle; 12% had
tried one; 9.5% used one daily.
Frequency
Fares
Travel information
Supervision
Access and characteristics of
stops
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
provision mode,
frequency of service,
stop facilities, walking
distance from bus
stop, supervision, fares
Piao et al., 2016
Autonomous
vehicles,
including
autonomous
shuttle
Questionnaire
administered online
and by phone (28
items): knowledge of
autonomous vehicles,
attractiveness and
concerns about
autonomous shuttles,
taxis and cars, and
attitude towards
owning and sharing
autonomous cars
Online questionnaire:
148 participants living
near an autonomous
shuttle demonstration.
Phone questionnaire:
352 participants living in
the La Rochelle area.
After resampling to
correspond to local
demography in terms of
age, gender and
education: 425
participants (53.6%
female)
Participants living, working or
studying in a city with an
autonomous shuttle
demonstration, 87% of them
had heard about autonomous
vehicles, and a minority (rate
unclear) had already tried an
autonomous shuttle
Fares
Concerns: incivilities, night
service
Supervision
Portouli et al.,
2017
Autonomous
shuttle
Study 1: face-to-face
questionnaire:
respondent’s
characteristics,
previous exposure to
the autonomous
shuttle, satisfaction
with it, usefulness,
safety perceived, and
willingness to use it
and pay for it
Study 2: paper
questionnaire: attitude
towards autonomous
Study 1: 200
autonomous shuttle
passengers (105
females)
Study 2: 519 Trikala
citizens (urban and
suburban areas)
Study 1: participants were
autonomous users; 40% had
used once, 42.5% twice, 17%
3-5 times and 1 person more
than 5 times
Study 2: participants were
aware of an autonomous
shuttle demonstration in
Trikala; 318 participants had
never used the autonomous
shuttle, 105 were regular users
Fares
Supervision
Age
Education
Employment
Previous experience
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
vehicles,
attractiveness,
concerns and
preferences
Ramseyer et al.,
2018
Autonomous
shuttle
Individual interviews.
Before an autonomous
ride: concerns,
anticipated
advantages, and
advance description of
the ride
After the ride:
description of the ride,
positive and negative
impressions, things to
be changed, changes
in previous concerns
and intention to use
autonomous vehicles
21 students in risk
management from a
university in Switzerland
Data collection before and
after a trial on an autonomous
shuttle (1st exposure to an
autonomous vehicle)
Waiting time
Vehicle speed
Braking behaviour
Supervision
Manual control means
Windows
Seating configuration
Roche-Cerasi,
2019
Autonomous
shuttle (+ 1
question about
autonomous
bus)
Online questionnaire
(27 questions):
mobility habits,
transport priorities,
autonomous shuttle
experience and their
usefulness, concerns
and trust and
respondents’
characteristics
1479 members of the
car federation of
Norway (19-98 years,
80.7% male). Sample
unrepresentative of the
Norwegian population
(in terms of age, gender,
income, travel habits).
91.8% of respondents had
heard of autonomous shuttles;
1.4% had tried one
Location context
Concerns
Automation level
Age
Gender
Education
Place of residence
Salonen, 2018
Autonomous
shuttle
Face-to-face
questionnaire:
perceptions of traffic
safety, on-vehicle
197 autonomous shuttle
passengers during an
important design
exhibition in Finland
Data collection after a trial on
an autonomous shuttle
Age
Gender
Education
Income
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
security and
emergency
management on an
autonomous shuttle
compared to a bus
travelling in the same
conditions, and
respondent’s
characteristics
(61.9% female;
discretionary sampling)
Employment
Salonen &
Haavisto, 2019
Autonomous
shuttle
Semi-structured
individual interview
(10-15 min): reaction
to the autonomous
shuttle, attitudes
towards it, social
factors and
passenger’s feelings
44 autonomous shuttle
passengers on a route
between a metro station
and a university in
Helsinki (45.5% females,
15-64 years, 50%
students)
Data collection after a trial in
autonomous shuttle
Frequency and schedules
Location context
Flexibility
Concerns: algorithm of
decision-making
Vehicle speed
Supervision
Previous experience
Knowledge of an accident
Media coverage
Stark et al., 2019
Three use
cases, including
autonomous
vehicle on a
traditional bus
route, and first
and last mile
service
Workshops including 3
focus groups and
individual interviews
about the needs,
requirements and
challenges of APTV
13-16 workshop
participants recruited
online: public transport
users, local authorities
and transport operators
Unspecified
Waiting time
Fares
Integration with other
transport means and
intramodality
Travel information
Reliability
Location context
Flexibility
Concerns: personal data
protection, night service
Vehicle speed
Countermeasures: child seats
safety seats, registration of
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
passengers, video and audio
surveillance, respect of
security standards
Vehicle size
Obstacle-free access
Gender
Vöge &
McDonald, 2003
APTV and
personal
autonomous
automobile
23 focus groups and
individual interviews
Total N unspecified
(>257). Potential users,
non-users, public
decision makers, public
and private operators in
seven countries (such as
France, Israel). 10-12
participants /focus
group; 27 participants
for individual interviews
Unspecified
Waiting time
Fares
Location context
Integration with other
transport means
Travel information
Flexibility
Vehicle speed
Countermeasures: seat belts,
prohibition of standing,
communication means,
autonomous medical
emergency management
Manual control means
Information about
autonomous functioning
Free internet access
Vehicle appearance
Vehicle size
Obstacle-free access
Overloading prevented
Cleanliness
Wicki et al., 2019
Autonomous
shuttle
Online state
preference
questionnaire (13 min)
with 3 alternatives:
autonomous shuttle,
879 respondents out of
1080 adult residents of
the Canton of
Schaffhausen invited to
participate. Analysis on
Respondents already knew
about an autonomous shuttle
test
Waiting time
Travel time
Fares
Occupancy rate
Weather
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
walking and rented
bike and respondent’s
characteristics
data of the 761
respondents who knew
about an autonomous
shuttle test in the
Canton
Mobility difficulties
Interest in technology
Previous experience
Wien, 2019; K.
Winter et al.,
2019
Autonomous
shuttle
Online state
preference
questionnaire with 3
alternatives:
autonomous shuttle
and regular bus and an
opt-out alternative,
respondent’s
characteristics
282 questionnaires
completed out of 305
citizens and employees
surveyed in two
municipalities (Vaals,
Netherlands, and
Aachen, Germany)
where autonomous
shuttles were to be
implemented.
Respondents used
public transport at least
yearly (48.9% female).
Sample representative
of public transport users
in the Netherlands
No previous exposure (data
collection before
implementation of an
autonomous shuttle trial)
Waiting time
Travel time
Fares
Flexibility
Supervision
Age
Gender
Travel habits
Interest in technology
Trust in autonomous vehicles
S. R. Winter et al.,
2018
Autonomous
bus
Online questionnaire
with two scenarios:
autonomous bus or
regular bus and a
willingness to ride
scale (study 1: within-
participants design;
study 2: mixed-
participants design)
Study 1: 510 American
participants (226
females)
Study 2: 571 American
participants (276
females). Convenience
sampling on Amazon
Mechanical Turk
Unspecified
Gender
Vehicle user (self or family
member)
Place of residence
Wintersberger et
al., 2018
Autonomous
shuttle
Face-to-face
questionnaire about
respondent’s
12 participants, aged
under 35, recruited on
the autonomous shuttle
Participants had no exposure
prior to the study; data
gathered before and after an
Travel duration
Vehicle speed
Previous experience
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-270 https://doi.org/10.1016/j.trf.2021.06.008
characteristics and
expectations and
individual semi-
directed interview
about opinions
pilot site in a Bavarian
city
autonomous shuttle trip and a
trip in a regular taxi
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
4 Discussion
The deployment of APTVs is relatively recent, and they exist mainly in the form of autonomous shuttles
as part of pilot experiments (The Aspen Institute Center for Urban Innovation, n.d.). The literature
review presented in this paper, which aims to contribute to the design and implantation of this new
mode of transport, so that it meets the needs of the greatest possible number of potential users,
provides a fairly exhaustive review of the factors of acceptability, acceptance and use of APTVs. In our
first section, we discuss the factors that are largely agreed upon in the literature. In a second section,
we look at factors which are the subject of controversy, and in a third section those that have been the
least studied or are the least well-documented.
In the literature, there is a consensus about the negative impact of users’ and potential users’ concerns
on the future usage of APTVs. These relate mainly to vehicle safety (fear of accidents), and to on-board
security (assaults and incivilities). Erratic and abrupt braking by the vehicle has also be found to have
a negative impact on future use of APTVs. Travelers who have experienced abrupt braking on an
autonomous shuttle may change their intention to use this type of vehicle in the future.
Countermeasures have been proposed to alleviate users’ concerns. Rules such as the prohibition of
standing when the vehicle is in motion could be imposed. Preventive equipment, such as seat belts,
child safety seats, video surveillance or a means of dealing with of emergencies (for example, a button
for emergency stops or to open the doors and a means of communication) could also be made
available. Future studies are required to further analyze the effect of these countermeasures on safety
and feelings of safety.
There is agreement across a number of studies on factors which increase willingness to use APTVs.
These factors relate mainly to the ways in which APTVs could improve mobility services. Potential users
estimate that they would save time and money, be more comfortable on-board and have good visibility
from the vehicle. Free internet access, comfortable and well oriented seats are also factors. Potential
users also require a means of compensating for the absence of a driver - for example, information
screens and easy, obstacle-free access to the vehicle. As for the location of APTV implementation,
normal urban traffic conditions are seen as less acceptable. Implementation in a more secure context,
for example on dedicated routes, on campus, or in areas with no public transport links, such as rural
areas, is seen as preferable. However, most of the studies conducted involved pilot implementations
of autonomous shuttles. These do not aim to respond to mobility needs, they are carried out with a
view to assessing and increasing technological maturity, or to provide a showcase.
Most of the personal factors which are consistently found to be positively associated with willingness
to use APTVs can be influenced by the vehicle’s characteristics or by the level of mobility service
offered. Trust in autonomous vehicles, users’ performance expectancy and effort expectancy, social
influence and perceived pleasure might therefore be greater when users or potential users interact
with APTVs which are secure, reliable, useful, efficient, comfortable, accessible, easy and pleasant to
use. In this perspective, exposure to an autonomous vehicle (through experience, word-of-mouth or
the media) can increase the likelihood of using an APTV on condition that the experience is positive.
Therefore, while it is important to establish contact between the public and autonomous vehicles in
order to improve their acceptance of APTVs, an unpleasant experience can have a negative and durable
impact on the public's attitude towards APTVs.
Divergent results highlighted in the present review may be explained by trade-offs between important
aspects. Low vehicle speed, for instance, can be perceived both as a marker of security, and a sign of
inefficiency. The presence of supervision, which can be reassuring for some users, can also be
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
perceived as evidence that the vehicle is not entirely reliable by others. Discrepancies surrounding
personal factors, in particular socio-demographic characteristics, also exist. Although male and
younger users and potential users appear to have a more positive attitude towards APTVs in some
studies, not all studies point in the same direction regarding the effects of gender, age, education level
and place of residence. In addition, inconsistences around ecological values could be related to the
fact that autonomous vehicles can be seen as being both ecological (since they are commonly
associated with electric vehicles), and as non-ecological (compared to walking or cycling). However,
these contradictory results could also be related to differences between studies in terms of
methodology (qualitative interview or online survey; involving a shuttle trial or not), nature and size of
study samples, usage contexts (campus, city center or rural environment) or vehicle considered
(shuttle, buses). In one study, for example, participants indicated that their positive perception of the
safety of an autonomous shuttle might change if the vehicle was larger (for example a bus), if there
was no supervisor, or if the journey took place on a real road and at normal speed (Eden et al., 2017).
Finally, a number of factors cited across studies should be investigated more thoroughly in future
research in order to assess their impact on acceptance of APTVs. These factors are the display of
information about autonomous functioning, vehicle appearance, air-conditioning, cleanliness,
prevention of vehicle overload, vehicle access with a bicycle or a dog, and some stop characteristics.
Similarly, relatively little research has been carried out on personal factors, such as attitudes towards
public transport, behavioural control and need for control.
Other studies are also required to analyze the needs, expectations and concerns of elderly people and
people with disabilities in greater detail. Although some of the studies included in the present review
evoke the needs and concerns expressed on this subject by respondents, APTV accessibility for people
with disabilities and the elderly does not seem to have been studied specifically (Tabattanon et al.,
2019).
To summarize, the main factors of acceptance of APTVs relate to the quality of the service on offer, as
is the case for every means of public transport. As research has shown, autonomous aspects seem to
matter less than the improvement of mobility services (Fernández Medina & Jenkins, 2017; Hinderer
et al., 2018). Nevertheless, the autonomous aspect of APTVs and the absence of a driver bring new
concerns. These concerns are about the vehicle’s total dependency on technology, poor braking
behaviour, safety and on-board security. Factors related to comfort and vehicle access appear to be
less central, but results on these may be due to the fact that samples studied are not always
representative, and do not include the profiles of all potential users. Elderly people and people with
disabilities, who are not explicitly included in the studies we reviewed, may have greater needs in
terms of accessibility. In addition, for both safety and acceptability issues, implementation of APTVs
which are unreliable and inefficient appears to compromise the future use of these vehicles. While
rail-bound autonomous public transport vehicles (subways, trains, trams) are now a full part of the
transport supply, and are preferred over non-rail autonomous public transport vehicles (Pakusch &
Bossauer, 2017), these new autonomous systems give rise to concerns, and raise questions about their
acceptability. This literature review offers ways of alleviating concerns and of encouraging the future
use of APTVs. It could serve as a guideline for designers, manufacturers and policy makers, and help
them to provide autonomous mobility services which correspond to the needs of users and potential
users.
One limitation of the present literature review was that the majority of the studies reviewed here
consisted of surveys conducted on respondents who had never used an APTV. Some of the findings are
therefore based on the projections of potential users rather than on the actual opinions of real users,
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
limiting their generalization. As it is the case for recent publications (Bernhard et al., 2020; Hilgarter &
Granig, 2020), it can be reasonably expected that as more and more APTVs are introduced, future
studies will focus more on individuals who have already tried one of these vehicles, or who even use
them for day to day travel. Future studies will go on to fine-tune the findings of our present review of
the literature.
4.1 Conclusion
A great deal remains to be done before APTVs which correspond completely to users’ needs can be
successfully implemented. Although many pilot experiments with autonomous shuttles have been
conducted, they have not yet managed to entirely convince all potential users. The latter continue to
express concerns about safety, security, usability, accessibility and comfort. This review of the
literature allows us to conclude that in order to improve acceptance of APTVs, users’ confidence in
them must increase. At this stage it is important not to expose the public to pilot implementations with
negative connotations, especially those involving bad braking behaviours and which do not meet
mobility needs. It is essential to propose secure, useful and comfortable autonomous systems if we
wish to encourage more wide-spread adherence to APTVs.
5 Funding
This literature review has been conducted within the framework of the STAR project funded by FUI
(Fonds Unique Interministériel) of the French government.
6 References
* References included in the literature review
*Acheampong, R. A., & Cugurullo, F. (2019). Capturing the behavioural determinants behind the
adoption of autonomous vehicles: Conceptual frameworks and measurement models to
predict public transport, sharing and ownership trends of self-driving cars. Transportation
Research Part F: Traffic Psychology and Behaviour, 62, 349-375.
*Alessandrini, A., Alfonsi, R., Delle Site, P., & Stam, D. (2014). Users’ preferences towards automated
road public transport: results from European surveys. Transportation Research Procedia, 3,
139-144.
*Alessandrini, A., Delle Site, P., Gatta, V., Marcucci, E., & Zhang, Q. (2015). Stated preference logit
analysis of users’ attitudes towards conventional and automated buses (No. 0215).
*Alessandrini, A., Delle Site, P., Gatta, V., Marcucci, E., & Zhang, Q. (2016). Investigating Users’
Attitudes Towards Conventional and Automated Buses. International Journal of Transport
Economics, 43(4), 413‑436. https://doi.org/10.19272/201606704001
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
*Alessandrini, A., Delle Site, P., Stam, D., Gatta, V., Marcucci, E., & Zhang, Q. (2016). Using repeated-
measurement stated preference data to investigate users’ attitudes towards automated buses
within major facilities. Advances in Intelligent Systems and Computing, 539, 189‑199.
https://doi.org/10.1007/978-3-319-48944-5_18
*Anania, E. C., Rice, S., Winter, S. R., Milner, M. N., Walters, N. W., & Pierce, M. (2018). Why people
are not willing to let their children ride in driverless school buses: A gender and nationality
comparison. Social Sciences, 7(3), 34.
Azad, M., Hoseinzadeh, N., Brakewood, C., Cherry, C. R., & Han, L. D. (2019). A Literature Review on
Fully Autonomous Buses. Washington DC: Transportation Research Board.
Bernhard, C., Oberfeld, D., Hoffmann, C., Weismüller, D., & Hecht, H. (2020). User acceptance of
automated public transport: Valence of an autonomous minibus experience. Transportation
Research Part F: Traffic Psychology and Behaviour, 70, 109‑123.
https://doi.org/10.1016/j.trf.2020.02.008
*Chen, C.-F. (2019). Factors affecting the decision to use autonomous shuttle services: Evidence from
a scooter-dominant urban context. Transportation research part F: traffic psychology and
behaviour, 67, 195‑204. https://doi.org/10.1016/j.trf.2019.10.016
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information
Technology. MIS Quarterly, 13(3), 319‑340. https://doi.org/10.2307/249008
*Dekker, M. J. (2017). Riding a self-driving bus to work: Investigating how travellers perceive ADS-DVs
on the last mile. https://repository.tudelft.nl/islandora/object/uuid%253Ac9773355-d4a3-
4063-9799-11343c625c01?collection=education
*Dong, X., DiScenna, M., Guerra, E., & Transportation Research Board. (2017). Transit User Perception
of Driverless Buses. Transportation, 46(1), 35-50.
*Eden, G., Nanchen, B., Ramseyer, R., & Evequoz, F. (2017). Expectation and Experience: Passenger
Acceptance of Autonomous Public Transportation Vehicles. In R. Bernhaupt, G. Dalvi, A. Joshi,
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
D. K. Balkrishan, J. ONeill, & M. Winckler (Éds.), Human-Computer Interaction—Interact 2017
(p. 360‑363). Springer International Publishing Ag.
*Fernández Medina, K., & Jenkins, R. (2017). GATEway: Public Perceptions of a Last-Mile Driverless
Shuttle. https://gateway-project.org.uk/wp-content/uploads/2018/06/D3.7_TRL-Workshop-
Findings-Report.pdf.
Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and
research. Contemporary Sociology, 6(2), 244-245. https://doi.org/10.2307/2065853
*Földes, D., Csiszár, C., & Zarkeshev, A. (2018). User expectations towards mobility services based on
autonomous vehicle. In 8th International Scientific Conference CMDTUR 2018 (p. 7-14).
*Fröhlich, P., Schatz, R., Buchta, M., Schrammel, J., Suette, S., & Tscheligi, M. (2019). “What’s the Robo-
Driver up to?” Requirements for Screen-based Awareness and Intent Communication in
Autonomous Buses. i-com, 18(2), 151–165.
Gandia, R. M., Antonialli, F., Cavazza, B. H., Neto, A. M., Lima, D. A. de, Sugano, J. Y., Nicolai, I., &
Zambalde, A. L. (2019). Autonomous vehicles: Scientometric and bibliometric review.
Transport Reviews, 39(1), 9‑28. https://doi.org/10.1080/01441647.2018.1518937
Harb, M., Xiao, Y., Circella, G., Mokhtarian, P. L., & Walker, J. L. (2018). Projecting travelers into a world
of self-driving vehicles: Estimating travel behavior implications via a naturalistic experiment.
Transportation, 45(6), 1671‑1685. https://doi.org/10.1007/s11116-018-9937-9
*Herrenkind, B., Brendel, A. B., Nastjuk, I., Greve, M., & Kolbe, L. M. (2019). Investigating end-user
acceptance of autonomous electric buses to accelerate diffusion. Transportation Research Part
D: Transport and Environment, 74, 255‑276. https://doi.org/10.1016/j.trd.2019.08.003
Hilgarter, K., & Granig, P. (2020). Public perception of autonomous vehicles: A qualitative study based
on interviews after riding an autonomous shuttle. Transportation Research Part F: Traffic
Psychology and Behaviour, 72, 226‑243. https://doi.org/10.1016/j.trf.2020.05.012
*Hinderer, H., Stegmueller, J., Schmidt, J., Sommer, J., & Lucke, J. (2018). Acceptance of Autonomous
Vehicles in Suburban Public Transport An empirical study on requirements and prerequisites
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
expected by inhabitants. In Ieee International Conference on Engineering, Technology and
Innovation (Ice/Itmc). Stuttgart (p. 1-8). doi: 10.1109/ICE.2018.8436261.
*Kostorz, N., Hilgert, T., Kagerbauer, M., & Vortisch, P. (2019). What do people think about
autonomous minibuses in Germany? In 8th Symposium of the European Association for
Research in Transportation (p. 1-12).
*López-Lambas, M. E., & Alonso, A. (2019). The Driverless Bus: An Analysis of Public Perceptions and
Acceptability. Sustainability, 11(4986), 1-25.
*Madigan, R., Louw, T., Dziennus, M., Graindorge, T., Ortega, E., Graindorge, M., & Merat, N. (2016).
Acceptance of Automated Road Transport Systems (ARTS) : An Adaptation of the UTAUT
Model. Transportation Research Procedia, 14, 2217‑2226.
https://doi.org/10.1016/j.trpro.2016.05.237
*Madigan, R., Louw, T., Wilbrink, M., Schieben, A., & Merat, N. (2017). What influences the decision
to use automated public transport? Using UTAUT to understand public acceptance of
automated road transport systems. Transportation Research Part F-Traffic Psychology and
Behaviour, 50, 55‑64. https://doi.org/10.1016/j.trf.2017.07.007
Millonig, A., & Froehlich, P. (2018). Where Autonomous Buses Might and Might Not Bridge the Gaps in
the 4 A’s of Public Transport Passenger Needs—A Review. In Proceedings of the 10th
International ACM Conference on automotive user interfaces and interactive vehicular
applications. (p. 291-297).
*Monéger, F. (2018). Conception d’un service de transport par navettes autonomes acceptable et
sécurisé : Approche ergonomique par l’analyse des expériences vécues et des valeurs en acte
[PhD Thesis, Université Clermont Auvergne].
*Motak, L., Neuville, E., Chambres, P., Marmoiton, F., Moneger, F., Coutarel, F., & Izaute, M. (2017).
Antecedent variables of intentions to use an autonomous shuttle: Moving beyond TAM and
TPB? European Review of Applied Psychology-Revue Europeenne De Psychologie Appliquee,
67(5), 269‑278. https://doi.org/10.1016/j.erap.2017.06.001
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
*Nordhoff, S., de Winter, J., Madigan, R., Merat, N., van Arem, B., & Happee, R. (2018). User acceptance
of automated shuttles in Berlin-Schoneberg: A questionnaire study. Transportation Research
Part F-Traffic Psychology and Behaviour, 58, 843‑854.
https://doi.org/10.1016/j.trf.2018.06.024
*Nordhoff, S., de Winter, J., Payre, W., van Arem, B., & Happee, R. (2019). What impressions do users
have after a ride in an automated shuttle? An interview study. Transportation Research Part
F: Traffic Psychology and Behaviour, 63, 252‑269. https://doi.org/10.1016/j.trf.2019.04.009
Nordhoff, S., Kyriakidis, M., Van Arem, B., & Happee, R. (2019). A multi-level model on automated
vehicle acceptance (MAVA): A review-based study. Theoretical Issues in Ergonomics Science,
20(6), 682–710.
*Nordhoff, S., van Arem, B., Merat, N., Madigan, R., Ruhrort, L., Knie, A., & Happee, R. (2017). User
acceptance of driverless shuttles running in an open and mixed traffic environment. In
Proceedings of the 12th ITS European Congress, Strasbourg, France (p. 19–22).
*Pakusch, C., & Bossauer, P. (2017). User acceptance of fully autonomous public transport. In
Proceedings of the 14th International Joint Conference on e-Business and Telecommunications
2 (p. 52‑60).
*Papadima, G., Genitsaris, E., Karagiotas, I., Naniopoulos, A., & Nalmpantis, D. (2020). Investigation of
acceptance of driverless buses in the city of Trikala and optimization of the service using
Conjoint Analysis. Utilities Policy, 62, 1-9.
*Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., & Malhene, N. (2016). Public
Views towards Implementation of Automated Vehicles in Urban Areas. Transportation
Research Procedia, 14, 2168‑2177. https://doi.org/10.1016/j.trpro.2016.05.232
*Portouli, E., Karaseitanidis, G., Lytrivis, P., Amditis, A., Raptis, O., & Karaberi, C. (2017). Public attitudes
towards autonomous mini buses operating in real conditions in a Hellenic city. In 28th Ieee
Intelligent Vehicles Symposium (p. 571‑576).
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
*Ramseyer, R., Cimmino, F., Emery, L., Grezes, S., Grezes, V., Nanchen, B., Simon, E., & Fragniere, E.
(2018). Using Phenomenology to Assess Risk Perception of a New Technology in Public
Transportation the Case of the Autonomous Vehicles as Mobility as a Service (MaaS) in
Switzerland. In 2018 3rd International Conference on System Reliability and Safety (ICSRS) (pp.
289-293). https://doi.org/10.1109/ICSRS.2018.8688840
*Roche-Cerasi, I. (2019). Public acceptance of driverless shuttles in Norway. Transportation research
part F: traffic psychology and behaviour, 66, 162-183.
https://doi.org/10.1016/j.trf.2019.09.002
SAE International. (2018). Taxonomy and definitions for terms related to driving automation systems
for on-road motor vehicles. https://saemobilus.sae.org/content/j3016_201806
*Salonen, A. O. (2018). Passenger’s subjective traffic safety, in-vehicle security and emergency
management in the driverless shuttle bus in Finland. Transport Policy, 61, 106-110.
*Salonen, A. O., & Haavisto, N. (2019). Towards Autonomous Transportation. Passengers’ Experiences,
Perceptions and Feelings in a Driverless Shuttle Bus in Finland. Sustainability, 11(3), 1-19.
https://doi.org/10.3390/su11030588
Schade, J., & Schlag, B. (2003). Acceptability of urban transport pricing strategies. Transportation
Research Part F: Traffic Psychology and Behaviour, 6(1), 45-61.
Schuitema, G., Steg, L., & Forward, S. (2010). Explaining differences in acceptability before and
acceptance after the implementation of a congestion charge in Stockholm. Transportation
Research Part A: Policy and Practice, 44(2), 99-109.
*Stark, K., Gade, K., & Heinrichs, D. (2019). What Does the Future of Automated Driving Mean for
Public Transportation? Transportation Research Record: Journal of the Transportation
Research Board, 89-93.
Tabattanon, K., Sandhu, N., & D’Souza, C. (2019). Accessible Design of Low-Speed Automated Shuttles:
A Brief Review of Lessons Learned from Public Transit. In Proceedings of the Human Factors
and Ergonomics Society Annual Meeting, 63(1), (p. 526-530).
Preprint article published in Transportation Research Part F: Psychology and Behaviour, 81 (2021) 251-
270 https://doi.org/10.1016/j.trf.2021.06.008
The Aspen Institute Center for Urban Innovation. (n.d.). Bloomberg Aspen Initiative on Cities and
Autonomous Vehicles. Retrieved the 2019, June 24th, from https://avsincities.bloomberg.org/
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information
Technology: Toward a Unified View. MIS Quarterly, 27(3), 425‑478.
https://doi.org/10.2307/30036540
*Vöge, P., & McDonald, M. (2003). User needs analysis for automated urban transport systems – A
qualitative approach. In Proceedings of the 10th world congress on intelligent transport
systems and services (p. 16–20).
*Wicki, M., Guidon, S., Becker, F., Axhausen, K. W., & Bernauer, T. (2019). How technology
commitment affects willingness to use AVs: Results from realistic mode choice experiment for
a self-driving shuttle service. In 19th Swiss Transport Research Conference (p. 1-28).
*Wien, J. (2019). An assessment of the willingness to choose a self-driving bus for an urban trip: A public
transport user’s perspective. https://repository.tudelft.nl/islandora/object/uuid%3A8064cc17
-dc0e-4c0c-9a9c-6efca8564d94.
*Winter, K., Wien, J., Molin, E., Cats, O., Morsink, P., & van Arem, B. (2019). Taking the self-driving bus:
A passenger choice experiment. In 6th International Conference on Models and Technologies
for Intelligent Transportation Systems (MT-ITS), 1–8.
*Winter, S. R., Rice, S., Mehta, R., Walters, N. W., Pierce, M. B., Anania, E. C., Milner, M. N., & Rao, N.
(2018). Do Americans differ in their willingness to ride in a driverless bus? Journal of Unmanned
Vehicle Systems, 6(4), 267‑278. https://doi.org/10.1139/juvs-2018-0020
*Wintersberger, P., Frison, A.-K., & Riener, A. (2018). Man vs. machine: Comparing a fully automated
bus shuttle with a manually driven group taxi in a field study. In Adjunct Proceedings of the
10th International Conference on Automotive User Interfaces and Interactive Vehicular
Applications (p. 215–220).