User Experience and Analysis of an Autonomous Shuttle Service

Lova Andersson, Allegra Ayala, Shuan Chan, Kyle Hickerson, Liam Kettle, Lindsey A. Malcein

and Yi-Ching Lee

Department of Psychology, George Mason University, Fairfax, Virginia, U.S.A.

Keywords: Autonomous Shuttle, User Experience, Driving Automation Systems, Ridesharing, Public Transportation.

Abstract: As the use of autonomous vehicles for public transportation becomes more prevalent, it is important to

examine characteristics of potential users and their perception of the service. This study aimed to capture user

opinions and feedback from both riders and non-riders concerning an autonomous shuttle service. Potential

differences in user groups were examined as well, comparing employees of the Department of Defense to

civilian users. Participants generally held positive opinions about the shuttle, although riders were more likely

to rate the service favourably. Civilian users were also more likely to rate the shuttle favourably and more

often claimed that they would recommend it to others. The youngest participants tended to report higher levels

of agreement and acceptance on perceived safety and intelligence as well as the shuttle’s avoidance of

obstacles and obedience of traffic rules. Research in this area has implications for all facets of the

transportation industry as well as future users of autonomous public transportation.

1 INTRODUCTION

The Society of Automotive Engineers International

defines Driving Automation Systems as motor

vehicle driving automation systems that perform part

or all of the dynamic driving task on a sustained basis,

with further classifications for six levels of driving

automation, ranging from no driving automation

(Level 0) to full driving automation (Level 5) (SAE

International, 2018). Colloquially, “autonomous” or

“driverless” has been used to describe the major

feature of the Level 5 driving automation systems -

vehicles that can drive without human control

(Ruijten, 2018). Over the past several years, there has

been a push for the development and use of

autonomous vehicles (AV). A major motivator for

this has been the potential for increased roadway

safety. In 2015, the US National Highway Traffic

Safety Administration found that in 94% of

automobile crashes, fault was assigned to the driver,

meaning that human error played a role in the

accident. In their examination, these critical reasons

were classified into recognition errors, decision

errors, performance errors, and non-performance

errors (Singh, 2015). AVs have the potential to

mitigate various types of human errors in driving and

https://orcid.org/0000-0002-9383-4105

could play a significant role in accident reduction on

the roadways. With full implementation of AVs, it is

predicted that accidents could be reduced by up to

90%, which, in turn, could potentially save up to $190

billion in the healthcare costs that are associated with

these accidents (Bertoncello & Wee, 2015). Besides

safety, AV technology is also able to provide mobility

for non-drivers such as the young, the elderly, and

people with physical disabilities (Alkan, 2017).

Other recent research has focused on the benefits

of autonomous public transportation. One example of

this is autonomous shuttles (AS) or buses (AB). Like

autonomous personal vehicles, safety plays an

important role in the design and implementation of

AS. They also operate in environments where

unpredictable situations are inevitable, such as

interactions with pedestrians, intersections without

traffic lights, and roundabouts (Wang et al., 2018).

Passenger acceptance and willingness to ride the

AS should be considered in the design and

implementation of these shuttles. There are three key

factors that have been shown to determine

passengers’ acceptance of AS: safety, comfort, and

convenience (Eden et al., 2017). A study by Dong et

al. (2017) on an AB service in Philadelphia gave

further insight into passenger acceptance. Of the 891

370

Andersson, L., Ayala, A., Chan, S., Hickerson, K., Kettle, L., Malcein, L. and Lee, Y.

User Experience and Analysis of an Autonomous Shuttle Service.

DOI: 10.5220/0010408703700377

In Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2021), pages 370-377

ISBN: 978-989-758-513-5

surveyed riders, two-thirds were willing to ride in an

AB when a transit employee, who could perform take

over requests, was also on board. Only 13% of those

surveyed would agree to ride in the bus in the absence

of a transit employee. In addition, those under the age

of 45 years were more willing to ride in an AB –

possibly due to greater exposure to various digital

features and automated technology in this age group.

These results show optimism for an increase in

acceptance of automated technologies as younger

generations grow with the advancement of automated

technologies and along with it bring less scepticism

(Dong et al., 2017). In line with these results, the

Mcity research project conducted at the University of

Michigan found that riders were more likely than

non-riders (86% vs. 66%) to report trust in an AS

service (Kolodge et al., 2020). These findings further

emphasize the idea that exposure to technology may

have an effect on acceptance of technological

advancements.

In the past decade, there have been major shifts in

the public transportation market. With these shifts,

there has been a significant increase in the use of app-

based transportation services. For example, within the

past five years, the ridesharing industry has greatly

increased its share in the transportation market due to

easy accessibility and convenience. In 2016,

ridesharing apps such as Uber and Lyft surpassed

taxis in New York City for total number of pickups

(Wagner et al., 2018). A fairly recent implementation

within this ridesharing industry has been the use of

AVs. Starting in 2015, Uber started testing AVs in

Pittsburgh, Phoenix, and Toronto. Along with AV

Ubers and AV shuttles, driverless taxis have recently

been tested in Japan in 2018. The trial lasted roughly

one month and took place on a 5.3 km route that was

mapped out. In all, around 1,500 people applied to be

passengers in this study (Chowdhury, 2018).

Another major factor that plays a role in a

person’s acceptance is comfort. As AS becomes more

prominent, it is also important to design the shuttles

in a way that is comfortable for all passengers. The

layout of seating on public transportation plays a role

in the social comfort of passengers (Thomas, 2009).

Seating layouts that force passengers into close

proximity with strangers can lead to social discomfort

(Thomas, 2009). In a ridesharing context, seating

impacts both passengers’ privacy and comfort (Ong

et al., 2019). The lack of passengers’ privacy and

comfort during rides is further exacerbated when in

the presence of others; this could be dependent on

whether the riders are familiar with each other. For

instance, a study investigated social interactions on

railway transit and found that people who were

familiar with one another, such as friends, were less

reserved and interacted more (Bissell, 2010). Those

who are sharing rides with familiar people, such as

friends or regulars, may be less bound by the social

tension that is created through a close quarters seating

layout. Additionally, seat availability and design may

serve to influence general comfort. Seats with clearly

defined boundaries and separation from others are

more ideal to passengers (Lombardi & Ciceri, 2019).

Most user acceptance studies in the context of

AVs to date focused on passenger cars, little has been

done to look at the perceptions people have of larger

AVs such as shuttles. The current research focuses

specifically on perceptions of an AS service and the

likelihood to recommend this mode of transportation.

This study is a secondary data analysis on an AS

feasibility study conducted at a military base. Details

of the study can be found in Allen et al. (2020).

2 METHODOLOGY

2.1 Description of the Autonomous

Shuttles

The dimensions of the exterior of the AS are 12.86

feet by 6.73 feet with a height of 8.20 feet. The

wheelbase of the vehicle extends to 8.29 feet. The

interior height reaches 6.40 feet. Each AS can carry

up to 1,350 pounds, an estimated maximum of twelve

passengers, but only eight seats are present in this

model of AS. This passenger limit must also include

the safety operator. The AS can travel an average

distance of 40 miles at nominal conditions, and 25

miles if operating with the maximum load and

maximum air conditioning. The maximum speed is

25 mph and one and a half hours is required to reach

a full charge. The AS was programmed to operate on

a defined route at the military base, and a safety

operator was required to be present during all

operations and to take-over manual control of the AS

if necessary.

2.2 Study Procedures and Data

Collection

This research consisted of two phases: a pilot,

invitational phase (during July 2019) and a main

study (from late August to end of September 2019).

2.2.1 Pilot Study

During the pilot phase, the study team invited

individuals who worked on- and off-base (including

User Experience and Analysis of an Autonomous Shuttle Service

371

officials from other Department of Defense (DoD)

and Federal agencies as well as organizations in the

local area) to either observe the operations of the AS

or ride the AS. This study received Institutional

Research Board approval from the authors’ university

and US Army Engineer Research and Development

Center’s Construction Engineering Research

Laboratory. Upon experiencing the AS (either as a

rider or a non-rider observer), participants were asked

to complete either a paper version of the survey (on-

site) immediately or an electronic version of the

survey administered by the AS company (on-line)

within a few days. It took approximately five minutes

to complete the survey.

Of the 47 valid responses, all participants were

passengers who had ridden the shuttle either one or

two times. The mean age of this data set was 44.4

years (SD = 11.29). No other demographic

information was collected. A fourth of participants

(25.53%) lived or worked on the base; 10.64% of

participants worked for the DoD but did not live on

base, while the remainder (63.83%) of participants

did not work for the DoD. Participants received their

information about the shuttle primarily from the

onboard safety operators (91.48%), while some

participants heard from media (14.89%), word of

mouth (4.26%), and information operator

publications (4.26%). Three participants received no

information before their ride (6.38%).

2.2.2 Main Study

The study team welcomed anyone who worked on-

and off-base to experience the AS, which operated

during a two-hour lunch period. Through

advertisements, personnel who worked or lived on-

base, visitors to the base, and individuals who heard

about the AS could ride the AS and consent to

participate in the main study. This study received

Institutional Research Board approval from the

authors’ university and US Army Engineer Research

and Development Center’s Construction Engineering

Research Laboratory. Upon experiencing the AS

(either as a rider or a non-rider observer), participants

were asked to complete either a paper version of the

survey (on-site) immediately or an electronic version

of the survey administered by the AS company (on-

line) within a few days. It took approximately five

minutes to complete the survey. A total of 21

questions were included in the survey: most of the

items were identical to those used during the pilot

study, but some adjustments and additions were

deemed necessary to capture the demographics of the

riders and non-riders during the main study. For

example, one question asked for participants’ normal

mode of travel on base and another asked for the

likelihood of recommending this service to others.

The same Likert-scale questions were included, with

the comfort rating being divided into two questions;

the first for riders and the second for non-rider

observers. An additional Likert-scale question asked

for the perceived value of the AS operating on the

base. The survey then asked if the riders would use

the service again. Participants were able to give open-

ended feedback at two points during the survey.

Participants who reported interacting with the AS

as a safety operator and those listed as “Other” were

removed from data analysis (n = 5). Participants who

had taken the survey multiple times were also

removed (n = 3). Of the remaining 98 valid responses,

67 were passengers (31 were non-rider observers).

The mean age of this data set was 37.71 years (SD =

14.85). The mean age for passengers was 40.62 years

(SD = 14.04) and the mean age for non-rider

observers was 31.40 years (SD = 14.82). No other

demographic information was collected. About half

(49.47%) of participants worked for the DoD. Almost

half of the participants travelled around the base in a

personal vehicle (47.96%), while the next largest

group walked (17.35%). The majority of participants

had been a passenger on the shuttle one to two times

(68.37%).

2.3 Simple Correspondence Analysis

Simple Correspondence Analysis (SCA) is an

exploratory method for visualizing contingency

tables on graphs and trends in the data (Clausen,

1998). The only assumption of SCA is that the values

are non-negative. In addition, outliers defined as one

standard deviation away from the centroid (origin)

were removed because they compress the SCA plots

and make interpretation difficult (Bendixen, 2003).

The units on the plots are standard deviations from

the centroid.

SCA was used to visualize participants’

perception of the AS service and technology across

three age groups. The six variables about the AS

service and technology were: Perceived Intelligence,

Regular Use of Shuttle, Perceived Safety, Perceived

Trustworthiness, Avoidance of Obstacles, and

Obedience of Traffic Rules. Participants rated their

level of agreement (strongly disagree to strongly

agree) for the first four variables and level of

acceptance (totally unacceptance to perfectly

acceptance) for the last two variables. Age was

collected as a continuous variable but for the purposes

of SCA, it was binned to have equal N across groups.

VEHITS 2021 - 7th International Conference on Vehicle Technology and Intelligent Transport Systems

372

Initially, we hypothesized that three age groups (two

dimensions) would be appropriate. After reviewing

the inflection point of the scree plots and eigenvalues

(variance) produced by the correspondence analysis,

three age groups (two dimensions) were deemed

appropriate for the analysis (Kassambara, 2017). The

age groups were 20-40, 41-51, and 52-61 for the pilot

study and 19-27, 28-45, and 46-70 for the main study.

Twelve contingency tables were analysed using SCA

(six variables of interest per study). The pilot study

had one participant removed for missing age values;

the main study had two removed. Data analysis was

conducted in R v.3.6.2 using FactoMineR and

factoextra packages (Le et al. 2008; Kassambara &

Mundt, 2020).

3 RESULTS

3.1 Pilot Study Results

The participants in the pilot study agreed that the

shuttle was intelligent (18.3%), safe (17.0%),

trustworthy (15.0%), comfortable (15.0%), and that it

would be used regularly (17.0%). Participants also

rated the shuttle as acceptable at following traffic

rules (12.4%) and avoiding obstacles such as

pedestrians and other vehicles (18.3%). A Chi-Square

test showed a significant association between age and

rating of Perceived Safety. χ

(6, N = 47) = 16.20, p =

.013. Everyone responded either “neither agree nor

disagree” or higher to the statement “The Vehicle is

Safe.” Those in the youngest age group (20-40)

responded “strongly agree” more than those in the 41-

51 and 52-61 age groups.

Results from the SCA indicated that, overall,

participants in the pilot study had a favourable view

of the AS service and technology. In five out of the

six variables of interest, participants reported

acceptability of at least neutral or higher. The SCA

plots are presented in the Appendix. SCA indicates

which groups have similar frequency counts (red for

the survey response and blue for age groups) and

therefore describes general grouping patterns

(Kassambara, 2017). Percent of variance explained

by the dimensions is presented in Table 1. Of note,

two outliers were found in the Avoidance of

Obstacles variable (slightly unacceptable, n = 44) as

well as one outlier in the Perceived Safety variable

(neither agree nor disagree, n = 45).

When looking at the Perceived Intelligence plot,

it was interesting to note that both older age groups

clustered closely around “strongly agree” and

“agree,” respectively. However, for the Regular Use

of Shuttle variable, both 20-40 and 52-61 age groups

were grouped around “agree” indicating similar

frequency responses. The youngest age group

responded the most frequently with “strongly agree”

to the Perceived Safety variable. For Perceived

Trustworthiness, individuals aged 52-61 had similar

response frequencies with “neither agree nor

disagree” as well as “agree” while individuals 41-51

grouped more closely with “somewhat agree.”

Avoidance of Obstacles showed that the youngest age

group (20-40) mostly reported “acceptable.” For the

Obedience of Traffic Rules variable, individuals aged

41-51 were grouped with “slightly acceptable” and

“perfectly acceptable” while those aged 20-40

grouped closer to “acceptable.”

Table 1: Variance (%) Explained by Dimension 1 and 2 –

Pilot Study.

Variable

Variance in

Dimension 1

Variance in

Dimension 2

Perceived

Intelligence

71.15

28.85

Regular use of

Shuttle

97.05

2.95

Perceived

Safety

97.58

2.42

Perceived

Trustworthiness

98.35

1.65

Avoidance of

Obstacles

89.53

10.47

Obedience of

Traffic Rules

92.25

7.75

3.2 Main Study Results

The passengers in the main study reported that the

most common reason for riding was curiosity, at

29.5%. The next most reported reason was for

research (25.7%), followed by convenience (8.6%).

Only two participants were interested in accessibility

(1.9%) and 13 participants listed multiple reasons for

riding the shuttle.

Participants who worked for the DoD rated the AS

negatively more often than their counterparts for the

perceived value to the base (U = 673.00, p = .024).

Those who did not work for the DoD stated that they

would be more likely to recommend the AS to a friend

(U = 469.00, p < .001) (Figure 1). When comparing

riders to non-riders, riders rated the AS favourably

more often on many variables including Perceived

Safety, Perceived Trustworthiness, and the value of

the shuttle to the base (Table 2).

A Chi-Square Test showed no significant

association between the typical method of

User Experience and Analysis of an Autonomous Shuttle Service

373

transportation around the base and DoD employment,

(4, N = 77) = 4.16, p = 0.38.

Figure 1: Distribution of Recommendation Ratings Across

DoD and non-DoD Participants.

Table 2: Riders vs Non-Rider Ratings of AS – Main Study.

Riders

Non-Riders

Mean

Rank

Mean

Rank

Recommend to

Others

52.47

20.43

194.00

5.40

0.000

Perceived Value

on Base

49.54

33.11

516.00

2.91

0.004

Perceived

Intelligence

56.18

35.06

591.00

3.61

0.000

Perceived

Safety

57.45

32.32

506.00

4.30

0.000

Perceived

Trustworthiness

56.47

34.44

571.50

3.75

0.000

Avoidance of

Obstacles

53.50

40.85

770.50

2.13

0.033

Obedience of

Traffic Rules

53.80

40.21

750.00

2.33

0.020

Results from the SCA indicated that participants

in the main study had a favourable view of the AS

service and technology. The SCA plots are presented

in the Appendix. Of note, after examining the SCA

plot for the Avoidance of Obstacles variable, four

outliers from ratings of “slightly unacceptable” and

“unacceptable” were detected and removed, leaving n

= 92 for the analysis. The SCA plot for Perceived

Trustworthiness had one outlier removed from ratings

of “somewhat disagree,” leaving n = 95 for the

analysis. Similarly, the Perceived Safety plot revealed

one outlier from ratings of “strongly disagree,”

leaving n = 95 for the analysis. Percent of variance

explained by the dimensions is presented in Table 3.

For the Perceived Intelligence variable, the

youngest group (19-27) was more highly associated

with the highest level of agreement (“strongly

agree”), while the older group (46-70) was more

closely associated with a weaker positive response

(“somewhat agree”). The middle age group 28-45

was associated with “agree” and “neither agree nor

disagree.” The closest association for the Regular Use

of Shuttle variable was with individuals in the middle

age group (28-45) who most frequently responded

“agree.” Other responses did not have close

groupings. The Perceived Safety variable showed that

individuals in the youngest age group (19-27)

frequently strongly agreed that the shuttle was safe

while participants in the middle age group (28-45)

were neutral in opinion. The Perceived

Trustworthiness variable did not have any patterns of

note. The Avoidance of Obstacles variable showed an

association between the 19-27 group with “strongly

agree.” Finally, for the Obedience of Traffic Rules

variable, the closest frequency count was with

individuals in the youngest group (19-27) finding the

service “perfectly acceptable.”

Table 3: Variance (%) Explained by Dimension 1 and 2 –

Main Study.

Variable

Variance in

Dimension 1

Variance in

Dimension 2

Perceived

Intelligence

57.86

42.12

Regular use of

Shuttle

74.66

25.33

Perceived Safety

71.30

28,70

Perceived

Trustworthiness

95.60

4.40

Avoidance of

Obstacles

77.69

22.32

Obedience of

Traffic Rules

72.04

27.96

4 DISCUSSION

The aim of this study was to explore rider and non-

rider perceptions of an AS service and technology,

along with their likelihood of recommending it to

future users. Those who chose to ride in the AS were

more likely to rate the shuttle positively and more

likely to recommend the service to a friend or

colleague. However, employees of the DoD were not

as likely to recommend the AS when compared to

non-DoD employees.

The open-ended feedback helped to identify some

of the issues these participants felt about the AS. The

first issue was related to the pre-defined route the AS

had to follow, and many participants expressed a

desire to see changes to the defined route with

comments such as “More stops… maybe faster,”

“More hours,” and “Better routes needed.” There

were also requests for specific changes to the route

such as, “Stop closer to Hatfield Gate. In January,

February, and March we have workshops at Brucker

Hall and a shuttle between Hatfield Gate and Brucker

would be very useful.” This issue was also found in a

similar AV study involving a shuttle on a set route

(Eden et al., 2017). Second, participants made

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374

comments about the ride not being as smooth as they

would like with sudden jerky acceleration and

breaking, which Eden et al. (2017) also found was an

issue for riders. One participant stated, “I sat in the

back seat which made me nauseated with the jerky

and fast stops and starts. I had to move to a side seat

and sit with my legs toward the front to support me. I

would not ride it again til that was fixed.” Third, some

riders desired more clear communication regarding

which stop the shuttle was at, along with information

about unexpected situations such as stopping for a

parked vehicle. This is backed up by the finding that

an AV with an interface that communicates with

passengers is found to be more trustworthy (Ruijten

et al., 2018). Lastly, some participants were not fond

of the size or arrangement of seating in the AS. Some

passengers commented that they felt the seats were

uncomfortable or should be larger. Additionally, all

seats were placed along three sides of the shuttle and

face inward, which forced participants to look

towards each other or the door if they did not wish to

interact with other riders. One participant remarked

on the need for both, simply stating “larger, front

facing seating.” Research conducted by Ong et al.

(2019) in which typically shared transportation

methods were partitioned off for privacy garnered

similar feedback from participants who enjoyed the

idea of avoiding interaction with a stranger during

their ride.

The trends seen in the SCA plots suggest that the

younger age group (e.g., ages 19-27 in the main

study) usually reported higher levels of agreement

and acceptance on the surveys. This was very

prevalent when examining topics such as Perceived

Safety and Avoidance of Obstacles. These findings

were also seen in the results of the Chi-Square test in

the pilot study that examined the association between

vehicle safety and age, where the youngest group of

participants were more likely to rate the AS as safe.

However, in the main study, this trend was contrasted

by the next age group (28-45), who reported neutral

responses to Perceived Safety. It is surprising that this

age group was the most associated with agreement

that the AS service would see regular use despite

generally not viewing it as particularly safe. More

research should be conducted to further examine the

perceptions from different age groups, in particular,

the middle age group, to determine the motivations

they may have about AS usage despite holding a

lower view of its safety.

One of the limitations of this study was the use of

a military base as the testing ground for the shuttle.

While civilians were permitted onto the base to ride

the AS, it is unlikely that this would be common

knowledge for some people. Much of the sample

consisted of DoD employees, where ideally the

sample would have been more diverse. The sample

may have also been impacted by the pilot phase of the

study, in which one could only ride the AS by

invitation. Without an invitation, potential users

might have been turned away during this portion of

data collection and might not have returned during the

main study phase, although the research team

encouraged some DoD employees to try out the

service.

There was also a concern that participant answers

were potentially influenced by the safety operators

who were present during the AS rides. These

operators were employees of the AS company and

were trained to give a more interactive experience in

which they gave a short presentation about the shuttle

and participants could ask questions. It has been

found that the presence of an employee onboard can

influence overall willingness to ride for participants

(Dong et al., 2019). The personable nature of the

operators may have also softened criticism of the

shuttle that some participants may have reported if

they were to ride it without an operator present.

The survey itself also faced some limitations.

Some participants had trouble receiving the email for

completing the survey on-line. As it was not asked

that they take it immediately, like the paper survey,

and some participants did not complete it. The on-line

survey also did not allow participants to revisit a

question after it was answered. After the initial pilot

phase, the wording for the question regarding comfort

was altered. The initial survey used during the pilot

study was also missing several questions that the later

version in the main study covered.

Overall, this research suggests that those who

experience an AS may hold a more positive outlook

on the future of the technology. Addressing the

negative feedback and desires of users will be

beneficial in creating a positive AS experience and

promoting the technology.

ACKNOWLEDGEMENTS

The order of the authorship is alphabetized by last

names. Each author contributed to the project: Yi-

Ching Lee: Conceptualization and Supervision;

Lindsey Malcein, Kyle Hickerson, Allegra Ayala:

Formal analysis; Kyle Hickerson, Allegra Ayala,

Lindsey Malcein: Visualization; Allegra Ayala,

Lindsey Malcein, Kyle Hickerson: Writing - original

draft; All authors: Writing - review & editing. We

would also like to acknowledge the efforts from Dr.

User Experience and Analysis of an Autonomous Shuttle Service

375

Lance Larkin, John Cliburn, and GJ Cedric Portea

who participated in project discussions during the

early phase of this research.

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APPENDIX

Pilot Study

Main Study

User Experience and Analysis of an Autonomous Shuttle Service

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