# Designing for Passengers’ Information Needs on Fellow Travelers:
A Comparison of Day and Night Rides
in Shared Automated Vehicles

Lukas A. Flohr  Ergosign GmbH, Saarbrücken & Munich, Germany  Saarbrücken
Graduate School of Computer Science, Saarland Informatics Campus, Saarbrücken,
Germany  Martina Schuß  Technische Hochschule Ingolstadt (THI), Ingolstadt,
Germany  Johannes Kepler Universität, Linz, Austria
Dieter P. Wallach  University of Applied Sciences Kaiserslautern,
Kaiserslautern, Germany  Antonio Krüger  German Research Center for Artificial
Intelligence (DFKI), Saarland Informatics Campus, Saarbrücken, Germany
Andreas Riener

###### Abstract

Shared automated mobility-on-demand promises efficient, sustainable, and
flexible transportation. Nevertheless, security concerns, resilience, and
their mutual influence – especially at night – will likely be the most
critical barriers to public adoption since passengers have to share rides with
strangers without a human driver on board. As related work points out that
information about fellow travelers might mitigate passengers’ concerns, we
designed two user interface variants to investigate the role of this
information in an exploratory within-subjects user study ($N=24$).
Participants experienced four automated day and night rides with varying
personal information about co-passengers in a simulated environment. The
results of the mixed-method study indicate that having information about other
passengers (e.g., photo, gender, and name) positively affects user experience
at night. In contrast, it is less necessary during the day. Considering
participants’ simultaneously raised privacy concerns, balancing security and
privacy demands poses a substantial challenge for resilient system design.

###### keywords:

Automated mobility-on-demand; Automated vehicles; Ride-sharing; Security;
Information needs; Context-based prototyping; Immersive video-based driving
simulation.

111Both authors contributed equally to the paper.

##  1 Introduction

The rapid progress of automated driving technologies promises to revolutionize
public transportation (PT) by creating automated mobility-on-demand (AMoD,
[1]) systems. In AMoD, passengers are transported by driverless vehicles –
i.e., cars with SAE level 4 (high driving automation) or level 5 (full driving
automation) capabilities [2]. Those automated vehicles (AVs) will be guided by
intelligent traffic management systems. They enable efficient route planning
and smart ride-sharing, which will decrease the number of vehicles on the
streets [3], turning traffic jams into a remembrance of the past [4]. While it
is unclear whether private vehicles or shared options will dominate in the
future, the (potentially) most beneficial scenarios unfold when shared
mobility prevails over private vehicle ownership [5, 6]. To arrive at its full
potential, it is imperative that passengers not only share vehicles but also
share rides [7]. Automated ride-sharing has many similarities with today’s
forms of PT. However, its demand-orientated service approach offers both
high(er) efficiency and comfort for passengers. Shared AMoD (SAMoD) will lead
to fewer cars in the streets [8] and – as simulations suggest [3] – lower air
pollution [9]. Since drivers are not needed anymore, passengers will solely
interact with the AVs and the intelligent traffic management systems. Two
considerations have to be addressed when developing such systems. First,
passengers need to rely on digital user interfaces (UIs) that provide them
with trustful information in real-time, as well as with efficient controls for
their travel needs. Second, in SAMoD systems, passengers will share rides with
strangers during both day and night times. Since there is no human authority
(e.g., a bus driver) present anymore in AVs, users’ acceptance is likely to be
influenced by the presence of co-passengers [10, 11]. Information about fellow
travelers prior to and during the ride seems to have the potential to affect
user acceptance positively [12]. The question arises whether these findings of
are further influenced by gender and time of the day as, e.g., [11] found that
especially women are feeling anxious to share rides at night times.
Understanding the potential influence of gender and time of the day on user
acceptance, perceived security, and resilience in SAMoD systems is crucial for
designing inclusive and user-centered transportation solutions.

To overcome acceptance challenges and design resilient SAMoD systems, more
suitable service concepts and UIs are required. We agree with [13] that
"research is needed on how to enhance women’s security while not leaving other
groups of people out". Research in the context of PT shows that feelings of
anxiety and unease when traveling with strangers greatly influence perceived
security [14]. Building upon related work, we hypothesize that knowledge about
co-passengers might positively affect perceived security, acceptance, trust,
and overall user experience (UX). Consequently, this work investigates the
following research question (RQ):

  * RQ. How are SAMoD passengers’ perceptions of security and corresponding UX, trust, acceptance, and emotions influenced by the time of day of a shared ride and their knowledge of co-passengers?

Most related work mentioned above used (online) surveys to examine user
acceptance of (shared) AVs. As such, participants lack experience using SAMoD
systems. Therefore, we investigate our research question in a user study
conducted with 24 participants in Germany using a controlled simulated
environment enabling this very experience. On this basis, our empirically
grounded findings confirm but also challenge previous works on shared AVs and
shed new light on the effects of time of day and the interrelation of
(co-)passengers. The paper informs on SAMoD passengers’ information needs,
such as information about fellow travelers but also points out that providing
such information may come with tensions and costs, e.g., reduced privacy. The
findings may help SAMoD service providers create resilient systems and
desirable interactions in shared AVs that facilitate the technology’s adaption
and help passengers feel secure.

##  2 Background and Related Work

From an HCI perspective, SAMoD faces significant acceptance barriers. In this
section, we provide an overview of factors influencing the acceptance of SAMoD
and discuss methods for designing and evaluating adequate UIs to tackle those
barriers. Finally, we derive our research question and situate the
contributions of this paper among related work.

###  2.1 Factors Influencing the Acceptance of Shared Automated Mobility

The significance of shared mobility modes will continue to grow [7, 15] and
public entities must identify opportunities to engage with these to ensure
their benefits are widely and equitably shared. However, public acceptance
poses major challenges for AVs [16]. Acceptance factors identified by related
work [16, 17, 10, 18, 19] can generally be allocated to overall demographic
factors, system reliability and performance issues, security concerns, users’
expectations and trust, and privacy concerns vs. information demands.

Recent studies examined people’s willingness to switch from private to shared
mobility modes in the future of mobility [11], with demographics such as
gender [20] and age [21] as predictors for the adoption of shared AVs (SAVs)
and young men being the group with the highest openness towards this
technology. Some of the most critical barriers to accepting SAVs are related
to security concerns because rides will have to be shared with strangers [22,
13, 11, 23, 24, 10]. Clayton et al. [25] examined the willingness to share an
AV with other passengers and found uncertainty about sharing and a strong
preference for privately owned vehicles. An online survey by Pakusch et al.
[26] underlines the reluctance to switch from private rides to shared ones,
predicting that private AVs will dominate the future of automated driving.
Mapping these results to the context of SAVs, Lavieri and Bhat [27] found that
people were willing to pay extra fees for trips in SAVs when only the vehicle,
but not the trip, is shared with others. Their study indicated that privacy
and security concerns would prevent participants from opting for sharing rides
with strangers — affecting commuting trips to a minor extent than rides for
pleasure purposes [27].

A qualitative user study by Schuß et al. [11, 13] emphasizes security concerns
as an important issue for automated ride sharing, especially for women — and
particularly during the night. These results were confirmed by Piao et al.
[23, 20]. Passenger security will be challenging for SAMoD, with the time of
the day playing a essential role since passengers – particularly women [20] –
are more concerned about trips during the night [23]. In this context, the
absence of a human driver is essential [20, 11, 28, 29]. Lavieri and Bhat [27]
found that not having a driver on board in an AV seems to be particularly
problematic for Millennials as they see a driver as a kind of "guardian".
Consequently, confirmed by Biermann et al. [30], there seems to be an
increased need for security. As a result, future passengers might tend to
accept the use of monitoring systems for the purpose of preventing crime,
vandalism, and in case of health emergencies [30]. In their online survey,
Sarriera et al. [22] found that major deterrents for adopting SAMoD are being
potentially related to unpleasant co-passengers, uncertainty regarding the
length of a trip, and preferring privacy during a ride. The authors also
discovered biased opinions toward passengers of different social statuses and
races, leading passengers to prefer to have more information about their co-
passengers [22]. An essential factor for adopting SAVs is related to
passenger’s acceptance to share space and time with strangers [21], which is
even more important for leisure trips than business trips [27].

People are still hesitant toward automated systems and giving up their
control. [17] establishes a triad of trust, control, and safety needs to
ensure positive user experiences during AV rides. They propose to provide
clear communication and transparent system feedback to increase these needs
and suggest using visual and auditory feedback about the next stop of
automated shuttles [17]. As mentioned above, the use of monitoring
technologies and information sharing has the potential to increase security
perception. At the same time, however, it needs to be taken into account that
travel information can be a private matter [31]. König et al. [12] evaluated
whether information about potential co-passengers influences the acceptability
of SAMoD systems and measured how different levels of information affected
participants’ compensation demands. Detailed information about co-passengers
proved to be beneficial [12]. Interestingly, they also found that information
about men as fellow travelers resulted in higher refusal rates than
information about women travelers [12]. In accordance with this observation,
women seem to prefer being matched with other women to increase feelings of
security [13, 29]. Indeed, women-only vehicles already have been discussed in
the context of public transportation [32], ride-hailing [33], and in the
context of SAVs [24]. The mentioned studies show that potential users have
security issues with SAVs and underline the importance for the HCI community
to come up with adequate solutions.

###  2.2 Perceived Security, Resilience, and Their Mutual Influence

Shared driverless travel poses new challenges for resilient system design.
Generally, resilience can be referred to as the "process and outcome of
successfully adapting to difficult or challenging […] experiences" [34]. In
terms of SAMoD, overall system resilience also depends on the psychological
resilience of (prospective) users. Particularly passengers’ perceived security
seems to impact resilience in various ways. Firstly, it influences
individuals’ trust in the system and their confidence in the system’s ability
to protect them from potential harm or threats [35]. This trust acts as a
foundation for their psychological resilience, as individuals are more likely
to be adaptive and resilient when they feel secure and protected [35]. In
addition, perceived security influences individuals’ willingness to report
security incidents or vulnerabilities [36]. A culture that encourages open
communication and reporting fosters resilience by allowing for timely
identification and response to security issues [37] – which then again also
increases overall system resilience. When individuals perceive that their
contributions are valued and acted upon, it enhances their motivation to
actively participate in maintaining and improving the system’s resilience
[38].

Overall, perceived security plays a vital role in shaping resilience by
influencing individuals’ mindsets, behaviors, and willingness to engage in
proactive actions within a system [39]. In turn, we argue that from a human
factors and ergonomics (HF/E) perspective, resilience plays a significant role
in influencing perceived security within a (SAMoD) system. When individuals
and organizations exhibit resilience, it creates a sense of confidence and
trust in the system’s ability to withstand and recover from adverse events or
security breaches. Taking into consideration the crucial role of perceived
security in SAMoD systems (Section 2.1), this perception of security is vital
as it will affect passengers’ interaction with and trust towards the system
and influence their willingness to use it. Consequently, factors affecting the
resilience of both individual users and the overall system should be
considered from early design phases. Regarding SAMoD, this particularly
involves considering them in the design of suitable user interfaces.

###  2.3 Interface Design and Evaluation for Shared Automated Mobility

SAMoD UIs can range, e.g., from passenger information displays in vehicles and
planning and booking applications on mobile devices to terminals at mobility
hubs. They will provide the sole basis for the communication of passengers and
the intelligent systems as no human operators (e.g., drivers) will be involved
anymore. In terms of interaction modalities, already familiar technologies
like touchscreens, information displays and control buttons seem to be
preferred by potential SAMoD users [30]. The preference for established
modalities, such as visual and auditory, and interior locations, such as the
front area, is reflected by the systematic literature review on the in-vehicle
design space by Jansen et al. [40]. They provide a comprehensive overview of
input and output modalities and information locations and highlight the
relevance of multi-modal in-vehicle interactions.

Since most currently available (S)AVs are still limited, prototyping and
simulation methods are used to test and evaluate future (S)AMoD UIs. To ensure
a meaningful transfer of study results to the development of SAMoD systems, it
is essential to integrate the highly dynamic element of the context of use
[41, 42]. In ubiquitous systems like SAMoD, this involves not only the
consideration of auditory and visual factors but also the inclusion of
surrounding elements like other people that might be present, as well as their
relation to the respective users [41]. There are several methods to prototype
the physical and social context of human-AV interactions [43], including lab-
based prototyping with mock-ups, virtual reality, and simulators [44, 45, 46,
42, 47], wizard-of-oz vehicles (WoOz) [48, 49, 50], and experimental AVs [51,
10, 52, 29]. [43] provide a detailed overview of suitable methods and discuss
the value of context-based interface prototyping for the AV domain. In
general, each method offers advantages and disadvantages that have to be
weighed by the experimenters depending on the focus of the study. While the
use of experimental AVs for evaluating SAMoD UIs intuitively seems to be the
first choice, it needs to be considered that current setups are still quite
limited, e.g., to specific test scenarios and low speed limits [52].If a study
purpose can be achieved under these limitations, actual AVs might be suitable.
However, to investigate human-AV interactions beyond those limitations, e.g.,
automated rides in complex urban environments, WoOz and simulators offer
promising alternative approaches. In WoOz setups used to simulate AVs, a
hidden driver de facto controls the vehicle, while study participants are told
that the vehicle is driving fully automated [53].

WoOz studies allow for conducting realistic ride studies in complex
environments. Still, the method is limited in terms of control and comparisons
between rides because each ride varies due to contextual factors (e.g.,
traffic density, time of day, or the behavior of other road users). In
contrast, simulators offer controllable and reproducible test environments
[54, 55]. As [46] point out, virtual-reality-based simulators are often quite
sophisticated constructs that can be applied to investigate driver-vehicle
interactions where the simulation needs to adjust to the
participants’/drivers’ steering input. Since users of SAMoD systems are
passive passengers, it is not necessary to enable study participants to
control the simulation. Simulations can thus also be realized using "immersive
video" [41], which offers a straightforward and time-efficient approach to
prototyping SAMoD systems, e.g., [45, 46]. The latter is quite fitting to
investigate human-AV interactions in specific situations (e.g., at a
particular time of day) in a controllable manner but still with an adequate
representation of the dynamic environment.

##  3 Material and Method

To investigate our research question, we created a UI prototype representing a
SAMoD in-vehicle passenger information display. Variants of the UI were
evaluated in an exploratory within-subjects user study with a diverse sample
of participants ($N=24$; gender-balanced, wide range of ages) using a video-
based automated vehicle simulator [46]. With our study, we aim to have a
closer look into the information needs of passengers and counteract the
limitations of an online survey by simulating rides in an SAV during different
times of the day. At the same time, we do not necessarily say this would be
the best solution. Quite the contrary, we acknowledge that 1) serious privacy
side effects could arise, and 2) stereotypes could be further manifested.
Still, we wanted to let participants experience receiving this information on
their fellow travelers and discuss with them how it would influence their
perceived security. Our motivation was to evaluate whether such a
controversial concept would convey security after all and, if so, under what
circumstances people would need and want to use it.

We identified leisure trips as a typical case for the use of SAMoD during both
day and night times (more details in section 3.3). In each simulated ride, an
in-vehicle UI prototype (section 3.2) provided participants with information
about the ride and fellow passengers. In the respective UIs, we varied the
type and amount of information participants received when co-passengers
boarded and left the vehicle. Information was either provided with personal
data on co-passengers (name, age, target destination, profile picture), or
without. We used a within-subjects design, and each participant experienced
four rides: two night and two day trips, one with and one without personal
information about co-passengers. The order in which each participant
experienced the variants was randomized and counter-balanced.

Since we wanted to investigate shared rides, we identified two options to
include the "sharing" aspect in the study: 1) simulating passengers
boarding/leaving the vehicle with sounds and visual information displayed on
the UI, and 2) using real persons (’actors’) that complement the setup.
Regarding the latter, Flohr et al. [46] investigated the effect of
supplementing SAV simulator studies with actors mimicking co-passengers. While
they found some support for the approach, it does not seem to increase
participants’ immersion in the simulation. Instead, it seems to increase the
occurrence of motion sickness symptoms in simulator studies [46]. Therefore,
considering the potential adverse effect on participants’ well-being during
the simulator study and the problematic pandemic situation at the time of the
study conduct, we decided to simulate co-passengers getting on and off the SAV
only virtually. While this supports, on the one hand, our intended focus on
the information display, this can, on the other hand, also be considered a
limitation of the study, which we further discuss in section 5.4.

The study was conducted in accordance with the ethical guidelines stated in
the Declaration of Helsinki [56]. Participants took part voluntarily, were
obliged to provide their written informed consent, and had the opportunity to
abort the study at any time without stating reasons.

Figure 1: Study participants experienced two day and two night rides in the
immersive video-based automated vehicle simulator.

###  3.1 Setup

Since contextual factors play a crucial role in passengers’ travel experiences
and information needs, we intended to establish a realistic but still
controllable test environment for the user study. Therefore, we adapted the
immersive video-based simulation setup used by Flohr et al. [46, 42] and
combined it with a tent-based vehicle mock-up (e.g., used by Schuß et al.
[11]) to provide even more realism. The resulting setup (Fig. 1, 3) consisted
of three LCD screens that played back videos representing a passengers’ view
out of the front, left, and right windows of a shared AV.

Similar to [46], we used audio and video footage of day and night rides
through an urban environment to create simulations for two night and two day
rides. The footage was captured using three action cameras mounted in the
center of a BMW i3’s windshield, as well as on the front side windows. In
addition, we enhanced audio footage with additional sounds (e.g., opening and
closing noises of sliding doors). Along with a 2x2 seating group, the footage
was played back on three NEC Full HD 55.1-inch TV screens situated in a tent-
based vehicle mock-up. The tent separated the simulation from the surrounding
lab environment to support participants’ immersion by entering a closed space
when boarding the simulated SAV (Fig. 3). The UI prototype of the passenger
information display was displayed visually on an additional 24.1-inch screen
(Fig. 1). Audio sounds and voice prompts were provided by a Logitech 2.1 sound
system.

###  3.2 Design Process and Prototypes

The tested UI prototypes were designed iteratively following findings from
related user studies and a comprehensive literature review. We used video-
based prototyping to create high-fidelity visual and auditory UI
representations that matched the video-based simulation. The visual
information display featured a split-view of 1) a schedule showing upcoming
stops, estimated arrival times, and information on co-passengers getting
on/off the vehicle, and 2) a map illustrating the current location of the AV
and the planned route (Fig. 2), which follows proposals of previous work
(e.g., [24, 46]). We created two general prototype variants to investigate the
research question (Fig. 2). While the first variant ("without") does not show
personal information about co-passengers, the second variant ("with") features
such information by displaying name, age, target destination, and profile
picture of co-passengers. For each test ride, participants experienced either
a prototype with or without information on co-passengers, i.e., the variant
stayed consistent within the rides.

Previous research suggests that combining these data reduces overall
compensation demands for sharing a ride with a stranger [12]. We did not
include a rating of fellow passengers, as rating systems hold discriminating
characteristics [13, 57]. We used AI-generated pictures with neutral facial
expressions [58] as photos of the entering fellow passengers. We included
fellow passengers’ age as we hypothesized that this information might
influence participants’ perceptions. Thereby, we defined two age groups: young
(between 20 and 30) and older (between 50 and 60).

Figure 2: Apart from time of day ("day" and "night"), study conditions varied
in the amount of provided information on co-passengers: 1) without
information, 2) with information. In the two rides with information, co-
passengers’ age varied between "young" and "older".

Age of fellow passengers was balanced so that each participant experienced one
ride with a younger man/woman and an older man/woman as we expected that age
could have an effect on passengers’ perceived security. The provided
contextual information (map, street names, etc.) matched the real-world
environment where the simulation footage was recorded and animated (using
Adobe After Effects CC 2021) according to the simulated vehicle’s movements
(e.g., the position of the AV in the map). For permutation purposes, we
created eight video prototypes of the UI to have one variant without and one
with information on co-passengers for all four simulated rides. Signal sounds
and voice prompts complemented the visual UI (e.g., without: "Next stop: [stop
name]. One passenger gets on. One passenger gets off."; with: "Next stop:
[stop name]. [Name of passenger] gets on. [Name of passenger] gets off.").
Voice prompts were created using text-to-speech conversion by Microsoft Azure.

###  3.3 Scenarios

We intentionally included participants covering a wide age range in the study,
with young people not working yet, and older adults who do not work anymore.
To provide for a broad spectrum of participants’ real lives, we chose leisure
trips as scenarios for the four rides in the study. Since people are reported
to be more likely to reject sharing rides with unknown fellow passengers for
leisure trips compared to commute trips [27], we wanted to explore whether
information about other passengers would mitigate this observation. All
participants engaged in four trips: two during the day and two at night. We
used storytelling to create authentic scenarios for each trip to enhance
immersion. The day trips went from a bakery to a park to meet friends and
back. The night trips started nearby the passenger’s home and had a restaurant
as a destination where some friends were supposed to meet and were also round
trips. To get even better acquainted with the scenario, participants received
a paper ticket before each ride with their name, destination, departure and
arrival time. After reading the scenario to them and handing over the ticket,
our participants entered the shuttle bus, chose one of the seats in the front
row, and one of the investigators started the video simulation. During each
trip, one man and one woman as a co-passenger entered the vehicle virtually
(i.e., this was only stated by the information displayed in the UI prototype).
We did not randomize the order, i.e., it was always the woman entering first
to avoid losing statistical power due to too many conditions. However,
participants always rode with only one person at a time since we hypothesized
that it would affect participants’ perceived security whether they would be
sharing rides with a single man/woman or multiple persons simultaneously. The
first (virtual) co-passenger entered at the first stop and got off at the
second stop, where the second co-passenger entered the vehicle. At the third
stop, participants’ reached their target destination.

###  3.4 Procedure and Measurements

We used a mixed-method approach [59] and triangulated quantitative data
collected during and between rides with observations and qualitative interview
data. Each study session can be divided into three parts: briefing and pre-
questionnaire, test rides and measures, and post-session interview. Each
session took between 60 to 90 minutes in total.

Figure 3: Study procedure (top) and sequence of the four simulated SAMoD rides
(bottom).

####  3.4.1 Briefing and Pre-Questionnaire

After receiving a briefing comprising general information about the study goal
and the procedure, participants signed a declaration of consent. Then, they
filled out a demographic pre-questionnaire. We also included the short version
of the Big Five inventory [60, 61] to get insights into a participant’s
personality. Prior research showed that psychological factors and attitudes
most likely influence people’s adoption of AVs [62, 63, 64]. As the level of a
person’s anxiety influences the perceived security [65], we also included the
state-trait anxiety inventory (STAI) [66] in our pre-questionnaire. Since
current research is not conclusive on whether having experienced any sort of
crime has an influence on perceived security [14], we left this aspect out.

####  3.4.2 Test Rides and Measures

During each of the four rides, participants filled out Russell’s Affect Grid
[67] in an adapted emoji-based version inspired by [68] using pen and paper.
The Affect Grid is one of the most widespread models for emotion measurement
and consists of two dimensions to measure: pleasure (displeasure – pleasure)
and arousal (low energy – high energy) [69]. Each time information about an
upcoming stop and entering or leaving passenger was displayed during the ride,
participants were instructed to set a cross to express their current emotional
state in the grid.

After each ride, participants got off the simulated automated vehicle and
summarized their subjective emotional constitution throughout the journey by
drawing an emotion curve on a template also used by [48, 42]. Subsequently,
the experimenter accompanied them to a workplace where they filled out a
digital questionnaire. Starting with the short version of the User Experience
Questionnaire (UEQ-s; 8 bipolar items; 7-point scale; [70]) as well as the
Usefulness [71] and Attractiveness [72, 73] dimensions of the UEQ+ (4 bipolar
items for each dimension; 7-point scale; [71]) participants assessed their
experiences of the ride and respective HMI concept. Since we expected the type
and amount of provided information to have an effect on passengers’ trust,
participants also assessed the Trust in Automation scale of Körber (2 items;
five-point Likert-type scale; [74]). Furthermore, we investigated users’
acceptance with the Intention to Use (2 items; 5-point Likert-type scale), and
Perceived Usefulness (3 items; five-point Likert-type scale) dimensions of
Chen’s adaption of the technology acceptance model [75]. Subsequently, we
included Dekker’s Security Concerns scale (1 item; 5-point Likert-type scale;
[76]) and the Perceived Risks scale (1 item; 5-point Likert-type scale; [77])
as risk also has an influence on the perceived security [65]. After the last
ride, each participant additionally filled out the Igroup Presence
Questionnaire (IPQ, 14 items; 7-point Likert-type scale; [78, 79]) to assess
the quality and immersion of the simulated environment.

####  3.4.3 Post-Session Interview

Finally, we conducted a semi-structured post-session interview with each
participant. We asked open-ended questions about the rides in general and the
co-passenger information that was provided by the UI. Participants were asked
which version of the UI they liked best and why. Participants were also
prompted about potential feelings regarding security in the respective
conditions, and we inquired whether some information was missing from their
point of view. With the consent of participants, audio captures of all post-
session interviews were recorded for an in-depth post hoc analysis.

###  3.5 Participants

In total, 24 participants (12 women, 12 men, 0 diverse, 0 n/a; from 18 to 81
years, $M(SD)=40.5(21.3)$, $Median=30$) took part in the study. All
participants were recruited through university mailing lists and word of mouth
and attended the study voluntarily. For participation, all of them received
financial compensation (approx. 25 US dollars). Their national background was
[blinded for review], [blinded for review], [blinded for review], [blinded for
review], and [blinded for review]. We used the STAI inventory to measure
participants’ interindividual tendency to evaluate situations as threatening
or to react with increased feelings of anxiety. According to the reference
values of the trait anxiety scale (items 21-40; [66]) our participants are at
the expected medium level of responding with anxiety. The women in our study
had a mean value of $M=36.5$ ($SD=7.0$; $Mdn=38.0$; expected value according
to references = 37.0) and the men a mean of $M=35.8$ ($SD=4.4$; $Mdn=36.0$;
expected value according to references = 34.5). Participants fall into the
average age group between 36 to 65 years and have a high educational level.
They correspond approximately to the reference values of the Big5-short (see
[80]) for extraversion ($M(SD)=3.25(1.29)$; reference: $M(SD)=3.62(.91)$),
agreeableness ($M(SD)=3.56(0.9)$; reference: $M(SD)=3.43(.79)$),
conscientiousness ($M(SD)=3.93(1.03)$, $M(SD)=3.47(.95)$; reference:
$M(SD)=4.2(0.77)$), neuroticism ($M(SD)=2.45(0.94)$, $M(SD)=2.48(0.9)$)
openness to experience ($M(SD)=3.45(1.21)$; reference: $M(SD)=3.70(0.89)$). We
therefore assume that the obtained results are not falsified through a non-
representative sample (e.g., a sample with exceptional high scores in
neuroticism could have an impact on the perceived security).

##  4 Results

For the quantitative results, descriptive and inferential statistics were
calculated using JASP 0.16 [81] and jamovi 2.2.5 [82]. The audio-recorded
post-session interviews were transcribed verbatim and analyzed applying
qualitative content analysis [83, 84] with MAXQDA [85]. Session notes and
anecdotal evidence during the study complemented the data collection.

###  4.1 Dependent Variables

In the following, we report on descriptive and inferential statistics for a
comparison of the study conditions in terms of our dependent variables, as
well as for an assessment of the simulated setup by having a look at
participants’ presence perception. We computed repeated measures analysis of
variances (RM-ANOVA) to explore differences in the study conditions with the
RM factors ’time of day’ (day, night) and ’information on fellow passengers’
(without, with) as well as the between subjects factor ’gender’ (women, men).
One woman (P21) only completed three of the four rides due to occurring
simulator sickness symptoms. The missing data of P21 was imputed with maximum
likelihood estimates (e.g., [86]) for the respective scales. When a RM-ANOVA
returned significant ($\alpha=.05$) for a certain scale, post-hoc tests in the
form of Holm-adjusted pairwise comparisons for all conditions were calculated.
Effect sizes were interpreted according to Cohen [87].

Figure 4: Boxplots of UEQ-s scales (pragmatic UX and hedonic UX), usefulness,
and attractiveness (-3 = low; 3 = high) for the four study conditions and the
between-subjects factor gender.

####  4.1.1 User Experience

With reference to the UEQ-s benchmarks [88, 70], the tested SAMoD system
received excellent ratings for both pragmatic and hedonic UX quality
throughout study conditions (Fig. 4). While we did not find meaningful
differences in terms of pragmatic quality , hedonic quality , and usefulness,
a RM-ANOVA revealed significant differences for the UEQ’s attractiveness scale
with regard to time of day
($F(1,22)=6.820,p=.016,\eta\textsuperscript{2}\textsubscript{G}=0.026$) and an
interaction effect of passenger information and gender
($F(1,22)=5.059,p=.035,\eta\textsuperscript{2}\textsubscript{G}=0.021$). Post-
hoc tests show that participants’ overall impression was significantly more
positive ($t=2.612,p\textsubscript{holm}=.016$) during daytime than during
nighttime (Fig. 4), with a mean difference of $M(SE)=0.3(0.1)$ and a medium
effect of $Cohen^{\prime}s~{}d=0.533$. Despite the significant results of the
RM-ANOVA, an interaction effect of information and gender was not confirmed by
subsequent pairwise comparisons.

####  4.1.2 Acceptance

A between-subjects effect of gender returned significant in the RM-ANOVA for
both used scales of Chen’s TAM [75]: Perceived Usefulness
($F(1,22)=7.586,p=.012,\eta\textsuperscript{2}\textsubscript{G}=0.194$) and
Intention to Use
($F(1,22)=6.490,p=.018,\eta\textsuperscript{2}\textsubscript{G}=0.159$). Post
hoc comparisons confirm that women perceive the tested SAMoD system to be more
useful than men do (Fig. 5; $t=2.754,p\textsubscript{holm}=.012$) with a mean
difference of $M(SE)=0.5(0.2)$ and a medium-sized effect of
$Cohen^{\prime}s~{}d~{}=~{}0.562$. Similarly, women show a higher Intention to
Use the SAMoD system compared to men (Fig. 5) with a mean difference of
$M(SE)=0.5(0.2)$ and a medium-sized effect
($t=2.547,p\textsubscript{holm}=.018$, $Cohen^{\prime}s~{}d=0.520$). Apart
from the between-subjects effect and the generally medium-high to high
acceptance ratings of the SAMoD system, no meaningful within-subjects effects
of time of day and passenger information on Perceived Usefulness and Intention
to Use were revealed.

####  4.1.3 Security, Trust, and Perceived Risk

Participants’ trust in the automated system was medium-high among all
conditions (Fig. 5). With regards to the medium-rated security concerns (Fig.
5), participants seem to have some, but no severe concerns on their security
during their ride. No meaningful difference induced by time of day or
passenger information was detected. A significant difference was found in
terms of perceived risks
($F(1,22)=7.321,p=.013,\eta\textsuperscript{2}\textsubscript{G}=0.013$). AMoD
rides without information were perceived as significantly more risky than
rides with information about fellow passengers (Fig. 5) with a mean difference
of $M(SE)=0.2(0.1)$ and a medium-sized effect
($t=2.706,p\textsubscript{holm}=.013$, $Cohen^{\prime}s~{}d=0.552$).

Figure 5: Boxplots of acceptance scales (perceived usefulness, intention to
use), trust in automation, security concerns, and perceived risk (1 = low; 5 =
high) for the four study conditions and the between-subjects factor gender.

####  4.1.4 Emotion

Judging from visual inspection of the affect grids and emotion curves (Fig.
6), participants found rides during daytime and without information to be most
pleasant. Rides without information seem to receive more positive assessments
whereas the UI variants with information show higher dispersion in the affect
grids. Generally, rides during daytime seem to be perceived more pleasant than
night rides. In accordance with that, the statistical analysis of the
quantified ($min=1,max=10$) uni-dimensional subscales of the affect grid
(pleasure, arousal) revealed no meaningful effect in terms of arousal but
significant differences in the pleasure ratings with regards to the time of
day ($F(1,43)=12.386,p=.001,\eta\textsuperscript{2}\textsubscript{G}=0.032$).
Rides during daytime ($M(SD)=7.6(2.2)$) received higher pleasure ratings than
rides during nighttime ($M(SD)=6.8(2.2)$) with a mean difference of
$M(SE)=0.8(0.2)$ and a medium-sized effect
($t=3.519,p\textsubscript{holm}=.001$, $Cohen^{\prime}s~{}d=0.525$).

Figure 6: Stacked Emotion Curves (left; Opacity: 0.1; Normalized at
‘Departure’) and Affect Grids (right) for the Four Study Conditions.

###  4.2 Qualitative Content Analysis

For the qualitative content analysis [83, 84], interview transcripts were
initially explored line-by-line. In a second step, we highlighted text
passages, searched for keywords, and added notes. Subsequently, the
transcripts were scrutinized again and codes were derived from the text by
applying inductive coding to refine themes and codes in an iterative process
until the final expressions were identified. In the following, we present our
main findings (e.g., statements expressed during the post-session interviews)
with their number of mentions (n) and the number of women and men in our study
mentioning them. First, we present the perceptions of the rides in general.
Then, we cluster them according to three main topics: information preferences,
day vs. night, and the type of information that participants were requesting.

####  4.2.1 Presence Perception and Experience of the Rides

In general, participants described the four rides as positive and considered
the ride in the simulator as short, entertaining, and pleasant. Moreover,
participants emphasized how realistic the four trips felt to them: "Yes, it
was quite real and I didn’t feel I am in the simulation room and it was so
real. It was quite good, yeah." [P15], which is also reflected in the medium
to high ratings for the four IPQ scales (Realism ($M(SD)~{}=~{}4.0(1.1)$),
Involvement ($M(SD)~{}=~{}3.3(1.1)$), Spatial Presence
($M(SD)~{}=~{}4.1(0.9)$), and General ($M(SD)~{}=~{}4.9(0.8)$). Participants’
immersion in the simulated SAMoD can be judged to be quite high. Participants
compared the simulated AMoD journey to using public transportation systems
such as buses or metros today (16; 6 women, 6 men).

####  4.2.2 Information Preferences

Overall, the qualitative data obtained in the study show that participants
favored to have information about their co-passengers (15; 9 women, 6 men)
over having no information (8; 2 women, 6 men). The most important reason for
preferring the UI version with co-passenger information was security (22; 12
women, 9 men): "I would have felt more secure with the display with the
information and picture." [P05], "I felt so much more secure compared to the
other version." [P22]. Participants considered the information as more
pleasant (9; 5 women, 4 men) in terms of being connected to others: "when the
person comes in and you have a little info about them, I thought that was
pleasant. You could also – in case something happens – address them by name
or, yes, it is more pleasant than the anonymous [version]." [P04]. Other
advantages of having knowledge about fellow passengers were that participants
considered it to be more interesting (4; 1 women, 2 men) and humane (3; 1
women, 1 men). Participants who preferred having information about other
passengers where also willing to share these information about themselves. In
line with this finding, the most important reason for preferring the UI
version without information was privacy (17; 4 women, 6 men): "My first
thought was ’Oh no, people will know my name’. I don’t like that at all."
[P12]. Other participants regarded this information as not important (4; 1
woman, 3 men). Displaying passengers’ details was even seen as insecure (3; 2
men) or untrustworthy (2; 1 man) as these details could potentially harm
people. One participant expressed worries about the security of our young faux
passenger ("Anna") as he elaborated: "Well, at night you’re just a bit more
insecure, for example, when drunk, young people hop on. So [my worries] were
also related to Anna, because people might think ’Oh, here comes Anna now,
maybe we can hit on her or something.’ That would be quite insecure for her
then." [P05]. Although of our 24 participants, 15 expressed they would prefer
the UI version with information, we would like to point out that this was not
a clear decision every time. One participant even was unable to decide which
version they preferred. Most participants found pros, as well as cons, for
both versions and were weighing these off until finally making a decision.
While this reflects how security and privacy are antagonists, the
appropriateness of the variants was considered to be highly context-dependent,
as outlined in the following paragraph.

####  4.2.3 Day vs. Night

Generally speaking, our qualitative data confirms the difference the time of
the day makes for sharing rides in SAVs with strangers as their number of
mentions is higher (35; 9 women, 7 men) than statements that do not emphasize
this importance (9; 2 women, 7 men). In this context, participants stated
time-related concerns like "during the night one is generally more careful and
feels vulnerable [P09]. Several women (17; 9 women) expressed concerns when
sharing rides with unknown men and said they would favor sharing a vehicle
with other women at night over mixed vehicles. For instance, [P03] explains
"well, especially in the dark. During the day is not that tragic, but in the
dark, I don’t want to share a ride with a man or get off the vehicle with
him.". Interestingly, some of the men in our study conveyed similar feelings
towards sharing rides with other men (8; 7 men) – particularly at night:
"Because it was Brigitte who got on at the first stop and then at the second
stop it was a gentleman. That indeed made a difference to me." [P11]. As a
reason they stated to feel more secure as a statement like, i.e., "men tend to
be more aggressive"[P05] indicates. Participants also made clear that they
would not need the displayed information on co-passenger during the day, but
would prefer to have the information during the night: "Especially at night it
was more pleasant for me and more important. […]. The fact that I was
registered, for example, the [man/woman], as well. Yes, that was much more
important for me at night than during the day." [P22].

####  4.2.4 Type of Information

We asked participants which type of information they considered to be the most
important one/s. The fellow passenger’s profile picture was regarded to make
all the difference (23; 7 women, 8 men) since it gives "an impression of the
person that is going to get on the vehicle at a glance" [P16]. In this regard
the photo seem to give participants a feeling of control over the situation
while the other information provided was rather a "nice-to-have" [P23].
Knowing beforehand who would enter the vehicle also conveys security: "Yes, I
mean, I saw the picture and it looks nice and I actually had less fear."
[P03]. The co-passenger’s gender was essential, as well (13; 5 women, 2 men),
followed by their age (10; 6 women, 2 men), the name (8; 3 women, 2 men), and
the respective destination of the co-passengers (7; 2 women, 2 men). Most of
the participants in our study stated that the information the system was
offering was sufficient and emphasized how helpful it was to see the vehicle’s
route and its arrival time on the display. Some participants provided
improvement suggestions such as getting information in case people with
special needs, big luggage, or strollers would enter the vehicle, or whether
seat belt use was compulsory.

##  5 Discussion

Overall, the results underline people’s openness towards SAMoD, which is in
line with previous work [11, 89]. Participants considered SAMoD to be useful
and reported relatively high trust in the technology, intention to use, and
positive experiences of the (simulated) SAMoD rides. However, participants
also expressed concerns regarding security – especially with regard to night
rides. In the following, we discuss our findings in detail and situate them
among previous work.

###  5.1 Night Trips Require Higher Levels of Information

In general, the SAMoD rides during the day were evaluated more positively than
night rides. Participants consider the overall attractiveness of the SAMoD
system higher and report more pleasant rides during the day. Rides without
information about co-passengers were perceived as more pleasant than rides
with information. We hypothesize two reasons as sources of this findings: 1)
participants are used to receiving no information about others when sharing a
ride (as is the case in public transportation), and 2) people generally prefer
rides during the daytime. This interpretation is comprehensively supported by
our qualitative data and is in line with existing data from research in public
transportation [23, 90, 91].

In contrast, rides with information provided by the in-vehicle UI were
experienced to be significantly less risky compared to rides without
information about co-passengers. Again, this is reflected in our qualitative
data, with 21 participants underlining increased perceived security through
the information. This can be taken as a general preference for information
about co-passengers — particularly during the night and is in line with [92],
who found that people are willing to provide information such as their gender,
age, etc. to visually impaired persons in public spaces, if higher security
assurances can be made. While during the day, information about fellow
passengers seems to have rather adverse effects (e.g., in terms of emotion),
this changes during the night, where it has, on the contrary, positive
effects. Prior work underlines the importance of privacy particularly in
public transportation [93]. Security and privacy are often antagonists in
today’s public systems and this dynamic has implications for resilience from a
human factors perspective. This became evident in our study as participants
mentioned privacy concerns when displaying personal information about other
passengers, or themselves. During the interviews, participants weighed the
pros and cons of having (no) information. Despite a preference for information
during the night, this was not a clear outcome, which is also apparent in a
higher dispersion of the Affect Grid assessments for the rides with
information. While the information on co-passengers positively influenced
security for some participants, there were also concerns that this information
could have a negative effect exactly on security as strangers would know one’s
name and destination. To overcome the conflict between security and privacy,
it needs to be investigated which information people feel comfortable sharing
in order to increase perceived security.

From a human factors perspective, it is crucial to design systems that allow
for individual differences and preferences, considering passengers’ diverse
needs and concerns. Resilience can be fostered by providing customizable
options for displaying personal information, allowing passengers to make
informed choices that align with their comfort levels.

###  5.2 Both Men and Women Prefer Sharing Rides with Women

While both men and women generally considered SAMoD systems useful, women
rated them significantly more so and uttered a higher intention to use such
services. We assume that finding is related to their (security) concerns in
today’s public transportation systems, especially considering night rides [11,
13, 23, 20]. In combination with the qualitative data and the discovered
interaction effect of passenger information and gender, this finding provides
evidence that women seem to consider SAMoD systems as more secure than
’classic’ public transportation. Women and men alike explained in the
interviews that they prefer sharing rides with women. This is in line with the
findings of [12], who found people have higher refusal rates towards men as
co-passengers. On the other hand, Polydoropoulou et. al [29] found different
preferences of passengers for sharing with women/men between countries and
cultures and that the number of fellow travelers further influences those
preferences. In our study, we focused on rides with only one co-passenger as
we expected this constellation would have the biggest effect on security.
However, our results and the results from previous work [12, 29] underline
once more the complexity of the topic.

###  5.3 Balancing Security and Privacy as a Design Challenge

In terms of overall SAMoD system design, considering resilience from a human
factors perspective is crucial. However, there is most likely no ’one-fits-
all’ solution [94]. As, e.g., passengers’ security needs are higher during the
night, our data points toward flexible solutions for different times of the
day. Based on our results, we propose that UIs for ride-sharing should provide
general information on the route, arrival time, subsequent stops, and further
information and functionalities to increase passengers’ (feeling of) security
for night rides. Providing information on fellow travelers can serve as a
suitable option to do so. In our study, having a photo of fellow travelers was
considered the most important information unit and was beneficial for
passengers’ feeling of security, while information on age, name, and
destination played a subordinate role. In the study, we chose portraits with
neutral facial expressions. However, other expressions might induce different
– positive or adverse – feelings, e.g., feelings of insecurity. Given that
photos seem to provide passengers with (at least some feeling of) control over
the situation, they might be used in booking apps or in-vehicle displays.
Passengers could then look for an alternative vehicle, or leave the vehicle at
the next stop if someone’s photo would make them feel uncomfortable. The
feeling of control has been shown to have a positive effect on psychological
security in the context of public transport [95] and, based on our results, we
hypothesize that displaying a photo fosters this control, aligning with the
principles of resilience.. However, given the disagreement among our
participants and the aforementioned privacy issues, we suggest 1) not exposing
sensible data about co-passengers during the ride and 2) considering
alternative approaches. In terms of (1), it might be beneficial to relocate
the information retrieval about fellow passengers to another time and place,
e.g., the booking phase. For instance, [12] compared private and shared
options on a mobile booking app and found that people tend to rather opt for
shared rides when having detailed information on their fellow travelers prior
to booking. This could also serve as a means to increase (perceived) security.
In terms of (2), Schuß et al. [96] propose a "buddy system" to address women’s
security needs (during the night) that takes advantage of the fact that other
passengers can also provide security. Instead of seeing them as potentially
harmful, their approach focuses instead on the fact of not being alone and
feeling secure instead of the feeling of controlling the situation through
information. The concept of "social passengering" [97] among passengers inside
the same or different vehicles points to a similar direction and might be
beneficial for the perceived security. By acknowledging the trade-off between
security and privacy and offering flexibility in information disclosure, SAMoD
systems can adapt to individual needs, enhancing passengers’ overall
experience and resilience within the system.

###  5.4 Limitations

SAMoD is still a relatively ’theoretical’ subject [98] with real-life
applications remaining missing. Therefore, we let our participants experience
a SAMoD system in a simulated environment. While participants report high
presence perception and immersion, external validity is impaired due to the
lab-based setup. As we were weighing off the negative side effects that come
with lab studies, we opted for the simulated environment over conducting,
e.g., a WoOz study in real traffic conditions, to compare the study conditions
while ensuring high internal validity and high controllability.

As mentioned in section 3, we decided to simulate the presence of other
passengers in a shared ride only virtually with sounds and display
visualizations. While this was in line with the recommendation of [46] and
facilitated the study’s conformity with applicable hygiene regulations during
the Covid-19 pandemic, the representation of a shared ride’s social contextual
is limited. On the other, considering our study design with multiple
measurements during a test ride, the physical presence of another person might
have affected participants’ assessment of the information and consequently the
study’s reliability. Furthermore, we did not intent to focus on the inherent
social factors or mutual relationships (that definitely play an essential role
in the context of shared mobility), but focused on the provided information.
Nevertheless, this should be considered when conducting further studies on
SAMoD.

Taking into account the large and diverse population of future SAMoD users,
our study has been conducted with a small sample and, although having placed
value on a broad spectrum of people (gender-balanced, different age groups,
different cultural backgrounds, different education levels), it covers only a
part of the variety of potential users. According to the STAI inventory, our
participants had relatively low levels of trait anxiety. Since this trait
likely has an effect of risk and security evaluation, generalizability is
limited.

Furthermore, the study was conducted during the COVID-19 pandemic. We applied
precautions like distancing and hygiene measures and followed the regulations
of local and national authorities. While we consider the pandemic’s effect on
the study conducted to be minor, it might have affected the sample composition
as, e.g., only people with medium fear and anxiety have signed up for the
study. It would be interesting to repeat this study with people that show
higher levels of trait anxiety as this trait influences the evaluation of risk
and security of situations, and we hypothesize that these people could have
evaluated the presented prototype in a more positive way.

The selection of the displayed information on co-passengers covers only a part
of the potential variety and might have fostered stereotypes. We derived the
solution with information about co-passengers based on existing research
findings [11, 12] and aimed to evaluate whether the availability positively
influences security, UX, trust, and acceptance of SAMoD passengers. By no
means we intended to manifest potential stereotypes or the exclusion of people
through our selection. However, we want to point out that the selection likely
affects the results (e.g., people might refuse rides with others due to their
"look"). We are aware that the gender and age of other passengers is a limited
view. Other factors, such as race, appearance, or the supposedly associated
social statuses definitely play a role in people’s assumptions about other
people. However, we did not include more personal characteristics to 1) not
confound too many different independent variables in the display variants and
2) we wanted to draw a clear line between evaluating the information about
other passengers and participants’ potential biases about, e.g., other
cultures, as we aimed for the former.

###  5.5 Future Work

Passengers’ information demands in SAMoD systems are a highly complex and
context-dependent issue requiring more research, especially on how to overcome
the conflict between security and privacy by design.

Based on our results, we suggest extending the conduct of context-based
empirical studies investigating factors like daytime and fellow passengers in
SAMoD systems along the whole travel journey. Since, e.g., security issues are
relevant for the booking, the ride itself, and on-/off-boarding [11]. While
our study focused on the ride itself, further (empirical) studies should also
consider the booking phase and the off-boarding when investigating the effect
of co-travelers and time of day on passengers’ need for information and
controls. Here, additional information and safety measures (e.g.,
emergency/support button) might support passengers’ feeling of control and
security. To yield results with high external validity, future studies might
include more contextual factors such as the (physical) presence of various and
multiple other people in SAMoD rides during different situations. E.g., actors
could be used to mimic specific situations [46].

It would also be interesting to repeat this study in different cultural
contexts, as we conducted our study in Germany, where security in public
transportation offers high levels of security [95]. However, we assume that
conducting similar studies in countries, such as India or Latin American
countries, where public transportation is more difficult to access –
especially for women [90] – might yield different results. The applied
simulation environment presents a context-based prototyping approach that can
be used, e.g., to replicate this or similar studies in other countries and
investigate potential cultural differences regarding passengers’ (information)
requirements. Future work might also consider the potential impact of culture
and race as an independent variable in the information display. This could
result in an exploration of people’s explicit and implicit biases based on
given prior knowledge.

We used the front of the vehicle as the output location of the information, as
these are common modalities [40]. Future concepts might also investigate
whether (the combination with) other modalities, such as tactile, influence
the perception of the presented information and the feeling of security.

##  6 Conclusion

In this paper, we report on a simulator user study ($N=24$) investigating the
effects of time of day and provided information on fellow travelers on SAMoD
passengers’ UX, acceptance, feeling of security, and emotions in shared
automated rides. While the evaluated SAMoD system received excellent
assessments of hedonic and pragmatic UX, trust, and acceptance, participants
emphasized security concerns – mainly when using SAMoD at night. Furthermore,
both women and men preferred sharing rides with women over sharing rides with
men as co-passengers during the night, whereas, during the day, this
information negatively affected participants’ evaluation of the SAMoD system.
Associated risks were experienced lower when participants were provided with
information about their co-passengers. Most participants generally preferred
having information on co-passengers, with photos of fellow travelers
considered the most important information element. However, our results yield
ambiguities since providing personal information also triggered privacy
concerns among participants. This can be taken as an illustration of the
complexity of psychological security and its context dependency. Building upon
these findings, providing UIs with information on fellow passengers can
support SAMoD passengers’ feeling of security in shared rides and potentially
improve UX, user acceptance, and overall system resilience. However, due to
privacy concerns and associated risks, the timing and placement of the
information need to be questioned. It might be beneficial to provide this
information during the booking phase but not within the vehicle. Future work
should consider the whole travel journey of SAMoD, foster the inclusion of
contextual factors, and investigate how the provision of additional
information and safety measures (e.g., emergency and support features) can
increase passengers’ feeling of control and security.

##  7 Acknowledgements

This research was partly funded by the German Federal Ministry for Economic
Affairs and Climate Action (BMWK) under grant number 19A21047I (SUE) and by
the German Federal Ministry of Transport and Digital Infrastructure (BMVI)
under grant number 16AVF2134G (APEROL). We want to thank Claus Pfeilschifter
for the technical support and Tatjana Röhr for the support in the study
conduct and data analysis. Furthermore, we want to thank the study
participants for their participation and the anonymous reviewers for their
time and helpful feedback.

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