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Scoping Out the Scalability Issues of Autonomous
Vehicle-Pedestrian Interaction
Tram Thi Minh Tran
tram.tran@sydney.edu.au
Design Lab, Sydney School of
Architecture, Design and Planning,
The University of Sydney
Sydney, NSW, Australia
Callum Parker
callum.parker@sydney.edu.au
Design Lab, Sydney School of
Architecture, Design and Planning,
The University of Sydney
Sydney, NSW, Australia
Martin Tomitsch
martin.tomitsch@sydney.edu.au
Design Lab, Sydney School of
Architecture, Design and Planning,
The University of Sydney
Sydney, NSW, Australia
ABSTRACT
Autonomous vehicles (AVs) may use external interfaces, such as
LED light bands, to communicate with pedestrians safely and intu-
itively. While previous research has demonstrated the eectiveness
of these interfaces in simple trac scenarios involving one pedes-
trian and one vehicle, their performance in more complex scenarios
with multiple road users remains unclear. The scalability of AV
external communication has therefore attracted increasing atten-
tion, prompting the need for further investigation. This scoping
review synthesises information from 54 papers to identify seven
key scalability issues in multi-vehicle and multi-pedestrian envi-
ronments, with Clarity of Recipients, Information Overload, and
Multi-Lane Safety emerging as the most pressing concerns. To guide
future research in scalable AV-pedestrian interactions, we propose
high-level design directions focused on three communication loci:
vehicle, infrastructure, and pedestrian. Our work contributes the
groundwork and a roadmap for designing simplied, coordinated,
and targeted external AV communication, ultimately improving
safety and eciency in complex trac scenarios.
CCS CONCEPTS
•General and reference →Surveys and overviews.
KEYWORDS
autonomous vehicles, external communication, eHMIs, vulnerable
road users, vehicle-pedestrian interaction, scalability
ACM Reference Format:
Tram Thi Minh Tran, Callum Parker, and Martin Tomitsch. 2023. Scoping
Out the Scalability Issues of Autonomous Vehicle-Pedestrian Interaction. In
15th International Conference on Automotive User Interfaces and Interactive
Vehicular Applications (AutomotiveUI ’23), September 18–22, 2023, Ingolstadt,
Germany. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/
3580585.3607167
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AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany
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ACM ISBN 979-8-4007-0105-4/23/09. . . $15.00
https://doi.org/10.1145/3580585.3607167
1 INTRODUCTION
Autonomous vehicles (AVs) are often hailed as a safer alternative to
human drivers because they can react faster and more accurately
to hazards on the road [
3
,
33
]. However, before AVs can be safely
integrated into our transportation system, certain roadblocks must
be overcome, including the ability of AVs to communicate and
interact seamlessly with vulnerable road users (VRUs), such as
pedestrians [
36
,
70
]. The absence of interpersonal cues, such as
drivers’ hand signals and eye contact, is likely to cause uncertainty
and misunderstanding for pedestrians in ambiguous situations. To
address this challenge, researchers and the automotive industry
are investigating the use of external Human-Machine Interfaces
(eHMIs) as a way for AVs to communicate with pedestrians [
22
,
24
,
74
]. For example, the Mercedes-Benz F015 concept projects
a pedestrian crossing onto the road to provide pedestrians with
important information about the vehicle’s intended actions [63].
The study of AV external communication has seen signicant
growth in recent years, leading to a plethora of eHMI design con-
cepts that can be classied in various ways [
24
]. These interfaces are
often evaluated using scenario-based approaches, initially focusing
on basic encounters between a single AV and a pedestrian [
20
,
83
].
Preliminary evidence suggests that eHMIs may help to alleviate
uncertainty [
44
] and foster trust [
32
] in AVs. As such, the automo-
tive research community within the eld of HCI is increasingly
exploring the scalability of eHMIs in more complex trac scenarios
involving multiple road users.
Existing literature on AV external communication includes sev-
eral notable works that delve into the scalability of eHMIs. In their
literature analysis, Colley et al
. [20]
examined evaluation setups of
38 studies with regard to scalability factors (number of pedestri-
ans, vehicles, lanes, and noise). Colley and Rukzio
[18]
proposed
a design space that incorporated situational factors that aect the
scalability of eHMIs, such as communication relationships (one-
to-one, one-to-many, many-to-one, and many-to-many). Dey et al
.
[24]
developed a classication taxonomy for eHMIs and highlighted
scalability-related dimensions of a design concept, including com-
munication strategy (mass or targeted), communication resolution
(clarity of the intended recipients), and the number of users that
can be addressed at a time. However, to date, no comprehensive
review of the scalability issues that may arise has been conducted,
limiting a thorough understanding of the community’s collective
challenges to inform future research eorts.
In this study, we conducted a scoping review of AV external
communication from 2014 - 2022 to identify scalability issues that
have been discussed and/or empirically observed. These issues are
167
AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany Tran et al.
categorised into two groups: those caused by the increase in the
number of AVs (as well as mixed trac
1
) and those caused by the
increase in the number of pedestrians. Considering the most press-
ing issues, we pinpointed essential communication qualities for
eHMIs to excel in complex trac scenarios and propose high-level
research directions focused on three communication loci: vehicle,
infrastructure, and pedestrian.
Contribution Statement: This study contributes to the domain
of AV external communication within HCI by oering a compre-
hensive review of the scalability issues of eHMIs in complex trac
scenarios. Our analysis illustrates the attention these issues have
received within the automotive research community and introduces
high-level approaches to address them. The study aims to inform
the development of more eective and scalable eHMIs, ultimately
contributing to the safe integration of AVs into the transport sys-
tems of future cities.
2 METHODS
We conducted a scoping review, a preliminary assessment of the
available literature on a particular topic, following the methodolog-
ical framework proposed by Arksey and O’Malley [5].
2.1 Data Sources and Search Strategies
We retrieved relevant literature on AV external communication
from four major databases: ACM Digital Library, IEEE Xplore, Sci-
enceDirect, and Google Scholar. We performed a keyword search
(within the title, abstract, and author keywords) using a query
adapted from Dey et al
. [24]
:‘autonomous OR automated OR self-
driving OR driverless AND car OR vehicle AND pedestrian AND
interface OR interaction OR communication’ (see Appendix A for
the exact query syntax used for each database). We did not use
‘scalability’ as a keyword because not all publications explicitly
used this term. We limited the search results to publications dated
between 2014 and 2022, which corresponds to a period of acceler-
ated development in eHMI concepts [
24
]. The last search date was
October 22, 2022.
Our search query yielded 1305 entries (ACM = 233, IEEE Xplore
= 461, ScienceDirect = 111, Google Scholar
2
= 500). After importing
research results to a spreadsheet and removing 230 duplicates, 1075
publications remained to be screened.
2.2 Eligibility Criteria and Paper Selection
We included papers that met the following criteria:
•
Language: The paper must be written in English, the primary
language of the research team.
•
Publication type: We considered full conference papers, late-
breaking work (work in progress), journal articles, and tech-
nical reports, allowing for a comprehensive and timely un-
derstanding of the topic.
•
Relevance: The paper should focus on AV external commu-
nication. Furthermore, it must discuss and/or investigate the
1
Mixed trac refers to situations in which AVs must interact with human-driven
vehicles on the same roads.
2
The search on Google Scholar returned a large number of entries 19,100; therefore,
we decided to conclude the search at page 50 after three consecutive pages of not
nding any relevant entries.
scalability of eHMIs in complex trac scenarios involving
multiple vehicles or pedestrians.
Our goal was to identify not only distinct arguments but also
monitor the frequency of scalability discussions, leading us to in-
clude publications with similar viewpoints. We excluded papers
that, despite featuring a multi-user setup, did not contain any in-
formation about the scalability of eHMIs. For example, the virtual
environment in the study by Böckle et al
. [11]
included a vehicle in
the adjacent lane alongside the autonomous shuttle; however, the
presence of the additional vehicle was not the main focus of the
research, it had no textual description, and it did not demonstrate
any reported impact on the ndings.
The rst author conducted the screening of the 1075 papers in
two stages. In the initial stage, titles and abstracts were assessed for
their relevance to AV external communication, resulting in 230 pa-
pers. The subsequent stage involved a thorough review of full-text
papers to determine the presence of eHMI scalability information,
resulting in 46 papers. Additional eligible papers were incorporated
from the references of the aforementioned related works [
18
,
20
,
24
],
as well as from recently published papers not initially captured in
the search. This brought the total number of publications to be
analysed to 54. A PRISMA (Preferred Reporting Items for System-
atic Reviews and Meta-Analyses) ow diagram, which illustrates
the inclusion and exclusion of papers throughout each stage of the
review process, along with a list of included publications, can be
found in Appendix B.
2.3 Data Charting and Data Analysis
The rst author charted the following details from each included
paper: author, year, title and eHMI scalability information (quoted in
the authors’ original words). For papers featuring empirical studies
that examined eHMIs in complex trac situations, additional data
on eHMI design concept, eHMI placement (locus), positions of
additional pedestrians, trac type (mixed or all AVs), and evaluation
method were also recorded.
During the familiarisation phase with the data, it was observed
that the information related to eHMI scalability issues was largely
well-dened, suggesting a lower likelihood of varying interpreta-
tions. For instance, a statement like ‘the increase in the cognitive
load imposed on a pedestrian as the number of AVs with LED boards
increases’ [
72
] denotes an issue of information overload. As a re-
sult, a single coder with subject matter expertise was engaged to
ensure uniformity throughout the analysis process. The rst author
undertook a thematic analysis [
12
] of the collected scalability infor-
mation, applying the anity diagramming method. This analysis
process employed a bottom-up approach, consolidating discussions
around similar issues and resulting in the identication of seven
distinct themes corresponding to seven scalability issues: Informa-
tion Overload,Multi-Lane Safety,Audibility,Clarity of Recipients,
Group Inuence,Visibility, and Privacy. Additionally, a top-down
approach was utilised to categorise these issues into two groups:
those that arise in scenarios involving multiple vehicles, and those
surfacing in scenarios with multiple pedestrians.
To mitigate the risk of bias or oversight in this setup, weekly
discussions were scheduled with the second author during the cod-
ing process. Upon identifying the nal issues, they were presented,
168
eHMI Scalability Issues AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany
along with their associated scenarios and underlying causes, to the
remaining authors to determine whether they agreed with these
ndings or had additional insights. Although the identied scalabil-
ity issues remained unchanged after the validation process, several
critical discussions emerged. Primarily, the top-down division may
inadvertently simplify the intricate nature of the interactions at
play. Indeed, some issues may not be strictly conned to either a
multi-vehicle or a multi-pedestrian scenario; instances where they
cross these boundaries exist. Consider Information Overload, this
issue is classied under multi-vehicle scenarios, but it could also
occur in a multi-pedestrian situation. Imagine a single AV that must
communicate with multiple pedestrians dispersed in various loca-
tions. Simultaneously processing these multiple signals could lead
to information overload for the pedestrian. Despite this potential
overlap, we maintain the division to highlight the context where
the issue is most likely to surface, thus facilitating a more targeted
approach to addressing these issues.
3 RESULTS
3.1 Scalability Issues
In Table 1, we categorised eHMI-related scalability issues into those
relating to multiple vehicles and those concerning multiple pedestri-
ans. We also highlighted empirical studies that examined eHMIs
in multi-vehicle and/or multi-pedestrian scenarios. In Table 2, we
summarised the commonalities of these empirical studies.
3.1.1 Information Overload. This concern has been raised as early
as initial investigations into eHMIs. The term generally refers to
a situation where the amount of information provided exceeds a
person’s cognitive processing capacity, resulting in poor decision
quality [
30
,
37
]. Moore et al
. [65]
were among the scholars arguing
that the eHMIs might transform street-crossing into an ‘analytical
process’ and suggested the use of implicit motion cues for routine
interactions. In classifying 70 eHMI concepts proposed by industry
and academia, Dey et al
. [24]
also found that many designs utilised
multiple modalities and displays (i.e., communication devices) and
conveyed numerous messages. The authors thus emphasised the
crucial need for creating a balance between leveraging redundancy
(to foster interpretation and accuracy of use) and avoiding informa-
tion overload. Mahadevan et al
. [62]
conrmed this issue, where
the study participants responded unfavourably to a mixed interface
consisting of LED lights on the street, a printed hand mounted on
the vehicle, and an auditory alert from a smartphone. The interface
was deemed confusing and time-consuming as pedestrians had to
wait for all go-ahead signals to be activated. Nonetheless, reducing
the number of stimuli may not necessarily result in a reduced cog-
nitive load. For example, participants in a study by Dey et al
. [23]
preferred to have eHMIs communicate an AV’s intent at all times
rather than only during interactions (e.g., giving way).
A proliferation of AVs on urban streets is expected to exac-
erbate the issue of information overload in several ways. First,
without a standardised universal set of symbols, manufacturers
may adopt dierent interface designs to communicate a vehicle’s
awareness and intents [
87
]. Second, a dynamic trac scenario
may involve AVs with various levels of automation (e.g., partially
and fully automated) [
47
,
48
] and in dierent states of operation
(e.g., cruising and stopping) [
23
]. The increased number of inter-
faces and their myriad dierences are expected to cause a signi-
cant amount of visual clutter and demand greater attention from
pedestrians [
23
,
47
,
72
,
76
,
88
]. Information overload could easily
lead to the inability to identify the most critical pieces of informa-
tion [
23
,
73
] and, thus, pose a high level of safety risks [
47
,
48
].
Trac eciency may also be adversely aected in multi-lane cross-
ing scenarios where pedestrians must process multiple cues to cross
the road safely [
46
,
89
]. Holländer et al
. [46]
found that the indi-
vidual AV signals (e.g., projected crosswalks) caused participants
to stay longer in the rst lane while waiting for the second lane
to clear. Consequently, several studies have aimed to combine in-
formation from multiple vehicles and provide pedestrians with an
augmented reality (AR) safety corridor [41,80,84].
3.1.2 Multi-Lane Safety. In a mixed trac environment, pedestri-
ans are likely to encounter AVs with varying degrees of automation
alongside conventional vehicles. In light of this, Mok et al
. [64]
and Moore et al
. [65]
mentioned the risks of eHMIs diverting pedes-
trian attention away from other road users and their motion cues.
A VR-based study investigating pedestrian crossing behaviour in
mixed trac [
61
], however, revealed that participants acted more
cautiously when encountering vehicles that did not communicate
explicitly (i.e., those without an interface).
Multi-vehicle scenarios and mixed trac conditions also necessi-
tate caution in selecting the message perspective for eHMIs. Studies
have found that egocentric messages suggesting a pedestrian action,
such as ‘Walk’, have higher clarity ratings and faster response times
compared to allocentric messages communicating the AV’s intent
and states, such as ‘Braking’ [
29
]. As stated by Eisma et al
. [29]
,
the former perspective explains why AVs are stopping and does
not require pedestrians to shift their mental perspective. Nonethe-
less,eHMI-design best practices are moving away from the use of
advice and instructions due to concerns about safety and liability
issues (e.g., ISO/TR 23049:2018 [
35
]). Firstly, instructional eHMIs
may lessen pedestrians’ responsibility in making crossing deci-
sions, leading to an overreliance on the user interface [
62
]. More
importantly, such eHMIs risk creating a false expectation of the
state of the surrounding (mixed) trac, which is beyond the AV’s
control [
4
,
22
,
24
,
39
,
44
,
54
]. For instance, a design concept where
a zebra-crossing is projected onto the area in front of the vehicle
could lead pedestrians to cross the subsequent lane when it might
not be safe to do so [
46
,
58
]. Given this, Löcken et al
. [58]
and Colley
et al
. [17]
emphasised the importance of AVs considering the status
of the other lanes when providing a crossing signal to pedestri-
ans. One example involves the concept of the omniscient narrator,
where a vehicle changes the communication message based on its
knowledge of the trac situation [19].
3.1.3 Audibility. Mahadevan et al
. [62]
posited that multiple un-
synchronised AVs communicating with pedestrians using audio
messages may result in unpleasant noise rather than benecial
information. Investigating a trac scenario with two AVs oering
auditory cues, Colley et al
. [19]
found that some participants heard
only one message or an echo when the vehicles arrived simulta-
neously. Furthermore, in densely populated urban areas, auditory
cues may be drowned out by the noise arising from the high vehicle
volume on the streets [61].
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AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany Tran et al.
Table 1: Scalability issues of eHMIs in multi-vehicle and multi-pedestrian scenarios.
Scalability issues Studies*
(15) Information Overload [41] [46] [47] [73] [84][23] [24] [48] [62] [65] [72] [76] [87] [88] [89]
(14) Multi-Lane Safety [19] [46] [61][4] [17] [22] [24] [29] [39] [44] [54] [58] [64] [65]
(3) Audibility [19] [61][62]
(30) Clarity of Recipients
[
16
] [
27
] [
28
] [
43
] [
46
] [
47
] [
84
] [
90
][
1
] [
2
] [
9
] [
22
] [
24
] [
25
] [
26
] [
29
]
[38] [40] [44] [51] [52] [54] [56] [69] [72] [76] [78] [79] [80] [88]
(5) Group Inuence [15] [50] [61] [14][55]
(5) Visibility [85][6] [31] [71] [88]
(1) Privacy [57]
*Bold citations refer to empirical studies that examined eHMIs in multi-vehicle and/or multi-pedestrian scenarios.
Table 2: Empirical studies examining eHMIs in multi-vehicle or multi-pedestrian scenarios.
References eHMI Locus Pedestrians*Vehicles Environment**
Troel-Madec et al. [85] Lateral LED display Vehicle - Multi AVs Virtual reality (VR)
Rossi-Alvarez et al. [73] LED light band Vehicle - Multi AVs Test track
Hesenius et al. [41] Wearable AR Pedestrian - Multi AVs Image
Tran et al. [84] Wearable AR Pedestrian - Multi AVs VR
Colley et al. [19] Auditory message Vehicle - Multi AVs VR
Holländer et al. [46] Projection, Smart curbs
Vehicle, Infrastructure
Opposite side Multi AVs VR
Dietrich et al. [28] Projection, Signaling light Vehicle Opposite side - VR
Colley et al. [16] Texts on windshield Vehicle Opposite side - VR
Wilbrink et al. [90] LED light band Vehicle Same, Opposite side - Video
Holländer et al. [47] Smartphone Pedestrian Same side Multi AVs Video
Hoggenmüller et al. [43] LED light band Vehicle Same side - VR
Dey et al. [27] Contextual interfaces Vehicle Same side - VR
Colley et al. [15] LED light band Vehicle Group - VR
Joisten et al. [50] Walking man, Smiling face Vehicle Group - VR
Chen et al. [14] LED light band Vehicle Group Mixed trac Public roads
Mahadevan et al. [61]
Mixed (LED light, physical hand,
haptic cue, auditory message)
Vehicle, Infrastructure,
Pedestrian
Group Mixed trac VR
*Additional pedestrian(s) in the scenario: forming a group with the participant or standing at a distance (same side or opposite side).
**Evaluation environment
3.1.4 Clarity of Recipients. Directing eHMI communication mes-
sages at specic recipients is deemed imperative to ensure that
pedestrians are condent they are being addressed by the AV, anal-
ogous to the acknowledgement conveyed by human eye contact. A
study investigating dierent light-based eHMIs in a shared space
setting revealed that most participants noticed the signal but did not
assume it was intended for them, even though the scene involved
only one pedestrian [40].
The directedness of eHMIs may be further compromised when
multiple pedestrians are present, potentially leading to misunder-
standings about which pedestrian the AV is attempting to com-
municate with [
1
,
2
,
9
,
16
,
22
,
24
–
29
,
38
,
43
,
44
,
46
,
47
,
51
,
52
,
54
,
56
,
69
,
72
,
76
,
78
–
80
,
84
,
88
,
90
]. Studies have highlighted that the
presence of other pedestrians introduces uncertainty to crossing
scenarios [
90
] and reduces the communication clarity of eHMIs [
16
].
Moreover, non-directed eHMIs signicantly increased a pedes-
trian’s willingness to cross compared to the baseline condition with
no eHMI [
27
,
90
], even in scenarios where the yielding message
was intended for another [
27
]. This nding suggests that without
clear and directed communication, pedestrians are more likely to
misinterpret AV communication and respond inappropriately, re-
sulting in severe consequences in real-world trac situations [
27
].
Notably, the likelihood of undesirable or adverse outcomes may
increase when eHMIs give commands or instruct pedestrians to
cross [
1
,
22
,
29
,
44
,
52
,
54
,
72
,
76
,
79
]; a display that signals ‘Go
ahead’, for instance, could prompt non-targeted pedestrians to en-
gage in risky behaviour.
3.1.5 Group Influence. Research has indicated that pedestrians
crossing in groups tend to be more careless and pay less attention
to crosswalks and approaching trac [
70
]. It is, therefore, of value
to determine whether such group inuence remains when pedes-
trians interact with AVs equipped with eHMIs [
55
]. Mahadevan
et al
. [61]
investigated the scenario of AI-based agents with dier-
ent crossing behaviours (none, early crossers, and timely crossers)
crossing the road alongside the participants in mixed trac. Al-
though the agents’ behaviours did not signicantly impact the
participants’ willingness to cross, half of the participants indicated
that the agents may have aected their crossing strategy. In their
observation study, Chen et al
. [14]
found stronger evidence of the
prevalence of herd behaviour among pedestrians, with most in-
dividuals in a group crossing situation not making any eort to
observe the trac if another person was already present in the
crosswalk. To investigate whether the eect of eHMIs is stronger
than the inuence of group pedestrian behaviour, Colley et al
. [15]
examined a situation where virtual pedestrians in close proximity to
the participants ignored the AV’s non-yielding intention. Although
the authors were unable to determine which factor had a greater
170
eHMI Scalability Issues AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany
impact, they found that eHMIs continue to positively aect trust,
cognitive load, and communication quality.
It should be noted that the actual behaviour of other pedestrians,
rather than their mere presence, impacts participants’ crossing
behaviour [
15
,
16
,
50
]. For instance, a standing pedestrian group
that did not engage in any specic action (e.g., step onto the street to
cross) had no eect on participants’ crossing duration [
16
] and did
not induce any imitable behaviour [
50
]. Nonetheless, participants
in the study by Joisten et al
. [50]
felt that crossing the street in a
group increased their safety and condence as they believed the
AV could more easily detect a group than a single pedestrian.
3.1.6 Visibility. An eHMI display located on the exterior of a ve-
hicle or projected onto the road might present visibility issues,
especially in shared spaces where pedestrians approach from vari-
ous directions [
31
,
71
]. A co-design study conducted by Asha et al
.
[6]
also revealed that wheelchair users may encounter various vi-
sual obstructions, such as roadside elements and the presence of
other pedestrians. A line of multiple vehicles one after the other
further complicates the visibility of eHMIs. According to 3D simula-
tion results [
85
], a frontal eHMI display is optimal only if a vehicle
is the rst one in a lane. This issue has led to the incorporation
of multiple displays [
60
], a 360-degree LED light band [
13
], or a
roof-mounted cylindrical interface [88] in several eHMI concepts.
3.1.7 Privacy. In ride-sharing scenarios, directed eHMIs can help
pedestrians identify the AV that is trying to pick them up [
38
].
However, eHMIs that disclose private information have received
negative evaluations [
57
]. Rather, when the goal is to easily locate
a car in a crowd, using a distinctive colour or graphical symbol or
comprising a combination of letters and numbers has been deemed
acceptable [
13
,
43
,
57
]. Anthropomorphic robotic eyes that can
convey ne-grained turning directions may also aid in identica-
tion [38].
3.2 General Remarks
3.2.1 Research Foci. The Clarity of Recipients (55.6%, 30) has formed
the primary concern of the research community, followed by Infor-
mation Overload (27.8%, 15) and Multi-Lane Safety (25.9%, 14). This
may be the case since the issue of recipient clarity extends beyond
scenarios involving multiple pedestrians. In addition to pedestri-
ans, other VRUs, such as cyclists [
45
], and drivers of conventional
vehicles may also benet from AV explicit communication. The
inclusion of these diverse trac participants may signicantly in-
crease the complexity of ensuring that AV communication reaches
the intended road users. For instance, in examining the implicit
and explicit communication of an AV interacting simultaneously
with a pedestrian and a driver of a conventional vehicle, Hübner
et al
. [49]
highlighted an issue with recipient clarity, as a majority
of the participants reported feeling wrongly addressed when the
AV signalled the right of way to the other human road user.
Out of 54 selected papers, 16 (29.6%) were empirical studies,
suggesting that researchers are actively investigating eHMI scala-
bility and seeking evidence to support their hypotheses and ideas.
However, it also indicates that there may still be room for more em-
pirical research to solidify the knowledge base in this area. Within
this context, researchers have taken dierent approaches. Some
have assessed established design concepts, such as the LED light
bands, in more complex trac scenarios [
15
,
27
,
73
,
90
]. These
studies contribute valuable insights regarding the underlying con-
ditions, the severity of scalability issues, and whether they are
signicant enough to warrant further investigation. In contrast,
other researchers have proposed new design concepts to address
specic scalability issues, such as Smart Curbs [
46
] and wearable AR
solutions [
41
,
84
]. It should be noted that at the time of the review,
several new concepts had not undergone formal evaluation [
80
,
88
]
and were not counted as empirical studies. Nonetheless, the emer-
gence of these ideas further emphasised the growing interest and
innovation in scaling up AV external communication.
3.2.2 Evaluation Method. The identied empirical studies have
been largely conducted in a controlled laboratory environment,
with VR simulations being the most frequently used prototype
representation (62.5%). This nding suggests that VR is a suitable
test bed for exploring the scalability of eHMIs as it allows for the
design and evaluation of novel design concepts under various traf-
c scenarios while ensuring the safety of participants. According
to a review of VR studies on AV–pedestrian interaction [
83
], the
eectiveness of VR simulations could be further enhanced through
the use of more realistic AV driving behaviour and the inclusion
of other road users in the same scenario using coupled/distributed
simulators [
8
]. The latter approach is particularly appealing as it is
currently unclear how the use of human-controlled avatars rather
than AI virtual agents might impact group inuence and the clarity
of recipients.
Notably, two of the studies evaluated eHMIs in a more realis-
tic environment (i.e., a closed test track facility [
73
] and public
roads [
14
]). Rossi-Alvarez et al
. [73]
conrmed some problems pre-
viously identied in VR simulations [
84
], such as participants miss-
ing eHMI light patterns due to looking back and forth between
the two AVs. Meanwhile, in their public experiment, Chen et al
.
[14]
observed a stronger eect of group inuence on pedestrians’
crossing behaviour. In both studies, the use of physical prototypes
helped elucidate how the visibility of the interface was aected by
factors such as the sun or the angle at which it was viewed [
14
,
73
].
These ndings demonstrate the value of evaluating AV external
communication under real-world trac conditions.
4 DISCUSSION
Despite the growing number of relevant empirical studies in recent
years, the most pressing scalability issues of eHMIs have yet to be
fully resolved. As a rst step to structure future research eorts, we
propose overarching research directions aimed at designing scalable
AV-pedestrian interactions and reect on the study limitations.
4.1 Research Directions based on
Communication Locus
According to the comprehensive review by Dey et al
. [24]
, around
two-thirds of existing eHMI design concepts incorporated visual
and auditory cues onto vehicles. This underlines the necessity
for scalable vehicle-based eHMIs. Nevertheless, researchers have
also proposed extravehicular solutions such as urban infrastruc-
tures and pedestrians’ personal devices (e.g., wearables and smart-
phones) [
24
,
27
,
79
]. As a result, three distinct communication loci,
171
AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany Tran et al.
vehicle-based, infrastructure-based, and pedestrian device-based,
are being explored simultaneously as potential solutions to address
eHMI scalability issues. This section revisits the denition and char-
acteristics of communication locus, aiming to establish a common
understanding within the research community before delving into
their potential in facilitating simplied communication (presenting
information in a clear, concise, and easily understandable manner),
coordinated communication (synchronising and harmonising the
exchange of information between dierent systems), and targeted
communication (providing the right information to the right recip-
ients at the right time). These three communication qualities are
identied as particularly relevant in overcoming the most signi-
cant challenges related to eHMI scalability.
The locus of AV communication, or interface location, was orig-
inally dened by Mahadevan et al
. [62]
in a participatory design
study. This design dimension includes four categories based on
where participants placed their interfaces: (1) vehicle-only, (2) vehi-
cle and infrastructure, (3) vehicle and pedestrian, and (4) mixed. In
this proposal, while the vehicle is always responsible for communi-
cating with pedestrians, this responsibility may be shared with road
infrastructures (e.g., trac lights) and pedestrians’ personal devices
(e.g., smartphones). In the design space for AV external communica-
tion proposed by Colley and Rukzio
[18]
, the communication locus
remains the same, though the categories are revised to represent
independent placements, including those of the vehicle, infrastruc-
ture, and pedestrian. In this paper, we classied projection-based
eHMIs (e.g., [
66
]) as part of the vehicle category, mainly because
the projections originate from and reect the vehicle’s intentions
even though they are not physically located on the vehicle.
The primary distinction between infrastructure and pedestrian-
based eHMIs versus vehicle-based eHMIs is that the communication
signals are detached from the vehicle. Being detached eHMIs, there
exists two dierent roles infrastructures and personal devices can
play:
•
As communication outlets: In this role, infrastructures and
personal devices transmit communication signals from AVs
to pedestrians. For instance, Mahadevan et al
. [62]
used a
smartphone to relay the message ‘I can see you’ to pedestri-
ans [
62
]. However, their ndings showed that pedestrians
considered this type of message more reliable when it origi-
nated from the vehicle rather than a third-party source, as it
is closely connected to the vehicle’s operation.
•
As communication sources: In this second role, infrastruc-
tures serve to facilitate trac, such as the Starling Cross-
ing, which adjusts its road markings in real time to guide
pedestrians, cyclists, and drivers [
86
]. On the other hand,
pedestrian devices oer personal guidance for navigating
the environment; for example, a smartphone application
might provide on-screen directions to enhance pedestrian
situational awareness while crossing roads [47].
Distinguishing between these two roles is crucial because they
may have diverse safety and liability implications, varied user ex-
periences, and dierent technical requirements in terms of hard-
ware, software, and communication protocols. Furthermore, the
second role goes beyond the classic understanding of eHMIs, which
mainly involve external interfaces that convey AV intentions and
operational states to pedestrians and other VRUs. In the context
of designing scalable AV-pedestrian interaction, our focus will be
solely on the second role.
4.1.1 Vehicle-based: In densely populated urban areas, the pres-
ence of numerous vehicles each equipped with a unique eHMI can
potentially increase the visual and auditory stimuli, contributing
to an already dynamic and possibly overwhelming environment.
Given the abundance of proposed eHMI design concepts, standard-
isation emerges as an essential and imminent direction to achieve
simplied communication. Standardised cues not only make the
learning process easier for road users but also reduce the variety of
cues they encounter. This uniformity lessens the cognitive eort
involved in interpreting and reacting to eHMI signals. The notion
of less cognitive demand is based on the principle of cognitive econ-
omy, [
21
] where our minds seek to minimise the amount of mental
eort spent on processing stimuli. International Organisation for
Standardisation (ISO) has established a working group
3
(ISO/TC
22/SC 39/WG 8) dedicated to advanced driver assistance systems,
automated driving, and eHMI standardisation for external com-
munication. The process of standardising eHMIs is intricate and
ongoing, requiring close collaboration among diverse stakeholders
in the automotive industry. These stakeholders must determine
which dimensions to standardise while considering individual, cul-
tural, and regulatory dierences to ensure the eectiveness and
widespread adoption of the resulting standards.
One important research direction in the development of eHMIs
is determining under which circumstances eHMIs are truly neces-
sary, as opposed to maintaining an always-on mode of operation.
This approach may help to prevent excessive stimuli and conserve
system resources such as energy and processing power. In line with
this, Dey et al
. [23]
examined the need for an eHMI to communi-
cate an AV’s non-yielding intent. However, the ndings indicated a
preference for eHMIs that communicate an AV’s intent explicitly
at all times, highlighting the need to determine a threshold beyond
which the information provided becomes detrimental [62].
Another solution involves using interconnected eHMIs, where
a single vehicle communicates the intentions of all other vehicles
in the vicinity [
19
,
46
]. Such eHMIs, enabled by connected vehi-
cle technology, can potentially lower pedestrians’ cognitive load
by minimising the number of communicating AVs and enhance
pedestrians’ safety in heavy trac by tailoring the communication
to the prevailing trac conditions. However, preliminary ndings
have been mixed due to pedestrians’ unfamiliarity with the con-
cept of connected vehicles [
19
]. From a technical perspective, the
interconnected eHMI approach adds complexity to communica-
tion protocols, such as deciding which AV takes on the primary
communication role. Addressing potential challenges related to
data security and issues like delays or loss of connectivity is also
crucial to maintain pedestrian safety. As a result, further research
is necessary to determine the viability of interconnected eHMIs
as a design concept, taking into account both human factors and
implementation feasibility.
With respect to targeted communication, vehicle-based eHMIs
can direct their messages in a specic direction. For example, Gui
et al
. [38]
investigated how robotic eye gazes can convey an AV’s
3https://www.iso.org/committee/5391225.html, last accessed April 2023
172
eHMI Scalability Issues AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany
ne-grained moving directions, enabling pedestrians to clear the
path in an open space or determine if the AV (taxi) intends to pick
them up. The Volvo 360c concept incorporated directional warn-
ing sounds aimed at pedestrians who unexpectedly step onto the
road [
13
]. Kaup et al
. [53]
proposed the concept of directed signal
lamps capable of addressing multiple road users separately with dis-
crete light channels. Another approach to achieving targeted com-
munication involves presenting a pedestrian’s position on an eHMI
display in a simplied schematic form (e.g., a dot [
88
] or a strip [
67
])
or adjusting communication based on the distance between the
vehicle and the pedestrian (distance-dependent eHMIs) [
24
,
25
].
According to the taxonomy established by Dey et al
. [24]
, all these
design concepts can be classied as partially scalable, meaning they
can address multiple road users concurrently but only to a certain
extent. We argue that this limited degree of scalability may not
necessarily be viewed a drawback, given that most trac situa-
tions and interactions usually involve a manageable number of
road users. Instead, the more critical aspect is the eHMI’s ability
to deliver unambiguous information about whether it is safe for
specic road users to proceed. For example, road projections visual-
ising the precise location at which the vehicle will stop can clearly
convey the intended recipient [
23
]. As a result, high communication
resolution should be made a key design goal for eHMIs and must
be thoroughly assessed in scenarios that are likely to occur, such
as urban intersections and pick-up/drop-o zones.
4.1.2 Infrastructure-based: The majority of infrastructure-based
design concepts leverage existing trac elements that are both
familiar to pedestrians and universally understood, such as ze-
bra crossings [
42
,
59
,
86
]. By integrating interactive features into
these well-known elements, infrastructure-based designs may en-
able pedestrians to quickly adapt to the new systems without fac-
ing a steep learning curve. In situations with multiple vehicles,
infrastructure-based systems provide a centralised source of infor-
mation for pedestrians, making it easier to process the data without
having to attend to multiple vehicle-based displays simultaneously.
One primary advantage of infrastructure-based concepts in co-
ordinated and targeted communication lies in their integration of
adaptive trac management systems. These systems can dynami-
cally adjust trac control measures by leveraging real-time trac
data gathered from various sources, such as sensors, cameras, and
connected networks. For instance, the Starling Crossing [
86
] adapts
its conguration to dierent road users, environmental conditions,
times of day, trac volumes, and pedestrian behaviours, includ-
ing distractions or haste. Similarly, Smart Curbs [
46
] extend the
traditional use of in-ground LED trac signal lights [
68
]. They
detect approaching cars and use LEDs embedded in the curbs to
communicate crossing instructions to pedestrians based on their
current position. These systems can prioritise pedestrian crossings,
promoting city walkability while optimising trac ow [
46
]. Addi-
tionally, infrastructure-based concepts are often perceived by road
users as having more authority in facilitating trac [
84
], which
may contribute to a higher level of trust and compliance.
Despite the potential of smart infrastructures to enhance urban
environments and transportation systems, the research commu-
nity also acknowledges the challenges it presents, such as high
initial development costs, ongoing maintenance, and regular up-
grades, which can be particularly burdensome for resource-limited
cities and developing countries [
79
]. Other concerns include the
impact of signal interference and network congestion on the re-
liability of wireless communication [
79
], as well as the potential
for vandalism or tampering to cause system malfunctions or in-
accurate data [
19
]. Consequently, future directions should focus
on developing cost-eective, resilient solutions and strategically
implementing them in areas where they can signicantly improve
safety and eciency, such as pedestrian-dense environments and
accident-prone zones. Alongside these eorts, it is crucial to em-
phasise user-centred design and human factors research to prevent
overreliance on technology and ensure individuals maintain a sense
of personal responsibility while navigating trac.
4.1.3 Pedestrian-based: Leveraging wearables [
41
,
84
] and smart-
phones [
34
,
47
], these design concepts oer the potential to consol-
idate communication cues from multiple AVs and enable commu-
nication with numerous relevant pedestrians [
24
]. This approach
enables tailored communication based on individual preferences
and needs and supports context-aware communication by account-
ing for factors such as the user’s location, speed, and direction of
movement. Furthermore, the advent of connected vehicle technol-
ogy may allow personal devices to function as virtual pedestrian
light systems, creating an innovative, infrastructure-free means of
requesting pedestrian right-of-way at intersections [82].
While Vehicle-to-Pedestrian (V2P) smartphone applications con-
tinue to be the primary focus in research for AV-pedestrian commu-
nication [
75
], there is a growing interest in wearable AR technology
as an emerging research avenue [
41
,
69
,
79
–
81
,
84
]. This interest
stems from the potential advantages of wearable AR devices over
traditional smartphone applications, such as oering a more im-
mersive and intuitive experience, enhancing situational awareness,
and enabling hands-free operation [
77
]. Furthermore, wearable AR
can bolster spatial awareness by delivering contextual information
about the user’s environment, including the location and trajectory
of nearby vehicles, potential hazards [
81
], or suggested routes [
41
].
However, wearable AR devices may face challenges in terms of
long-term use or user acceptance due to their form factor, weight,
and design [
7
,
10
]. Additionally, these devices, by design, can collect
more personal data like location and gaze direction compared to
smartphones, potentially raising privacy concerns for some users.
More research is needed to address these challenges and develop
user-friendly, privacy-preserving solutions that can facilitate wide-
spread adoption. However, in order to foster inclusivity and equity
in AV-pedestrian communication, it is crucial not to rely solely on
wearable AR technologies [79].
4.1.4 Summary. A comparative analysis of three communication
loci—vehicle, infrastructure, and pedestrian based on their poten-
tial for simplied, coordinated, and targeted communication is
summarised in Table 3. In the pursuit of designing scalable AV-
pedestrian interactions, each of these loci exhibits distinct benets
and drawbacks. However, most of them are derived from theoret-
ical reasoning and assumptions rather than empirical data. This
necessitates further research and validation through real-world
experiments, user studies, and data-driven approaches. Addition-
ally, exploring multiple communication loci rather than focusing
173
AutomotiveUI ’23, September 18–22, 2023, Ingolstadt, Germany Tran et al.
Table 3: Overview of potential research directions for enhancing scalability in AV external communication: A comparative
analysis based on Vehicle, Infrastructure, and Pedestrian loci.
VEHICLE
INFRASTRUCTURE
PEDESTRIAN
Simplied Standardised cues
On-demand operation
Interconnected eHMIs
Central source of information Cue consolidation
Coordinated Interconnected eHMIs Adaptive trac management V2P applications
Targeted High-resolution
communication
Instructions based on
pedestrian position
Tailored communication
via wearables/smartphones
on just one enables the development of more adaptable, reliable,
and inclusive eHMI solutions that cater to a wide range of situa-
tions, user needs, and abilities. By considering the strengths and
weaknesses of each communication locus, researchers can iden-
tify potential synergies and develop more eective, evidence-based
designs that enhance the safety and eciency of AV-pedestrian
interactions in diverse contexts. In fact, a hybrid loci approach,
which incorporates built-in redundancy and increased reliability,
has been previously explored and recommended in the works of
Mahadevan et al
. [62]
and Löcken et al
. [59]
, demonstrating the
potential value of combining multiple communication loci in eHMI
solutions.
4.2 Limitations
Our work has several limitations. Primarily, the comprehensive-
ness of our review could be impacted by our choice of keywords
and selection strategy, potentially resulting in the omission of rele-
vant studies. Moreover, the lack of multiple coders independently
analysing the data could raise questions about the consistency of
data interpretation and limit the generalisability of our ndings.
Within the scope of this paper, our primary emphasis is on AV-
pedestrian interactions. We made a conscious decision to not delve
into the complex dynamics involving other road users such as cy-
clists, motorbike riders, and conventional drivers. This focus, whilst
necessary for the initial exploration, might lead to an incomplete
understanding of the overall communication ecosystem and limit
our insights on the scalability of eHMIs across dierent types of
road users.
5 CONCLUSION
Our review revealed that since the 2020 study by Colley et al
. [20]
,
which reported eHMIs being predominantly evaluated in simple
trac scenarios, there has been a growing focus within the au-
tomotive research community on the ability of eHMIs to handle
larger numbers of pedestrians and vehicles in complex trac en-
vironments. Analysing 54 papers discussing scalability issues, in-
cluding 16 empirical studies examining eHMIs in multi-vehicle or
multi-pedestrian situations, allowed us to identify and organise the
challenges faced by AV external communication. Our review oers
researchers insight into the possible challenges of implementing
eHMIs in real-world situations. Additionally, we have highlighted
essential communication qualities required for eective eHMIs in
complex situations and proposed high-level research directions
focused on three communication loci: vehicle, infrastructure, and
pedestrian, to guide future eorts in this domain.
ACKNOWLEDGMENTS
This research is supported by an Australian Government Research
Training Program (RTP) Scholarship and through the ARC Discov-
ery Project DP200102604, Trust and Safety in Autonomous Mobility
Systems: A Human-centred Approach. We extend our gratitude to
the anonymous reviewers for their insightful comments and sugges-
tions. Additionally, we thank the coordinator for their invaluable
assistance throughout the shepherding process. Their eorts have
signicantly contributed to the nal version of this paper.
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