# Firefighters’ Perceptions on Collaboration and Interaction with Autonomous
Drones: Results of a Field Trial

Moyi Li<EMAIL_ADDRESS>0009-0008-9638-7890 University of
ZurichZurichSwitzerland ,  Dzmitry Katsiuba<EMAIL_ADDRESS>0000-0002-4341-5738 University of ZurichZurichSwitzerland ,  Mateusz Dolata
<EMAIL_ADDRESS>0000-0002-2732-4465 University of
ZurichZurichSwitzerland and  Gerhard Schwabe<EMAIL_ADDRESS>0000-0002-0453-9762 University of ZurichZurichSwitzerland

(2024)

###### Abstract.

Applications of drones in emergency response, like firefighting, have been
promoted in the past decade. As the autonomy of drones continues to improve,
the ways in which they are integrated into firefighting teams and their impact
on crews are changing. This demands more understanding of how firefighters
perceive and interact with autonomous drones. This paper presents a drone-
based system for emergency operations with which firefighters can interact
through sound, lights, and a graphical user interface. We use interviews with
stakeholders collected in two field trials to explore their perceptions of the
interaction and collaboration with drones. Our result shows that firefighters
perceived visual interaction as adequate. However, for audio instructions and
interfaces, information overload emerges as an essential problem. The
potential impact of drones on current work configurations may involve shifting
the position of humans closer to supervisory decision-makers and changing the
training structure and content.

Firefighting, Autonomous drone, Emergency intervention, Field trial

††journalyear: 2024††copyright: rightsretained††conference: Proceedings of the
CHI Conference on Human Factors in Computing Systems; May 11–16, 2024;
Honolulu, HI, USA††booktitle: Proceedings of the CHI Conference on Human
Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI,
USA††doi: 10.1145/3613904.3642061††isbn: 979-8-4007-0330-0/24/05††ccs: Human-
centered Computing Interaction design; Empirical studies in interaction
design††ccs: Information system Information system applications

##  1\. Introduction

Introducing new technologies catalyzes a transformation in traditional system
operation models. In the area of emergency response, drones are especially
anticipated as a tool that, through their mobility, could provide new
information, shorten response time, or perform dangerous tasks. Drones have
also proven practical and reliable for such tasks (Roldán-Gómez et al., 2021;
Ausonio et al., 2021). In the foreseeable future, such aerial vehicles might
become integral to many fire departments worldwide. However, their integration
in firefighting processes and their acceptance by the public remain a
challenge (Dolata and Schwabe, 2023). Specifically, it is unclear how existing
processes need to be adapted to incorporate drone system.

Firefighters often confront a hazardous working environment in searching,
rescuing, and fire-extinguishing. Despite fire brigades’ current efforts to
enhance safety measures to minimize casualties (Kang et al., 2016; Smith,
2011), there remain numerous unpredictable factors during their operations
that can lead to accidents (Khan et al., 2022). Hence, as technology permits,
the idea of using drones to complete specific hazardous tasks has emerged,
offering additional options for conducting firefighting operations. The
applications of drones are gradually extending beyond tasks that endanger the
health of firefighters: drones are used to collect additional data that were
not available before, explore the surroundings, or assure the safety of the
area. This prompts scholars to contemplate the potential for variability in
the roles of drones within firefighting teams and the potential implications
for current organizational structures. Exploratory research (Khan and
Neustaedter, 2019) shows that firefighters and emergency responders need
precise information and reliable communication and have concerns about drones’
ability to deal with emergencies and make decisions. Domain experts also
identify the design needs for the interface of drone systems in emergencies,
such as distinct visual cues and explanations for drone decisions (Agrawal et
al., 2020). Another study proposes the direct communication between
firefighters and drones, and presents a set of gestures (Alon et al., 2021).
Results of (Dolata and Aleya, 2022) point out the need to explore such
collaboration from a social-technical perspective. Later work identifies the
challenges of collaboration, intermediary devices, and information extraction
from videos and re-emphasizes the importance of trust (Hoang et al., 2023).
However, previous studies relied primarily on surveys and interviews and did
not expose firefighters or citizens sufficiently to actual operations
involving drones. Since it is likely that participation in an operation might
raise new issues or turn concerns obsolete, we decided to explore
firefighters’ and the public’s concerns in a trial.

The application of drones in firefighting has been proven feasible; for
instance, drones equipped with infrared sensors are already used for fire
source detection (Christensen, 2015; Zhang et al., 2021; Abdelrahman et al.,
2017). This suggests that drones will become more prevalent in firefighting
operations as technology matures. _Human-drone interaction_ (HDI) and its
application in emergency response often involve applying knowledge from
multiple fields such as philosophy, design, and engineering (Baytas et al.,
2020). The complexity brought by this makes the design of such systems more
intricate, and it is unclear if prior knowledge is still applicable.
Additionally, it is important to validate existing organizational frameworks
in practice, i.e., we need to understand how drones fit and extend processes
and hierarchies involved in firefighting operations. The importance of
adequate organizational frameworks in emergency situations has been broadly
discussed in earlier research. The seminal work of Weick (Weick, 1993)
analyzed the Mann Gulch fire disaster that resulted in the death of 13
firefighters. This work identified distrust in the commander’s decisions, late
sensemaking, and poor communication as the primary reasons for the tragic
deaths of firefighters in the Mann Gulch incident. The critical question posed
in Weick’s research is: Is there an appropriate firefighting organizational
framework to manage the hazards brought about by change (Weick, 1993)? He
believed constructing a virtual model capable of providing an overall
situation and assigning roles to participants could be a potential solution.
In this framework, interactions among individuals with mutual respect and the
creation of a trusting environment are particularly crucial for handling
unforeseen situations. We believe that drones can provide assistance in
constructing the overall scenario for their ability to gather comprehensive
information within a short time. Drone systems could be a suitable solution
for connecting and organizing firefighters. However, the design of such
systems depends on how firefighters perceive the system’s functionalities.

Therefore, in this paper, we address the following two research questions:

  1. RQ1.

What would be the potential design of an autonomous drone system to support
firefighting emergency response?

  2. RQ2.

What challenges does the use of autonomous drones pose for human-drone
interaction during firefighting operations?

To address our research questions, we reviewed the literature about the
support provided by drones and ways of HDI in firefighting. The results of
previous studies show that effective interaction between drones and humans
requires a multisensory approach (Cacace et al., 2016). Based on this, we
designed an interactive drone system consisting of two drones incorporating
sound, visuals, and interfaces. We tested this system in two real-life
firefighting exercises. Subsequently, we conducted post hoc interviews with
firefighters and bystanders and performed a qualitative analysis of the
results to assess the system’s impact on existing firefighting practices.

Our results demonstrate that the autonomous drone system provides the
advantage of exploring the environment more efficiently than the original
organizational framework without drone support. However, as our results
indicate, use of drones might create information overload and pose privacy
concerns when conveying information through sounds or videos. Firefighters who
participated in the trials believed that instantaneous interaction would be
less efficient because it occupies their memory space during emergent
situations. Both commanders and firefighters believed that information could
reach all members of the firefighting team instead of being forwarded only to
the commanders. While there is no doubt about the drones’ capability to
perform instrumental tasks, we still consider it necessary for humans to
supervise the decisions made by the drones. Introducing drones may also
stimulate the need to train higher-level team personnel in robotics knowledge.

##  2\. Background

###  2.1. Autonomous Drones

The drone evolution is heading toward a higher degree of autonomy. A
literature review in 2015 (Floreano and Wood, 2015) categorized drone autonomy
into three levels: motor, reactive, and cognitive autonomy. In a 2020 study by
Nonami (Nonami, 2020), the researcher further classified the current and
future autonomy of drones into six levels, with the highest level signifying
drones flying independently to a destination relying solely on vision. The
automation of drones is now evident in functions such as automatic navigation,
landing, charging, target object localization, and tracking (Sani and
Karimian, 2017; Woo et al., 2017; Henry et al., 2020). Changes in autonomy may
impact how people perceive interactions with drones. However, research on
autonomous drones has less frequently considered how to measure and implement
such changes in the design of drone systems.

Exploring autonomous drone applications across various domains represents a
trending and expansive research avenue. Autonomous drones find practical
applications in fields like the military, mining, photography, logistics,
agriculture, and more (Patil et al., 2020; Jones et al., 2020a; Mademlis et
al., 2018; Budiharto et al., 2019). The results of these studies indicate that
autonomous drones can play a significant role in collecting and transmitting
information and assisting in rescue missions. This suggests that autonomous
drones also hold great potential for applications in the field of
firefighting. However, research on drones in firefighting remains relatively
limited. Researchers have identified tasks where autonomous drones could
potentially aid in fire source identification and detection (Yadav, 2020). The
design requirements for autonomous drone applications in firefighting and
firefighters’ concerns regarding autonomous drones are still under
investigation. For this reason, our study includes the exploration of how
firefighters perceive autonomous drones used in their work. We provide an
interactive interface with events identified and decisions made by drones.

###  2.2. Human-drone interaction

To establish a system where drones assist firefighters in extinguishing fires,
we have also reviewed the existing literature for proposed modes of human-
drone interaction. Table 1 presents a list of interaction modes and the
literature sources introducing them. Tezza and Andujar’s survey (Tezza and
Andujar, 2019) provides a detailed overview of various approaches to
interfacing with drones. Their research encompasses controlling the system
through a remote controller, gestures, voice commands, brain-computer
interaction, touch input, and multimodal approaches (Tezza and Andujar, 2019),
along with their corresponding advantages and disadvantages. Gesture, voice,
BCI, and touch interactions are particularly relevant to our study, as they
enable direct interaction between firefighters and drones. Additionally, light
appears to be another interaction method between humans and drones in
spacious, open environments (Herdel et al., 2022; Abtahi et al., 2017).

Table 1. List of Human-drone interaction approaches in previous research Interactions | Literature | Description
---|---|---
Light |  (E et al., 2017) (Ginosar and Cauchard, 2023) | Drones use light on them to send messages to humans at an outstanding position in the air.
Audio |  (Mohsan et al., 2022) (Choutri et al., 2022) | Humans and drones communicate with each other through voices and sounds.
Gesture |  (Cauchard et al., 2015) (Medeiros et al., 2020) | Humans give instructions to drones by changing the shape and position of hands and arms.
BCI |  (Saeedi et al., 2016)(Sanna et al., 2022)(Wolf and Iskhakova, 2022) | Humans directly communicate with drones through devices that can capture their brain movements.
Tactile | (Abtahi et al., 2017) | Humans give instructions to drones through physical contact.

Gesture interaction primarily involves conveying instructions to drones using
different hand shapes and positions or other parts of the human body (Cauchard
et al., 2015; Medeiros et al., 2020). Research on sound-based interaction has
matured and gained recognition in practical applications. Common sound-based
interaction is drones transmitting information to humans in a unidirectional
way (Mohsan et al., 2022), while literature (Choutri et al., 2022) also
introduced the bidirectional voice interaction through interface or
controller. _Brain-computer interaction_ (BCI) is an approach that enables
direct communication between the human brain and digital devices. This type of
human-drone interaction in firefighting typically involves capturing human
thoughts through devices and transmitting them to drones (Saeedi et al., 2016;
Wolf and Iskhakova, 2022). It is considered a potential method for swiftly
conveying human intentions to drones. Tactile interaction refers to
interaction between humans and drones through direct physical contact. Light-
based interaction (Cauchard et al., 2015; Abtahi et al., 2017) typically
involves drones transmitting simple messages by controlling the integrated
spotlights (color, target of exposure, dynamics, etc.). The design needs of
interfaces for drone systems in terms of information filtering, retrieval, and
explanations are also widely discussed (Jones et al., 2022; Hoang et al.,
2023; Agrawal et al., 2020).

The above studies were primarily conducted in general human-drone interaction
scenarios rather than in the context of emergency response. The potential
impact of transitioning from traditional communication methods is also an open
topic that requires examination. For these reasons, we designed our drone
system (Section 3.2) based on previous interaction approaches to find out
which tasks can be supported and how firefighters may react.

###  2.3. Drones in emergency firefighting response

Researchers have been studying the application of digital technologies in
firefighting operations for decades. Research in the field of firefighting
technologies encompasses digital instruction files (García-Hernández et al.,
2019), radio communication (Denef et al., 2011), aerial and ground robots
(Zhao et al., 2022; Jindal et al., 2021), intelligent protective clothing
(Et.al, 2021; Choi et al., 2021), and organizational systems for evaluating
tasks and optimizing processes (Jiang et al., 2004; Monares et al., 2011).
Among these, drones are considered to be particularly helpful for firefighting
missions in hazardous or large areas. Engineering researchers are currently
exploring drones in firefighting as a trending topic.

Drones have demonstrated their capacity to address the limitations of human
crews in extreme and hazardous environments during firefighting operations
(Kahiluoto et al., 2020), as well as the crucial issues in search and rescue,
such as communication and time-saving (Desjardins et al., 2014; Jones et al.,
2020b; Mayer et al., 2019). Researchers have extensively investigated the use
of drones for searching and rescuing victims (García-Hernández et al., 2019;
Pelosi and Brown, 2017; Alharthi et al., 2021). In addition to surveying vast
or perilous areas, drones also find applications in firefighting for
extinguishing fires (Barua et al., 2020; Aydin et al., 2019) and improving
communication signals (Monares et al., 2011).

The utilization of multi-drone systems in firefighting has gained prominence
in recent years, particularly in the context of forest fires. A survey
(Roldán-Gómez et al., 2021) examining the current deployment of drone swarms
in forest fires revealed that firefighters tended to allocate drones for
information collection, such as monitoring fires and assessing their potential
spread risks. Sherstjuk et al. (Sherstjuk et al., 2019) introduced a drone
swarm as a novel approach for responding to forest fires, while Ausonio et al.
(Ausonio et al., 2021) proposed a framework for organizing drone swarms more
effectively in wild firefighting, adapting to changing water needs in various
scenarios.

The potential applications of drones in firefighting appear limitless, yet
there are differing opinions on their use in this context. Two studies
indicated that German firefighters still harbored concerns about the limited
capabilities and applications of drones in firefighting (Schlauderer et al.,
2016; Weidinger et al., 2018). Past research has extensively explored the
specific applications of drones in firefighting. However, there is limited
literature on multi-drone systems regarding task allocation and their impact
on firefighting teams. Thus, in our research, we attempt to study how an
autonomous multi-drone system can be deployed and contribute to enhancing
communication in firefighting through a two-role drone system providing
support for scouting, evacuation, and rescue.

###  2.4. HDI in emergency response

Human-drone interaction in emergency response has concentrated on interaction
techniques, targets, communication channels, and impact on stakeholders. 911
callers and Canadian firefighters articulated their expectations and concerns
regarding integral drone systems employed for communication, filming, and
indoor searching, assessing whether the public would find such systems
credible and trustworthy (Khan and Neustaedter, 2019). Later study
investigated the design requirements for rescue system interfaces among domain
experts (Agrawal et al., 2020) and introduced and evaluated a set of gestures
for interactions between firefighters in action and drones (Alon et al.,
2021). Recent work that delved into drone swarm system interfaces revealed
that firefighters desire components to control the level of autonomy and
simpler means of interaction to replace gestures and keypad input (Hoang et
al., 2023). An examination of drone swarms in forest fires (Bjurling et al.,
2020) demonstrated dynamic human-drone interaction occurring at corresponding
levels in both teams, inspiring future research to explore flexible and
efficient interactions between drone swarms and firefighter crews. Prior
research also studied how new tools like drones could influence teamwork for
search and rescue (Mencarini and Zambon, 2023). The work of Jones et al.
proposed that drones could be an approach to enhance coordination during
rescue (Jones et al., 2020b). Social acceptance is frequently discussed in HDI
(Oltvoort et al., 2019; Lidynia et al., 2017; Herdel et al., 2021;
PytlikZillig et al., 2018; Chang et al., 2017), especially when talking about
autonomous machines (Tolmeijer et al., 2022). Among these discussions, drones
for public services, such as policing and firefighting, receive more trust
(Lidynia et al., 2017; Herdel et al., 2021). Still, the latest research
presents the public’s concerns about fairness during interactions when
applying drones in police operations (Dolata and Schwabe, 2023).

Despite the insightful results from the above research, we still have doubts
about their reliability while applying drones in practical firefighting
operations. Aligned with previous research, we believe it is important to
investigate from a sociotechnical perspective when designing drone systems to
identify potential needs (Dolata and Aleya, 2022). Specifically, this refers
to investigating more deeply into firefighters’ reactions toward drones under
firefighting. Unpredictable reactions in firefighting can cause serious, even
life-threatening, consequences when the change is too dramatic. Most of the
above studies were conducted in simulated settings, where firefighters learned
about drone usage through descriptions, images, or videos. However, the
ability of the above presentations to narrate real-life scenarios is
relatively limited. Firefighting operations can be more complicated, with
numerous details under variable situations. How firefighters perceive the
advantages and drawbacks of drone systems in actual operations remains
unknown. Therefore, we conduct field trials to engage with firefighters in
firefighting exercises. The goal is to evaluate our multi-drone system and
collect insights about firefighters’ perceptions under real cases.

##  3\. System description

To support firefighters during an emergency response with autonomous drones,
examining existing emergency response processes and firefighting challenges is
essential. As part of the preliminary investigation, we first conducted and
analyzed several interviews with representatives of various fire departments
in Switzerland and studied the existing regulations. We collected data about
the firefighting practices and gained insight into how they envision drones
providing support. Additionally, the firefighters shared a firefighter
handbook describing their procedures and instructions for handling diverse
situations. Based on the gathered information, we can outline the initial
firefighting scenario, encompassing the organizational structure of a
firefighting team and the general response process to fire incidents. Next, we
describe current practices, communication within a firefighter team, and the
proposed drone system.

###  3.1. Case description

Volunteer firefighting typically involves four major phases in response to an
emergency (refer to Figure 1):

Phase 1: The firefighting operation commences with the receipt of a fire or
emergency report via a phone call. Phase 1 encompasses the period from when
the fire brigade receives the information to its arrival at the scene. During
this phase, the commander is assumed to be the primary decision-maker. They
must assess the fire situation, determine the required personnel and equipment
for dispatch, and, if possible, establish an initial firefighting plan.
Critical information such as terrain conditions, fire size, and available
resources like water sources plays a pivotal role in decision-making during
this phase.

Phase 2: The second phase is the preparation stage upon reaching the scene.
Here, the commander can provide a more precise assessment of the fire and task
priorities while firefighters commence preparatory work.

Phase 3: Subsequently, the firefighting phase entails the rescue and
extinguishing of the fire. In the case of building fires, firefighters must
make critical decisions, including whether and how to enter the building,
among others. In wildfires, they need to determine the fire’s extent, assess
the risk of spreading, and identify the search area. If there are victims,
firefighters evaluate their injuries and the complexity of the rescue
operation to prioritize rescue efforts. One of the main challenges in this
stage, especially in the context of large fires, is ascertaining the number
and locations of injured individuals.

Phase 4: The fourth phase pertains to firefighting activities after the fire
has been extinguished. In the post-fire phase, the remaining tasks involve
inspecting potential embers, documenting the site, and implementing any
necessary remediation measures.

Figure 1. Current firefighting procedure

A timeline showing four phases of a typical building fire operation. Phase 1:
A building is on fire is reported. Phase 2: Firefighters arrive at the
building. Phase 3: Firefighters extinguish fire with water pump. Phase 4:
Firefighters check if there are still unextinguished fire covered under the
building, sometimes with help from drones.

In many firefighting operations, one or two operational commanders take charge
of overseeing the overall situation and making decisions regarding personnel
and equipment deployment. When it comes to incorporating drone support
selectively, the drone team operates under the authority of the commander.
Moreover, stakeholders with the potential for information exchange during fire
incidents include victims, bystanders, and medical personnel. Communication
between firefighters and bystanders involves conveying information about the
fire situation and evacuation instructions. Bystanders may also seek fire-
related information. Once the firefighters have found the victims,
firefighters must assess their physical condition and, on occasion, relay
information to medical personnel. The information mentioned above, once
filtered, is reported to the operational commander to formulate an overall
situational assessment. Currently, the use of drones is initiated at the
commander’s request, and the drone team does not constitute an integral part
of the on-scene fire unit.

Figure 2. Organization of the firefighting unit, including an optional drone
team

A triangle containing three part to show the information flow within
firefighting team. On top is the commander, receiving information from both
firefighters in the lower left corner and drone officer in the lower right
corner. Drone officer receives information from the tablet, which shows the
interface of our drone system.

The initiation of drone usage can occur at the commander’s request during any
phase. It’s worth noting that the drone team is not an integrated component of
the firefighting unit at the scene. Figure 3 illustrates a possible setup in a
scenario without autonomous drones.

Figure 3. Current firefighting scenario without autonomous drones

A figure simulating the building fire scene. The core area is called the
danger zone, which includes the building on fire, firefighters who are trying
to extinguish the fire, and the water supply. The danger zone is surrounded by
barriers. Outside the danger zone is the restricted zone, which includes
curious bystanders, the nearby road, fire trucks, other groups of
firefighters, and the commander for this operation. The meeting zone for all
firefighters is also in the restricted zone. This figure is to give an
overview of what the typical building fire operation procedure and positions
for different roles look like.

###  3.2. Drone System

Over the past three years, we have worked on the use of drones in emergency
services like police operations, gaining valuable insight and expertise in
this dynamic field. We expanded the collected experience and design knowledge
from existing literature through discussions with firefighters. Interviews
with predefined questions helped us to generate ideas and suggestions for
deploying the autonomous drone system and to expand the rationale with an
empirical basis for design decisions. Based on the current firefighting
operational procedures, we developed a scenario aimed at integrating
autonomous drones into firefighting practices, including specific interactions
between drones and firefighters or bystanders.

To fulfill the fire brigade commander’s need for an initial on-site
assessment, we introduced an autonomous drone right at the beginning of the
operation. In our envisioned scenario, a preliminary scouting (master) drone
departs from the fire station and arrives at the fire location ahead of the
firefighting team (Phase 2a). An autonomous drone identifies potential fire
points and victims and then dispatches the more agile soldier drone to confirm
these findings. Figure 5 illustrates the suggested adaptations to the
emergency operation process, while Figure 6 depicts the modified organization
of the fire scene.

The proposed system employs two types of drones: the DJI Matrice 30, serving
as the command (master) drone with night vision capability, the ability to
operate in adverse weather conditions, and location reporting via Flighthub 2;
and the DJI Avata, functioning as the soldier drone with motion control and a
smaller form factor, allowing it to navigate indoor spaces. Both drones
seamlessly interact with the system and can provide real-time services as
required. Communication with the drone operator is facilitated through a
tablet application supporting live streaming, an emergency case map, and
decision-relevant notifications (refer to Figure 4).

Figure 4. Overview of the drone system user interface for Drone Officer in
firefighting team

A figure showing the overview of the user interface and all the foldable
components. On the interface, there are livestream and thermal camera videos
of Avata, livestream, and map of Matrice 30, buttons for the message box and
priority list. The message box component includes all the messages, sending
time, and using different colors to mark the type and emergent level of the
messages. The priority list component includes the type of incident, priority,
and button to change the priority by hand.

In designing human-drone interaction, our goal was to identify the most
suitable interaction modes to facilitate effective communication between
firefighters and drones. This selection was made thoughtfully, taking into
account several critical factors, including the firefighters’ familiarity with
automation technology, information processing capabilities, and ability to
respond swiftly while engaged in high-pressure tasks.

Informed by input from experienced firefighters, we prioritized audio and
lighting interaction modes for effective communication during firefighting
operations. The rationale behind opting for audio and lighting interaction
modes is multifaceted. Firstly, these modes enable communication over extended
distances, a vital aspect when dealing with potentially hazardous and
expansive fire scenes. Moreover, they offer the advantage of minimal training
requirements, making them accessible not only to firefighters but also to
uninvolved individuals who may find themselves in emergencies. In our
envisioned scenario, the drone first indicates who it is communicating with by
rotating itself in the direction of the receiver and flashing its spotlight
twice. The rotation of the drone on its own is not sufficient, as it is not
always visible at great distances and in the dark. For audio/verbal
communication, we decided to use audio broadcasting. Verbal addressing of
specific people (e.g., with an exact description of the person) seems to be
effective only to a certain extent. People who are not in the spotlight may
ignore the message and not feel addressed as they prioritize the spotlight
interaction mode. Conversely, people who are not addressed and are not in the
spotlight may still feel involved in such situations, as people in emergencies
tend to perceive all information as potentially important. Nonetheless, these
different modes of interaction collectively serve to attract the attention of
those in the immediate proximity of the emergency location.

However, it is essential to note that specific interaction modes were deemed
unsuitable for our purposes. Gesture-based communication, while
technologically appealing, presented drawbacks that outweighed its benefits.
High latency and imprecise control (Tezza and Andujar, 2019) posed significant
challenges, potentially exacerbating issues in larger fire scenarios.
Furthermore, firefighters are often constrained in their ability to use
gestures freely, rendering this mode impractical in many situations.
Similarly, touch-based interaction and BCI were ruled out as viable options
for communication between firefighters and drones. Safety considerations were
pivotal in this decision, as both touch and brain-computer interaction
necessitate physical contact or invasive procedures that could compromise
safety in hazardous environments. Additionally, these modes exhibited slower
input and output responses, a critical factor in emergency operations where
rapid communication can be a matter of life or death.

##  4\. Method

This study was part of a larger project that used a user-centered approach to
determine the potential applications of autonomous drones to assist
firefighters. We started with an ideation phase, after which we proposed an
autonomous drone system. Subsequently, through two field trials conducted in
collaboration with two fire departments, we aimed to evaluate firefighters’
work processes, investigate the use of the drones to detect the source of the
fire and possible victims, study the interaction with drones, and determine
bystanders’ perceptions. The primary objective of the field trials was to
glean insights into how firefighters could effectively integrate autonomous
drones into emergency operations, ascertain the optimal design principles for
drone systems supporting firefighters, and understand the advantages and
challenges perceived by citizens regarding drones that capture video footage
of emergency situations and interact with victims and bystanders.

The field trials were part of regular firefighting exercises by two volunteer
fire departments in two towns in Switzerland. In Switzerland, the spirit of
volunteering is deeply ingrained, and in most cantons men and women dedicate
themselves to the community on a part-time or voluntary basis. This commitment
is not only reflected in the role of the militia in the army and national
defense but also extends to civilian civil protection, especially the fire
department. The seamless interaction between the military and fire departments
is underlined by common ranks and rapid access to essential equipment and
personnel, demonstrating a joint effort to protect the population and respond
effectively to emergencies. The fire departments generally deal with all types
of incidents. Their main tasks include firefighting, responding to natural
disasters (e.g. hail, storms, snowfall, flooding), responding to reports from
fire alarm systems, rescuing people on the road, engaging in operations on
railroad systems, etc. Often two or more main tasks may overlap in one
incident. During the fall 2022 exercises, we simulated a real firefighting
operation in two distinct setups: a building fire and a forest fire, which we
conducted with different participants. Firefighters were actively involved in
realistic tasks and used prototype autonomous drones to manage emergencies.
Subsequently, we conducted and recorded group discussions and individual
interviews with the test subjects and used these recordings as the basis for
our findings.

Figure 5. Field trial firefighting procedure

A new timeline showing the phases of a building fire operation with the
assistance of drones. Phase 1 and 4 remain the same as shown in Figure 2.
Phase 2 is divided into two sub-phases. The whole figure is organized as
follows. Phase 1: A building is on fire is reported. Phase 2a: Drones arrive
at the building before firefighters arrive. Phase 2b: Firefighters arrive at
the building, and check the situation based on information provided by drones.
Phase 3: Firefighters extinguish the fire with a water pump, with a drone
monitoring the scene in the air. Phase 4: Firefighters check if there is still
unextinguished fire covered under the building, sometimes with help from
drones.

Figure 6. Field trial firefighting scenario including autonomous drones

A figure simulation the building fire scene with drones in the firefighting
team. This figure is built based on Figure 3. The existing roles and their
positions remain unchanged. Besides, we have the master drone, scouting above
the fire scene for any accidents. And we have the soldier drones to deliver
messages to the victims in the building and figure out what are their
situation. A new character, drone officer, is added next to the commander to
deal with information collected by drones and pass them to the commander.
Also, the situation of the fire scene can be checked through the screen in the
back office of the fire station.

###  4.1. Field trial scenario

The field trial focused on fire incidents occurring within buildings or in
forested areas and involved a total of 95 participants, categorized into three
primary groups. First, we enlisted firefighters from two volunteer fire
departments, where participants held positions as general commanders, exercise
commanders, or civilian members of the firefighter department. Notably, these
individuals were not career firefighters or part of the professional
firefighting staff but rather dedicated volunteers contributing to
firefighting efforts. Before the commencement of the field test, we
established communication with the responsible exercise commander to delineate
the conditions and exercise setup. While the primary commander’s role was to
oversee the entire operation, the exercise commander’s task was to
meticulously plan and organize the exercise to emulate the most realistic
scenario. Consequently, exercise commanders were not directly involved in the
firefighting or rescue operations.

In addition to the existing task forces, new roles were introduced. The
general commanders received support from drone officers stationed alongside
them. These drone officers accessed the drone’s video stream via a handheld
digital device, evaluated the information, and subsequently relayed it to the
commander. Participation in the exercises was compulsory for all civilian
members of the department; albeit, they received limited information about the
training schedule and the inclusion of drones in the operation.

Second, in accordance with the scenario, the field trial encompassed
individuals with varying degrees of injury and mobility. The primary
responsibility of these individuals was to remain stationed in assigned
locations and await rescue. They were afforded the opportunity to interact
realistically with their surroundings, including the drones, and collaborate
with firefighters to aid in their location and rescue. This segment of the
trial facilitated an exploration of the potential and challenges associated
with drone interaction among different user groups.

Last but not least, the trial included subjects who were presumed to be
indirectly affected by the fire, primarily serving as bystanders who happened
to be near the fire scene. These participants were informed that they were
taking part in a live fire exercise that would involve novel technologies.
Bystanders were positioned at various locations, as depicted in Figure 7. To
heighten the realism of the situation and simulate the varying attention
levels of bystanders, all participants were assigned individual tasks
unrelated to the fire incident. For instance, a small group was tasked with
playing volleyball on the lawn at the backside of the building, thereby
initially remaining unaware of the ongoing events or the use of drones.
Throughout the field trial, bystanders were afforded the freedom to act
according to their discretion. They could respond to requests from
firefighters or drones as the situation unfolded. For documentation and
evaluation purposes, the progress of the field test was recorded from
different vantage points.

Figure 7. The location used for the field trial with indicated relevant areas

A bird-eye view of a building and its surroundings (grass fields, streets,
river, trees) with indicated seven different areas: P1: drone team hub, P2:
bystanders: backside, P3: bystanders: riverside, P4: bystanders: frontside,
P5: victims, P6: firefighters: main operation area, P7: firefighters: water
access area. Further, there are indicated four positions where cameras were
placed to record the action of the firefighters and bystanders

As the bystanders carried out their assigned tasks, the exercise commander
initiated the field trial by either igniting the fire (in the case of a forest
fire) or activating the smoke machine (in the case of a building fire). Within
a few minutes, information regarding the fire incident reached the fire
station, prompting the general commander to activate the alarm, resulting in
the immediate mobilization of the entire crew. The command center promptly
initiated the operation by issuing orders for the deployment of the drones.
These drones departed from their base, located approximately 1500 meters away,
and swiftly transmitted initial imagery of the emergency location. Merely one
minute after the alarm was sounded, the drones were airborne. Meanwhile, it
took the civilian members of the fire department an additional 15-20 minutes
to arrive at the scene.

This operation involved the utilization of two drones operating as a
coordinated team. While one drone provided an aerial overview and established
communication with bystanders and potential victims through loudspeakers and
spotlights, the second drone executed a thorough search for victims within the
building or the forest. The operation concluded once all victims were
successfully rescued, the fire was extinguished, and any potential residual
embers were eliminated.

We seamlessly integrated the following preselected scenarios for human-drone
interaction into the firefighters’ routine exercises to replicate real-life
conditions as accurately as possible:

  1. (1)

Verify the correct address and confirm the fire location

  2. (2)

Obtain information about the surroundings, including determining the extent of
the fire

  3. (3)

Contact third parties and instruct them to vacate access roads, entrances,
rescue lanes, and water resources

  4. (4)

Continuously gather information and evaluate future events

  5. (5)

Provide support and conduct a search for individuals, including potential
victims, within the emergency area

  6. (6)

Conclude the operation and document incidents

To create the illusion of complete drone autonomy during our study, we
employed a Wizard of Oz (WoZ) technique, following established methods
(Karjalainen et al., 2017; Dahlbäck et al., 1993; Cauchard et al., 2015). This
approach enabled us to monitor and control the drone’s actions to ensure the
safety of all participants. By concealing the human operator behind a curtain,
we crafted the impression among participants that the drone was functioning
independently. This deliberate concealment facilitated an unbiased assessment
of participants’ interactions with the technology.

The field trials provided an effective means to evaluate the practical
feasibility and effectiveness of autonomous drone systems in actual emergency
situations. The selection of these scenarios was informed by an analysis of
previous fire brigade operations, which revealed that the drone could reach
the fire’s source more swiftly than the initial fire unit. Consequently, in
the initial phase, the drone was often the sole representative of the
firefighting team at the scene, raising questions about the drone’s legitimacy
and the public’s perception of it.

###  4.2. Participants and Data Collection

A total of 67 firefighters (including commanders) participated in both
exercises (see Table 2). The participation of the firefighters in the
exercises was mandatory and was not remunerated. Some of the firefighters had
prior experience using drones in emergency situations; they operated and used
drones to investigate emergencies in the field.

The research team employed the snowball method (word of mouth) and direct
engagement with participating fire departments to recruit 22 volunteers for
the bystander role. In recognition of their participation, which encompassed
approximately 2 hours, bystanders received compensation amounting to 70 Swiss
francs (comprising 25 Swiss francs per hour along with travel expenses) in
adherence to university practices. These two hours encompassed preparation,
active participation in the field trial, subsequent group and/or individual
interviews, and scenario resolution. Furthermore, six victims participated in
both field trials, and they were directly recruited from the participating
fire departments.

Following the conclusion of each field trial, participants engaged in brief
interviews conducted by a member of the research team. An internal fire
brigade debriefing also took place after each exercise, with a representative
from the research group permitted to attend these discussions. Due to the
volunteer basis of the fire department, the exercises were scheduled in the
evening to maximize firefighter participation. However, this timing posed a
limitation for planned interviews, as not all participants were available for
post-exercise interviews. Nevertheless, a total of 50 interviews were
successfully conducted across both field trials (refer to Table 2). After
Field Trial 1, interviews with bystanders averaged 12.7 minutes, while those
with firefighters averaged 18 minutes. Subsequently, during Field Trial 2,
interview durations increased, averaging 17.45 minutes for bystanders and 19
minutes for firefighters.

Table 2. Number of subjects who took part in the field trial and number of interviews conducted per group of participants (in brackets) Participants group | Field Trial 1 | Field Trial 2
---|---|---
Bystander | 11 (11) | 11 (11)
Victim | 3 (0) | 3 (3)
Commander | 1 (1) | 1 (0)
Exercise Commander | 2 (2) | 2 (2)
Drone officer | 1 (1) | 1 (1)
Firefighter | 30 (7) | 29 (11)

The interviews followed a semi-structured format, encompassing five primary
topics: overall impressions, perceptions of drone performance, interactions
with the drones, autonomy of the drones, and accountability and responsibility
concerning drone actions. We delimited our focus to these topics for two
primary reasons. First, expanding the scope of the interviews would have
placed an excessive burden on the research team, and conducting immediate
post-field trial interviews on a wider array of subjects would have been
unfeasible. Secondly, we aimed to minimize waiting times to sustain
participant motivation and engagement. For this study, our primary emphasis
centers on questions related to overall impressions, perceptions of drone
performance, interactions with the drones, and drone autonomy.

###  4.3. Data analysis

The primary objective of the field trial was to acquire insights into how
autonomous drone systems should be designed to aid firefighters, how citizens
perceive the interactions with drone systems, and what benefits and challenges
drone systems could have on the firefighting team. The recorded interviews
underwent transcription following the intelligent wording standard.
Subsequently, the transcripts underwent analysis within the exploratory-
interpretive paradigm (Saldana, 2021; Stebbins, 2001), wherein the researchers
pursued a shared interpretation of the data rather than striving for absolute
objectivity.

The data analysis unfolded in two distinct phases. First, a single researcher
employed a bottom-up approach to identify predominant themes. This initial
step led to the identification of 2399 pertinent passages, which were
categorized under 51 secondary codes within five overarching themes:
Firefighting Regulation, Interaction, Potential Applications, Perceived
Support and Problem. The sub-codes encompassed topics related to the
suitability of drones in saving time, the efficiency of interaction, their
impact on bystander emotions, issues of responsibility, moral decision-making,
technical safety, transparency, and other pertinent considerations. For
instance, sub-codes like ”Situation awareness” and ”Psychological effect”
within the Perceived Support theme were employed to categorize paragraphs
discussing participants’ comprehension of on-site situations based on drone-
provided information and the comfort derived from the interaction. In Table A,
we present a description for every theme and some example sub-codes and data.
The accuracy of coding underwent verification through iterative checks
conducted by a second researcher, with borderline cases resolved through
discussions.

In the second phase of analysis, the authors collaborated with fellow
researchers in an iterative sense-making and data-restructuring process. This
collaborative effort involved asynchronous exchanges through a shared
repository and participation in two interpretation workshops, which included
members of the authors’ research group, including those who supported the
field trial as assistants. Through this method, the authors systematically
evaluated the comprehensiveness and authenticity of their interpretation,
ensuring that the results were not solely shaped by individual perspectives
but rather cultivated through an intersubjective approach. The sense-making
process played a pivotal role in refining the organizational framework of our
study’s findings, leading to the consolidation of the initial five overarching
themes into two primary meta-topics: enhancing autonomous drone systems and
examining the impact of autonomous drone applications. This restructuring made
it necessary to subject the previously coded data to a new structure.
Specifically, the categories Perceived Support and Problems were combined into
a comprehensive overarching category Impact on firefighters which includes
aspects such as changed processes, changes in team structure, training
considerations and reliance dynamics. To provide a more nuanced understanding,
the results were further subdivided based on the different emotions expressed
in the statements. The explanation of these identified categories and their
associated meanings is presented in the results section, taking into account
the findings from the group discussions.

##  5\. Results

###  5.1. Improving autonomous drone system

####  5.1.1. Comments on current functions

Since our research is centered around firefighters, we primarily assessed the
sentiments and recommendations of the firefighters to evaluate these
functions. However, to achieve a more comprehensive understanding of how these
interaction methods can support firefighting activities in real-world
scenarios, we also considered the assessments of other stakeholders in our
analysis.

Participants from both trials acknowledged the effectiveness of both lighting
and broadcasting interactions. The utility of the lights received positive
feedback, as they facilitated victim location in dark and expansive areas. No
dissenting opinions were voiced regarding this feature. Victims, bystanders,
and firefighters involved in the rescue task also noted that the drone’s
lighting improved visibility during nighttime operations. Besides, bystanders
also showed affection for the spotlights as the lights increased the perceived
credibility of drones and the information that came from them:

> F34111In our coding system, we employ distinct labels for various groups of
> participants to facilitate citations. Each label comprises a designation
> code followed by an ID number (#): firefighter (F#), commander (C#),
> exercise commander (EC#), drone officer (DO#), victim (V#), and bystander
> with (B#) : “The rescue squad was then able to locate the drones using its
> positioning lights, so they were actually able to find these people
> relatively quickly.”

> B13: “And what I also saw was that they also pointed directly at things with
> the light beam. If you had to look at this on a map, you don’t know if the
> location is here or a few trees further back. With the drone, you could see
> it well.”

> B15: “I have to say now, the big drone with the spotlight already seems
> pretty professional.”

Participants held varying opinions regarding the interaction between drones
and individuals over the radio. Some participants believed that the radio
transmissions they received provided sufficient information about the
situation and guided their subsequent actions. Specifically, firefighters
found audio instructions valuable for evacuating uninjured bystanders from
hazardous areas. Firefighters engaged in the evacuation task (F40) credited
these instructions with effectively motivating people to move as required:

> F40: “The drones can talk to them. That’s what I’ve seen today, that they
> can make announcements or something. That they can address people.”

Conversely, a different group of participants, primarily bystanders,
questioned the effectiveness of radio broadcasts due to concerns about the
optimal drone distance for audio communication. Two participants reported
difficulty distinguishing the intended recipients of the instructions during
drone broadcasts because the drone’s position for audio transmission was often
farther away from them than the distance between groups of participants. These
participants also mentioned that the small drone could be bothersome and
distracting when it flew too close to them. Therefore, designers should
explore options for positioning the drone closer to participants for audio
playback without causing resistance to the instructions or develop methods to
differentiate audio broadcasts for various participant groups:

> B15: “With the instructions, I also still see a little bit of disadvantages.
> Because there were two groups pretty close to each other. And there was a
> short moment where it was not quite clear to which group the instruction
> applied. And that can be very dangerous, of course. When the drone says: ’Go
> along the fence!’ And there are two groups standing along the fence. Then
> both groups meet in the middle, and that may not be the point.”

Furthermore, conflicting viewpoints emerged regarding the use of broadcasting
for evacuation instructions and providing information about the fire situation
to different participant groups. This discrepancy centered on the amount of
information bystanders should be given during firefighting operations.
According to the firefighting commander during the building fire trial, he
preferred not to relay detailed information to crowds to avoid inducing fear
and panic:

> C1: “You (crowds) can see that there’s a fire over there. But whether
> there’s a trash can burning or something like that (should not be told to
> them). And I also don’t want to have to tell them that there are still
> children in there or something like that. No, so that’s good enough for me.”

On the other hand, bystander groups expressed a desire for more information
from drone broadcasts. They felt that they could not fully rely on simple
instructions from drones directing them where to go, as they did not perceive
drones as representing the firefighting agency. Their preferred interaction
mode involved the drone providing on-site information so they could plan their
next steps. However, they also recognized that relying on the drone for
information reduced their need to approach firefighters for updates, which
could be valuable during critical missions:

> B10: “If you look from the outside, as it is an exercise, maybe all the
> processes should have gone in a bit more detail.”

> B13: “ She just took the decision away from me because she just said, ’We’re
> supposed to wait there for the fire department.’ And maybe not going closer
> to the fire to watch, but yes wait for the fire department. It said
> something about a forest fire. We were told to wait there, that the fire
> department was on its way and there were not much more instructions than
> that.”

Feedback on the message and livestream functions was provided by two
firefighters who directly interacted with the drone system in both trials.
Information overload was a recurring concern discussed in relation to the
drone system interface. The drone commander from the building fire trial
emphasized the need to rapidly identify crucial messages while managing high-
pressure tasks and the ability to review messages later. To address this
issue, modifications were made for the second field trial, including changes
to the message box and a priority list that reordered messages based on time,
highlighting essential ones. Firefighters from the second trial expressed
approval of the pop-up message feature when a victim was detected. They also
suggested improvements to the livestream function, such as the addition of
rewinding and enlarging capabilities to enhance the interface’s
comprehensibility.

####  5.1.2. Design needs for next steps

To explore potential interface improvements aligned with participants’ needs,
they offered several suggestions beyond the tested interactive experiences
with the current drone system.

In line with the findings of Khan et al. (Khan and Neustaedter, 2019),
participants expressed a desire for the drone system to detect hazardous
incendiaries and investigate dangerous environments, particularly to benefit
firefighters. Furthermore, the commander in the first trial discussed the
potential of redirecting information to lower-level team members as a solution
to address information overload. He proposed the idea of utilizing smart
helmets equipped with real-time thermal camera images, marked assemblies, and
environmental data collected by drones before firefighters enter the scene.
Such implementation, from the commander’s perspective, would alleviate the
pressure associated with decision-making and task allocation.

If these smart helmets were to be integrated into the drone system, a crucial
consideration would be the classification of information based on tasks and
urgency levels before transmission to the interface.

Firefighters also expressed the need to integrate their current tools and
documents, such as firefighting maps and digital systems, into the drone
system. Both the commander and one of the firefighters from the second trial
introduced the concept of merging these materials with the drone system:

> F38: “We have an incident command system, and if you could couple that
> together a little bit, that would be great, of course. So, that the image
> runs in the back, you know?”

> EC3: “There’s already a lot of predefined points… There I got water
> (pointing at a map)… There is a whole folder ’forest fire’ where everything
> is stored… if you can program that into a drone so that the drone also has
> that information… then the drone can give me a smart suggestion then I say,
> ’Yeah, that’s fine.’ The rest is already defined.”

Bystanders emphasized the importance of enhancing the credibility of drones
for emergency evacuations. They highlighted that trust in a drone and its
instructions hinges on the understanding that these autonomous vehicles are
affiliated with a firefighting team. Participants suggested that proactive
advertising through local media, such as radio, to inform the public about
drones joining fire stations could help establish a connection between
firefighters and drones. Additionally, participants recommended using
distinctive markings on the drone’s body, such as fire alarm symbols or blue
lights, to convey its purpose for emergency response and build trust.

Interestingly, the firefighting commander’s preference for drones to organize
firefighters, rather than bystanders or victims, was unexpected. He explained
that it’s uncertain how individuals outside the firefighting team would
respond to instructions from autonomous vehicles. This unpredictability could
divert commanders’ limited attention to episodic events and increase
complexity, exacerbating the issue of information overload if interactions are
not well-tested and simplified:

> C1: Yeah, you could see that nowadays, if we had an emergency and there
> would be bystanders, let’s say 100 people, and we would be saying: ’Please
> go to the side’, 80 would have left immediately and said: ’Yes, yes. It’s
> fine. Do your excellent job. We’re leaving’, and 20 would have still tried
> and come forward again somewhere else to look. And would have come there or
> there to look again.”

Firefighters offered more specific feedback on the autonomous decision-making
capabilities of drones and how they would interact with drones they perceived
as autonomous. Many participants believed that semi-autonomous drones would be
the most suitable solution for their current needs. In such cases, drones
would facilitate the decision-making process by presenting potential solutions
and optimal choices for humans to consider, with firefighters ultimately
making the final decisions:

> EC3: “If you can program that into a drone so that the drone also has that
> information. Then again it makes sense for it to say, ’Hey, in this case,
> operation commander, the location is there optimal or there optimal.’ And
> then I also say, ’Yes, it is. It really is.”’

Participants expressed mixed sentiments regarding the high level of autonomy
in drone systems. On one hand, the two-way communication tested in the trials
was deemed insufficient by both firefighters and bystanders. They expected
more advanced communication capabilities, such as the ability to issue voice
commands to visible drones or ask questions. Higher autonomy was seen as a
means to provide intelligent objects for quicker, more complex two-way
communication. On the other hand, many participants harbored reservations
about completely autonomous drones or drones making decisions independently.
Concerns centered on safety and privacy issues associated with autonomous
drones. Interestingly, one firefighter even raised the concern that
overreliance on drones could become a problem if drones operated independently
without human supervision, potentially leading to humans neglecting crucial
details while handling related tasks and losing control of the overall
situation:

> F43: “Yeah, I think it definitely would. I feel like if you always knew:
> ’The drone will be there.’ I don’t know, but I would imagine there would be
> a certain reliance on the device. And there would then also perhaps be a
> certain implicitness. People would say: ’Yeah, the drone went looking and it
> didn’t find anything. It’s fine.’ So, then you would have to maybe take
> yourself by the nose a little bit and say. ’Hey, maybe go look again
> yourself.’ ”

Among these comments was the intriguing suggestion for additional training to
familiarize drones with firefighting work, enabling them to find their place
within the team due to their unique capabilities. Similarly, firefighters
would benefit from training to understand new tasks and approaches when
working with drones as new team members.

###  5.2. Impact on Firefighting

####  5.2.1. Changes in the process

Participants frequently cited time-saving as a prominent advantage of using
drones. According to trial results, drones could reach the fire site 5-10
minutes faster than the firefighters. During this period, drones could survey
the scene and relay information about the terrain and fire situation to the
commander. Drones proved especially valuable for searching and reassuring
victims in complex terrain or open spaces. According to one exercise
commander, a key benefit was the potential rearrangement of task orders and
decision-making locations with the inclusion of drones. Commanders could
assign tasks before arriving at the scene:

> DO1: “I mean, that was actually really positive. You actually had the
> information quickly and could accordingly send people to rescue or support
> there.”

> F37: “The best thing was that we actually found at least one person
> relatively quickly… It just sped up that we got to the places. So, it
> actually saved us time finding people.”

####  5.2.2. Changes in team structure

In general, participants primarily viewed drones’ roles during the trials as
supportive tools for firefighters. For example, five participants described
drones as a source or intermediary of information between the fire and
firefighters. Several participants likened drones to teammates for
firefighters. A firefighter from the building trial even remarked that the
role of a drone felt more human-like than that of a tool. Similarly, a
firefighter from the forest fire trial perceived drones as akin to co-workers
capable of autonomous decision-making.

Based on preliminary interviews, many firefighters, particularly high-level
commanders, expressed the need to filter information from drones to avoid
information overload. The commander from the building fire trial proposed the
idea of having a new team member alongside him to handle the video feeds and
messages sent by drones during exercises. Another commander from the building
fire trial suggested that the person responsible for managing drone-derived
information should be an officer with expertise in drones and the operational
process:

> DO2: “That we say, I don’t always have to have people physically on-site,
> but we do it with a drone that can continuously fly over the entire fire
> object. And with thermal imaging, it actually needs an operator who can
> interpret the image, of course. That is, of course, crucial. ”

####  5.2.3. Changes in training

Introducing a new team member into the firefighting unit would necessitate
training to facilitate seamless collaboration. This experiment highlighted the
fact that the majority of firefighters still lack a comprehensive
understanding of drones’ capabilities and limitations, leading to a lack of
confidence when interacting with them. However, commanders expressed optimism
about addressing this issue through repeated training and the integration of
drone experts into the firefighting team:

> C1: “You would have to practice it like we do it with everything else. You
> would have to use the drone in exercises like today and build on this and
> notice: ’What can the drone do?’, ’What does the drone need to be able to
> do?’, or: ’What are the drone’s limits?’ So, without having practiced with
> it 10 times, of course, I would never take the drone into a mission.
> Otherwise, I really wouldn’t know how to interact with it. So, you really
> have to practice it. Just like we have to practice now with the machines,
> that we have water. Practicing until you say: ’Now the drones are ready and
> I’m ready.”’

> DO2: “Because it was the first time, it was still very unfamiliar and not
> easy to understand all the equipment and how to use the interface. But it
> wasn’t bad. It was just unfamiliar. So, it was not a problem. From my point
> of view, nothing was bad.”

####  5.2.4. Reliance

Concerns also surfaced regarding the potential loss of control over
firefighting operations due to reliance on information provided by drones. For
several firefighters, decisions made by automated machines were not entirely
trustworthy and could not serve as the sole source of information for building
situational awareness on-site. Therefore, combining information from drones
with data that firefighters could access and verify was deemed essential.

> F35: “The only possible disadvantage I would see is that people were a bit
> too reliant or if they got information that they misinterpreted.”

##  6\. Discussion

###  6.1. Choice of interactions

Expanding upon Alon’s previous research (Alon et al., 2021), we have delved
into alternative approaches for fostering direct communication between drones
and firefighters, reducing reliance solely on commanders as intermediaries.
Our exploration has encompassed the utilization of light signals and audio
instructions as means of interaction. Our primary objective has been to gain
insights into how firefighters perceive these novel interaction methods in
real-world firefighting scenarios and to identify areas where potential
improvements can be made. The findings from our study reveal that firefighters
responded positively to the use of light signals as a form of guidance for
locating victims. In contrast, the broadcasted audio instructions from the
drones were met with some concerns regarding clarity.

One notable observation is that firefighters generally favor light-based
interactions due to their simplicity and effectiveness. They say that
information conveyed through light signals is straightforward and these
signals remain visible in the sky until firefighters acknowledge them by
reaching the designated location. This feature alleviates the need for
immediate processing of information upon receipt, which stands as a notable
advantage over audio interactions.

Based on these findings, we envision two potential avenues for enhancing these
interaction methods. Firstly, visual interactions, facilitated by lights
mounted on drones, could offer a more efficient means of communication for
tasks beyond locating victims. Drawing inspiration from previous research on
human-drone interaction (E et al., 2017; Ginosar and Cauchard, 2023), these
lights could convey information about the current task, signal the next
action, or issue commands through variations in color, flashing patterns, and
blinking frequency. Within a firefighting context, it is plausible that drones
could employ different light colors to indicate the urgency of a task, thus
directly delivering critical information to firefighters without necessitating
an intermediary commander. This would, of course, imply adequate training for
the firefighters who need precise, ad hoc understanding of drones‘ light-based
messages.

Secondly, enhancements can be made to audio interactions to ensure clarity and
specificity, particularly when targeting specific groups. One potential
solution involves utilizing light signals to illuminate the intended recipient
group while simultaneously playing voice instructions. This dual-mode approach
could potentially address concerns related to audio instructions lacking
clarity and ensure that the information reaches the right audience
effectively. Another issue about audio interaction is the perceived
credibility. There are concerns about whether drones can be perceived as
representative of firefighting teams and how this will affect trust from the
perspective of emergency responders (Khan and Neustaedter, 2019). Our results
show that bystanders have the same doubts when receiving information through
broadcasting. In addition, Khan et al. also state that drones with prominent
appearances for emergency services may increase perceived credibility (Khan
and Neustaedter, 2019). According to bystanders in our field trials, they also
prefer visual marks such as blue lights or firefighting symbols to a statement
of affiliation before broadcasting. The potential reason could be that visual
marks are more common for representing emergency response and can be
constantly observed during operation.

###  6.2. Information overload

The issue of information overload in emergency response operations has been a
longstanding concern, and the introduction of digital systems and devices has
only exacerbated it (Jiang et al., 2004; Cowlard et al., 2010). In line with
the research conducted by Khan and Neustaedter (Khan and Neustaedter, 2019),
it is evident that drone systems pose a significant challenge in terms of
information overload. The autonomous drone system, at its current stage, has
not entirely resolved this issue. Autonomous drones possess the capability to
swiftly gather much information, yet this may introduce additional challenges.
For instance, much information delivered at once might force the commander to
make many decisions immediately. In that time, they would have limited
cognitive resources to attend to information provided by firefighters.
Therefore, exacerbation of information overload emerges as a primary challenge
in the design of autonomous drone systems.

Previous literature has offered limited comprehensive solutions to this
problem. However, our study yielded two potential measures proposed by
firefighters to mitigate information overload in the scenario: enabling the
autonomous drone system to provide selectable decision options and
facilitating the storage of information in easily retrievable formats (such as
video rewinding and message pop-ups). One notable concern regarding the first
solution pertains to the credibility of decisions made by drones, especially
in situations involving moral choices during rescue operations. Firefighters
remain skeptical about autonomous drones making critical decisions based on
essential information. Many of them still hold the belief that humans should
be the decision-makers in such scenarios, as machines are perceived to lack
empathy. In contrast, higher-ranking firefighters tend to see the advantages
of machines, which can rapidly consider multiple factors and potentially
exhibit a lower error rate than humans. Consequently, if the drone system were
to assume the role of decision-maker, several aspects, including firefighter
acceptance, model training processes, and success rates compared to humans,
warrant further exploration.

Regarding the enhancement of information traceability, prior research has
demonstrated the effectiveness of video rewinding in mitigating information
overload, particularly in educational contexts (Oza and Tarafdar, 2021).
Insights gained from interviews with firefighters reveal that specific
firefighting tasks often adhere to established procedures. Such procedures, as
well as local regulations, are embedded in files, maps, and the incident
system. Those artifacts are also used to share information between
firefighters and make decisions during operations. As of now, some of the
artifacts are being used in physical form (maps), and others are digitized
(incident system). This generates discontinuities between media. Adding drones
amplifies this challenge, as drones provide very dynamic, rich information
with higher temporal resolution. Therefore, the discussion on information
traceability raises considerations on how to integrate existing data and
systems with drone systems. Previous research suggests that the information
provided by drones could help construct the mapping system for search and
rescue (Alharthi et al., 2021). Other researchers believe it is important to
organize the current data before introducing a data stream from new
communication approaches and build adjustable systems for different roles to
select the information they need (Jones et al., 2020b). A later study suggests
that live-streaming video should be used as a supplement to existing
information sources rather than a replacement (Jones et al., 2022). Our
results indicate that the combination of previous and new data is also
associated with the autonomy of the drones. An interesting comparison is that
when firefighters suggested integrating drone information into the event
system, they considered only the tool attributes of drone information
collection. However, when the commander proposed having drones learn existing
rules, they considered the possibility of drones making independent decisions.
This insight can inspire interface designers of autonomous drone systems to
pre-set a list of significant events that may occur during the process and
annotate them in the video progress bar and message panel for easy reference
in drone system design. The layout of interface modules, aimed at distributing
information more logically, also emerges as a research topic deserving of
further exploration.

Furthermore, our findings have highlighted another issue: when information is
not adequately filtered and prioritized, drones may transmit irrelevant
information to bystanders, potentially burdening firefighters with unnecessary
work. This issue aligns with previous research findings (van Erp et al.,
2015). Some studies suggest that in emergency response situations involving
interactions between responders and bystanders, the operation should focus on
minimizing the negative impact of any conflicts rather than attempting to
resolve them entirely (van Erp et al., 2018). During the field trial, drones
amplified bystanders’ demands for more detailed information about the fire.
This engenders controversy concerning the positive impact of drones on
response times and may also contribute to exacerbating information overload
because through the interaction with firefighters further irrelevant
information might enter the exchange. One conceivable solution involves
categorizing information permissions hierarchically and granting firefighters
control over the level of information disseminated to bystanders. Previous
research suggests that transparency about drones’ use and their tasks might
improve bystanders’ sense of safety (Dolata and Schwabe, 2023). It suggests
that transparency about drones can be established prior to their use by
firefighters through broad information campaigns instructing the population on
how to behave and interpret the presence of drones. This could reduce the risk
of conflicts and escalating information demand. Still, the psychological
impact of drones on bystanders and the potential for them to escalate
conflicts in extreme situations remain uncertain aspects that warrant further
investigation.

###  6.3. Change of configuration

The alteration of firefighting configurations is another challenge for both
drone system designers and firefighting teams. We can address discussions
regarding this challenge from two perspectives: the role of drones after
integration into the firefighting team and the potential change of existing
firefighting roles.

Results from the field trials indicate that, at the current stage, most
firefighters perceive drones as tools rather than companions. Firefighters
primarily view drones as valuable for scouting and swiftly providing essential
information. However, especially among those in higher-ranking roles, there is
a belief that as drone autonomy advances, drones‘ acceptance and involvement
in firefighting operations will increase. This suggests that the demand for
drones to perform tasks with low levels of automation has not diminished with
technological advancements. Instead, there is an emerging demand for drones to
participate in decision-making processes. It’s conceivable that future drone
swarm operations may involve autonomous drones in both decision-making and
task execution, potentially forming hierarchical structures similar to human
teams or even integrated in human chain of order. Unlike the findings in
(Bjurling et al., 2020), we anticipate that in the future, drones will become
integral parts of the human team rather than separate entities comprising
teams of drones and firefighters.

The inclusion of drones has highlighted the necessity for a role within the
firefighting team that combines firefighting management skills with expertise
in drone technology. Currently, it seems that a new commander would fill this
role. However, as drones become more integrated into firefighting training,
this role may eventually merge with the existing operation commander position.
Additionally, many firefighters have already suggested that drones could
effectively replace human counterparts in search and reconnaissance tasks,
aligning with previous research findings. With a growing number of drones
within the system, it’s conceivable that the need for firefighters in
reconnaissance tasks may decrease in the future. Firefighters’ focus may shift
toward collaborating with or monitoring the automated decision-making
processes of the drone system. Moreover, autonomous drone systems could alter
the timing and location of decision-making, potentially allowing many
decisions currently made on-site to occur before arrival or by personnel in a
remote location. While this could reduce the risk of on-site accidents from
negligence, it’s essential for the system to have a well-defined allocation of
decision-making responsibilities and a designated person to avoid disputes
(Jiang et al., 2004).

###  6.4. Communication demands of stakeholders

Although our focus in this paper is on firefighters, comparing the viewpoints
of other stakeholders with those of firefighters can provide insights into the
design of drone systems. In search and rescue, communication is important to
increase trust and reduce mental pressure for participants (Mencarini and
Zambon, 2023). Our results show that drone systems can facilitate
communication among stakeholder groups. However, different groups have varying
communication needs.

We see that firefighters, bystanders, and commanders have different attitudes
toward sound interaction. They prefer lighting for different reasons: For
firefighters and commanders, light improves visibility at night, which helps
them to examine the scene and locate the victims. For bystanders, the
spotlight increases the credibility of drones. For victims, light means they
are identified and implies that rescue is coming soon, which provides comfort
when they are trapped or injured. We believe this divergence arises from the
distinct requirements of their roles. Firefighters consider the quality of
interaction primarily based on its substantial assistance in specific
firefighting tasks (evacuating the public, rescue operations, etc.). Preferred
interactive methods should enable the drone to undertake part of the
communication work with bystanders. High-ranked firefighters showed a focus on
the simplicity of interaction and its potential impact. Their needs were
driven by the immense workload and the psychological pressure of organizing
and making decisions within a short time frame. Bystanders are more concerned
about the manner and quality of interaction; they hope the interaction is
friendly, reliable, and detailed. Victims seek more emotional support from
interaction with drones. They wish the interaction to be more continuous and
intelligent.

Balancing the communication needs of different stakeholders will be a
challenge. On the one hand, communication signals that can be commonly
identified should be concise (Desjardins et al., 2014), which aligns with the
points of the commanders but for different reasons. Commanders wish to have
clear but limited information passed to the public to avoid panic and
overinterpretation of the situation. On the other hand, knowledge gaps during
the crisis may contribute to the spread of rumors (Starbird et al., 2020),
indicating that passing on enough information to the public is necessary under
emergencies. This aligns with firefighters’ and bystanders’ views. In addition
to the previously discussed approach of controlling information flow through
grading, determining the extent of information sharing based on the scenario
and the stakeholders present may also be a solution. Another way to enhance
communication is through repetitive training. Practicing with safety tools can
optimize the coordination and processes of a rescue team (Desjardins et al.,
2014). Integrating drone systems into firefighter training not only builds
trust in the system but also helps in defining the role of drones within the
team. This facilitates the establishment of stable coordination methods and
task processes.

Overall, the findings highlight the pervasiveness of information overload
caused by drone systems across the design and implementation process. Whether
in interface design, interaction mode selection, or structural reorganization,
both firefighters and designers are likely to encounter the challenge of
simplifying and directing information. If firefighters can widely accept
autonomous drone decision-making, the system may reduce the volume of
unprocessed information transmitted to them, thereby alleviating this issue.
However, the application of autonomous drones in firefighting is still in its
nascent stages, and many firefighters remain hesitant to trust decisions made
by machines. This recalls the lessons from the Mann Gulch fire tragedy (Weick,
1993). Consequently, the process of integrating autonomous drones into
firefighting decision-making must be iterative, allowing both firefighters and
drones to adapt to each other’s presence. Incorporating human-in-the-loop
training into the design process of autonomous drone systems, ensuring the
involvement of all human team members, can be pivotal for future development
and research.

##  7\. Limitation and Future Work

The study primarily focused on the ways in which drone systems support
firefighters during building and forest fires, offering valuable insights into
these specific contexts. However, internal validity could be strengthened by
expanding the investigation to include various firefighting tasks such as
tunnel rescues, water rescues, fire monitoring, and predictions. Future
research should broaden its scope to explore how drones can effectively aid in
these diverse tasks, providing a comprehensive understanding of their
potential applications and impact. Another area for future investigation lies
in exploring the quantitative impact of larger drone swarms on firefighting
and rescue operations. Our study concentrated on a restricted set of
interaction methods based on light, voice, and interface support, tailored to
firefighters’ needs during the trial. Subsequent research could examine the
effectiveness and feasibility of incorporating voice to specifically address
receivers, touch, and brain-computer interfaces in real firefighting
scenarios, offering insights into novel ways of enhancing communication and
control.

A limitation of the study relates to the sample size, as perspectives were
gathered from only two voluntary fire departments in Switzerland. To enhance
external validity, future research should include a more extensive sample of
field trials that encompasses a broader range of fire departments, both
volunteer and professional. The study captured the perspectives of only two
voluntary fire departments in Switzerland, and the transferability of results
to professional departments may be nuanced. Aspects such as personnel
availability, particularly qualified unmanned aerial vehicle (UAV) commanders,
might be perceived differently among professional firefighters compared to
their volunteer counterparts. This approach would provide a more
representative understanding of how drone systems could be applied in
different firefighting contexts. Additionally, our research was geographically
confined to Switzerland, and the influence of local firefighting regulations
and cultural factors on participants’ perspectives may have introduced biases.
Expanding the study to encompass diverse firefighting contexts globally would
enhance the generalizability and applicability of our findings.

##  8\. Conclusion

This research explored the functions and impact of the autonomous drone system
through two field trials, simulating building and forest fire operations,
respectively. We conducted field trials to simulate the autonomous features of
the system and gathered data from participants to assess their perceptions and
offer suggestions for such a system. The results pertaining to light, sound,
and interface interactions can serve as guidance for drone system designers.
Light is expected to find more applications in future designs, while voice
interactions have the potential to facilitate firefighters’ tasks while also
raising concerns related to privacy and unforeseen events. Additionally, our
findings reveal the challenges associated with addressing information overload
and adapting to changes in team structure as firefighters incorporate
autonomous drones into their existing configurations. Suggestions for
mitigating information overload can benefit both designers and firefighters,
aiding in the development and utilization of these systems in firefighting
contexts. Furthermore, our findings on the impact of autonomous drone systems
suggest that these systems could entail increased responsibilities for making
decisions related to drone operations, offering insights into potential role
reorganization within firefighting teams. Our study contributes to the HCI
community in terms of drone system design and also provides suggestions for
the firefighting teams for future changes.

###### Acknowledgements.

This study was conducted as part of the project ’Automated Decision-Making and
the Foundations of Political Authority,’ funded by the Swiss National Science
Foundation (project number 208013). We express our sincere gratitude to all
project members for their valuable feedback and active involvement during the
development and evaluation of the solution. Special thanks to the participants
in the field trials for generously sharing their opinions and feedback. Our
appreciation also goes to the fire stations in Altdorf and Silenen, as well as
the firefighters in the trials, for their unwavering support and collaboration
during the exercises. We extend our thanks to the members of the University of
Zurich for their crucial support during data collection and analysis: Yiwei
Wu, Andreas Bucher, Sven Eckhardt, Beat Furrer, Simon Giesch, Yiming Hu,
Yinglun Liu, and Pascal Marty. Additionally, we express our gratitude to the
anonymous participants of our study and the review team for their invaluable
advice concerning this manuscript.

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##  Appendix A Description of codes, sub-codes and example of data

Codes | Description |  | Examples of
---
subcodes
Example of data
Firefighting Regulation |  Firefighting incidents and corresponding measures. | Type of fire |  | … there is the room fire, which is the next biggest type
---
of fire, and is already very critical. And beyond that,
we have fires in commercial buildings, fires in entire
residential buildings, industrial fires, and so on …
Organization |  | … for example, how the damage site is organized. We
---
have a material depot, we have an assembly area, we
have the incident, and we have the operation
commander’s location …
Communication |  | … we had radios and we were connected to each other
---
like that, and the exercise commander was standing
next to me …
Interaction |  Interactions participants captured in the trials and how they feel about them. | Livestreaming |  | … so that interaction, I saw where the drone was,
---
what it was doing, and where the injured persons
were …
Lightening |  | … I also saw that they pointed directly at things with
---
light. If you have to look at the map, you don’t know
where the location is as there are a few trees behind:
with drones, you can see it well …
Audio |  | … the information came to me via audio, I was able
---
to brief the rescue team accordingly …
Support |  Perceived support from the drone system during the field trials. | Situation awareness |  | … so I saw that someone needed to be rescued and
---
was able to pass it on to the command center. That
was actually the positive (aspect) of the whole thing …
Victim rescue |  | … so I was in the rescue troop. That’s why we had
---
to deal with the drone. And that was actually
great that you had a clue where the person was …
Instructions |  | … there was a drone broadcasting to us, saying that
---
us need to evacuate from here since the building
is on fire. It can be dangerous. I think its helpful …
Application |  Suggestions regarding new feature in the system or improvement of existing features. |  | Suggest optimal
---
decision
| … It can make suggestions, which would be really
---
helpful. I really think that can take some burden
of the commander …
| After-fire
---
check
| … an ember, which is then covered with black ash.
---
You see from the outside, you think: ”Yes, it’s
extinguished,” but then you have to check with
the thermal imaging camera to be sure …
Delivery |  | … I know there are drones that can lift a lot of things
---
as well. So, you might be able to provide something
to a person somewhere that’s in a hardly accessible
location even if it’s just a water bottle …
Problem |  Perceived problems or potential concerns about using drones for firefighting | Privacy |  | … data protection is certainly an issue. Personal
---
security, so that it is simply there …
Technical |  | … a technical limit that was reached, but it’s a
---
technical system and every technical system has
its technical limit …
Interaction |  | … the radio was going non-stop, of course. So,
---
there was just too much information …