A Study of Knowledge Exchange for Airborne Delegation in C-SAR

Mission

T. Pagliardini-Leduc

, T. Letouze

, M. Poret

, B. Le Blanc

, D. Marion

J. Diaz-Pineda

, M. Gatti

, B. Claverie

and J-M Andre

Thales AVS, Bordeaux, France

Bordeaux INP-ENSC, IMS UMR 5218, Université de Bordeaux, CNRS Talence, Bordeaux, France

Thales LAS France, Bordeaux, France

Keywords: Leadership Delegation, CROP Concept, Knowledge Exchange, Collective Self-Confrontation Method,

Operational Challenges.

Abstract: Leadership delegation is a critical process stemming from the Command and Control (C2) centre, overseeing

various operational activities. Its primary objective is to assign strategic authority from C2 Air operators to

operational units. The initial step involves transferring comprehensive knowledge frameworks to local entities.

Implementing Common Relevant Operational Picture (CROP) concept enhances delegation capabilities

across diverse operational setups. CROP facilitates sharing necessary and relevant knowledge (and

information) among small collaborative teams, aligning with distributed situational awareness principles. This

study presents a new method to evaluate the significance of exchanged information to improve collaboration

between fighter pilots and military air traffic controllers in complex Combat-Search and Rescue (C-SAR)

scenarios. It focuses on identifying Necessary Shared Knowledge Elements (NSKE) crucial for mission

success. A collective self-confrontation method involving pilots and controllers acting out simulated scenarios

demonstrates effectiveness in determining NSKE. A demonstrator methodology and graphical interface are

suggested to aid operators during knowledge transfer in complex situations, supporting them visually through

the CROP. This approach allows supporting different actors in operation for the design of appropriate

representations associated with recommendations for future enhancements.

1 INTRODUCTION

Leadership delegation is a process originating from

the Command and Control Centre (C2) (Claverie &

Desclaux, 2016), a centre responsible for the overall

supervision of all types of operations carried out by

units in the field, which aims to transfer strategic

authority (the decisions of a C2 Air operator) to an

operational unit. One of the first stages of the

delegation of control is the transfer of the global

knowledge framework to a local entity.

https://orcid.org/0009-0008-6556-0750

https://orcid.org/0000-0002-8670-0280

https://orcid.org/0000-0002-2471-373X

https://orcid.org/0000-0002-7131-1805

https://orcid.org/0009-0002-6399-1051

https://orcid.org/0009-0007-0591-7706

https://orcid.org/0009-0000-5817-5063

https://orcid.org/0000-0002-7131-1805

https://orcid.org/0000-0001-9844-4694

Our study is focusing on how to evaluate the optimal

knowledge transfer in a collaborative work. To be

more precise, the study concerns the evaluation of a

methodology based on the representation of a CROP

(Common Relevant Operational Picture) instantiated

in a use case - known as the HMI CROP.

The importance of situational awareness in

decision-making and situation management is well

established (Endsley, 2021), particularly in complex

situations involving several agents with different

knowledge and goals (Steen-Tveit & Erik Munkvold,

Pagliardini-Leduc, T., Letouze, T., Poret, M., Blanc, B., Marion, D., Diaz-Pineda, J., Gatti, M., Claverie, B. and Andre, J.

A Study of Knowledge Exchange for Airborne Delegation in C-SAR Mission.

DOI: 10.5220/0012961800004562

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Cognitive Aircraft Systems (ICCAS 2024), pages 58-63

ISBN: 978-989-758-724-5

2021). A definition of situational awareness has been

proposed by Endsley (1988, 1989, 2000). For this

author, at the level of the individual, situational

awareness (SA) is "the perception of the elements in

the environment within a volume of time and space,

the comprehension of their meaning and the

projection of their status in the near future". In the

case of a team, Demir et al. 2017 propose "the degree

to which each team member possesses the situation

awareness required for his or her responsibilities"

(Endsley & Jones, 2001). According to Neville A.

Stanton, SA for a team is also known as Distributed

Situation Awareness (DSA) (Salmon, 2008). His

definition is: "activated knowledge for a specific task

within a system .... [and] the use of appropriate

knowledge (held by individuals, captured by devices,

etc.) which relates to the state of the environment and

the changes as the situation develops". The team's

situational awareness is maintained by information

transactions. One agent can compensate for the

degradation of another agent's SA. This follows the

work of Wei’s team (2017), who proposes that team

members don’t share all the information for a

dedicated the environment with other members, but

selected common elements to be shared, known as

common SA requirements. This later definition

relates to the Necessary Shared Knowledge Exchange

that needs to be exchanged among the members of the

team (Cain et al., 2016).

The Common Operational Picture (COP) is

defined by the United States Army Combined Arms

Center (2022) as “(Army) A display of relevant

information within a commander’s area of interest

tailored to the user’s requirements and based on

common data and information shared by more than

one command.”. This definition is quite restrictive

and is more a manifestation of the need to share a

common representation of an activity rather than truly

theorizing it.

Baber and collaborators (2013) highlight some of

the limitations of Common Operational Picture

(COP): "Although COP can offer benefits in terms of

information flow, it can create problems of

information overload, irrelevant information or

distraction for team members." These authors also

introduce another concept, the CrOP: "An alternative

system, known as a CrOP (Common relevant

Operational Picture), comprises a number of smaller

shared systems linked to agents with the same

situational awareness needs". This concept has been

used, for example, in the study of SA in commercial

aviation (Leduc et al., 2022).

1.1 Problematic and Hypotheses

In the context of collaborative work, what is the value

of CROP and how relevant are its elements for

sharing? By involving participants in a complex

scenario in which sharing information between team

members is essential to success, we hypothesise that

the contribution of a technological tool supporting

CROP can improve the sharing of mental

representations within the team. We design an

experimentation that offers a detailed and precise

evaluation of CROP. It enables the identification of

the specific elements of the activity that facilitate

teamwork and sharing of representation. The process

of identification is made possible by an interface

annotation task, which is initiated in the event of an

interruption to the scenario. In the course of this task,

the subject is required to annotate the CROP support

interface. It is hypothesised that the result of this

annotation is representative of the essential element

in the constitution of a common representation of the

task.

2 METHODS

2.1 Participants

Six operators took part in the experiment (three pilots

and three controllers) (mean of age: M=51.8 SD=3.4).

Both pilots and controllers have been retired from the

French armed forces for less than 6 years, but pilots

are still providing training for the armed forces. They

gave us their consent to participate before being brief

for their role in the experiment. All the operators are

former fighters or controllers. Many of them have

experienced a Search and Rescue mission in their past

experience.

2.2 Scenario Design

The evaluation process for this study consists of

having a pilot and a controller sitting in two different

rooms and playing out simulated C-SAR scenario

while their behaviour is monitored. The C-SAR

mission has been broken down into several phases to

provide a robust assessment of the information

relating to its activity.

This scenario was designed and implemented on a

consumer simulation software. The software Digital

Combat Simulator – DCS (Digital Combat Simulator,

2024) has been chosen among others (detailed in the

simulation setup section) to instantiate our scenario.

A Study of Knowledge Exchange for Airborne Delegation in C-SAR Mission

The scenario is broken down into a set of five

consecutive missions, each subdivided into two to

four steps representing major phases of the

progression of events, decisions and actions. The

scenario was designed iteratively according to

discussions and pre-tests with experts: pilots and

controllers (see the briefing on the map: Air Task

Order (ATO), on Figure 1).

Figure 1: Organization of the required software for the C-

SAR use case, within the stations.

The initial goal of the mission is to provide an Air

interdiction on enemy bases. The scenario is located

on the Caucasian theatre. Multiple tactical elements

have been set to make the simulation more realistic

and make the participant engaged in this environment

(detailed in the legend of the Figure 1).

To achieve their goal in the scenario, the

following assets are engaged:

- Uzi1 is an air fighter patrol where the pilot

participant plays the leader of the two fighters.

They are set for Air/Ground capacities and

tasked to engage the target TGT1. The

wingman is AI controlled. The pilot

participant can interact via the Radio with its

wingman that is played by one of the

experimentation accomplices.

- Cyrano is an AWACS (Airborne Warning and

Control System) with the task of control over

all the assets engaged. This role is played by

the controller participant.

- And other several assets that are piloted by an

AI system (blue and red forces) such as a blue

tanker, blue fighters, red fighters, ground

vehicles.

The scenario emphasizes collaborative working to

support the delegation, as at one point the wingman is

hit behind enemy lines. All the assets involved in the

surveillance and safety of the wingman on land then

have to be reorganized.

2.3 Simulation Setup

Figure 2: Simulation setup with their software to support

the use case scenario.

The experimental setup is made up of four

workstations named “Pilot” “AWACS”, “XP” and

“Stream”. The first two are used by the test

participants who play as the pilot and controller, and

the latter two are for the operators handling the

experiment (Figure 2). Each workstation is equipped

with a pair of headphones, microphones, and camera

video over the same network for monitoring

purposes. The participants can communicate via the

open-source software DCS Simple Radio Standalone

(Ciribob, 2024) through their headphones.

Figure 3: Pilot's workstation including the cockpit, the static

HMI CROP and the geospatial HMI CROP.

Each participant has at their disposal three screens

(Figure 3, Figure 5). The first one is their workstation:

the fighter cockpit for the pilot provided by the DCS

Client; the display of what an AWACS operator can

see rendered by the LotAtc software (DArt, 2024)

connected to DCS. The second is the instantiated

CROP interface is presented as a series of static

images. Each one of the images displays the relevant

information upon each step of the scenario. Those

ICCAS 2024 - International Conference on Cognitive Aircraft Systems

images are shown to the participants via a web

interface opened on dedicated screens of the “Pilot”

and “AWACS” stations. An operator at the “XP”

station is tasked with changing the images being

displayed as the scenario progresses. For each

change, a brief audio notification plays in order to

direct the participants’ attention to the new

information being provided.

Figure 4: Data flow of simulators within CONTINUUM-

Core.

Legend: POP – Personal Operational Picture, RKX -

Relevant Knowledge Exchange, PROP – Personal Relevant

Operational Picture, COP – Common Operational Picture,

CROP – Common Relevant Operational Picture, CA-PROP

– Collective Augmented Personal Relevant Operational

Picture

The last screen available is the spatially informed

part of the CROP information. This visualization is

provided in the consumer software Tacview (Raia,

2024) as a dynamic cartographic display. This display

uses data which are gathered from the pilot’s and

controller’s points of view, then aggregated and

filtered for relevance using a custom-made program

called CONTINUUM-Core (Figure 3).

In other words, all the tactical data related

to the simulation software is gathered to the

CONTINUUM-Core, while the data related to

analysing the behaviour of the participants are saved

to the “Stream” station. More precisely, the “Stream”

station runs the consumer software OBS Studio (Lain,

2024) specialized in capturing and synchronizing all

of the aforementioned video and audio streams,

including radio, into a single video for later

commentary and analysis.

2.4 Procedure

By splitting the experiment into separate missions, we

were able to pause in between phases in order to

gather spontaneous feedback from the participants

immediately after their experiences with the interface.

Each participant was introduced to the CROP HMI to

be used in the upcoming chapter before it starts. Then

they can react to the CROP HMI that were shown

over the past chapter by writing down their remarks

over printed versions of the interface.

Figure 5: Controller's workstation including the cockpit, the

static HMI CROP and the geospatial HMI CROP

In addition to the elements mentioned above, each

participant returned an annotation of the static CROP

images. Participants were asked to assess the

information value of each graphic element in terms of

relevance. Information is categorized according to the

criteria described in the result section. Afterwards,

participants took part in a self-confrontation

(Theureau, 2010). The collective self-confrontation

interviews were carried out in order to capture the

different points of view on the activity. To be more

precise, this interview allows us to get deeper in the

understanding of the operator’s activity and the

analysis of the annotations of the CROP HMI. Those

sessions were recorded for future analysis.

A Study of Knowledge Exchange for Airborne Delegation in C-SAR Mission

3 RESULTS AND DISCUSSION

In order to answer our hypothesis, during the

experiment the participants shared their impressions

of the different HMI CROP mock-ups linked to the

different phases of the scenario. The components of

each model were evaluated according to four

relevance criteria:

• Relevant information, which allows me to

carry out my task or understand the situation;

• Irrelevant information that can disturb me in

my task, mislead me or distract me;

• Useful but not essential information, which

does not disturb my task;

• Missing relevant information to add to the

component;

In addition, to analyse the comments about the

interface from the self-confrontation interviews, these

were recorded and then transcribed using an

algorithm.

A synthesis was then produced from the

handwritten comments on the interfaces and the

comments from the self-confrontation interviews.

A quantitative analysis of the results was carried

out, counting the number of comments made by all

the participants for each component of each interface,

with reference to the four relevance criteria

mentioned above.

Figure 6: Quantitative analysis of HMI CROP components.

From Figure 6, we see that certain meteorological

and event information, as well as information related

to the in-flight report, are mainly considered as

irrelevant or even disturbing information.

However, the information relating to the state of

the tactical situation remains variable, while the

direction indication data is mainly relevant.

Moreover, regarding the operators involved in the

operation, this information is useful to them and

should contain additional information for each asset

(such as their altitude block or their task).

Furthermore, the PR-11-LINE and CSARIR

components (checklist) allowing them to identify and

transmit the various information relating to the

ejected ally are mainly relevant for pilots and

controllers.

The C-SAR (Combat Search and Rescue) package

launch information is also mostly relevant and useful,

but needs additional information (such as the package

arrival time).

As far as immediate action is concerned, i.e. the

recommendations made by the interface to the

participants, these results essentially show that this

information is relevant, even if some participants

indicated that it was irrelevant or even disturbing.

This can firstly be explained by the fact that some

participants had not understood that this component

presented recommendations that they could either

accept or reject. In addition, others explained that for

them to be able to make these decisions, it would have

to be assigned to a specific role (such as ACE -

Airspace Control Element, or TEA - Terminal

Engagement Authority).

Lastly, the information highlighted in the

interface receives a large number of comments. This

information is mainly relevant and enables them to

carry out the task and understand the situation, even

if some of it remains irrelevant. This component of

the interface is highly contextual and can therefore

contain very different information from one moment

to the next. The different opinions thus depend on the

context.

4 CONCLUSIONS

The methodology we implemented enabled us to

demonstrate that the relevance of information is

contextual, but also that the need to access this

information strongly depends on the type of task

being performed. Indeed, whether the task consists of

taking information or making decisions, the need for

relevant information, and in particular access to it,

will vary. What's more, in our military context, the

acceptance of the task delegation is closely linked to

the delegation of the associated role. Thus, the results

presented suggest that interaction with the

recommendations made by the system is essential in

order to pursue the relevance analysis and thus assess

the acceptance of delegation and its use in operation.

Finally, we have highlighted the interest of CROP and

shown that it seems to be the preferred and

indispensable support for the acceptance and quality

ICCAS 2024 - International Conference on Cognitive Aircraft Systems

of delegation. The step forward is to evaluate the

following question: does the CROP support the

mechanism of delegation for future collaborative

avionics?

ACKNOWLEDGEMENTS

This research was funded by the HEAL consortium

(Human Engineering for Aerospace Lab) and its

members, namely THALES and Bordeaux-INP

associated with the University of Bordeaux.

REFERENCES

Baber, C., Stanton, N. A., Atkinson, J., McMaster, R., &

Houghton, R. J. (2013). Using social network analysis

and agent-based modelling to explore information flow

using common operational pictures for maritime search

and rescue operations. Ergonomics, 56(6), 889–905.

https://doi.org/10.1080/00140139.2013.788216

Cain, A. A., Schuster, D., Edwards, T., & Schuster, D.

(2016). A Quantitative Measure for Shared and

Complementary Situation Awareness. Proceedings of

the Human Factors and Ergonomics Society Annual

Meeting, 60(1), 1816–1820. https://doi.org/10.1177/

1541931213601416

Ciribob. (2024). DCS-SimpleRadioStandalone: An open

source Stand alone Radio for DCS integrating with all

clickable cockpits and FC3 Aircraft (2.1.0.2)

[Computer software]. https://github.com/ciribob/DCS-

SimpleRadioStandalone

Claverie, B., & Desclaux, G. (2016). C2 - command and

control: Un système de systèmes pour accompagner la

complexité. Communication et organisation. Revue

scientifique francophone en Communication

organisationnelle, 50, Article 50. https://doi.org/10.40

00/communicationorganisation.5449

DArt. (2024). ATC/GCI view of the battle in LotAtc

[Computer software]. RBorn Software. https://www.

lotatc.com/

Digital Combat Simulator | DCS World | Combat

Simulator. (2.8). (2024). [Computer software]. Eagles

Dynamics.

https://www.digitalcombatsimulator.com/fr/

Endsley, M. R. (1988). Design and Evaluation for Situation

Awareness Enhancement. Proceedings of the Human

Factors Society Annual Meeting, 32(2), 97–101.

https://doi.org/10.1177/154193128803200221

Endsley, M. R. (1989). Situation awareness in an advanced

strategic mission (No. NOR DOC 89-32). Hawthorne,

CA: Northrop Corporation.

Endsley, M. R. (2000). Theoretical Underpinnings of

Situation Awareness: A Critical Review. In M. R.

Endsley, D. J. Garland, M. R. Endsley, & D. J. Garland

(Eds.), Situation Awareness Analysis and Measurement

(1–January 2000, pp. 3–21).

Endsley, M. R. (2021). SITUATION AWARENESS. In G.

Salvendy & W. Karwowski (Eds.), HANDBOOK OF

HUMAN FACTORS AND ERGONOMICS (1st ed., pp.

434–455). Wiley. https://doi.org/10.1002/97811196

36113.ch17

Endsley, M. R., & Jones, W. M. (2001). A Model of Inter

and Intra-Team Situation Awareness: Implications for

Design, Training and Measurement. CA, Human

Factors and Ergonomics Society, 25.

Lain. (2024). Open Broadcaster Software | OBS [Computer

software]. https://obsproject.com/fr

Leduc, T., Le Blanc, B., Diaz-Pineda, J., Gatti, M.,

Dormoy, C.-A., Andre, J.-M., & Hourlier, S. (2022).

The Benefit of Relevant Knowledge Exchange in

Reduced Crew Operations. 2022 IEEE/AIAA 41st

Digital Avionics Systems Conference (DASC), 1–5.

https://doi.org/10.1109/DASC55683.2022.9925738

Raia. (2024). TacView—The Universal flight Data Analysis

tool [Computer software]. Raia Software Inc.

https://www.tacview.net/

Salmon, P. M. (2008). Distributed Situation Awareness:

Advances in Theory, Measurement and Application to

Team Work. 306.

Steen-Tveit, K., & Erik Munkvold, B. (2021). From

common operational picture to common situational

understanding: An analysis based on practitioner

perspectives. Safety Science, 142, 105381.

https://doi.org/10.1016/j.ssci.2021.105381

Theureau, J. (2010). Les entretiens d’autoconfrontation et

de remise en situation par les traces matérielles et le

programme de recherche «cours d’action». Revue

d’anthropologie Des Connaissances, 4(4–2).

United States Army Combined Arms Center. (2022). Field

Manual No. 3-0 (p. 280). Headquarters, Department of

the Army. https://armypubs.army.mil/epubs/DR_pubs/

DR_a/ARN36290-FM_3-0-000-WEB-2.pdf

Wei, C., Yong, W., & Manrong, Y. (2017). Pre-signal

Control of Comprehensive Waiting Area Based on

Traffic Operation Benefit Evaluation. Journal of

Chongqing Jiaotong University (Natural Science),

36(11), 78.

A Study of Knowledge Exchange for Airborne Delegation in C-SAR Mission