Providing Information on the Spot: Using Augmented Reality for Situational Awareness in the Security Domain

Action teams (Sundstrom 1999) or extreme work teams (Jones and Hinds 2002) in the security domain work highly interdependent and collaborative by nature. Still, effective collaboration in this field seems to be difficult to realize. (Berlin and Carlström 2011) study why collaboration often is minimised at an accident scene. Based on observations and semi-structured interviews, they discover that collaboration is often considered as ideal rather than something that is really carried out. As major reasons for only limited forms of collaboration, they identify information asymmetry, uncertainty and lack of incentives. (Smith et al. 2008) are of the opinion that it is difficult to consider crime scene examination from a team perspective, as usually several different teams from different organisations need to work together. The work is then centred around the collection of information and evidence in consultation with different people. The work effectiveness relies very much on the efficiency of each individual team, the communication of results and the coordination among the teams.

In the security domain, operational units rely on quick and adequate access and exchange of accurate context-related information (Lin et al. 2004). Quality information can help members of the operational units to resolve problems (Brown 2001) and to facilitate or maintain situational awareness (Straus et al. 2010). There is a mismatch between the information needs of operational units and the ability of ICT to provide the information (Manning 1996; Sawyer and Tapia 2005). Such a mismatch can impact the performance of teams and can ultimately save or cost lives (Jones and Hinds 2002). Bharosa et al. (2010) discuss challenges and obstacles in sharing and coordinating information during multi-agency disaster response. They consider challenges from an inter- and intra-organisational perspective, as well as the perspective of individuals. Major challenges are identified as conflicting role structures, mismatch between goals and independent projects, focus on vertical information sharing, information overload, inability to determine what should be shared or the prioritization of own problems. Bharosa et al. (2010) further identify factors to influence information sharing and coordination such as improving interaction and familiarity of other roles, knowledge of other agencies’ operations or the information and system quality. Reuter et al. (2014) examine mobile collaboration practices in crisis management at an inter-organizational level. Their study shows that new informal communication practices with current technology, i.e. mobile phones, needs to be derived. Mobile phone calls help to include remote actors in the situation assessment, but that verbal communication alone is not enough to facilitate situational awareness. Furthermore, challenges with regard to information flow during crisis management occur (Militello et al. 2007). Based on case studies, Militello et al. (2007) identify asymmetric knowledge and experience, barriers to maintaining mutual awareness, and uneven workload distribution and disrupted communication as major challenges. For each of the challenges different recommendations are presented. To overcome asymmetric knowledge, they suggest providing communication tools and training with their usage. To improve mutual awareness, they propose the use of shared displays. To address uneven workload, they suggest to more clearly assign roles and to make their responsibilities known across organisations. The latter is also stressed by (Drabek and McEntire 2002).

There are some further issues analysed in police teamwork, which are related to our study. Streefkerk et al. (2008) noticed that police officers often have no overview of availability and location of other team members. As a result, police officers often do not know which of their colleagues are available to handle an incident and incidents may go unattended. Motivated by this observation, they consider team awareness as the major challenge for police team tasks.

The above discussion shows that, though collaboration of different organisational units is desired, several challenges need to be addressed. Among the major challenges are information asymmetry among the different organisational units, the efficiency as well as limits of verbal communication, the knowledge of the responsibilities of the different organisation and finally the situational awareness of the different team members.

Human factors research into individual situational awareness originated from the study of military aviation, where pilots interact with highly dynamic, information-rich environments. A widely adopted definition of 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” (Endsley 1995). SA includes thus the understanding and comprehension of a given environment and situation, as context for one’s own actions. In this view, SA is seen as a cognitive product of information-processing (Salmon et al. 2009). The concept of SA has been used in several other domains such as energy distribution, nuclear power plant operational maintenance, process control, maritime, or tele-operations (Salmon et al. 2008). Still, several researchers argue that a universally accepted definition of the SA is yet to emerge (Salmon et al. 2008).

In CSCW research, awareness is similarly an ambiguous term. In general, awareness refers to actors’ taking heed of the context of their joint effort (Schmidt 2002). Awareness in this understanding can be distinguished from notions of attention or focus by its secondary nature. Awareness cannot be provided, as the alignment and integration of actions occurs seemingly without effort. For achieving this seamless way of collaboration, actors seem to both actively display and monitor each other’s actions (Schmidt 2002). In this understanding, awareness is understood as an on-going interpretation of representations (Chalmers 2002). Even though it seems to be more a question of observing and showing certain modalities of action, information sharing is crucial to develop awareness, as it allows teams to manage the process of collaborative working, and to coordinate group or team activities (Dourish and Bellotti 1992). Awareness information therefore plays a mediating role for collaboration and creating shared understanding (Gerosa et al. 2004). However, several different types of awareness can be distinguished (Schmidt 2002): general awareness (Gaver 1991), collaboration awareness (Lauwers et al. 1990), peripheral awareness (Benford et al. 2001; Gaver 1992), background awareness (Bly et al. 1993), passive awareness (Dourish and Bellotti 1992), reciprocal awareness (Fish et al. 1990), mutual awareness (Benford et al. 1994), workspace awareness (Gutwin and Greenberg 2002).

Workspace awareness is defined “as the up-to-the-moment understanding of another person’s interaction with the shared workspace” (Gutwin and Greenberg 2002). Workspace awareness can be considered as a specialized kind of SA that involves a shared workspace and the task of collaboration (Gutwin and Greenberg 2002). Though workspace awareness cannot be compared with the high information load and or highly dynamic situations for which the concept of SA is researched, both concepts share important characteristics. For workspace awareness and SA, people need to gather information from the environment, understand what the gathered information is about and predict what this means for the future. Shared visual spaces provide SA and facilitate conversational grounding (Fussell et al. 2000, 2003). In collaborative environments, visual information about team members and objects of shared interest can support successful collaboration and enables greater SA (Gergle et al. 2013). SA is thus crucial for fluid, natural and successful collaboration to adjust, align and integrate personal activities to the activities of other – distributed – actors (Gutwin and Greenberg 2002).

Many studies show that the quality of communication or information sharing has a relation with team performance (Artman 2000; Pascual et al. 1999; Stammers and Hallam 1985). Artman (2000) showed that for the development of SA in a team, it is preferable that information is provided sequentially in order to allow time for every team member to develop their own SA. Pascual et al. (1999) highlight the importance of regularly updating each other in a team, to develop a shared understanding of a situation. As a solution, they propose the coordination of the updates as being an important task of a team leader. Furthermore, Stammers and Hallam (1985) indicate the need to align the organization of a team, especially with regard to information input and output, to the complexity of the task.

Team effectiveness is often reflected by the degree in which team members engage in processes for sharing information (Bowers et al. 1998), while being engaged within both verbal and non-verbal communication. Poor SA is often associated with accidents and incidents, and with reduced effectiveness of a mission (Taylor and Selcon 1994). In face-to-face interactions, it seems to be relatively easy to develop SA of other actor’s actions. For distributed actors, this becomes more difficult. Technology used might diminish the information one actor perceives, compared to a face-to-face situation, as it is more difficult to perceive other actors’ body language. When technology is used, the artefacts provided are a source of SA, too. Especially the change of an existing artefact gives off information (Gutwin and Greenberg 2002). Therefore when using AR technology, it is necessary to investigate how it may be used to gain a deeper understanding in supporting the development of SA for distributed actors in the security domain and what kind of artefacts to provide.

Most of the work in the security domain is conducted within teams. People in teams need to act reciprocally; they are interdependent to other team members and share one working environment. To better understand SA within teams, Endsley (1995) introduces the concept of team SA which is defined as “the degree to which every team member possesses the situation awareness required for his or her responsibilities” (Endsley 1995). According to Endsley and Robertson (2000), successful team performance requires that individual team members have a good SA on their specific task and that good team SA is dependent on team members understanding the meaning of the exchanged information in the team. Endsley and Robertson (2000) further suggest team performance is linked to shared goals, the interdependence of team member actions and the division of labour between team members. Human factors research further identified the concepts of shared SA as “the degree to which team members have the same SA on shared SA requirements” (Endsley and Jones 2001) and distributed SA which is defined as “SA in teams in which members are separated by distance, time and/or obstacles” (Endsley 2015). Endsley (2015) further points out that despite being distributed “the SA needs of the team members are the same as when they are collocated, but are made much more difficult to achieve”. This distributed SA concept needs to be contrasted with a more systemic understanding of distributed SA, which views “team SA not as a shared understanding of the situation, but rather as an entity that is separate from team members and is in fact a characteristic of the system itself” (Salmon et al. 2008). The latter understanding of distributed SA assigns SA not only to human actors but also technological artefacts (Stanton et al. 2006). With that it contradicts Endsley’s assumption that SA is a uniquely cognitive construct by taking a world view on SA (Salmon et al. 2008).

In summary, supporting SA can improve collaboration as it enables actors to adjust, align and integrate own activities with those of other distributed actors. In this relation, shared visual spaces and visual information further enable supporting successful collaboration and SA. It is an open question whether Augmented Reality is able to provide visual information in such a way that it also supports successful collaboration and SA. To determine this, it is necessary to gain more understanding of SA for teams in the security domain. In the following, we distinguish between individual SA and team SA. However, we do not follow Endsley and Jones (2001) in their understanding of shared SA that requires “shared mental models” as this ends up in a tautology that defines cooperative work by a shared goal and assigns this to actors by assessing whether they all act in concert (Schmidt 2011).

AR systems support distributed collaboration processes in various application domains. To explore the effect of AR systems on collaboration, studies compared classical communication systems with the new support provided by AR. Wang and Dunston (2011) present an AR-based system for remote collaboration and face-to-face co-located collaboration in the scenario of detecting design errors. Both approaches are studied and compared to a traditional paper-based drawing review method, pointing to the advantage of mixed-reality for remote collaboration tasks.

Schnier et al. (2011) focus on studying the issues around establishing the joint attention toward the same object or referent in a physically co-located collaborative AR system. The experiments involve pairs of users seated face-to-face at a table in a shared physical environment. Each user is equipped with an HMD. Users can grasp physical objects, each having attached an AR visual marker, and pass them from one user to the other during a collaborative design task. The study reveals the difficulties in coordinating participants’ foci of attention. The authors advocate that establishing coordination and joint attention could benefit from adequate support for a participant to access the co-participant’s visual orientation in space.

Gu et al. (2011) conduct a study on the impact of 3D virtual representations and the use of tangible user interfaces using AR technology. The results indicate that the change from a physically co-located working environment to a virtual co-located scenario encourages the AR users to smoothly move between working on the same tasks and working on different tasks or different aspects of the design process. The findings emphasize the capability of 3D virtual worlds to support awareness during remote collaboration, with no major compromises for the communication and representation.

Dong et al. (2013) present ARVita, an advanced collaborative AR tool with problem solving capabilities to be applied in classroom and in professional practice. In ARVita, multiple users with HMDs sit around a table, where they interact with and visualize dynamic simulations of engineering processes, which are overlaid on the surface of the table. The table-based media allows for natural collaboration among people to quickly exchange ideas, using the AR-based support, which providing better means for collaborative learning and discussion.

The effect of AR systems on collaboration is in some cases studied using a game-oriented approach. Wichert (2002) Wichert (2002) describes a mobile collaborative AR system that uses web technologies. In the collaborative environment, several users wearing HMDs can play a 3D Tetris-like game. The players can be located in the same room but also in different locations. The game setup provides support for studying the two types of AR-based collaboration: the co-located collaborative interaction with skilled workers, each having a different view of the AR world and the indirect interaction with a remote expert that has the same view as the skilled worker. This early paper identifies shared visualization for the remote expert, common and private information exchange, representation of interaction results, the use of colour, arrows and numbers, as key components of an AR system that simulates the collaboration of skilled workers to a remote teacher.

Datcu et al. (2013) present an AR-based collaborative game relying on free-hand interaction. Here, the game is used to study the effect of AR when supporting complex problem solving between physically co-located and virtually co-located participants. Within the game, the goal of jointly building a tower of coloured blocks represents an approximation of a shared task. Individual expertise is modelled as the possibility to move blocks of a distinct colour and shared expertise is modelled by the possibility of all players to move blocks of the same colour.

Procyk et al. (2014) propose a shared geocaching system that allows players to see remote locations while holding conversations. The study points to the value of mobile video chat support as an enhancement of shared geocaching experiences. Furthermore, the authors highlight the role of the asymmetrical experiences and information exchange as important factors to improve parallel experiences of users who are engaged in remote common activities.

The way information is presented within AR has a strong influence on the shared understanding of a problem and the current situation as well as any solution to follow. Ferrise et al. (2013) use AR to teach maintenance operations by combining instruction manuals with simulation. Here, a skilled remote operator guides a trainee that is equipped with AR technology. The operator can visualize instructions in AR on how the operations should be correctly performed, by superimposing visual representations on the real world product. Shvil, an AR system for collaborative land navigation, overlays visual information related to the explorer onto a scaled physical 3D printout of the terrain, at the physical location of the overseer (Li et al. 2014). The collaboration process between the overseer and local explorer provides live updates on the current location and the path to follow by the field explorer.

Nilsson et al. (2009) present an AR collaboration system that supports placing and modifying event and organization-specific symbols on a shared digital map associated to a crisis management scenario. Even though the task of creating a shared situational picture scored well with the paper map standard, the AR-based collaboration allows users to better focus on the task in a less-cluttered joint work environment. Team cognition is supported by providing information for joint work, gesturing and joint manipulation of symbols.

Gurevich et al. (2012) propose TeleAdvisor, a remote assistance hands free assembly that enables a remote helper to give directions to a local user by voice and by projecting information directly in the physical environment of the local worker. A tele-operated robotic arm having attached a pico-projector and a video camera, directs the remote user towards the point of need, and emphasizes graphically with rectangles, the remote’s view to the local. The results highlight the remote’s ability to control the robotic arm to fully understand the work environment. The findings show that a remote helper prefers to generate graphical representations in the form of free sketch annotations and pointers. They further indicate that text and icon-based annotations are not used at all during the collaborative work sessions.

Alem et al. (2011) propose ReMoTe, a remote guiding system that integrates non-mediated hand gesture communication in the mining industry. In ReMoTe, an expert remotely assists a worker using hands to point to certain locations and to show specific manual procedures. The expert hands are shown to the local worker in the form of virtual hand projections indicating the correct hand actions. The system implements a panoramic view over the local user’s workspace, to enhance the remote users ability to maintain an overall awareness of the local’s activity and workspace.

Streefkerk et al. (2013) find remote’s annotations usable and intuitive, concluding that such virtual tags can speed up the trace collection process, and can reduce time for documentation during collaborative work sessions in forensic investigations. Virtual tags are appreciated to increase the user awareness over the crime scene and are found to decrease the initial orientation requirements at the scene. Furthermore, the study of Domova et al. (2014) shows that instantly synchronized snapshots and annotations in form of pointers and overlaying drawings, lead to a general acceptance of the system and provided more efficient means of conveying spatial information. This resulted in lower frustration and better communication between the field worker and remote expert. The described AR system improves situational awareness by offering a wide field of view, shared visual space, tracking the attention focus of the other participant, and the support for gesturing within shared visual space. A more expressive and arguably more intuitive interaction with the scene is proposed by a tablet-based system, that incorporates a touchscreen interface through which a remote user can navigate a physical environment and create world-aligned annotations (Gauglitz et al. 2014a, b).

The above discussion provides several examples for the use of AR to support collaboration among users in various domains. The examples provided vary in several aspects. Users are either physically or virtually co-located. They use free hand or tangible interaction with physical objects. In some cases, users are static. In others, users are mobile. Finally, some AR systems make use of HMDs while others rely on different visualization devices. Common to all examples, is the underlying idea to provide information in AR and thereby improve awareness and collaboration.

Based on the considerations above, an AR system in the security domain needs to support virtual annotations for local and remote users to create shared situational awareness in physically distributed security units (Nilsson et al. 2009). Due to the nature and the intensity of activities in the security domain, an AR system further needs to rely on an egocentric vision provided by cameras in the HMD cameras rather than on vision from external sensors and on-site projection. Following (Gurevich et al. 2012), an AR system needs to offer annotation tools for remote and local users in combination with marker-less tracking for natural interaction experiences. In contrast to the presented approaches that rely on tablet computing devices, an AR system for the security domain needs to use HMDs, as thereby information can be provided in the direct sight of the users and users can keep their hands free (Wille et al. 2013). Finally, compared to (Domova et al. 2014) an AR system needs supports asymmetry in media (Voida et al. 2008) and asymmetry in experiences (Procyk et al. 2014) to allow remote users temporarily decouple from a local user’s video stream and focus on details in the provided view.

In order to test the AR technology and to gather insights into its usability for real fieldwork in emergency teams, it is important to develop highly realistic scenarios. Scenarios provide hands-on experiences with real-life problem solving tasks (Niehaus and Riedl 2009) in safe experimental environments. With such scenarios, realistic situations can be simulated in order to gather deep insights (Schön 1983).

Scenarios show aspects of games, involving play based on certain rules, take place within a defined location, are limited in time, and follow specific rules (Brandt 2006). Earlier design experiences with operational units in the security domain (Lukosch et al. 2014) show that by using the Triadic Game Design (TGD) philosophy (Harteveld 2011) playful, meaningful and realistic scenarios can be identified. TGD (Harteveld 2011) is an end-user oriented design approach, distinguishing three equally important components: Play, Meaning, and Reality. TGD emphasizes that all three aspects have to be balanced within a design in order to develop a valid, meaningful, and engaging game experience.

During a half-day workshop, in which 12 members of 4 different operational units participated, 3 different scenarios have been identified. The TGD philosophy was used as a guideline for the workshops. The three elements Play (P), Meaning (M), and Reality (R), have been addressed while defining the scenarios. Together with the experts from the security domain, we held a structured brainstorm session, in which we first defined the necessary elements of reality (R) needed for the test scenarios. It was soon clear that highly realistic scenarios with a similar amount of stress and a realistic story line would be needed in order to explore the feasibility of the AR technology. Thus, the reality aspect addresses all circumstances that are derived from real life situations of emergency teams, such as realistic communication means, physical attributes at the scene and clothing worn during the test. Secondly, the meaning (M) aspect of the scenarios was addressed by defining clear measures of the usability of the AR technology as the aim of this study. Thirdly, within the play (P) aspect, we formulated which kind of actions and decisions are possible and required within the scenario, but also which procedures and protocols would define the ‘rules’ of the scenario.

The scenarios focus on tasks for individual operational units. Their main purpose is to introduce the AR system as well as evaluate its feasibility and usability. In all 3 scenarios, the AR technology is used to establish virtual co-location. Virtual co-location entails that people are virtually present at any place of the world and interact with others that are physically present in another location by using AR techniques. Figure 1 illustrates virtual co-location of two policemen. A local policeman wearing an HMD (see Figure 1 (left)) is connected to a remote colleague (see Figure 1 (right)). By streaming the video captured from the camera in the HMD, the remote colleague can see what the local policeman is seeing and provide additional information on the situation in the display of the HMD to the local colleague. In the scenarios, interaction is thus limited to oral communication and the remote colleague providing additional information on the situation. The following sections describe the three scenarios identified and indicate the different elements Play (P), Meaning (M), and Reality (R) of the TGD philosophy.

Eleven policemen and inspectors from 3 national Dutch security institutions participated in the usability study, playing roles in the 3 scenarios: VIP protection (see Section 0), forensic investigation (see Section 3.1.2), and domestic violence (see Section 3.1.3). 4 of the participants were involved in the design of the scenarios. The rest of the participants were chosen at random and their availability on the day of the experiment. None of the participants has used our AR system before. All experiments took place indoors at a real training environment, belonging to the Dutch police in Leusden, The Netherlands. For each experiment, 2 participants are required: the local person that wears the HMD and the remote person in front of a laptop. The local and remote persons are situated in different physical locations (but in the same house) and are connected via a local network.

In order to investigate the usability of AR support for security teams, each participant filled in a questionnaire (see Table 1) after the experiment. The questionnaire consists of 16 closed and 8 open questions on the usability of the system, as well as its ability in regards to information exchange. The questionnaire is also based on the TGD approach and has already been used in studies conducted in the game design field (Bekebrede 2010; Harteveld 2011). TGD is also used as background for the survey to investigate whether the three aspects of reality, meaning and play could have been addressed with this set-up of a test scenario, and whether the AR technology was able to support a well-balanced scenario. Endsley’s conceptualization of situational awareness (Endsley 1988) was used to explore the aspects of situational awareness as starting point for the second study. An interview round concluded the evaluation.

All participants of the experiment were given an oral briefing on the goal of the experiment. Each participant knew the designed scenarios due to earlier written communication or participation in the design session of the scenarios. The VIP protection scenario was played a total of 4 times with the participants, alternating the roles of the local and remote colleague. The forensic investigation scenario was played 2 times. Again, the participants changed their role from one round to the other. Finally, the domestic violence scenario was played twice with the participants alternating their roles.

Following the description of the scenarios, only the remote participant was able to manipulate the virtual content through a classical 2D user interface, while the local could only see it. For each of the 3 scenarios, the user interface offered different functionality for the remote user.

We have developed a framework named DECLARE (DistributEd CoLlaborative Augmented Reality Environment). DECLARE is based on a centralized architecture for data communication, to support virtual co-location of users. DECLARE consists of four major components (see Figure 2):

This section reports on the results of the interviews and the data from the evaluation questionnaire (see Table 1) filled in by the participants at the experiment. The AR system as introduced above, was used as supporting means for the distributed security teams. Table 3 presents the medians (Mdn) and interquartile ranges (IQR) per scenario, on each Likert item. In the following, we discuss the feedback of the participants per scenario.

In summary, the participants of the first test appreciated the shared visualization, the communication, the directions of the external supervisor and the person profile pictures being delivered on the spot. The evaluation of the answers indicates that the scenarios were clear and attractively built, with clear instructions and explanations given beforehand. The location and the setup which included weapons, real handcuffs, visual representations of blood patterns and injuries (on a mannequin in the forensic scenario) contributed to the realism of the scenarios. Table 4 presents in short the overall findings of the usability study.

In most cases, the virtual information was easily recognizable and displayed at the right time. The ability of the AR system to add information to a real situation and to support collaboration among distributed users, showed positive effects on communication and team SA. With the TGD approach, we were able to create realistic circumstances to test the feasibility and usability of AR technology in the security domain. The limitations of the technology, mainly the use of the heavy backpack, showed how important the relationship to the real work environment was for the participants. Additionally, while AR technology was appreciated by most of the participants for easily sharing information within and amongst teams, they also reported on information overload introduced by the technology.

Thus, the first test showed limitations of the AR technology, mainly because of the immobility of the system and its user. The test results lead to an improvement of the AR system towards a wireless connection. Furthermore, a free hand user interface was introduced. With these improvements, we set up a second study, moving a step further in the direction of exploring the use of AR for the development of team SA.

Like in the first study, TGD influenced the design of the scenarios for the study on AR technology to foster collaboration and SA within and between emergency units. The scenarios were developed in a similar workshop as described above (see 3.1). During a half-day workshop, in which 6 members of the Dutch Police, the Netherlands Forensic Institute (NFI), and the fire brigade of the port of Rotterdam participated, 2 different scenarios have been identified.

The following sections describe the 2 identified scenarios. Compared to the earlier described 3 scenarios, the following scenarios were designed in order to evaluate the effect of the AR system on collaboration and situational awareness in the different teams (police, fire department and forensics). For that purpose, the scenarios are designed in such way that they can be played in two conditions: (1) with AR support for virtual co-location and (2) when using standard equipment following standard procedures.

13 participants in total took part in the experiment. Participants were chosen randomly, due to their availability on the day of the experiment. All participants were male, with an age from 25-54 years (M = 37.8 SD = 10.0). All had a minimum of 2 years experience in their recent professional occupation. The most experienced had 12 years of experience in his field (mean = 6.3). 3 participants were forensic researchers from the Netherlands Forensic Institute (NFI). 3 were firemen from the fire brigade at the port of Rotterdam. 3 were policemen from the Dutch Police in North-Holland. 2 were from a close protection team in the Dutch police and 2 were from a reconnaissance team from the Royal Netherlands Marechaussee (RNLM), which is a gendarmerie corps, i.e. a police corps with military status. In addition to the above participants, 3 more members of the above organizations participated to play the roles of the inhabitant of the apartment in the ecstasy lab scenario, the contact person as well as the VIP. These 3 members were also involved in the design of the scenarios.

In this second study, our aim was to investigate how distributed security teams collaborate with AR technology, and which effect the AR technology has on situational awareness of these teams. We used a pre-questionnaire as first measurement method (see Table 5). With the pre-questionnaire, data was collected about the participants’ background, their experience in the domain with AR technology and their expectations towards the experiment.

For the first run through the scenario, participants were given the technology currently available in the field, such as their standard issue communication equipment and a camera. For the second run, one local participant used the AR support system described in chapter 3, to establish virtual co-location with a remote colleague. When using AR support, participants also used their standard communication equipment. After both rounds, a questionnaire was provided to the participants, which consisted of two sets of questions. Table 6 shows the questionnaire for the participants using AR support. The questionnaire for the participants when having no AR support only differs with regard to question 2.2. The first two sections of the questionnaire are related to the experiment itself. The third section assesses the quality of collaboration, by asking questions along the 7 dimensions of collaboration quality as introduced by (Burkhardt et al. 2009).

As we discussed in section 2.2, situational awareness includes the perception, comprehension and prediction of each other’s actions within a given situation in order to align and integrate the team members’ actions. The fourth section of the post-questionnaire consists of a self-rating of the individual situational awareness. Several different measurement methods exist for measuring the level of situational awareness. The measurement approaches include freeze probe techniques, real-time probe techniques, self-rating techniques, observer rating techniques, and performance measures (Salmon et al. 2009). Very little measurement approaches exist for distributed or team situational awareness. For the questionnaire we use the validated post-test self-rating technique (Taylor 1990) as this avoids the freezing of action during the test, like when applying the SAGAT method (Endsley et al. 1998). Even though the freeze-probe methods provide more significant data, it has the important drawback of interrupting an action, and thus may negatively affect performance. Self-rating techniques such as the SART questionnaire are administered post-trial, and thus have a non-intrusive character. Furthermore, in their study, (Salmon et al. 2009) come to the conclusion that a post-test self-rating technique is applicable whenever “SA content is not pre-defined and the task is dynamic, collaborative, and changeable and the outcome is not known (e.g. real world tasks)” (Salmon et al. 2009). By assessing the individual SA, the team SA can be judged as well as this is defined as “the degree to which every team member possesses the situation awareness required for his or her responsibilities” (Endsley 1995).

Finally, after each experiment, a structured de-briefing was used to further investigate the experiences of the participants with the technology, their self-rating collaboration quality and SA. Two video cameras were used to record the experiment in order to conduct a qualitative analysis, again along the seven dimensions described by (Burkhardt et al. 2009). One video camera was placed to record the actions and communications on the spot (local person), the other was recording the actions and communication of the remote person. This camera was also used to record the de-briefings.

Table 7 illustrates the categories taken into account for the statistical analysis. The six categories C01-C06 are linked to the ecstasy lab scenario. From these six categories, three are representing experiments using AR support C01-C03 and three are representing experiments without AR support C04-C06. The VIP scenario is studied using the four categories (C07-C10). From these four categories, the three categories C07-C09 are representing experiments using AR support and C10 is representing the experiment without AR support. In addition, the six categories C11-C16 are not dependent on the scenario. Out of these, the two categories C15 and C16 are not dependent on the role played by the participants during the experiment sessions.

To derive relevant observations from the data, the medians are used as primary comparison criterion. The comparisons take into account valid pairs of categories, which in turn, relate to the experiments from the same scenario and role. The categories C11-C14 are exceptions in the sense that they refer to experiments on both scenarios. Still, C11-C14 consider the role played during the experiment while C15 and C16 just distinguish whether AR support was used or not. Table 8 displays the pairs of categories for investigation. Please, note that the categories C7 and C9 are not used for comparison, as the non-AR VIP scenario was played without a remote colleague, as this resembles current work practices.

All experiments took place indoors in a real training environment at the Netherlands Forensic Institute (NFI). The testing altogether lasted one day. Figure 7 shows the plan of the CSI lab at the NFI. The upper highlighted box shows the plan of the apartment that was used as ecstasy lab and as the location for the house visit. The apartment consists of four rooms, i.e. a bedroom, a bathroom, a kitchen and living room combination and an entrance hall. The orange highlighted box in the middle of the plan resembles a typical Dutch street. During the experiment, this area was used by the different emergency teams to orally brief each other about the situation. The lower highlighted box shows the location for the remote colleague and further activities around the experiment, like briefing and de-briefing. The location is physically separated from the apartment by walls and doors, so that remote and local persons could only interact via the available technology.

All participants of the experiments were given a slide presentation to introduce the goal of the experiment. In addition to this general presentation, the participants of the ecstasy lab scenario experiment, i.e. 3 policemen, 3 firemen and 3 forensic investigators, were given a presentation on the general outline of their scenario with and without AR support. The same applies to the participants of the VIP scenario, i.e. 2 members of the close protection unit and 2 members of the reconnaissance team.

Each of the scenarios was played 2 times with and without AR support. First, the scenarios without AR support were played. Then, the scenarios with AR support were played. Between each round, the setup of the apartment was changed to avoid sequence effects. These changes included moving evidence from one location to another in the ecstasy lab scenario, or hiding different suspect objects in the VIP scenario. In addition, the roles of the participants were rotated to allow all participants to experience the local and remote role, e.g. a fireman who in the first round had the role of the remote colleague became the local fireman with AR support in the second round.

After the introductory presentation, all participants were asked to fill in the pre-questionnaire (see Table 5) simultaneously. After each round, all participants were asked to fill in the post-test questionnaire (see Table 6) and participate in a structured de-briefing session.

Compared to the previous experiment, the remote and the local user were both able to interact and manipulate the virtual content, using a classic 2D graphical user interface (for the remote user) and a 3D user interface with hand gestural input (for the local user). For each scenario and for each role the participants had, the user interfaces were customized according to their specific requirements. To become acquainted with the AR system, each participant group was trained on the remote user interface as well as the 3D user interface for the local user.

In order to support the new scenarios, we extended our DECLARE framework (see Figure 8). Apart from a few minor changes in all components, major changes were made to the local user AR support component. These changes were necessary to enable local users to interact with the virtual content. For that purpose, the RGB-D camera of the HMD was used to enable hand tracking and implement a 3D user interface, allowing users to interact with the system with their bare hands. The following sections describe in detail the changes compared to the first evaluation round and explains the functionality available for local and remote users.

This section reports on the results of the study on collaboration and situational awareness. In the following, we firstly discuss in detail the quantitative results from the questionnaires and secondly the qualitative results from the de-briefings.

Table 13 presents in short the overall findings of the study on collaboration and situational awareness.

The experiment further showed that participants, both local and remote, experienced lower arousal with AR technology, compared to the same scenario without AR technology support. Additionally, reported focus and attention level were lower with AR technology. Participants also reported that they had less mental capacity while using AR technology than while not using it. This issue could be related to the fact that the AR technology was new to all participants and that they had to adapt to the system, which asks for additional mental capacity to the situation when not using AR technology. Related to the outcomes from the de-briefing, this result matches with the experience of a high workload by the participants.

Operational units rely on quick and adequate access and exchange of accurate context-related information (Lin et al. 2004). The exchange and access of information is further a prerequisite for SA (Endsley 1995) and up-to-date information facilitates and maintains situational awareness of operational units (Straus et al. 2010). The experiment showed that AR technology can be used for context-related information access and exchange in the safety domain. While current technology (mostly mobile phones) is very limited in the ability to record and share a detailed picture of a crime scene, AR technology enables users to focus on details and to support oral communication on details in the crime scene. On the other hand, the strong focus on details sometimes hindered the ability to gather the bigger picture of the scene. Still, the possibility to share information among the different organisations, using AR clearly showed to the participants that their actions have consequences on the work of other emergency services in the process and that proper information transfer is crucial. Thereby, AR indirectly increased the awareness of the participants, for inter-organisational collaboration and their own role in it. This is in line with (Reuter et al. 2014) who identified that shared information increases awareness along the organizational chain.

The experiment also illustrates shortcomings of the current technology. Some policemen experienced difficulties due to the temporary loss of visual tracking, which was caused by a very high pace of the tasks and to an improper calibration for the marker-less tracking. As the used RDSLAM system (Tan et al. 2013) relies on a computer vision-based algorithm, the quality of the calibration and online tracking strongly depend on both the richness of visible patterns (for the calibration step) and the good illumination conditions in the physical environment. Occasional technical issues were noticed during the experiment for interacting within the AR system in such conditions. The participants pointed out that some actions were slower than in real operations.

The de-briefings clearly show that the participants see the most value of the AR technology, in introducing a remote user with whom audio and video is shared in real-time. This new role, including the ability to easily interact with the scene through the AR system by placing virtual objects, setting marks or taking pictures, is evaluated as an added value to the work at a crime scene. The remote user is considered as a useful advisor in stressful situations and can provide the external support that action teams depend on (Sundstrom 1999). Using AR for such a virtual co-location of remote users might thus address the mismatch of the information needs of operational units and the ability of ICT to provide the information (Manning 1996; Sawyer and Tapia 2005). It was very beneficial that the interaction with the AR system was very easy for the remote person. The value of the remote user is also supported by the results of the post-test self-rating of SA. The remote user in the ecstasy lab scenario received the highest score for individual SA, and scored highest on understanding the situation. The de-briefing showed that the collaboration with the remote user also lead to a higher team SA, as participants playing the local role greatly appreciated the advice and actions of the remote user.

The ability of simultaneously sharing the view of the crime scene is also seen critically related to privacy issues. As contact persons might not know who is connected to the AR system, the technology might not be accepted in all places, e.g. work with VIPs. On the other hand, all participants mentioned the usefulness of the AR technology for big events and for training purposes.