Urban Search And Rescue Research Articles

Firefighters and police search dog handlers’ experiences working closely with paramedics in urban search and rescue incidents: a qualitative focus group study from Oslo

BackgroundRescue operations are in Norway defined as situations where patients are difficult to access or that more resources are needed than the health services alone possess and can put in operation (Bull A, Redningshåndboken er endelig her! [Internet]. Hovedredningssentralen. 2018 [cited 2023 May 15]. Available from: https://www.hovedredningssentralen.no/redningshandboken-er-endelig-her/). Rescue operations after large incidents may include civil protection, military forces, non-governmental organizations and other resources, but the initial rescue effort must be performed by the emergency services as time often is of essence. The central area of an accident where special training and personal protection equipment is necessary or mandatory is called the Hot Zone. This study examines Urban Search And Rescue (USAR) firefighters and police officers reported experiences from ambulance personnel’s contribution in the Hot Zone.MethodsWe conducted five focus group interviews with USAR-trained firefighters and police officers. The interviewees were those on duty on the agreed dates. The interviews were taped, transcribed, and analysed using thematic analysis as described by Braun & Clarke.ResultsThree themes were identified; Feeling safe during missions, Building USAR capacity, and Trust-building within USAR-teams. The firefighters and police officers reported their and the patients’ safety are best managed by EMS-personnel, whose presence strongly contributes to their own feeling of safety in a dangerous area. When EMS handles victims and injured emergency workers, firefighters and police officers can focus on their own primary tasks. Indeed, interviewees reported that building a USAR capacity depends on having USAR-trained EMS-personnel in the Hot Zone. The interviewees have clear and consistent opinions on how to establish an interagency USAR capacity effectively. Trust is paramount to the interviewees, and they express a high degree of trust within USAR Oslo.ConclusionsFirefighters and police officers regard USAR-trained EMS-personnel as a natural and integrated part in urban search and rescue teams. EMS-personnel in the dangerous area deliver safety and medical professional assistance to both rescue workers and patients. Informants in this study had clear opinions on how to establish and maintain such a service.

Differences in Initial Healthcare Responses Between Turkey and the Conflict-Ridden Area in Syria Following February 2023 Earthquakes

Abstract Objective This study analyzes disparities in initial healthcare responses in Turkey and Syria following 2023 earthquakes. Methods Using Humanitarian Data Exchange, Crude Mortality Rates (CMR) and injury rates in both countries were calculated, and temporal trends of death tolls and injuries in the first month post- catastrophe were compared. WHO Flash Appeal estimated funding requirements, and ratios of humanitarian aid personnel in Urban Search and Rescue (USAR) teams per population from ReliefWeb and MAPACTION data were used to gauge disparities. Results 56,051,096 individuals were exposed, with Turkey having 44 million vs 12 in Syria. Turkey had higher CMR in affected areas (10.5 vs 5.0/10,000), while Syria had higher CMR in intensely seismic regions (9.2 vs 7.7/1,000). Turkey had higher injury rates (24.6 vs 9.9/10,000). Death and injury rates plateaued in Syria after three days, but steadily rose in Turkey. Syria allocated more funding for all priorities per population except healthcare facilities’ rehabilitation. Turkey had 219 USAR teams compared to Syria’s six, with significantly more humanitarian aid personnel (23 vs 2/100,000). Conclusions Significant disparities in initial healthcare response were observed between Turkey and Syria, highlighting need for policymakers to enhance responses in conflict-affected events to reduce impact on affected populations.

Three-Dimensional Flight Corridor: An Occupancy Checking Process for Unmanned Aerial Vehicle Motion Planning inside Confined Spaces

To deploy Unmanned Aerial Vehicles (UAVs) inside heterogeneous GPS-denied confined (potentially unknown) spaces, such as those encountered in mining and Urban Search and Rescue (USAR), requires the enhancement of numerous technologies. Of special interest is for UAVs to identify collision-freeSafe Flight Corridors (SFC+) within highly cluttered convex- and non-convex-shaped environments, which requires UAVs to perform advanced flight maneuvers while exploiting their flying capabilities. Within this paper, a novel auxiliary occupancy checking process that augments traditional 3D flight corridor generation is proposed. The 3D flight corridor is established as a topological structure based on a hand-crafted path either derived from a computer-generated environment or provided by the human operator, which captures humans’ preferences and desired flight intentions for the given space. This corridor is formulated as a series of interconnected overlapping convex polyhedra bounded by the perceived environmental geometries, which facilitates the generation of suitable 3D flight paths/trajectories that avoid local minima within the corridor boundaries. An occupancy check algorithm is employed to reduce the search space needed to identify 3D obstacle-free spaces in which their constructed polyhedron geometries are replaced with alternate convex polyhedra. To assess the feasibility and efficiency of the proposed SFC+ methodology, a comparative study is conducted against the Star-Convex Method (SCM), a prominent algorithm in the field. The results reveal the superiority of the proposed SFC+ methodology in terms of its computational efficiency and reduced search space for UAV maneuvering solutions. Various challenging confined-environment scenarios, each with different obstacle densities (confined scenarios), are utilized to verify the obtained outcomes.

Towards Visual Inspection of Distributed and Irregular Structures: A Unified Autonomy Approach

This paper highlights the significance of maintaining and enhancing situational awareness in Urban Search and Rescue (USAR) missions. It focuses specifically on investigating the capabilities of Unmanned Aerial Vehicles (UAV) equipped with limited sensing capabilities and onboard computational resources to perform visual inspections of apriori unknown fractured and collapsed structures in unfamiliar environments. The proposed approach, referred to as First Look Inspect-Explore (FLIE), employs a flexible bifurcated behavior tree that leverages real-time RGB image and depth cloud data. By employing a recursive and reactive synthesis of safe view pose within the inspection module, FLIE incorporates a novel active visual guidance scheme for identifying previously inspected surfaces. Furthermore, the integration of a tiered hierarchical exploration module with the visual guidance system enables the UAV to navigate towards new and unexplored structures without relying on a map. This decoupling reduces memory overhead and computational effort by eliminating the need to plan based on an incrementally built, error-prone global map. The proposed autonomy is extensively evaluated through simulation and experimental verification under various scenarios and compared against state-of-art approaches, demonstrating its performance and effectiveness.

Understanding the Impact of Team Cognitive Load and Advice Compliance in Urban Search and Rescue Task

This research concentrates on the impact of Artificial Social Intelligence (ASI)'s advice intervention text messages and the compliance of three human team members, who communicate via voice to carry out victim rescue operations, on the team's performance. This experiment takes place in a simulated Urban Search and Rescue (USAR) task environment built using Minecraft. The ASI agent, utilizing its analytical components designed around interactive real-time measurements, oversees the team's behavior in the USAR task environment. The agent discerns and forecasts the human team members' actions, offering interventions via text messages to foster and sustain team efficacy. The study examines (1) the influence of the team's cognitive load on message compliance from the advisor, and (2) how these elements collectively affect team performance. The results show a positive association between cognitive load, compliance, and enhanced task performance, despite the lack of a significant correlation between cognitive load and compliance.

Inclusion of Confined Space Rescue in EMS Physician Fellowship Programs

Introduction: In July 2021, the ACGME updated the Program Requirements for Graduate Medical Education in Emergency Medical Services to include participation in special operations trainings as a required key index procedure during an EMS fellowship. These requirements now include documentation of “participation in confined space, technical rescue, or collapse/trench training”. EMS fellowships may have limited opportunities for fellows to actively participate in these complex events. Background: Federal or State Urban Search and Rescue (USAR) teams present a unique opportunity to meet this training requirement. USAR teams perform search and rescue operations in collapsed structures and provide emergency medical care for entrapped survivors, task force personnel, and search canines. The physician is integrated into the Incident Command Structure of the USAR teams under the Medical Branch as the “Medical Team Manager”. This provides a defined team role in training and promotes physician level knowledge and skills in rescue operations. Methods: The University of Chicago EMS Fellowship partnered with Illinois Task Force-1 USAR team to meet the new training requirements and participate as a Medical Team Manager on the team. Results: During the 12-month fellowship period, the EMS fellow participated in monthly USAR training that included both single day and multi-day exercises. The exercises included scenarios with complex hazardous materials, confined space rescue, high angle rescue, collapsed structure and trench rescue. With a dedicated physician role on the USAR team, the EMS fellow integrates into the response structure as a Medical Team Manager and can learn how to deliver high quality patient care in an austere environment. USAR training fulfilled several of the new ACGME key index procedure for an EMS fellow in the special operations environment including participation in hazardous materials response training, participation in confined space, technical rescue, or collapse/trench training, and participation in vehicle rescue/extrication training. Conclusions: EMS fellowship programs can collaborate with Urban Search and Rescue teams to provide training opportunities in confined space rescue to meet ACGME requirements for key index procedures and integrate qualified EMS physicians into USAR responses. Collaboration between EMS fellowship programs and USAR teams can be mutually beneficial.

A Field Communication System for Volunteer Urban Search and Rescue Teams Combining 802.11ax and LoRaWAN

Despite the technological progress achieved by our society, natural or man-made disasters continue to pose a challenge and put to the test the organization and preparedness of government apparatuses. The loss of life and property following calamities motivates citizens into action. In response, volunteer Urban Search And Rescue (USAR) organizations are established with the aim of providing help when needed. Just like their government funded and run counterparts, these organizations try to use what technology has to offer to improve their efficiency. However, they face challenges due to their limited funding and inability to access certain resources such as licensed spectrum for their communications. This situation is further deteriorated because civilian communication infrastructure cannot be relied upon to be available in case of disasters. Communications are paramount for any operation, let alone USAR. To address this need, we have designed and built a field deployable communication system that is able to leverage what existing communication infrastructure is available and utilizes 802.11ax and LoRaWAN that operate in unlicensed spectrum to provide wireless local connectivity. The performance and suitability of the system have been tested in various small and large-scale exercises, while the range and transmission speed achieved by 802.11ax over its predecessors are determined through a measurement campaign. In this article, we report the results and lessons learned from our approach to fill this communication gap and the suitability of the selected technologies for the role.

Virtual Reality Training for Post-Earthquake Rescue Operators.

Urban Search And Rescue (USAR) personnel need to be appropriately trained to effectively operate in post-disaster conditions, as they need to quickly identify locations where the presence of survivors is more likely. Currently, the training procedure for this kind of triage is based on showing static pictures presenting different types of building collapses accompanied by cards providing additional environmental information. This article presents VRescue, a simulator for training USAR operators using the paradigm of immersive virtual reality (VR). VRescue recreates a range of operation conditions (day/night, presence of people, dangerous locations, etc.) experienced by real rescuers, and enables learning the use of the equipment commonly used in such scenarios.

The Role of Nurses in the Reclassification Exercise of the Japan Disaster Relief Search and Rescue Team (the JDR Rescue Team)

Introduction:The JDR Rescue Team has successfully completed the INSARAG External Re-Classification (IER) process, which evaluates the operational capability and capacity of Urban Search and Rescue (USAR) teams and has achieved the highest “Heavy” reclassification in November 2022. Two nurses participated in the IER process as part of the medical unit of JDR Rescue Team. In addition, ten registered nurses cooperated as Exercise Control (EXCON).Method:Summarize the JDR Rescue Team and medical unit and make observations on what nurses did in the IER.Results:The JDR Rescue Team is dispatched by the Government of Japan in response to large-scale disasters overseas. The task force team has 75 members from various specialties, including the rescuer, and medical unit. The medical unit consists of one medical manager, 2 doctors, and two nurses. There are currently about 50 registered medical unit members in our team, and of these, a total of 23 nurses are registered. The role of nurses during the IER process, includes a 36-hour non-stop scenario-based exercise. The team nurses are involved in various roles, such as Confined Space Medicine (infusion for patients, assisting on-site amputation), caring or treating injured rescuers and search dogs, providing health and welfare monitoring and operating a decontamination system. The EXCON nurses were involved in managing the simulation. One of their key roles was to play as a victim realistically so as to provide a sense of tension for the simulation.Conclusion:The JDR Rescue Team has more medical unit members than those in other countries. In particular, teams with so many nurses are rare. nurses played a vital role in this IER. The contribution of nurses is identified in order to make the international USAR team more strong and more flexible.

Intelligent Insect–Computer Hybrid Robot: Installing Innate Obstacle Negotiation and Onboard Human Detection onto Cyborg Insect

Developing small mobile robots for Urban Search and Rescue (USAR) is a major challenge due to constraints in size and power required to perform vital functions such as obstacle navigation, victim detection, and wireless communication. Drawing upon the idea that insects’ locomotion can be controlled, what if we further utilize the insects’ intrinsic ability to avoid obstacles? Herein, a cockroach hybrid robot (≈ 1.5 cm height, 5.7 cm length) that implements the abovementioned functions is developed. It is tested in an arena with randomly placed obstacles, and a motion capture system is used to track the insect's position among the untracked obstacles. A navigation algorithm that uses an inertial measurement unit (IMU) is developed to heuristically predict the insect's situation and stimulate the insect to escape nearby obstacles. The utilization of insect's intrinsic locomotor ability and low‐powered IMU reduces the onboard power load, allowing the addition of a human‐detecting function. An image classification model enables the use of an onboard low‐resolution infrared camera for human detection. Consequently, a single hybrid robot is established that includes locomotion control, autonomous navigation in obstructed areas, onboard human detection, and wireless communication, representing a significant step toward real USAR application.

USAR decision-making: the role of hazard-specific expertise and risk assessment

The accepted detrimental effects of climate change and the anticipated increased frequency of cascading disasters means there is a pressing requirement to equip search and rescue teams with the capability to perform effective and complex risk assessments. This paper investigates risk-based decision-making expertise in the aftermath of the 2011 earthquake and tsunami in Japan. It compares the actual decisions made by an Urban Search and Rescue (USAR) commander, with the decisions that a cohort of people working within search and rescue made, when provided with the same decision context using 3 vignettes. Variations in the results are explored in terms of the complexity of the risk decision and the type of expertise required. The findings indicate that as the risk becomes more complex, the percentage of answers that were the same as the USAR commander (that we deem as ‘correct’ as they did not result in any adverse outcomes for the USAR team) decreased. Training entities need to provide decision-makers with the necessary human capabilities so they can perform the complex risk assessments required to make decisions in low-probability yet high-consequence disasters.

An Inclusive Model for the Urban Search and Rescue Teams (USAR)

The work performed by the urban search and rescue (USAR) teams is, from every standpoint, difficult to exactly define, since their main mission, which is to save lives, is joined by a series of tasks typical of disaster risk management, which makes them one of the most complex professions and therefore, with the strictest training requirements. Within these requirements, the fact is that USAR teams must be trained to serve a wide population diversity, which also involves the skills to manage critical situations where an inclusive approach is vital. To face this challenge, it is necessary to develop inclusive strategies according to the reality of these teams. In this article, the authors perform a deep analysis to the existing literature and by means of an exhaustive evaluation get to propose an inclusive model for the USAR teams. This model allows to define not only the reach of the inclusion term in these teams, but also helps to establish strategies to reformulate the training plans and programs of recruiting and retention of new members.

Impact of Transparency and Explanations on Trust and Situation Awareness in Human–Robot Teams

Urban Search and Rescue (USAR) missions continue to benefit from the incorporation of human–robot teams (HRTs). USAR environments can be ambiguous, hazardous, and unstable. The integration of robot teammates into USAR missions has enabled human teammates to access areas of uncertainty, including hazardous locations. For HRTs to be effective, it is pertinent to understand the factors that influence team effectiveness, such as having shared goals, mutual understanding, and efficient communication. The purpose of our research is to determine how to (1) better establish human trust, (2) identify useful levels of robot transparency and robot explanations, (3) ensure situation awareness, and (4) encourage a bipartisan role amongst teammates. By implementing robot transparency and robot explanations, we found that the driving factors for effective HRTs rely on robot explanations that are context-driven and are readily available to the human teammate.

Exploration of the Impact of Interpersonal Communication and Coordination Dynamics on Team Effectiveness in Human-Machine Teams

Teams composed of human and machine members operating in complex task environments must effectively interact in response to information flow while adapting to environmental changes. This study investigates how interpersonal coordination dynamics between team members are associated with team performance and shared situation awareness in a simulated urban search and rescue (USAR) task. More specifically, this study investigates (1) how communication recurrence affected and reflected coordination dynamics between a USAR robot and human operator when they used different communication strategies, and (2) how these dynamic characteristics of the human–robot interpersonal coordination were associated with the team performance and shared situation awareness. The USAR interpersonal coordination dynamics were systematically characterized using discrete recurrence quantification analysis. Results from this study indicate that (1) teams demonstrating more flexibility in their coordination dynamics were more adaptive to changes in the task environment, and (2) while robot explanations help to improve shared situation awareness, revisiting the same communication pattern (i.e., routine coordination) was associated with better team performance, but did not improve shared situation awareness.

Explanations and trust: What happens to trust when a robot partner does something unexpected?

Performance within Human-Autonomy Teams (HATs) is influenced by the effectiveness of communication between humans and robots. Communication is particularly important when robot teammates engage in behaviors that were not anticipated by the human teammate which could degrade trust. However, the literature on trust repair focuses on the role of apologies which may not be appropriate for an unexpected behavior since this behavior may not be an error. Explanations are one method that can be used by robot teammates to avoid costly trust degradation when human expectations are violated. The current study used an Urban Search and Rescue (USAR) scenario to examine the role of explanation in a context wherein a robot teammate deviated from an expected behavior. The current study examined how trust, trustworthiness, and responsibility attribution were influenced by observing the robot teammate deviate from an expected behavior. Participants (N = 148) used an online platform to view videos of the robot: 1) following a planned search path, and 2) deviating from a planned search path. A debriefing event between the human and the robot followed each search activity. Four explanation conditions were tested in the debriefing phase following the behavioral violation. Results showed that trust and trustworthiness (ability, benevolence, and integrity) declined following the unexpected behavior. Accordingly, responsibility attribution shifted from the human to the robot following the unexpected behavior. Explanation strategies that focused on communicating why the event occurred by highlighting the robot's environmental awareness were most effective at buffering the decline in trust and trustworthiness.

“I Am Here”: Investigating the Relationship Between Sense ofDirection and Communication of Spatial Information

Navigation is critical for everyday tasks but is especially important for urban search and rescue (USAR) contexts. Aside from successful navigation, individuals must also be able to effectively communicate spatial information. This study investigates how differences in spatial ability affected overall performance in a USAR task in a simulated Minecraft environment and the effectiveness of an individual’s ability to communicate their location verbally. Randomly selected participants were asked to rescue as many victims as possible in three 10-minute missions. Results showed that sense of direction may not predict the ability to communicate spatial information, and that the skill of processing spatial information may be distinct from the ability to communicate spatial information to others. We discuss the implications of these findings for teaming contexts that involve both processes.

Trailblazing Roblox Virtual Synthetic Testbed Development for Human-Robot Teaming Studies

Virtual testbeds are fundamental to the success of research on cognitive work in safety-critical domains. A testbed that can meet researchers' objectives and create a sense of reality for participants positively impacts the research process; they have the potential to allow researchers to address questions not achievable in physical environments. This paper discusses the development of a synthetic task environment (STE) for Urban Search and Rescue (USAR) to advance the boundaries of Human-Robot Teams (HRTs) using Roblox. Virtual testbeds can simulate USAR task environments and HRT interactions. After assessing alternative STE platforms, we discovered Roblox not only met our research capabilities but also would prove invaluable for research teams without substantial coding experience. This paper outlines the design process of creating an STE to meet our research team's objectives.

Deep-Reinforcement-Learning-Based Autonomous Establishment of Local Positioning Systems in Unknown Indoor Environments

Local positioning systems (LPSs) serve as a feasible alternative to provide positioning service in global navigation satellite system (GNSS)-denied environments. When the area of interest is unknown and potentially dangerous, e.g., urban search and rescue (USAR), or unreachable, e.g., extraterrestrial exploration, the autonomous establishment of LPSs by a robot is an attractive approach to coping with the demand for positioning service. In this article, we investigate the autonomous establishment problem in indoor scenarios, where a robot carrying several positioning beacons intends to place them sequentially to establish high-quality positioning services for the area of interest. To solve the complicated sequential decision problem, we first model the optimal positioning beacon configuration problem and then model the autonomous establishment process as a partially observable Markov decision process (POMDP). We apply deep reinforcement learning (DRL) to solve the POMDP. Extensive simulations, including comparisons with other baselines and generalization experiments, demonstrate the advantages of the proposed DRL-based autonomous establishment of LPSs.

Emergency Response System Combining the Internal and External Domains (ERSCIED)

Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR) operations. The previous studies aimed to develop a dynamic agent-based simulation model in post-earthquake emergency response operations combining rescuers and victims using geospatial information systems and multi-agent systems (GISs and MASs, respectively). We use multi-agent system engineering (MaSE) to construct this model and cluster points are proposed to assemble rescuers and victims. We also proposed an approach for dynamic task allocation and for establishing collaboration among agents based on contract net protocol (CNP) and the [Formula: see text]-means clustering method. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and expert evaluation is used to sort the priorities of cluster points. The experimental background is set in the central area of Chengdu, Sichuan Province, China. 200 victims with different demands and 30 rescuers with the same rescue capability are randomly distributed in this area. We use different victim speeds to simulate different degrees of seismic damage. Compared with normal search and rescue, the ERSCIED can make some use of the capabilities of the victims for the improvement of emergency effectiveness when the victims and rescuers have a similar speed (1:1) or the victims are not much slower than the rescuers (1:2). When the victims are much slower than the rescuers (1:10), the rescuers have to wait for a long time at the cluster points and it will lead to a waste of resources. The parameters of rescuers and victims can be changed to meet different emergencies and the ERSCIED can provide effective auxiliary decision-making information for decision-makers.

Urban search and rescue (USAR) simulation in earthquake environments using queuing theory: estimating the appropriate number of rescue teams

PurposeThe duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.Design/methodology/approachIn the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.FindingsThe calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.Originality/valueThe originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.