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The great success of unmanned aerial vehicles (UAVs) in performing near-real time tactical, reconnaissance, intelligence, surveillance and other various missions has attracted broad attention from military and civilian communities. A critical contribution to the increase and extension of UAV applications, resides in the separation of pilot and vehicle allowing the operator to avoid dangerous and harmful situations. However, this apparent benefit has the potential to lead to problems when the role of humans in remotely operating “unmanned” vehicles is not considered. Although, UAVs do not carry humans onboard, they do require human control and maintenance. To control UAVs, skilled and coordinated work of operators on the ground is required.

Lockheed Martin has been a premier builder and developer of manned aircraft and fighter jets since 1909. Since then, aircraft design has drastically evolved in many areas including the evolution of manual linkages to fly-by-wire systems, and mechanical gauges to glass cockpits. Lockheed Martin's knowledge of manned aircraft has produced a variety of Unmanned Aerial Vehicles (UAVs) based on size/wingspan, ranging from a micro-UAV (MicroStar) to a hand-launched UAV (Desert Hawk) and up to larger platforms such as the DarkStar. Their control systems vary anywhere between remotely piloted to fully autonomous systems. Remotely piloted control is equivalent to full human involvement with an operator controlling all the decisions of the aircraft. Similarly, fully autonomous operations describe a situation that has the human having minimal contact with the platform. Flight path control relies on a set of waypoints for the vehicle to fly through. This is the most common mode of UAV navigation, and GPS has made this form of navigation practical.

If these tasks are broken down by aircrew position, the pilot (often called the operator) is the prime command and control coordinator, while the second crew member (the sensor operator) is responsible for collecting, processing and communicating sensor data. There is often an overlap of duties between these two crew members, but the operation of smaller UAVs is commonly only controlled by these two personnel. An illustration of the ground control shelter interface used by a typical Army UAV pilot (AVO, Air Vehicle Operator) for the US Army Shadow UAV follows (Fig. 1).

DoD accidents are classified according to the severity of injury, occupational illness, and vehicle and/or property damage costs (Department of Defense, 2000). All branches of the military have similar accident classification schemes, with Class A being the most severe. Table 1 shows the accident classes for the Army. The Air Force and Navy definitions of Class A–C accidents are very similar to the Army's definition. However, they do not have a Class D. As the total costs of some Army UAVs are below the Class A criteria ($325,000 per Shadow aircraft; Schaefer, 2003), reviewers have begun to add Class D data into their analyses (Manning, Rash, LeDuc, Noback, & McKeon, 2004; Williams, 2004).

This paper analyzes how the use of unmanned aerial vehicles (UAVs) or “drones” in foreign interventions abroad have changed the dynamics of government activities domestically. Facing limited or absent constraints abroad, foreign interventions served as a testing ground for the domestically constrained U.S. government to experiment with drone technologies and other methods of social control over foreign populations. Utilizing the “boomerang effect” framework developed by Coyne and Hall (2014), this paper examines the use of drones abroad and the mechanisms through which the technology has been imported back to the United States. The use of these technologies domestically has substantial implications for the freedom and liberties of U.S. citizens as it lowers the cost of government expanding the scope of its activities.

The Cognitive Engineering Research Institute's First Annual Human Factors of unmanned aerial vehicles (UAVs) Workshop, held on May 24–25, 2004 in Chandler Arizona, and Second Annual Human Factors of UAVs Workshop, held on May 25–26, 2005 in Mesa Arizona, brought to light many human factors issues regarding the technology and operation of UAVs. An integral part of the event was the involvement of military UAV operators from the U.S. Air Force (USAF), U.S. Navy, and U.S. Army. The involvement of UAV operators in the workshops was valuable in linking developers and human factors researchers in the improvement of UAV systems and operations – a practice that is too often implemented only after a system is deployed and the problems are found. The experience of operators serves as a “user's account” of the issues and problems concerning the operation of UAVs. The fact that operators have had first hand experience in operating UAVs provides a unique perspective to the problem of identifying the most pressing human factors issues. The purpose of this chapter is to highlight the perspectives of two UAV operators that helped to set the tone for the entire First Annual Human Factors of UAVs Workshop.

The successful culmination of missions based on Unmanned Aerial Vehicles (UAV) can be measured with two main parameters: (1) successful mission completion: all objectives of the mission (e.g., maneuvering and navigation, reconnaissance and targeting or search and rescue, and return) were accomplished and (2) safety: no damage to the vehicle and no fatalities or injuries to any human were sustained throughout the mission. Automation of the UAV's control and operations increasingly becomes a determining factor in successful mission completion and increased safety. However, in this day and age of automatically launched and retrieved swarms of UAVs, the human operator still has a critical role. Human-controlled UAVs will persist for a long time and human error is a factor that still needs addressing in the age of automation. Even a single person, who has flown radio-controlled model aircraft as a hobby since childhood, can still cause the crash of an expensive UAV in a matter of seconds. Moreover, there are aspects of human error in UAV control that can have important implications to the implementation of automation and to keeping the human operator in the control loop.

SD is defined as a failure to sense correctly the attitude, motion, and/or position of the aircraft with respect to the surface of the earth (Benson, 2003). The types of SD are generally thought to be “unrecognized” and “recognized” (Previc & Ercoline, 2004). Although a third type has been reported (incapacitating), this type seems irrelevant to UAV operations. Unrecognized SD occurs when the person at the controls is unaware that a change in the motion/attitude of the aircraft has taken place. The cause is often the result of a combination of sub-threshold motion and inattention. This type of SD is known to be the single most serious human factors reason for aircraft accidents today, accounting for roughly 90% of all known SD-related mishaps (Davenport, 2000). Recognized SD occurs when a noticeable conflict is created between the actual motion/attitude of the aircraft and any one of the common physiological sensory mechanisms (e.g., visual, vestibular, auditory, and tactile). Recognized SD is the most common type of SD, accounting for the remaining SD-related accidents.