Discuss the see-and-avoid challenges facing UAV operations
The status of unmanned aerial vehicles (UAVs) and how they fit into the National Airspace System (NAS) has not yet been ratified by the necessary authorities. The UAVs’ biggest challenge remains their ability to adhere to the Federal Aviation Regulations’ (FARs) right of way stipulations. These stipulations govern situations where aircraft are being flown under bad weather, and they include a ‘see and avoid’ clause. This means it is up to the person flying the aircraft to give his/her fellow pilots the right of way. The ‘see and avoid’ stipulation remains a big challenge for UAVs, although there is a lot of ongoing research to help solve this problem.
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The FARs right-of-way rule states that “when weather conditions permit, regardless of whether an operation is conducted under instrument flight rules or visual flight rules, vigilance shall be maintained by each person operating an aircraft so as to see and avoid other aircraft” (Barnhart & Shappee, 2012). This rule presents a major challenge for UAVs because of most of these aircraft use sensors. It is difficult for sensors to match the same ‘see and avoid’ capabilities of a human being in terms of observing contradictory air traffic and ground barriers. The present technology is yet to match the capabilities of an actual human being. There is ongoing research that seeks to overcome this disadvantage using a technical solution.
Currently, the ‘see and avoid’ shortcoming is compensated for using sensor payloads. Even though there are no pilot on-board UAVs, “a sensor payload senses and avoids collisions during air operations” (Valavanis, 2011). Nevertheless, the Federal Aviation Administration (FAA) has not yet given certification to any sense-and-avoid technology that can replace human presence or the use of chase planes. The research that aims to come up with an FAA-certifiable device that can accomplish conflict-avoidance in UAVs is underway.
Define and provide examples of purpose-driven sensors
Purpose-driven sensors refer to those sensors that are mounted on UAVs for collection purposes. Currently, UAVs are used for a myriad of purposes by “government agencies, research bodies, academic institutions, scientists, law enforcers, and other institutions” (Barnhart & Shappee, 2012). For instance, a popular package delivery company is considering using UAVs in its operations within the United States.
Purpose-driven sensors are mounted on UAVs with the aim of collecting a specific type of information. This information may be regarding weather, intelligence, security, and astronomy. Most purpose-driven sensors were initially used by the military and scientists. For instance, the military and other government intelligence bodies use purpose-driven sensors to collect still and video images. Images and videos are usually collected using low-light and daylight cameras. On the other hand, “thermal imaging cameras operate in the infrared (heat radiation) wavelength spectra, permitting interpretation of images at night and low visibility conditions” (Everaerts, 2008). The quality of the data collected using purpose-driven sensors might be affected by external factors such as weather conditions and the level of technology used. Purpose-driven technology is also employed in civil aviation. The type of technology used in this field includes remote sensing. The purpose-driven sensors used in civil aviation might include multi-spectral, electro-optical, and infrared cameras. Using the images provided by these cameras, researchers could be able to explore flora and fauna in remote places without the usual human presence.
The scientific community is at the forefront of advocating for the use of UAVs. On the other hand, UAVs have aided researchers in collecting data from various types of environments and applications. The importance of purpose-driven sensors has also risen with the advent of global warming. Most purpose-driven sensors are environmentally friendly, and the technology can be used without interfering with sensitive eco-systems. For instance, remote sensors can be mounted in small UAVs that weigh around fifty pounds or in big UAVs that weigh over fifteen thousand pounds (Clough, 2005). This makes it easy to use any purpose-driven sensors in UAVs.
In which contexts, phases of operations, and for which types of UAVs do you think human factors play the greatest part in ensuring operational efficiency and efficacy?
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The efficiency of UAVs is closely tied to several human factors. All UAVs are dependent on a ground control system (GCS). The connection between UAVs and the GCS determines the success of their operations (Frew & Brown, 2008). While the machines are dependent on technology, the GCS is dependent on human efficiency. This makes the human factor an important aspect of the UAVs.
The communication between the GCS and the UAVs is two-way. The human pilots who are usually stationed at the GCS send commands to the UAVs while the machines send useful data to the pilots. The human factor in the operations of UAVs may vary depending on the type of operation being undertaken by the UAVs. For instance, UAVs that are used in the collection of data are not very dependent on the human factor. Data collection UAVs have a definite operation schedule that is not subject to changes. For example, surveillance UAVs can have a pre-planned flight path, and that path is not subject to any changes. On the other hand, operational UAVs are very dependent on the human factor. For instance, UAVs that are used in military operations are dependent on the efficiency of the pilots who man them. Any human error in operation-based UAVs can have far-reaching effects. For example, dropping weapons using UAVs requires great human efficiency.
Barnhart, R. & Shappee, E. (2012). Introduction to unmanned aircraft systems. New York, NY: Crc Press.
Clough, B. T. (2005). Unmanned aerial vehicles: Autonomous control challenges- a researcher’s perspective. Journal of Aerospace Computing, Information, and Communication, 2(8), 327-347.
Everaerts, J. (2008). The use of unmanned aerial vehicles (UAVs) for remote sensing and mapping. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, 1187-1192.
Frew, E. W., & Brown, T. X. (2008). Airborne communication networks for small unmanned aircraft systems. Proceedings of the IEEE, 96(12), 1-12.
Valavanis, K. (2011). Unmanned aerial vehicles. New York, NY: Springer.