Uncrewed Aerial Vehicles and Collisions

Uncrewed aerial vehicles are often used for various applications, including military training and reconnaissance. These vehicles are equipped with a range of sensors and a separation-management system designed to avoid collisions. They are also known for their ability to travel at extremely high speeds. Despite their speed, they are very stable and can handle several landings and take-offs, making them popular among commercial and recreational pilots.

Separation management

The emergence of unmanned aerial vehicles in the airspace has led to the need for safe separation management for these aircraft. This paper provides a brief overview of recent research in this area. In addition, the article reviews the most essential technologies for collision avoidance in integrated airspace.

The UAS operating environment is a complex and variable one. To achieve safe and efficient operation, standardization of processes is necessary. The international community has conducted an impressive amount of work on this topic. However, the pace of progress is inconsistent, and thus further research on the subject remains limited.

One key technology is the collision risk prediction method. This method involves generating and interpreting the probability of a collision based on a UAS and an external vehicle's corresponding performance.

Another approach is to determine the minimum distance required to prevent a collision. A separation threshold is a boundary that defines a minimum amount of time between the two aircraft that must remain separate to be allowed to enter or leave the airspace. There are several ways to determine this threshold. Some of these methods use the number of aircraft, while others use the distance between them.

Another technique for determining the separation is to use the time-and-distance combination approach. For this method, the time it takes for a UAS to reach the closest point of approach (CPA) is used to calculate the separation threshold.

Several researchers have studied the feasibility of calculating the time-and-distance combination. They have discovered that it is possible to compute the separation threshold for a cylindrical safety area. Moreover, the results hint at the threshold conditions for transition.

The study also highlights the feasibility of using AI to update the separation minima. While this is not yet fully developed, some initial results suggest this is an appropriate approach.

The safety separation maintenance process is essential to preventing a collision. This method is a form of a 'safety bubble' that can protect a UAS from an intruder.

Collision avoidance

A collision avoidance system is one of the most critical components of an unmanned air vehicle. It can be used in both civilian and military applications. These vehicles are equipped with onboard sensors, which provide a visual and audible image of their surroundings. To avoid collisions, the system must be capable of calculating distances to waypoints and determining a new flight path that is a suitable fit for the UAV.

Collision avoidance systems are complex and varied. Some may be probabilistic, while others require exact calculation. The most effective are cooperative. They need sharing of state information among the UAVs involved. This is a difficult task, especially for smaller UAVs. For example, when multiple drones collide, the consequences are disastrous, not to mention expensive.

Researchers had to consider all relevant factors to come up with the best possible solution. While the best method was not clear-cut, it was determined that the most reliable approach was based on a combination of stereo-vision imagery and radar.

As part of the process, a risk assessment module was designed. It calculates the probability of a collision, and a reroute trigger is set up when the priority of the UAVs involved in the potential crash is determined. When the threat is gone, the UAVs return to their original paths.

One way to reduce the number of collisions is to increase the sensing range of the UAV. For the purposes of this study, a range of three meters was used. However, this did not significantly affect the number of collisions.

Another approach is to plan collision-avoidance trajectories sequentially. This allows for more precise calculations while maintaining a good level of closeness to a predetermined flight path. But this approach also requires a significant amount of planning time.

A third approach is to use a sampling-based algorithm. This is a clever move since it improves the intelligence of automated systems. Instead of just sampling points, the algorithm determines the shortest and most efficient way to reach a destination.

Finally, an algorithm is paired with a sensor to detect a potential collision. While the most accurate detection might be impossible, it is worth considering.

Sensors

Unmanned aerial vehicles (UVs) can be used to carry out a variety of missions. These include agricultural surveying, aerial reconnaissance, and archeological surveys. There are many different types of sensors that can be installed on UVs.

Sensors can help UAVs detect the environment and alert for any system faults. They also increase the navigation capabilities of the UVs. To do this, the sensors need to be able to measure physical quantities in the environment.

For example, a LiDAR sensor can be used for mapping. This type of sensor can determine the position of an obstacle and can give detailed digital terrain models. It can also be used to produce soil maps and weed intensity maps.

Another type of sensor that can be mounted on a UAV is a thermal imaging sensor. These effectively measure heat and electromagnetic energy in the infrared wavelength range. Using a thermal sensor, farmers can better monitor the health of their crops. Similarly, a hyperspectral sensor can be used to detect plant diseases.

To detect an obstacle, a UAV must be equipped with various sensors. Some common ones are GPS and accelerometers. Alternatively, a combination of GPS and IMU can boost accuracy.

Radars and sonars are active sensors that send out radio pulses. They are often used for navigation by unmanned aerial vehicles. However, their performance can be degraded by various factors such as distance, noise level, and angular rate.

Passive acoustic sensors are a cost-effective and robust solution for monitoring TUAVs. The sensor network can be deployed remotely or unattended. Using these networks, it is possible to gather information about the TUAVs and relay it to the human operator.

Other types of sensors commonly used by UVs are visual, inertial, and thermal. Those types of sensors are essential for detecting obstacles and determining the UUV's position.

Although technology is developing rapidly, many challenges still exist. For example, the performance of UVs is affected by environmental factors, such as distance, noise, and the electromagnetic environment.

Class Lima concept

Class Lima is a new shared airspace concept for uncrewed aerial vehicles. It provides a comprehensive and versatile solution to the problem of integration of UAVs into shared airspace. This research aims to analyze and summarize the issues associated with integrating drones into shared airspace.

The need for a shared airspace solution is very pressing in busy airspace. This is because the current air traffic system has reached its capacity. There are also some problems related to weather and man-made disasters. Moreover, the uncrewed aerial vehicle industry is growing. Therefore, there is a need to collaborate with the broader aviation community.

A recent workshop has allowed the GA community to voice their concerns about drone operations. These participants were broken into interest groups, and various topics related to flight deconfliction systems were discussed.

Class Lima is a flexible and versatile airspace concept that allows drones to operate in combination with crewed aircraft. Unlike UTM, the concept is not designed for a single use case. Instead, it is intended to be used in low-traffic density regions, thereby bridging the gap until UTM is rolled out.

As with any shared airspace solution, infringements are a potential hazard. To ensure compliance, participants suggested that it is necessary to establish minimum equipment requirements. They agreed that this would require a detailed specification. In addition, they identified the need to define a specific limit for traffic densities.

One of the main challenges for UAVs is the precision of navigation-related measurements. If the measurements are inaccurate, it can lead to a landing spot that is not accurate or may cause a collision with an object.

UAVs need to be able to operate in various conditions. For instance, extreme weather can inhibit small UAVs from taking measurements. Another challenge is ensuring that the UAV avoids obstacles and moves along a predetermined path.

Other solutions are more focused on specific applications. For example, VHF-Out allows drones to broadcast automated position reports. However, this requires aircraft to have two VHF radio receivers. Also, it is crucial to monitor the power consumption of the UAV.

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