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INTELLLIGENT SYSTEMS ROADMAP
Topic Area: Intelligent Systems for Unmanned Aircraft Systems (UAS) Integration
in the National Airspace (NAS) at low altitudes.
Marcus Johnson, NASA Ames Research Center, Moffett Field, CA
Introduction
The use of unmanned aircraft systems (UAS) is projected to rise dramatically in next
several decades. Ongoing research has focused on the safe integration of UAS into the
National Airspace (NAS), however a number of technological, regulatory, operational,
and social challenges have delayed the wide spread use of UAS in the NAS. This
contribution to the Roadmap for Intelligent Systems will focus on the areas where
intelligent systems can address several of the technological challenges hindering safe
integration of UAS in the NAS.
The types of operations that will be addressed in this document are specifically UAS
that are conducting missions within visual line of sight (VLOS) and beyond visual
line of sight (BVLOS) at low altitudes in uncontrolled airspace (e.g. Class G).
Operations in controlled airspaces introduce a different set of technological,
regulatory, operational, and social challenges and are beyond the scope of this
document.
This contribution to the Roadmap for Intelligent Systems will focus on the areas
where vehicle automation, airspace management automation, and human-decision
support tools have technical challenges where intelligent systems can contribute to
a solution. Low altitude UAS operations are relatively non-existent in current
operations in the US national airspace system (NAS), thus there are many technical
challenges that arise as these vehicles will perform missions with increased level of
automation, in areas where there will be more frequent interaction with humans,
man-made structures and terrain than is common in todays operations. Intelligent
systems can contribute to the following areas in low altitude UAS operations:
- Human-system collaboration, situation awareness, and decision support
tools.
- UAS vehicle and ground support automation.
- Airspace management automation, security, safety, efficiency, and
equitability.
- Mission planning and contingency management
Due to the wide range of vehicle equipage and performance, mission, and challenges
related to geography additional applications of intelligent systems not included in
the list above may be realized as UAS operations are allowed in the airspace.
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Intelligent Systems Capabilities and Roles
Description of Intelligent Systems Capabilities
Limited commercial UAS operations are currently allowed in the airspace and thus there
are few examples of current intelligent systems technologies being used in operations.
This limitation is largely driven by policy and thus intelligent systems technology is
currently in research and development in many areas, but has not been used in practice.
Many applications where small UAS operating at low altitudes would be relevant are
currently being conducted by ground equipment, terrestrial equipment or manned aircraft
operations. In these current technical solutions there is a strong demand to drive down
operational costs, reduce risk damaging equipment or loss of life, and to reduce the
potential for human error.
Recently there has been increasing acceptance of intelligent systems technologies in other
industries, such as the automotive self-driving car technologies. The rise in acceptance
and success of these technologies may increase the likelihood of social acceptance of
small UAS. A path forward in integrating intelligent systems into this domain is to
demonstrate a variety of applications where intelligent system increases the reliability,
safety, and efficiency of systems, procedures, and operations. The goal is to enable an
increase of intelligent automation into allow for numerous operations with vehicles that
have limited size, weight, and power constraints whom are operating in complex
environments.
A short list of example desired intelligent systems capability goals for each identified
area of intelligent system contribution include the following:
- Human-System
o Reduce the probability of human commanding error
o Improve the situation awareness of the operator
o Increase automation on the vehicle such that the operators tasks are a
manage-by-exception
o Enable decision support tools for emergency situations and contingency
management
o Enable a single operator to command and control multiple vehicles
- UAS vehicle and ground support automation
o Provide onboard and/or ground-based separation assurance from other
airborne traffic, terrain and natural obstacles, man-made obstacles, and
people on the ground.
o Fault tolerant systems to reduce the risk in emergency situations (lost-link,
hardware failure, etc.)
o Path planning in complex environments (GPS-denied environments,
variable weather conditions and obstructions, man-made structure and
terrain avoidance, etc.)
o Vehicle health monitoring and diagnostics.
- Airspace Management
o Spectrum allocation and management.
o Airspace management system health monitoring
o Flight monitoring and conformance monitoring
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o Flight planning, scheduling and demand management and separation
assurance
o Contingency Management
o Providing information to various communities that are connected to the
airspace (other ATM systems, UAS operators, general aviation
community, public, law enforcement, etc.)
Mission planning and contingency management
o Risk-based operational planning and contingency management
o Using vehicle performance modeling to determine operation feasibility
and contingencies.
Technical Challenges and Technology Barriers
Technical Challenges
Due to the introduction of new vehicles into under-utilized low altitude airspace the state
of practice of new technologies in this area tends to err on the side of being risk adverse
in nature. Most emerging technologies to support small UAS operations are at a low
technology readiness level (TRL) and have not been tested in a variety of environments
over a myriad of conditions. Several vehicle technologies (automated take-off/landing,
detect and avoid systems, lost link systems, etc.) have been lab-tested and field tested in a
limited capacity, but few have intelligent system tools have made it to small UAS
operations.
Intelligent systems are considered a path towards increasingly automated and safe UAS
operations, however the technology has a stigma for being unreliable and could generate
hazardous situations under the right conditions. To overcome this, the intelligent systems
community needs to demonstrate the technical ability to perform increasingly automated
functions and to quantitatively show improvements in safety and reliability of the vehicle
systems and the airspace.
Another technical challenge may come from the human-centric mentality of most
engineering systems today. The incorporation of human-system teaming, collaboration
and even human assisted autonomous control of the vehicles and airspace are the
direction that small UAS business cases are moving towards. To enable operations with
operators that have limited training, vehicles that have a wide range of performance and
equipage, and potential substantial traffic densities, the human-centric model is not
scalable and thus alternative architectures for managing vehicles and airspace should be
explored. These architectures will require a more automation-centric framework and the
role of the human will change as the increase of automation is introduced into the system.
There are a number of technical challenges associated with successfully achieving the
vision articulated above. A few of them are articulated below.
a. Demonstration of certifiable detect and avoid solutions to provide separation
assurance
b. Development of a UAS Traffic Management System
c. Demonstrate a reliable command and control link for beyond line of sight
operations.
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d. Converge on a universally accessible intelligent automation framework
e. Development of a risk-based safety framework for evaluating missions and
managing contingencies
Laying the framework for how to evaluate safety and what metrics are appropriate for
increasing levels of automation in the systems and changing human roles are essential to
articulating and overcoming the reliability stigma that limits the use of intelligent systems
technologies. As more sophisticated algorithms and technologies get developed having
performance based standards to determine safety and interoperability with the current
airspace operations would yield a faster path towards adoption of new technologies.
Technical Barriers
Many of the technologies needed to achieve the desired intelligent automation vision are
in development or do not exist today. The largest barrier for intelligent systems in this
domain is to demonstrate the reliability and safety of various technologies on a
vehicle/ground platform, as well as, demonstrating how that technology will not degrade
safety of the airspace when that technology is introduced and interoperates with current
airspace operations.
Policy and Regulatory Barriers
While Class G airspace is uncontrolled, meaning that air traffic controllers do not today
provide separation services, every aspect of operations in Class G airspace remains
governed by the Federal Aviation Regulations (FAR). Today, the FAA grants waivers to
specific FARs on a case-by-case basis as a result of in-depth safety reviews. A key
challenge for enabling a high volume of small UAS operations in Class G airspace,
especially small low-cost vehicles across a wide range of missions, is to determine the
minimal set of regulatory requirements coupled with advanced traffic management tools
and procedures that ensures the continued safety of the NAS. Leveraging the existing
FARs when appropriate is advantageous because it allows the new operations to be
treated similarly to existing operations that have a proven safety record. At the same time,
many of the existing FARs will not cost-effectively promote the wide variety of missions
being considered. Ultimately, the regulatory requirements governing small UAS
operations will be a combination of both existing and new FARs.
Impact to Aerospace Domains and Intelligent Systems Vision
This contribution to the Roadmap for Intelligent Systems may provide a higher-level
perspective to the vision for intelligent systems for aerospace applications that is not
addressed in other aspects of the roadmap. For instance, technologies that are addressed
using intelligent systems for low altitude small UAS operations may have relevance for
advances in manned aviation operating in the air traffic management system.
Furthermore, vehicle technologies that are developed in the small UAS low altitude
domain may also have relevance for the automotive automation technologies as several of
the challenges overlap.
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Research Needs to Overcome Technology Barriers
Research Gaps
Operational Gaps
Research Needs and Technical Approaches
Prioritization
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