Determining Safe Access with a BestEquipped, Best-Served Model for Small
Unmanned Aircraft Systems
This paper describes Amazon’s proposed approach for determining airspace access for low-altitude
small unmanned aircraft systems. Amazon anticipates this model will be refined over time, and
will work in close collaboration with public and private industry on the development of the safest
system of access for a wide range of applications, not limited to package delivery.

Best-Equipped, Best-Served
Best-Equipped, Best-Served means that the vehicle equipment, often referred to as equipage,
network functionality and concept of operations (ConOps) determine whether or not the
required level of safety—as determined by the relevant performance standards and rules—is
achieved, and therefore, whether access to the airspace is granted.
Amazon envisions the safe operation of small unmanned aircraft systems (sUAS) as a
combination of real-time planning and on-board vehicle automation. With this approach,
required degrees of planning and automation vary based on vehicle capabilities, web-servicebased command and control, and ConOps. These capabilities are expected to be online, with
the network able to adapt in real time to varying situations, such as changes in weather and
emergency access needs.
When looking at equipage, there are a number of critical technologies currently being explored
in areas like vehicle-to-vehicle communications (V2V), command and control networks, and
sense-and-avoid (SAA) technology. It is important to note the two distinct types of SAA in
relation to vehicle equipage: collaborative and non-collaborative. V2V capabilities enable
collaborative SAA, providing vehicles with a way to communicate directly with each other to
create awareness and maintain separation. Sensor-based SAA capabilities, however, enable
non-collaborative separation between vehicles and non-equipped entities, which can range
from birds to balloons.

A Formula for Access
Airspace access for manned aircraft is determined by capabilities. For example, communication
and navigation equipage is required for transit through controlled airspace and to gain access to
certain airports. Amazon believes a similar model of determining access—one focused on

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 Determining Safe Access with a Best-Equipped, Best-Served Model for sUAS, July 2015

segregated blocks of airspace below 500 feet and away from most manned aviation
operations—is the best pathway for safe and scalable sUAS operations.
Evaluating the vehicle’s equipage and network capability in order to determine performance is
the first step. Once performance levels have been established, the operator’s ConOps
requirements will determine whether or not the operator is granted airspace access and can
safely perform the designated mission.
The variety of ConOps and vehicle capabilities means there is no one-size-fits-all model. For
example, an operator with a lesser-equipped vehicle may be able to achieve the required level
of safety if they are flying in a remote area. On the other hand, an operator seeking to fly in an
urban environment would have to meet a highly sophisticated equipage standard, with both
robust communications and the ability to avoid other airborne entities and people on the
ground.

Four Classes for Safe Operations
Operators seeking broad airspace access in multiple environments will need to have highlyequipped vehicles. They will also need to minimize interaction with lesser-equipped small
unmanned aerial vehicles, as well as the occasional manned aircraft flying at low altitude. To
ensure the safety and integrity of the overall system, it is paramount that all sUAS operators
understand where they can and cannot safely operate.
It is with this in mind that Amazon envisions four separate sUAS equipage classes: Basic, Good,
Better, and Best. These classes optimize for safe and efficient airspace operations by creating
categories of access based on capability. For example, a vehicle with an equipage classification
of ‘Good’ does not meet the vehicle capability requirements, such as automated collaborative
deconfliction (via V2V) and non-collaborative SAA, that are needed to perform a complex
mission in an urban environment. On the other end of the spectrum, operators requesting
access to execute missions with high complexity must equip in the ‘Best’ class and possess five
equipage elements: (1) geospatial data for safe separation from known hazards, (2) online flight
planning and management, (3) reliable Internet connection, (4) collaborative V2V SAA, and (5)
non-collaborative sensor-based SAA. It is Amazon’s position that these five ‘Best’ equipage
elements are essential for safe, highly-automated operations.
The following table identifies Amazon’s proposed classes, equipage capability examples, and
the resulting airspace access.

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 Determining Safe Access with a Best-Equipped, Best-Served Model for sUAS, July 2015

Class

Equipage Examples

Airspace Access

Basic

Radio control

Good

Basic + Ability to announce and log identity
location and activity via V2V; ability to receive
air traffic information, weather data, GPS and
Wifi; Internet connected via ground control;
proximity alerting to operator via
collaborative V2V; basic geospatial data
Good + Autopilot capable of autodeconfliction via collaborative V2V; on-vehicle
Internet connection; Automatic Dependent
Surveillance-Broadcast (ADS-B) Out
capability
Better + Non-collaborative SAA and
automated deconfliction; reliable on-vehicle
Internet connection; 4D trajectory planning
and performance management; geospatial
data of all hazards to navigation over 200 feet;
onboard vehicle condition monitoring system;
alternate landing execution; long-range SAA
able to detect and differentiate noncollaborative targets and safely deconflict;
ADS-B In/Out

Line of sight (LOS) flight in predefined
low risk locations
Basic + Unrestricted daytime LOS flight
less than 200 feet in rural operating
areas; limited operations in suburban
areas

Better

Best

Good + Daytime LOS flight less than 400
feet in suburban operating areas; limited
operations in urban areas

Better + Beyond line of sight flight less
than 400 feet in all operating areas,
including urban, with vehicle-to-operator
ratios greater than 1:1, transiting
between 200 feet and 400 feet; daytime
and/or nighttime; good weather or all
weather as determined by sensorpackage performance capabilities

The proceeding graphic takes it ones step further and illustrates the relationship between
vehicle capability, ConOps complexity and airspace access.

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 Determining Safe Access with a Best-Equipped, Best-Served Model for sUAS, July 2015

Creating Standards, Enabling Innovation
Aviation authorities, manufacturers and operators around the world have created high
standards for equipment, operations, reliability, and safety. In order to maintain and enhance
the level of safety achieved in aviation today for sUAS, aviation authorities should adopt
performance-based equipage and operating standards. Such standards will allow for the safety
of the system to improve as the technology improves, rather than locking into a specific set of
technologies that quickly become outdated.
It is Amazon’s position that a Best-Equipped, Best-Served model for determining airspace
access, alongside the creation of four separate sUAS equipage classes, is the safest way to
usher in this new era of aviation in scalable and sustainable way. Amazon is committed to
collaborating with industry to help define standards in a way that will provide operators,
manufacturers and policymakers with a clear understanding of what is needed to operate safely
in the shared global airspace.

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