Aeronautics & Astronautics Autonomous Flight Systems Laboratory A Risk Based Paradigm and Model for Unmanned Aerial Systems in the National Airspace March

Aeronautics & AstronauticsAutonomous Flight Systems Laboratory

A Risk Based Paradigm and Model for Unmanned Aerial Systems in the

National Airspace

March 29, 20112011 AIAA Infotech@Aerospace Conference

St. Louis, MO

Christopher Lum University of WashingtonBlake Waggoner Missile Defense AgencyKristoffer Gauksheim University of WashingtonJuris Vagners University of WashingtonTad McGeer Aerovel

Aeronautics & Astronautics

Autonomous Flight Systems Laboratory

University of Washington 2March 29, 2011


Mission Statement

People

To conduct research that advances navigation, guidance and control (GN&C) technology relevant to unmanned vehicles.

Juris Vagners Kristi Morgansen Uy-Loi Ly Christopher Lum Rolf Rysdyk

Kristoffer Gauksheim Amy Arbeit Blake Waggoner Esther Anderson




Motivation

FAA policy is very restrictive to UAS operations but…

“The FAA supports UA flight activities that can demonstrate that the proposed operations can be conducted at an acceptable level of safety.”

-Memorandum AFS-400 UAS Policy 05-01

State of Affairs

Challenges

FAA must ensure UAS operate at same level of safety as manned aircraft

Major issues Less reliable “See and Avoid” becomes “Sense and Avoid” Communication link liability




Goals

“Acceptable system safety studies must include a hazard analysis, risk assessment, and other appropriate documentation that supports the ‘extremely improbable’ determination.”

Motivation

Goals

Develop a user friendly tool for risk assessment. Tool should be mission specific. Analysis should be based on a simple, understandable model. Tool should be easily accessible and easy to use (web

implementation)




Deviation from Manned Paradigm

Traditional Aircraft Safety

1. People aboard primary aircraft

2. People aboard other aircraft

3. People on the ground

If group 1 safety is assured, group 2 and 3’s safety follows.

Aircraft must be reliable regardless of operating area.

With UAS, safety of primary aircraft is irrelevant.

Safety is a function of operational area of UAS.




Risk Assessment Goals

Effects of UAS Failures

Cost to replace aircraft Cost to repair damage Environmental impact

Lawsuits Negative publicityInjuries

LOSS OF HUMAN LIFE




Risk Framework

Cruise phase of flight only (takeoff/landing in controlled or restricted areas)

Allow for multiple operating areas models

Allow for transient aircraft models

Failures such as engine cut-off, structural failure, etc. are all grouped into a general failure rate. Measured experimentally.

Assumptions




Risk Assessment

Midair Collisions (transient & in-fleet) General Failure

Transient aircraft densitiesNumber of agents in teamCollision avoidance

Mean time between failuresNumber of agents in team

Pedestrian Strikes Building Strikes Pedestrian Strikes Building Strikes

AC dimensionsPed dimensionsBldg dimensionsPed densityBldg density

Fatalities Fatalities

Ped susceptabilityBldg protectionMission length

Total Fatalities and Liability Insurance Cost




Midair Collision Model

User inputs densities of transient aircraft and number of agents in team.

UA and transient aircraft recast as circles of equivalent cross sectional area.

Unmitigated collision rate based on random collision theory (Maxwell model)

Transient AC density from Flight Explorer PE




Midair Collision Model

Define collision avoidance factor for a party as percentage of time an otherwise imminent collision is avoided by that party alone.

1 -

Transient AC System Works

Transient AC System Fails

1 -

UASystem Works

UASystem Fails

Both transient and UA system must fail for collision to occur.

Collision rate b/w transient AC and UA

Collision rate b/w UA within team

Transient AC UA

Imminent Collision




Structured Airspaces

Can this model be modified for more structured airspaces such as near airports and other air corridors?

Apply evolutionary algorithm, data mining, and regression combo approach. Use Eureqa analysis toolkit. Rapidly identify function from

data to suggest underlying models of the physical process.

Eureqa tool by Schmidt and Lipson




Model Validation

Compare in-fleet collision avoidance model with historical data.

Simple model provides surprisingly accurate, order of magnitude results Historically, pilots avoid ~14% of imminent collisions.




Ground Strikes

Surface collisions Lethal areas depending on failure type.

Midair collisions yield vertical crash. General system failure yields horizontal, gliding crash.




Ground Strikes

Expected strike rate based on pedestrians/buildings density and dimensions and also aircraft dimensions.

Gas based midair collision model

Small aircraft in sparse area, low fatalities

Large aircraft in densely populated area, high fatalities

Strike rate due to general system failures

Strike rate due to midair

collisions (transient

and in-fleet)




Fatalities and Insurance

Fatalities in midair collisions based on passenger load of transient AC.

Fatalities from ground strikes based on UAS & building properties.

US Army correlation b/w kinetic energy & lethality

Unprotected structure Protected structure

Total fatality rate

General system failures

Midair collisions

May be easier to visualize cost of liability insurance for operation by assuming insurance payment per fatality (ie $10M/fatality)




Example: Border Patrol

“Customs and Border Protection has said it intends to increase unmanned aircraft systems across the country this year, and it expects a complete network of unmanned planes all along the border by 2015.”

-Tim Eaton, American-Statesman

Customs and Border Protection currently use MQ-9 Reaper to monitor Arizona-Mexico border.

3 aircraft in air, 24 hours a day for a year. Flying over populated and spare areas with transient aircraft in

airspace.

Is this operation safe?





UAS properties Frontal area = 18.5 m2

Velocity = 162 knots L/D = 25:1 → glide angle 2.3o

Class A mishap rate of 15.3/100,000 flight hours → λ = 1.53E-4 Reliable in-fleet collision avoidance → εua/ua = 0.9

Equipped with Mode C transponders → εua/o = 0.7

Frontal area approximation





Operating Area 600 km long, 20 km wide area → Aops = 12,000 km2

Population and building density from US Census Bureau and ZIP codes along border. Excludes 3 biggest cities on border (neglect 7% of area but exclude 48% of population). σb = 1.4 buildings/km2, σp = 0.26 people/km2

Due to size and speed, lethal to pedestrian → Dped = 1 fatality/strike

Buildings offer some protection → Dbldg = 0.42 fatality/strike

3 UAS flying year round, ML = 8760 hours





Transient Aircraft Density determined by polling Flight Explorer PE in region of

interest → 4.167E-6 AC/km3

Assume only regional jets in area Velocity = 432 knots Frontal Area = 80 m2

Passenger load = 45 people/AC AC under ATC control → εo = 0.95

Insurance Assume $10M liability per fatality

Transient AC traffic in area of interest from Flight Explorer PE





Results Ftransient = 6.03E-9 collisions/hr ↔ 1 collision every ≈19,000 missions

Ffleet = 1.11E-11 collision/hr ↔ 1 in fleet every ≈1,000 missions

Ffat,p = 1.51E-6 fatalities/hr ↔ 1 fatality due to general system failure every 75 missions

Ffat,midair = 2.72E-7 fatalities/hr ↔ 1 fatality due to midair collision (both transient and in-fleet) every 420 missions

M = $17.85/hr ↔ ≈$150K to insure per mission

System failure led to first crash in April 2006, no injuries

Interpretation General system failures are a much

bigger threat than mid air collisions. If flying manned aircraft with equivalent

reliability, expect 4 crashes and pilot fatalities. This is a good example of UAS being an effective replacement.




Example: Urban Applications

Use UAS to monitor activities around city Traffic monitoring Harbor patrol Law enforcement assistance Persistent Surveillance

Is this operation safe?





UAS Properties 4 MLB BAT UAS, 24 hr/day for 1 year.

Transient Aircraft Mixture of general aviation, regional,

and commercial (multiple transient AC models)

Operating Area Mixture of land and marine environments

in Seattle, WA (multiple operating areas). Boats modeled as buildings





Results

Parameter Land Areas Marine Areas

Ftransient 1 every 700 missions 1 every 1300 missions

Fped 1 every 1.3 missions 1 every 1700 missions

Fbldg 1 every 0.01 missions 1 every 420 missions

Ffat 1 every 0.4 missions 1 every 9 missions

M $25M per mission $1M per mission

Likely to strike pedestrians and buildings (significant secondary economic impact)

Ground based fatality is virtually guaranteed during a mission. Ground based operation area is much more dangerous than maritime

environment (maritime is still prohibitively costly >$1M per mission)




Web Based Implementation

Easy to use system to acquaint people with “risk based paradigm” Website helps users find information and perform calculations.

http://vger.aa.washington.edu/~afsl




Conclusions

Risk tool presented here is designed to be a reliable, accurate, and easily accessible method to estimate the risk to human life incurred from a given UAS operation.

Risk to human life is primary concern, economic impacts can be derived as secondary parameters.

Currently, tool is best used as an order of magnitude approximation due to large uncertainty in input parameters.

Estimates could be used to make a case to the FAA for safe operation of UAS in the National Airspace.

QUESTIONS?

Documents

Aeronautics & Astronautics Autonomous Flight Systems Laboratory A Risk Based Paradigm and Model for Unmanned Aerial Systems in the National Airspace March