Process for developing a statistical model to determine the workload of an aircraft pilot, model derived therefrom, apparatus for the embodiment of the said process and applications of the model

• US 5,075,881 A
• Filed: 05/13/1988
• Issued: 12/24/1991
• Est. Priority Date: 05/20/1987
• Status: Expired due to Term

• Current Assignee: Airbus Industrie
• Original Assignee: Airbus Industrie
• Inventors: Blomberg, Richard D., Speyer, Jean-Jacques, Fouillot, Jean-Pierre
• Primary Examiner(s): Gruber, Felix D.
• Application Number:
  US07/193,582
• Time in Patent Office: 1,320 Days
• Field of Search: 364/578, 364/554, 364/551.01, 364/400-402, 364/413.01, 364/413.02, 434/30, 434/372
• US Class Current: 703/2
• CPC Class Codes: G06F 2111/08 Probabilistic or stochastic CAD
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G09B 23/00 Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes in the nature of toys A63H

Abstract

A process for developing a statistical model to forecast the workload of an aircraft pilot (20), in particular that of a commercial airline pilot, as a function of objective flight parameters, wherein, during the course of at least one flight (real or simulated) of the aircraft, under defined flying conditions and flight conditions and stages which constitute the flight parameters, the aircraft pilot is asked to provide a rating of his workload according to a predefined scale, wherein this rating is logged at the same time as the corresponding flight parameters, and, simultaneously, the value of the significant data of the said parameters is measured, wherein, finally, a statistical correlation is established between the workload rating values on the one part and the aforesaid data and flight parameters on the other part.

Applicable to certification and development of an aircraft and training and skills development, to performance supervision and monitoring of an aircraft pilot'"'"'s extent of adaptation to a new aircraft.

Claims

1. A method for producing the statistical model for predicting a workload that an aircraft places on a pilot during actual or simulated flight as a function of predetermined objective flight parameters, the method comprising the steps of:

(a) defining a set of predetermined objective flight parameters corresponding to different preselected aircraft flight data, flight conditions of the aircraft, flying conditions, and flight stages;

(b) generating a signal prompting the pilot during n actual or simulated flight of the aircraft to rate his current workload according to a predefined scale;

(c) logging the workload rating made by the pilot in response to the prompting signal;

(d) measuring values of significant data of a plurality of applicable flight parameters when the prompting signal for a workload rating is generated;

(e) logging the measured values of the applicable flight parameters simultaneously with step (c);

(f) repeating steps (b) through (e) at least once in each of the preselected flight stages;

(g) correlating the workload ratings and flight parameters from step (f) to produce a statistical model of the workload on the pilot as a function of the flight parameters.

2. The process of claim 1 wherein step (g) comprises entering each workload rating and the measured values of the associated flight parameters obtained in step (f) into a relationship of the type:

space="preserve" listing-type="equation">Yi=A1 Zi1+A2 Xi2+. . . +An Xin+B1+B2+. . . +Bk+. . . +Bm+C,

wherein;

Yi is a variable related to a pilot workload PRi for a particular set of flight parameters;

Xij are available representing the significant data of a first set of flight parameters;

Aj are coefficients of multiplication;

Bk are coefficients of addition denoting a second set of flight parameters; and

C is an interception coefficient,

and then applying statistical analysis methods to the entered data.

3. The process of claim 2 wherein the first set of flight parameters represented by variables Xij are flight data relating to the aircraft itself, and the second set of flight parameters corresponding to coefficients Bk are the concurrent aircraft flight conditions, the flying conditions, and the flight stage.

4. The process of claim 2 wherein the first set of flight parameters related to the aircraft itself and the second set of flight parameters which determine the coefficients Bk employed in the development of the statistical model are successively listed in the tables below:

space="preserve" listing-type="tabular">______________________________________ SIGNIFICANT AIRCRAFT DATA UNIT RANGE ______________________________________ Rudder Angle Degrees +/- 180 Angle of roll Degrees +/- 180 Roll Speed Degrees/sec +/- 128 Aerodynamic speed Knots 15 to 450 Angle of incidence Degrees +/- 60 Speed N2 of engine 1 rpm 0 to 4400 ______________________________________ DATA No. DATA (AUTOMATIC FLIGHT CONTROLS) ______________________________________ 23 Altitude 24 Vertical speed (Vz) 25 Flare-out 26 Take-off computer (go around) 27 Take-off computer (take-off) 28 Level change 29 Radio guidance system (guide slope) 30 Longitudinal modes-following 31 Longitudinal modes-capture 32 Navigation 33 Course maintenance 34 Course selection 35 Radio guide azimuth (localizer) 36 Taxiing 37 Take-off 38 Taxiing (go around) 39 Lateral modes-capture 40 VOR 41 Lateral modes-following 42 Alignment 43 Transparent Piloting Engine Conditioning 44 Engine Conditioning Control ______________________________________ FLIGHT PARAMETERS ______________________________________ Ascent with both FMS (Flight Management Systems) disabled Ascent with one FMS disabled and one FMS engaged Ascent with both FMS engaged Cruising with both FMS disabled Cruising with one FMS disabled and one FMS engaged Cruising with both FMS engaged Descent with both FMS disabled Descent with one FMS disabled and one FMS engaged Descent with both FMS engaged Approach with both FMS disabled Approach with one FMS disabled and one FMS engaged Approach with both FMS engaged Landing with both FMS disabled Landing with both FMS engaged Taxiing post landing with both FMS disabled Taxiing post landing with one FMS disabled and one FMS engaged Taxiing post landing with both FMS engaged Go around or emergency descent with automatic thrust lever engaged Pre-flight with automatic thrust lever disengaged Pre-flight with automatic thrust lever engaged Taxiing with automatic thrust lever disengaged Taxiing with automatic thrust lever engaged Takeoff with automatic thrust lever disengaged Takeoff with automatic thrust lever engaged Ascent with automatic thrust lever disengaged Ascent with automatic thrust lever engaged Cruising with automatic thrust lever disengaged Cruising with automatic thrust lever engaged Descent with automatic thrust lever disengaged Descent with automatic thrust lever engaged Approach with automatic thrust lever disengaged Approach with automatic thrust lever engaged Landing with automatic thrust lever disengaged Landing with automatic thrust lever engaged ______________________________________

5. The process of claim 3 or 4 wherein the variables Xij also denote heart rate and heart rate fluctuations of the aircraft pilot that were recorded at the same times as the logging of the ratings by the pilot.

6. The process of claim 1 wherein step (b) further comprises simultaneously generating a signal prompting a copilot to rate his current workload, and step (c) further comprises logging the workload rating made by the copilot and the position in the cockpit of the one of the pilot and copilot who is flying the aircraft at the time of logging the rating.

7. The process of claim 2 wherein the predefined rating scale of step (b) comprises six rating indexes ranging from 2 to 7, in the order of increasing workloads.

8. The process of claim 7 wherein the pilot workload PRi expressed by the predefined workload ratings scale is a function of the variable Yi according to the relation:

space="preserve" listing-type="equation">PRi=3×

10.sup.Yi +1.

9. The process of claim 2 wherein variables Xij comprise the variables listed in the following table:

space="preserve" listing-type="tabular">______________________________________ Variable X.sub.ij ______________________________________ Decimal logarithm of the angle of roll (128) Rate of inversions of aerodynamic speed (64) Rate of inversions of the angle of incidence (64) Rate of inversions of the speed N1 of engine 1 Speed N1 of engine 1 (128) Decimal logarithm of the rudder angle (32) Rate of transitions through zero of the angle of roll squared (128) Decimal logarithm of the number of automatic flight controls engaged Rate of transitions through zero of the roll speed (128) Rate of transitions through zero of the roll speed squared ______________________________________ (128).

10. The process of claim 5 wherein variable Xij comprise the variable listed in the following table:

space="preserve" listing-type="tabular">______________________________________ Variable X.sub.ij ______________________________________ Decimal logarithm of the angle of roll (128) Rate of inversions of aerodynamic speed (64) Rate of inversions of the angle of incidence (64)222 Rate of inversions of the speed N1 of engine 1 Speed N1 of engine 1 (128) Decimal logarithm of the rudder angle (32) Rate of transitions through zero of the angle of roll squared (128) Decimal logarithm of the number of automatic flight controls engaged Rate of transitions through zero of the roll speed (128) Rate of transitions through zero of the roll speed squared (128) Tested pilot-Deviation of RR from the reference mean (128) Tested pilot-Reference weight Sigma RR (64) Tested pilot-Raw RR value (8) Tested pilot-Regression residuals of RR over 32 heartbeats Non tested pilot-Raw RR value (8) Non tested pilot-Deviation of RR from the mean over 16 heartbeats (128) Non tested pilot-Deviation of RR from the reference mean (64) Non tested pilot-Reference weight Sigma RR.sub.1 (64) Non tested pilot-Reference weight Sigma RR.sub.2 (64) Non tested pilot-Deviation of RR from the mean over 32 heartbeats (128) Non tested pilot-Regression residuals of RR over 32 heartbeats. ______________________________________

11. Apparatus for producing a statistical model that predicts a workload that an aircraft places on a pilot during an actual or simulated flight of the aircraft as a function of predetermined objective flight parameters, the apparatus comprising:

means for generating, during at least one selected flight stage of the aircraft, a signal prompting the pilot to rate his current workload according to a predefined scale;

means for logging the workload rating made by the pilot in response to the prompting signal;

means for measuring significant data of at least one set of predetermined flight parameters at the time of generating the signal prompting the pilot;

means for logging the measured significant data of the at least one set of predetermined flight parameters; and

a reference time clock for synchronizing each logged workload rating with the corresponding logged significant data of the flight parameters.

12. The apparatus of claim 11 wherein the means for logging the workload rating made by the pilot comprises a panel having means for displaying a prompting signal and means for logging a rating response made in accordance with a predefined rating scale, and the means for generating a prompting signal for the pilot to rate his current workload comprises means to address a prompting signal to a selected one of a plurality of crew members and means for logging the corresponding flight parameters.

13. The apparatus of claim 11 further comprising means for measuring and recording electrocardiograms of selected crew members in synchronization with the reference time clock.

14. The apparatus of claim 11 or 12 further comprising means for filming images of the cockpit, means for displaying and recording said filmed images, and means for overlaying output data from the means for generating a prompting signal and the workload rating logging means onto the display means.

15. A method for producing a statistical model for predicting a workload that an aircraft designated as a reference aircraft places on a pilot during actual or simulated flight as a function of predetermined objective flight parameters for use in certifying the reference aircraft and applying the statistical model of pilot workload as a function of predetermined flight parameters of the previously certified reference aircraft to the certification of crew assignments of a new aircraft, the model being in the form:

space="preserve" listing-type="equation">Yi=A1 Xi1+A2 Xi2+. . . +Aj Xij+. . . +An Xin+B1+B2+. . . +Bk+. . . +Bm+C,

wherein;

Yi is a variable representing a pilot workload for a particular set of flight parameters;

Xij are variables representing the significant data of a first set of flight parameters;

Aj are coefficients of multiplication determined by statistically correlating at least one set of logged pilot responses to requests for workload ratings during a plurality of flight stages of at least one actual or simulated flight of the aircraft with a set of simultaneously logged measurements of the significant data of the first set of flight parameters;

Bk are coefficients of addition denoting a second set of flight parameters and determined by statistically correlating said at least one set of logged pilot responses with a set of simultaneously logged measurements of the significant data of the second set of flight parameters; and

C is an interception coefficient, wherein the method comprises the steps of;

(a) defining a set of predetermined objective flight parameters corresponding to different preselected aircraft flight data, flight conditions of the reference aircraft, flying conditions, and flight stages;

(b) generating a signal prompting the pilot during an actual or simulated flight of the reference aircraft to rate his current workload Yi according to a predefined scale;

(c) logging the workload rating Yi made by the pilot in response to the prompting signal;

(d) measuring values Xij of significant data of a plurality of applicable flight parameters when the prompting signal for a workload rating is generated;

(e) logging the measured values Xij of the applicable flight parameters simultaneously with step (c);

(f) repeating steps (b) through (e) at least once in each of the preselected flight stages of the reference aircraft;

(g) correlating the workload ratings and flight parameters from step (f) to determine values of Bk and C so as to produce a statistical model of the workload Yi on the pilot of the reference aircraft as a function of the flight parameters;

(h) measuring the flight parameters defined in step (a) and denoted by variables Xij under various flight stages and conditions representative of predetermined certification rules during at least one test flight of the new aircraft;

(i) determine the status of the significant data Bk of the second set of flight parameters;

(j) calculating the corresponding values of the variable Yi by means of the model developed for the reference aircraft;

(k) deducing workload values according to a defined objective scale from the values of Yi calculated in step (j); and

(l) comparing the workload values of the new aircraft with the corresponding workload values of the previously certified reference aircraft.

16. The process of claim 15 wherein the variables Xij also denote heart rate and heart rate fluctuations of the aircraft pilot that were recorded at the same times as the logging of the ratings by the pilot.