Influence of cabin and cockpit environment on well-being and performance of flight and cabin crew results from the HEACE project

Transcription

1 Influence of cabin and cockpit environment on well-being and performance of flight and cabin crew results from the HEACE project Volker Mellert Ingo Baumann Nils Freese Roland Kruse Reinhard Weber Elisabeth Groll-Knapp Michael Trimmel Christoph Goger Michael Bellmann Hermann Remmers Arno Röder Peter Faulhaber Mario d Iscia Demos T. Tsahalis

2 Health Effects in Aircraft Cabin Environment cockpit included, focus on crew, passenger data in collaboration with TP FACE

3 Objectives of the HEACE project was to investigate the environmental condition and impact on human well-being and performance (1) in the cabin of an aircraft (simulator) in collaboration with Building Research Establishment BRE, UK Medical University Vienna, Austria EADS Corporate Research Center ITAP GmbH and

4 ... to investigate the environmental condition and impact on human well-being and performance (2) in real flights in collaboration with Medical University Vienna, Austria EADS Corporate Research Center ITAP GmbH Paragon Ltd and

5 ... to investigate the environmental condition and impact on human well-being and performance (3) with data analysis und response model development in collaboration with Building Research Establishment BRE, UK Medical University Vienna, Austria LFME, University of Patras, Greece CIRA, Italy

6 overview research objective / background /concept experimental design selected results from real flights physical environmental parameters PCA space of perception significant items / analysis ov variance (ANOVA) selected results from simulator facility PCA space of perception analysis of variance summary /conclusion

7 comfort, well-being, health, performance... key issues for passengers and crew in an aircraft European research to enhance friendliness of aircraft transport, since FP5 has significant impact on safety issues

8 projects related to aircraft cabin IDEA PACI (identification of a passenger comfort index) CIRA closed HEACE (health effects in aircraft cabin environment) Oldenburg University closed FACE (friendly aircraft cabin environment) Alenia running ICE (ideal cabin environment) BRE running... supported by the European Commission

9 environmental impact in cabin and cockpit sound and vibration air quality, draft, temperature passengers: seat comfort passengers: service by crew added values, specific to purpose of flight (e.g. successfull business trip, holiday trip) crew: mood/ friendlyness of passengers workplace in galley/ cockpit depends on before-flight condition...

10 objectives of the HEACE investigation to measure relevant environmental and instrinsic parameters (psychological, medical, before-flight condition,..., and physical, e.g.vibroacoustics) to investigate the human response to develop some kind of a human response model in order to relate environment response

11 concept to rely on measurements from in-flight/ real-world measurements to monitor precisely environmental condition to assess test persons response with questionnaires, tests and measurement of medical indicators to correlate/ relate environmental parameters with subjective/ objective response to set up a simulator test facility with virtual reality, i.e to reproduce real environmental parameters, in order to vary selected parameters to develop a (limited) human response model

12 experimental design monitor the environment (data logging all relevant conditions with certified instrumentation) design questionnaires (flight and cabin crew, additionally: passengers)

13 development of questionnaires (to be used for simulator experiments and in real flight) previous experience interview of crew personnel selection of key words (adjectives, antonyms) revise list of pairs of adjectives estimate duration to fill-in design proper layout (reading electronically) design proper scale (magnitude estimation, temperature scale [e.g. ASHRAE], link to existing scales, anchor estimates)

14 questionnaires (crew) health and well-being (30 items) environmental conditions (45 items) control over environment (8 items) relative comfort contribution (18 items) effect of the environment (18 items) ability to work (8 items) alertness and mood (9 items) similar for passengers, except work-related items but additional comfort-related items

15 measured parameters Physical parameters o Sound and vibration (time history and Level) o Temperature o Humidity o Draft o Air quality (CO 2, CO, VOCs, number of germs) Physiological parameters o Heart rate and -variability o Blood pressure o Oxygen saturation o Salivary cortisol o Skin conductance

16 selected results from in-flight tests 12/ flights Vienna Delhi Vienna (about 8 h duration each) 3 flights Vienna Tokio (Narita) Vienna (about 12 h duration each) mesurements performed in galley, cabin, cockpit and crew rest compartment 132 cabin crew 30 flight crew

17 for example: db(a) vs db(b) levels (all cases) 92 Cockpit Business 340 Galley Business 340 Eco Galley Eco1 340 Eco2 340 db(b) Galley Eco Cockpit 330 Business 330 Galley Business Eco1 330 Eco2 330 Galley Eco db(a)

18 Noise level distribution (along cabin) db(a) 80,0 78,0 76,0 74,0 72,0 70,0 68,0 66,0 cockpit business galbusi eco1 galeco1 eco2 galeco ,0 7,0 6, contribution of low frequency components db(b) - db(a) 5,0 4,0 3,0 2,0 1, ,0 cockpit business galbusi eco1 galeco1 eco2 galeco

19 data reduction principal component analysis of all cases, i.e. all answers of all persons during each monitored environmental condition clusters of similar perception, e.g. in 11 dimensions noise effects (distraction, annoyance,...) symptoms (headache, dizziness,...) vibration effects and motion temperature, climate motivation, concentration air quality activity (change of certain condition) communication (incl. intelligibility) draft and overall comfort symptoms related to dry air symptoms related to muscle/ jont pain

20 F1 F2 plane (all cases) 1 0,8 0,6 0,4 0,2 0-0,4-0,2 0 0,2 0,4 0,6 0,8 1-0,2 noise-effects symptoms vibration climate motivation -0,4-0,6-0,8-1

21 F1 F3 plane (all cases) 1 0,8 0,6 0,4 0,2 0-0,4-0,2 0 0,2 0,4 0,6 0,8 1-0,2 noise-effects symptoms vibration climate motivation -0,4-0,6-0,8-1

22 F2 F4 plane (all cases) 1 0,8 0,6 0,4 0,2 0-0,4-0,2 0 0,2 0,4 0,6 0,8 1-0,2 noise-effects symptoms vibration climate motivation -0,4-0,6-0,8-1

23 F1 F5 plane (all cases) 1 0,8 0,6 0,4 0,2 0-0,4-0,2 0 0,2 0,4 0,6 0,8 1-0,2 noise-effects symptoms vibration climate motivation -0,4-0,6-0,8-1

24 HEACE: Work share in data analysis statistical analysis (BRE, UVIENNA and UNOL) ANN, artificalneuralnetwork(cira, UNPA) UNOL: Focus on questionnaires and physical environmental parameters UVIENNA: Developed classes of highly significant medical and health indices LFME (UNPA): Developed a two-stage ANN with a mean error of prognosis of about 0.5 units (7-scale)

25 ANOVA analysis of variance reveals or rejects relationships between variables looks at significant differences in distribution of answers/ reactions related to specific environmental conditions, e.g. noise level does not require linear correlation or functional dependency

26 flight phase: Development of air quality stuffy fresh error < 1%

27 flight phase: Decline of motivation, concentration, energy motiv concen energ Err 10 %

28 concentration depends on flight direction (away from home, back to home) high Err < 0.1 % low away back

29 increase of symptoms (dry skin/ nose) with noise level AND flight duration Err 1%, 5 %

30 increase of symptoms (swollen legs/ feet) with noise level Geschätztes Randmittel von sym_24 5 phase Geschätztes Randmittel 4 3 Err < 0.3 % CdB_A (In Bereiche eingeteilt) 3 4

31 increase of symptoms (muscle/ joint pain in neck) with noise level 5 phase Geschätztes Randmittel Err < 0.4 % CdB_A (In Bereiche eingeteilt) 3 4

32 simulator experiments must provide the possibility to design an appropriate environmental condition but have only restricted virtual reality how much do simulators resemble real flights? are results comparable between real flights and simulator flights?

33 experimental design comparable questionnaire design (as in real flight) physical preparation of simulator for optimal virtual reality pre-tests in the AUA-simulator in Vienna main tests in the ACE in Watford (BRE) monitor the environment (data logging all relevant conditions)

34 AUA simulator in Vienna

35 simulated flight at AUA emergency trainer in Vienna

36 wired pilot in simulated flight

37 ACE at BRE in Watford

38 test persons altogether 22 flight crew members 86 cabin crew members 544 passengers crew was professional, passengers were selected at random in cooperation with the FACE techology platform NOTE: statistical basis

39 distributing questionnaires in ACE test rig

40 full 3 x 3 x 3 factorial design temperature t: 21-22, 24-25, C relative humidity rh: 5-10, 15-20, % sound and vibration s/v: 70, 73, 76 db(a) (+/ 0.5) [70 76, , db(a)] in order to compare each variable with each other

41 data reduction variance analysis : variables principal component analysis on 52 clusters of similar perception two main dimensions level of distraction/ annoyance [noise] feel over-all [air quality]

42 2-dim perception space (cabin crew) 1,0 0,8 Air quality in the cabin: freshness Air quality in the galley: freshness 0,6 0,4 overall comfort effect on comfort from noise in the galley -3=negative effect, +3=positive effect 0,2 light level of distraction / annoyance 0,0,0-0,8-0,6-0,4-0,2 0,0 0,2 0,4 0,6 0,8 1,0 working space effect on comfort from temperature in the galley "feel" -0,2-0,4-0,6-0,8 How do you feel at the moment (temp)? How would you change the temperature in the cabin? How would you change the temperature in the galley? c-air c-noise c-light cc-space c-comf g-air g-noise g-light gc-spac g-comf feel -1,0

43 ANOVA analysis of variance reveals or rejects relationships between variables looks at significant differences in distribution of answers/ reactions in the sets related to the three (given) noise levels does not require linear correlation or functional dependency

44 levels relates significantly to perceived volume of noise in cabin 4,6 4,4 Err < 1% Geschätztes Randmittel 4,2 4,0 3,8 3, DB

45 level relates significantly to effect from vibration on ability to work in the galley 0,0 -,1 Err < 1% -,2 Geschätztes Randmittel -,3 -,4 -,5 -,6 -, DB

46 Increasing level with time: Significant impact on noise in cabin level of distraction (3 %) level of annoyance (1 %) overall satisfaction (< 1 %) perception of vibration (< 2 %) and movement (< 1 %) symptoms (< 1%) lethargy/ tiredness difficulty in concentration/ remembering swollen or heavy legs/ feet headache

47 significant impact of db-level on peceived volume of noise (< 1 %) perceived level of vibration in cabin and galley (2 %) the effect of vibration on comfort in the galley (2 %) the experienced lethargy/ tiredness (2 %)

48 NO significant impact of db level on overall satisfaction with noise in the cabin (10 %) perceived level of annoyance due to noise in cabin (5 %) or galley (26 %) anything related to air quality and temperature any symptons like dry nose, swollen feet, headache etc.

49 3 x 3 x 3 design level increase level 1 level 2 level 3 level decrease level 3 level 2 level 1 1 hour temperature and humidity kept constant

50 decreasing level with time NO impact on previous items only on perceived volume of noise in the cabin (2 %)

51 change of perception with time level increase increase symptoms decrease time perception of symptoms NO perception or report on increase of symptoms

52 summary simulator experiments and real flight experiments reveal significant impact of environmental conditions at the workplace of cabin and flight crew on health, well-being, comfort, performance etc. the observed relationships with the cabin environment (which is determined by construction) are moderated by fixed conditions (e.g. flight direction, flight duration, personality of a crew member ) flight duration is an important moderator

53 conclusions modelling human response is very complex and has to take into account numerous interfering parameters a model has to comply with a high-dimensional input vector and a multidimensional output vector each group of subjects (pilots, cabin crew, passengers) requires specific modelling investigations on comfort, health, performance during real flight are highly time, effort, and costs consuming validation of simulator experiments with real flights are still incomplete - test beds must provide an excellent virtual reality