A quantitative framework to assess pilot workload during applications of airborne separation assistance

Yearwood, Pauline D. (2004) A quantitative framework to assess pilot workload during applications of airborne separation assistance. PhD thesis, University of Glasgow.

Abstract

One of the principal concerns with the introduction of Airborne Separation Assistance System (ASAS) Work Package 1 is the operational flexibility of delegating to pilots responsibility for maintaining separation as in keeping with applications of Limited, Extended and Full Delegation [183]. This operational flexibility, among other things, includes identification of potential problems, generation of solutions to resolve them, and implementation and monitoring of the chosen solution. It has also been predicted that this will introduce new performance issues and present implications that will reflect significant changes in the way pilots and air traffic controllers will perform their respective tasks [4], [174], [175], [176] and [177]. As human performance considerations are expected to be central to the performance of advanced cockpit and Air Traffic Management (ATM) system [11] there is the need to address concerns which arise [11] pertaining to the possibility of adverse changes, impact and implementation on the cognitive and behaviour processes of pilots and air traffic controllers. Against this background, the work in this thesis presents the development of an eighty- five factor task index and self-assessment performance framework for the determination of cognitive and performance challenges of pilots during applications of Limited, Extended and Full Delegation of Airborne Separation Assistance. The quantitative framework is developed using the technique of Critical Task Analysis (CTA) and is based on tasks which are inherent to dynamic situations during each respective application. The performance framework was then incorporated into an existing decision support tool, Multi-criteria Analysis for Concept Evaluation (MACE) [9] whose operating and performance utilities were extensively expanded and modified from forty factors to eighty five factors to present the novel approach of this thesis. This novel approach is the development of another decision support tool, Multi-criteria Analysis for Pilot Evaluation, (MpE). The objectives of MpE are: 1. To obtain quantitative measures of the workload of pilots during the ASAS applications already identified. 2. To clearly delineate the functions of pilot from those of ATC during the respective applications. 3. To predict the effects of change in the tasks environment on the workload of both human operators, pilots and controllers. To illustrate the functionality and capabilities of MpE two thousand hypothetical ASAS applications conducted by pilots were simulated. No statistical methods were employed for arriving at this number of 2000, however it was deemed that the number adequately covered the various combinations of the scenarios within the ASAS applications. To achieve objective three above, three hundred and fifty hypothetical ASAS applications conducted by air traffic controllers were simulations using the programme in its original form of (MACE). Whereas Situation Awareness may not be deemed as an ASAS application it was however included as an ASAS application during both simulations to provide insight into the cognitive processes involved in dimension of regulation and to confirm whether CDTI would enable a better representation of the traffic situation. In this thesis workload is defined as a comparison between Heaven and Hell where the closer to Heaven the workload is seen as easier and the closer to Hell the more difficult. To arrive at the workload measurements for pilots during each respective application the eighty-five factors served as indicators. Then, using a specific value scale provided by the programme these indicators were related to one or several Criteria, (a list provided by the programme expressing human dimensions) through linear regression. A quadratic solution where a positive result indicates the strength of the influence {Heaven) and a negative the weakness of the influence {Hell) provides the final outcome. Of the 2000 ASAS application simulations conducted for pilots, the overall regression coefficient p, (where p indicates the effect of change) derived from the coefficient 05 produced a value of p = 0.956. As this value is nearer to 1 it indicates a positive representation of the distance to Heaven, where the closer to Heaven the workload is seen as easier. Accordingly, from this result one can deduce that the work of pilots during the four ASAS applications will be easier.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: Occupational psychology.
• Colleges/Schools: College of Science and Engineering > School of Engineering
• Supervisor's Name: Goodchild, Dr. Colin
• Date of Award: 2004
• Depositing User: Enlighten Team
• Unique ID: glathesis:2004-71439
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 10 May 2019 14:40
• Last Modified: 22 Jul 2021 15:32
• URI: https://theses.gla.ac.uk/id/eprint/71439