Analysis of pilots’ acceptance of an assistance system for optimising fuel efficiency in continuous descent operation (CDO)

In theory, Continuous Descent Operation (CDO) promises a substantial increase in fuel efficiency in comparison to a traditional step wise descent. Its full potential, however, has not yet been realised in the field. The prototype of a newly developed assistance system is able to calculate a secondary flight plan for the descent inflight using updated weather data. The use of this system might narrow the gap between the theoretical and practical fuel efficiency advantage of CDO. However, adding yet another assistance system to the already task heavy flight phase of transition from cruise to descent further increases the pilots’ workload. This study examines the pilots’ acceptance of this system’s prototype. 24 active pilots participated in an online study. The sample included captains and first officers with varying experience. They were presented four flight scenarios and asked to indicate their willingness to use the proposed assistance system in each scenario. The scenarios varied in anticipated workload, remaining fuel on board, flight distance and deviation from scheduled arrival. Subsequently, the participants were asked to evaluate the proposed system quantitatively and give further qualitative feedback. A Generalised Estimating Equation (GEE) model was used to evaluate the quantitative data. The model results imply that the situational workload best predicts the system’s use: the system was highly accepted in less demanding flight scenarios while its use in more demanding flight scenarios (high traffic, technical incidents, ...) varied between participants. To a lesser extent the pilots’ evaluation of the system’s usefulness also predicts its use, such that pilots who find the system more useful are more likely to use it. Neither the pilots’ evaluation of the system’s ease of use nor its compatibility were significant predictors of its use. The qualitative feedback further suggests that an updated version of the proposed system might be regularly used during incident-free flight operation. Practically, the combined results imply a general acceptance of an assistance system aiming at increasing fuel efficiency even if it adds to the pilots’ workload. Further implications for the development of such a system are discussed, as well as theoretical implications regarding the construct of technology acceptance.

Authors

Institutions

Publication Details

Journal
Transportation research procedia
Published
2025-01-01
DOI
https://doi.org/10.1016/j.trpro.2025.05.016
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of pilots’ acceptance of an assistance system for optimising fuel efficiency in continuous descent operation (CDO)

Paul Jonas Goesmann
Transportation research procedia
Air Traffic Management and Optimization
article

Analysis of pilots’ acceptance of an assistance system for optimising fuel efficiency in continuous descent operation (CDO)

Paul Jonas Goesmann
article en

Abstract

In theory, Continuous Descent Operation (CDO) promises a substantial increase in fuel efficiency in comparison to a traditional step wise descent. Its full potential, however, has not yet been realised in the field. The prototype of a newly developed assistance system is able to calculate a secondary flight plan for the descent inflight using updated weather data. The use of this system might narrow the gap between the theoretical and practical fuel efficiency advantage of CDO. However, adding yet another assistance system to the already task heavy flight phase of transition from cruise to descent further increases the pilots’ workload. This study examines the pilots’ acceptance of this system’s prototype. 24 active pilots participated in an online study. The sample included captains and first officers with varying experience. They were presented four flight scenarios and asked to indicate their willingness to use the proposed assistance system in each scenario. The scenarios varied in anticipated workload, remaining fuel on board, flight distance and deviation from scheduled arrival. Subsequently, the participants were asked to evaluate the proposed system quantitatively and give further qualitative feedback. A Generalised Estimating Equation (GEE) model was used to evaluate the quantitative data. The model results imply that the situational workload best predicts the system’s use: the system was highly accepted in less demanding flight scenarios while its use in more demanding flight scenarios (high traffic, technical incidents, ...) varied between participants. To a lesser extent the pilots’ evaluation of the system’s usefulness also predicts its use, such that pilots who find the system more useful are more likely to use it. Neither the pilots’ evaluation of the system’s ease of use nor its compatibility were significant predictors of its use. The qualitative feedback further suggests that an updated version of the proposed system might be regularly used during incident-free flight operation. Practically, the combined results imply a general acceptance of an assistance system aiming at increasing fuel efficiency even if it adds to the pilots’ workload. Further implications for the development of such a system are discussed, as well as theoretical implications regarding the construct of technology acceptance.

Transportation research procediaVol. 88
Technische Universität Dresden (DE)
Technische Universität Dresden
Affordable and clean energy
Openalex Percentile: Top 86%
Air Traffic Management and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.