Relationships between workload and fatigue or sleepiness are investigated through the analysis of rosters and responses to questionnaires from Brazilian aircrews, taken from Fadigômetro database. The approach includes temporal markers—coinciding with Samn–Perelli (SP) and Karolinska Sleepiness Scale (KSS) responses—where SAFTE-FAST software outcomes are calculated. The latter results follow the increase of fatigue and sleepiness perceptions during the dawn (0h00 to 05h59), but underestimate self-rated scores during the evening (18h00 to 23h59). Importantly, the KSS scores and the inverse of SAFTE-FAST effectiveness fit the relative risk of pilot errors, representing interesting proxies for risk assessment. Linear relationships obtained between workload metrics, computed within 168-h prior to the responses, and self-rated SP and KSS scores provide a consistent method to estimate accumulated fatigue and sleepiness. Considering 7149 rosters of 2023, the duty time (DT), the number of flight sectors (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_21705_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="56" /> </InlineMediaObject> <EquationSource Format="TEX">\(N_{CREW}\)</EquationSource> </InlineEquation>) and the sum of flight sectors with sit periods longer than one hour (<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_21705_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="112" /> </InlineMediaObject> <EquationSource Format="TEX">\(N_{CREW}+N_{SIT}\)</EquationSource> </InlineEquation>) are associated with 70.1%/60.6% of the highest predicted scores of SP/KSS. Applying the mitigations <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_21705_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="80" /> </InlineMediaObject> <EquationSource Format="TEX">\(DT\le 44 h\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_21705_Article_IEq4.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="95" /> </InlineMediaObject> <EquationSource Format="TEX">\(N_{CREW}\le 15\)</EquationSource> </InlineEquation> and <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_21705_Article_IEq5.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="151" /> </InlineMediaObject> <EquationSource Format="TEX">\(N_{CREW}+N_{SIT} \le 19\)</EquationSource> </InlineEquation> for every 168-h interval yields a significant decrease in higher values of SP/KSS with minimal impact on roster coverage.

Aircrew rostering workload patterns and associated fatigue and sleepiness scores in short and medium haul flights in Brazil

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2025年10月29日

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Tulio E. Rodrigues,
Eduardo Furlan,
André F. Helene,
Otaviano Helene,
Eduardo Pessini,
Alexandre Simões,
Maurício Pontes,
Frida M. Fischer

摘要

Relationships between workload and fatigue or sleepiness are investigated through the analysis of rosters and responses to questionnaires from Brazilian aircrews, taken from Fadigômetro database. The approach includes temporal markers—coinciding with Samn–Perelli (SP) and Karolinska Sleepiness Scale (KSS) responses—where SAFTE-FAST software outcomes are calculated. The latter results follow the increase of fatigue and sleepiness perceptions during the dawn (0h00 to 05h59), but underestimate self-rated scores during the evening (18h00 to 23h59). Importantly, the KSS scores and the inverse of SAFTE-FAST effectiveness fit the relative risk of pilot errors, representing interesting proxies for risk assessment. Linear relationships obtained between workload metrics, computed within 168-h prior to the responses, and self-rated SP and KSS scores provide a consistent method to estimate accumulated fatigue and sleepiness. Considering 7149 rosters of 2023, the duty time (DT), the number of flight sectors ( \(N_{CREW}\) ) and the sum of flight sectors with sit periods longer than one hour ( \(N_{CREW}+N_{SIT}\) ) are associated with 70.1%/60.6% of the highest predicted scores of SP/KSS. Applying the mitigations \(DT\le 44 h\) , \(N_{CREW}\le 15\) and \(N_{CREW}+N_{SIT} \le 19\) for every 168-h interval yields a significant decrease in higher values of SP/KSS with minimal impact on roster coverage.