Analysis and Prevention of MCAS-Induced Crashes

Semi-autonomous (SA) systems face the C <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hallenge</small> of determining which source to prioritize for control, whether it is from the human operator or the autonomous controller, especially when they conflict with each other. While one may design an SA system to default to accepting control from one or the other, such design choices can have catastrophic consequences in safety-critical settings. For instance, the sensors an autonomous controller relies upon may provide incorrect information about the environment due to tampering or natural fault. On the other hand, the human operator may also provide erroneous input. To better understand the consequences and resolution of this safety-critical design choice, we investigate a specific application of an SA system that failed due to a static assignment of control authority: the well-publicized Boeing 737-MAX maneuvering characteristics augmentation system (MCAS) that caused the crashes of Lion Air Flight 610 and Ethiopian Airlines Flight 302. First, using a representative simulation, we analyze and demonstrate the ease by which the original MCAS design could fail. Our analysis reveals the most robust public analysis of aircraft recoverability under MCAS faults, offering bounds for those scenarios beyond the original crashes. We also analyze Boeing’s updated MCAS and show how it falls short of its intended goals and continues to rely upon on a fault-prone static assignment of control priority. Using these insights, we present SA-MCAS, a new MCAS that both meets the intended goals of MCAS and avoids the failure cases that plague both MCAS designs. We demonstrate SA-MCAS’s ability to make safer and timely control decisions of the aircraft, even when the human and autonomous operators provide conflicting control inputs.

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Publication Details

Journal
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published
2024-11-01
DOI
https://doi.org/10.1109/tcad.2024.3438105
Citations
3
Primary Topic
Automotive and Human Injury Biomechanics
Type
article
Field-Weighted Citation Impact
1.26

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article

Analysis and Prevention of MCAS-Induced Crashes

Noah T. Curran, Kang Geun Shin, Thomas W. Kennings
3 citations
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Automotive and Human Injury Biomechanics
1.26
article

Analysis and Prevention of MCAS-Induced Crashes

Noah T. Curran, Kang Geun Shin, Thomas W. Kennings
article en
3 citations

Abstract

Semi-autonomous (SA) systems face the C <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hallenge</small> of determining which source to prioritize for control, whether it is from the human operator or the autonomous controller, especially when they conflict with each other. While one may design an SA system to default to accepting control from one or the other, such design choices can have catastrophic consequences in safety-critical settings. For instance, the sensors an autonomous controller relies upon may provide incorrect information about the environment due to tampering or natural fault. On the other hand, the human operator may also provide erroneous input. To better understand the consequences and resolution of this safety-critical design choice, we investigate a specific application of an SA system that failed due to a static assignment of control authority: the well-publicized Boeing 737-MAX maneuvering characteristics augmentation system (MCAS) that caused the crashes of Lion Air Flight 610 and Ethiopian Airlines Flight 302. First, using a representative simulation, we analyze and demonstrate the ease by which the original MCAS design could fail. Our analysis reveals the most robust public analysis of aircraft recoverability under MCAS faults, offering bounds for those scenarios beyond the original crashes. We also analyze Boeing’s updated MCAS and show how it falls short of its intended goals and continues to rely upon on a fault-prone static assignment of control priority. Using these insights, we present SA-MCAS, a new MCAS that both meets the intended goals of MCAS and avoids the failure cases that plague both MCAS designs. We demonstrate SA-MCAS’s ability to make safer and timely control decisions of the aircraft, even when the human and autonomous operators provide conflicting control inputs.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsVol. 43(11)
University of Michigan (US)
Office of Naval Research
Openalex Percentile: Top 18%
Automotive and Human Injury Biomechanics
1.26
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