Human Performance Envelope as a set of interdependent factors for real-time monitoring of driver state

Driving is a complex perceptual-motor skill that combines cognitive, psychomotor, and perceptual abilities to operate a vehicle safely and efficiently. It involves the driver’s ability to manage emotions, such as stress and frustration or cognitive states, like drowsiness, distraction and maintain focus. In this context, the Human Performance Envelope (HPE) is described as a construct use to monitor driver status based on the combination of a set of interdependent factors and represented with a spiderweb model. Its goal is to minimize human error by analysing behaviour and decision-making while optimizing systems and environments to enhance performance. The influence of the activity demand on the model needs to be considered. Assuming that an HPE can be characterized for a specific actor, there could be a number of acceptable HPEs for the same actor, each depending on the activities performed. One possible approach to addressing activity-based HPEs is to isolate specific tasks or situations, assess its factors in those contexts, and determine the feasibility of defining a specific HPE for each activity. Depending on the value of each factor, the resulting model could evolve from fully acceptable to not acceptable. Based on an in-depth bibliographic research this work aims to populate the three main “HPE parameters” (workload, stress, and situation awareness). with vehicular, behavioural and physiological parameters

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-21
DOI
https://doi.org/10.5281/zenodo.17670480
Primary Topic
Human-Automation Interaction and Safety
Type
article
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article

Human Performance Envelope as a set of interdependent factors for real-time monitoring of driver state

Zenodo (CERN European Organization for Nuclear Research)
Human-Automation Interaction and Safety
article

Human Performance Envelope as a set of interdependent factors for real-time monitoring of driver state

article en

Abstract

Driving is a complex perceptual-motor skill that combines cognitive, psychomotor, and perceptual abilities to operate a vehicle safely and efficiently. It involves the driver’s ability to manage emotions, such as stress and frustration or cognitive states, like drowsiness, distraction and maintain focus. In this context, the Human Performance Envelope (HPE) is described as a construct use to monitor driver status based on the combination of a set of interdependent factors and represented with a spiderweb model. Its goal is to minimize human error by analysing behaviour and decision-making while optimizing systems and environments to enhance performance. The influence of the activity demand on the model needs to be considered. Assuming that an HPE can be characterized for a specific actor, there could be a number of acceptable HPEs for the same actor, each depending on the activities performed. One possible approach to addressing activity-based HPEs is to isolate specific tasks or situations, assess its factors in those contexts, and determine the feasibility of defining a specific HPE for each activity. Depending on the value of each factor, the resulting model could evolve from fully acceptable to not acceptable. Based on an in-depth bibliographic research this work aims to populate the three main “HPE parameters” (workload, stress, and situation awareness). with vehicular, behavioural and physiological parameters

Zenodo (CERN European Organization for Nuclear Research)
University of Modena and Reggio Emilia (IT), University of Bologna (IT), Politecnico di Milano (IT)
Peace, Justice and strong institutions
Openalex Percentile: Top 37%
Human-Automation Interaction and Safety
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