| People | Locations | Statistics |
|---|---|---|
| Ziakopoulos, Apostolos | Athens |
|
| Vigliani, Alessandro | Turin |
|
| Catani, Jacopo | Rome |
|
| Statheros, Thomas | Stevenage |
|
| Utriainen, Roni | Tampere |
|
| Guglieri, Giorgio | Turin |
|
| Martínez Sánchez, Joaquín |
| |
| Tobolar, Jakub |
| |
| Volodarets, M. |
| |
| Piwowar, Piotr |
| |
| Tennoy, Aud | Oslo |
|
| Matos, Ana Rita |
| |
| Cicevic, Svetlana |
| |
| Sommer, Carsten | Kassel |
|
| Liu, Meiqi |
| |
| Pirdavani, Ali | Hasselt |
|
| Niklaß, Malte |
| |
| Lima, Pedro | Braga |
|
| Turunen, Anu W. |
| |
| Antunes, Carlos Henggeler |
| |
| Krasnov, Oleg A. |
| |
| Lopes, Joao P. |
| |
| Turan, Osman |
| |
| Lučanin, Vojkan | Belgrade |
|
| Tanaskovic, Jovan |
|
Russwinkel, Nele
in Cooperation with on an Cooperation-Score of 37%
Topics
- driving
- attention
- autonomous driving
- driver
- driving simulator
- modeling
- variable
- mediation
- driving behavior
- automobile
- passenger
- passenger car
- vehicle occupant
- design
- truck driver
- truck
- highway
- steering
- reaction time
- expected value
- test track
- lateral control
- professional driver
- level 3 driving automation
- air traffic
- air traffic control
- computer programming
- computer science
- flight
- behavior
- machinery
- human being
- weather
- foundation
- aeronautics
- aviation
- cognition
- cockpit
- flight deck
- assessment
- perception
- beltway
- data
- crash
- poison
- interface
- brain
- alertness
- automation
- flight crew
- psychiatry
- emergency response time
- aircraft
- eye
- guideline
- eye movement
- control device
- estimating
- employed
- validation
- airport
- traffic load
- engineering
- supporting
- airport traffic
- tower
- workload
- dispatcher
- goodness of fit
- show 39 more
Publications
- 2022A Cognitive Model to Anticipate Variations of Situation Awareness and Attention for the Takeover in Highly Automated Driving
- 2021Familiarity and Complexity during a Takeover in Highly Automated Drivingcitations
- 2020Take-over expectation and criticality in Level 3 automated driving: a test track study on take-over behavior in semi-truckscitations
- 2020The Impact of Situational Complexity and Familiarity on Takeover Quality in Uncritical Highly Automated Driving Scenarioscitations
- 2020Towards Cognitive Assistance and Teaming in Aviation by Inferring Pilot’s Mental Statecitations
- 2020Towards a cognitive model of the takeover in highly automated driving for the improvement of human machine interaction.
- 2020ACT-R model for cognitive assistance in handling flight deck alerts
- 2020Tracing Pilots’ Situation Assessment by Neuroadaptive Cognitive Modelingcitations
- 2019Response times and gaze behavior of truck drivers in time critical conditional automated driving take-overscitations
- 2017A guideline for integrating dynamic areas of interests in existing set-up for capturing eye movement: Looking at moving aircraftcitations
- 2015Workload of Airport Tower Controllers: Empirical Validation of a Macro-cognitive Model
Places of action
article
Workload of Airport Tower Controllers: Empirical Validation of a Macro-cognitive Model
Abstract
The paper focuses on a validation study for a macro-cognitive model of mental workload of airport traffic controllers (ATCOs). This model constitutes a means for quantifying and analysing the distribution of ATCOs workload over time dependent on different traffic scenarios. Workload is modelled via the amount of chunks in working memory. In a one-factor experimental Simulator-Study workload ratings were gathered with different traffic load, using a modified RSME scale within and NASA-TLX after each scenario. The data are analysed and discussed concerning the successful experimental manipulation and the estimation of goodness of fit of the model and experimental data. Therefore the average workload ratings of the participant and the model within each scenario as well as the distribution of workload over time for each participant-model pair are compared. The developed model can serve as a tool for the design of adaptive automation and supporting systems and can help to better understand workload dynamics of airport traffic controllers.
Topics
Search in FID move catalog