| 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 (11/11 displayed)
- 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
Take-over expectation and criticality in Level 3 automated driving: a test track study on take-over behavior in semi-trucks
Abstract
With the introduction of advanced driving assistance systems managing longitudinal and lateral control, conditional automated driving is seemingly in near future of series vehicles. While take-over behavior in the passenger car context has been investigated intensively in recent years, publications on semi-trucks with professional drivers are sparse. The effects influencing expert drivers during take-overs in this context lack thorough investigation and are required to design systems that facilitate safe take-overs. While multiple findings seem to cohere in passenger cars and semi-trucks, these findings rely on simulated studies without taking environments as found in the real world into account. A test track study was conducted, simulating highway driving with 27 professional non-affiliated truck drivers. The participants drove an automated Level 3 semi-truck while a non-driving-related task was available. Multiple time critical take-over situations were initiated during the drives to investigate four main objectives regarding driver behavior. (1) With these results, comparison of reaction times and behavior can be drawn to previous simulator studies. The effect of situation criticality (2) and training (3) of take-over situations is investigated. (4) The influence of warning expectation on driver behavior is explored. Results obtained displayed very quick time to hands on steering and time to first reaction all under 2.4 s. Highly critical situations generate very quick reaction times M = 0.81 s, while the manipulation of expectancy yielded no significant variation in reaction times. These reaction times serve as a reference of what can be expected from drivers under optimal take-over conditions, with quick reactions at high speed in critical situations.
Topics
Search in FID move catalog