scholarly journals Prediction of take-over time in highly automated driving by two psychometric tests

DYNA ◽  
2015 ◽  
Vol 82 (193) ◽  
pp. 195-201 ◽  
Author(s):  
Moritz Körber ◽  
Thomas Weißgerber ◽  
Christoph Blaschke ◽  
Mehdi Farid ◽  
Luis Kalb
Keyword(s):  
Psychometric Tests ◽  
Automated Driving ◽  
Over Time ◽  
Highly Automated Driving

scholarly journals Calibration of Trust in Automated Driving: A Matter of Initial Level of Trust and Automation Driving Style?

2021 ◽  
Author(s):  
J. B. Manchon ◽  
Mercedes Bueno ◽  
Jordan Navarro
Keyword(s):  
Initial Level ◽  
Automated Driving ◽  
Human Machine Interaction ◽  
Driving Style ◽  
Automated Vehicle ◽  
Visual Behaviors ◽  
Trust In Automation ◽  
Machine Interaction ◽  
Over Time ◽  
Highly Automated Driving

Automated driving is becoming a reality, such technology raises new concerns about human-machine interaction on-road. Sixty-one drivers participated in an experiment aiming to better understand the influence of initial level of trust (Trustful vs Distrustful) on drivers’ behaviors and trust calibration during simulated Highly Automated Driving (HAD). The automated driving style was manipulated as positive (smooth) or negative (abrupt) to investigate human-machine early interactions. Trust was assessed over time through questionnaires. Drivers’ visual behaviors and take-over performances during an unplanned take-over request were also investigated. Results showed an increase of trust in automation over time, for both Trustful and Distrustful drivers regardless the automated driving style. Trust was also found to fluctuate over time depending on the specific events handled by the automated vehicle. Take-over performances were not influenced by the initial level of trust nor automated driving style.

scholarly journals Take-Over Time: A Cross-Cultural Study of Take-Over Responses in Highly Automated Driving

2021 ◽  
Vol 11 (17) ◽  
pp. 7959
Author(s):  
Gregor Strle ◽  
Yilun Xing ◽  
Erika E. Miller ◽  
Linda Ng Boyle ◽  
Jaka Sodnik
Keyword(s):  
Cultural Differences ◽  
Cultural Study ◽  
Driving Simulator ◽  
Cross Cultural ◽  
Automated Driving ◽  
Secondary Tasks ◽  
Safe Driving ◽  
Cross Cultural Study ◽  
Over Time ◽  
Highly Automated Driving

The article presents a cross-cultural study of take-over performance in highly automated driving. As take-over performance is an important measure of safe driving, potential cultural differences could have important implications for the future development of automated vehicles. The study was conducted in two culturally different locations, Seattle, WA (n = 20) and Ljubljana, Slovenia (n = 18), using a driving simulator. While driving, participants voluntarily engaged in secondary tasks. The take-over request (TOR) was triggered at a specific time during the drive, and take-over time and type of response (none, brake, steer) were measured for each participant. Results show significant differences in take-over performance between the two locations. In Seattle 30% of participants in Seattle did not respond to TOR; the remaining 70% responded by braking only, compared to Slovenian participants who all responded by either braking or steering. Participants from Seattle responded significantly more slowly to TOR (M = +1285 ms) than Slovenian participants. Secondary task engagement at TOR also had an effect, with distracted US participants’ response taking significantly longer (M = +1596 ms) than Slovenian participants. Reported differences in take-over performance may indicate cultural differences in driving behavior and trust in automated driving.

scholarly journals Dynamic scan paths investigations under manual and highly automated driving

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jordan Navarro ◽  
Otto Lappi ◽  
François Osiurak ◽  
Emma Hernout ◽  
Catherine Gabaude ◽  
...  
Keyword(s):  
Relative Frequency ◽  
Human Locomotion ◽  
Visual Scanning ◽  
Automated Driving ◽  
The Gaze ◽  
Visual Inputs ◽  
Gaze Patterns ◽  
Gaze Behaviour ◽  
Scan Paths ◽  
Highly Automated Driving

AbstractActive visual scanning of the scene is a key task-element in all forms of human locomotion. In the field of driving, steering (lateral control) and speed adjustments (longitudinal control) models are largely based on drivers’ visual inputs. Despite knowledge gained on gaze behaviour behind the wheel, our understanding of the sequential aspects of the gaze strategies that actively sample that input remains restricted. Here, we apply scan path analysis to investigate sequences of visual scanning in manual and highly automated simulated driving. Five stereotypical visual sequences were identified under manual driving: forward polling (i.e. far road explorations), guidance, backwards polling (i.e. near road explorations), scenery and speed monitoring scan paths. Previously undocumented backwards polling scan paths were the most frequent. Under highly automated driving backwards polling scan paths relative frequency decreased, guidance scan paths relative frequency increased, and automation supervision specific scan paths appeared. The results shed new light on the gaze patterns engaged while driving. Methodological and empirical questions for future studies are discussed.

First encounter effects in testing of highly automated vehicles during two experimental occasions – The need for recurrent testing

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jonas Andersson ◽  
Azra Habibovic ◽  
Daban Rizgary
Keyword(s):  
Driver Behavior ◽  
Added Value ◽  
Future Research ◽  
Gaze Behavior ◽  
Repeated Testing ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Perceived Safety ◽  
Repeated Interaction ◽  
Over Time

Abstract To explore driver behavior in highly automated vehicles (HAVs), independent researchers are mainly conducting short experiments. This limits the ability to explore drivers’ behavioral changes over time, which is crucial when research has the intention to reveal human behavior beyond the first-time use. The current paper shows the methodological importance of repeated testing in experience and behavior related studies of HAVs. The study combined quantitative and qualitative data to capture effects of repeated interaction between drivers and HAVs. Each driver ( n = 8 n=8 ) participated in the experiment on two different occasions (∼90 minutes) with one-week interval. On both occasions, the drivers traveled approximately 40 km on a rural road at AstaZero proving grounds in Sweden and encountered various traffic situations. The participants could use automated driving (SAE level 4) or choose to drive manually. Examples of data collected include gaze behavior, perceived safety, as well as interviews and questionnaires capturing general impressions, trust and acceptance. The analysis shows that habituation effects were attenuated over time. The drivers went from being exhilarated on the first occasion, to a more neutral behavior on the second occasion. Furthermore, there were smaller variations in drivers’ self-assessed perceived safety on the second occasion, and drivers were faster to engage in non-driving related activities and become relaxed (e. g., they spent more time glancing off road and could focus more on non-driving related activities such as reading). These findings suggest that exposing drivers to HAVs on two (or more) successive occasions may provide more informative and realistic insights into driver behavior and experience as compared to only one occasion. Repeating an experiment on several occasions is of course a balance between the cost and added value, and future research should investigate in more detail which studies need to be repeated on several occasions and to what extent.

scholarly journals Highly Automated Driving, Secondary Task Performance, and Driver State

2012 ◽  
Vol 54 (5) ◽  
pp. 762-771 ◽  
Author(s):  
Natasha Merat ◽  
A. Hamish Jamson ◽  
Frank C. H. Lai ◽  
Oliver Carsten
Keyword(s):  
Task Performance ◽  
Secondary Task ◽  
Automated Driving ◽  
Highly Automated Driving
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