Trust in Automation – Before and After the Experience of Take-over Scenarios in a Highly Automated Vehicle

Gold, Christian; Körber, Moritz; Hohenberger, Christoph; Lechner, David; Bengler, Klaus

doi:10.1016/j.promfg.2015.07.847

Cited by 267 publications

(149 citation statements)

References 18 publications

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“…the Trust Promoted group looked at the NDRT for a longer time, while having a lower glance frequency and glance percentage on the road and instrument cluster. Contrary to a previous study (Gold, Körber, Hohenberger, Lechner, & Bengler, 2015), participants with higher trust scanned the environment less. This relationship could not be found regarding the difference between both groups except in Interim 2.…”

Section: Discussioncontrasting

confidence: 82%

“…Since our results are in accordance with previous results, we believe that our conclusions are nonetheless valid, however, we recommend a large sample size for a more exact parameter estimation and for future confirmatory work. Also, since age has been shown to be relevant for trust in automation (Gold et al, 2015;Wiegmann, McCarley, Kramer, & Wickens, 2006), a more diverse sample regarding age should be chosen. The measurement of trust by questionnaires and its relationship to behavioral measures has yet to be investigated psychometrically in further detail.…”

Section: Limitationsmentioning

confidence: 99%

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Introduction matters: Manipulating trust in automation and reliance in automated driving

2018

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Trust in automation is a key determinant for the adoption of automated systems and their appropriate use. Therefore, it constitutes an essential research area for the introduction of automated vehicles to road traffic. In this study, we investigated the influence of trust promoting (Trust promoted group) and trust lowering (Trust lowered group) introductory information on reported trust, reliance behavior and takeover performance. Forty participants encountered three situations in a 17-minute highway drive in a conditionally automated vehicle (SAE Level 3). Situation 1 and Situation 3 were non-critical situations where a take-over was optional. Situation 2 represented a critical situation where a take-over was necessary to avoid a collision. A non-driving-related task (NDRT) was presented between the situations to record the allocation of visual attention. Participants reporting a higher trust level spent less time looking at the road or instrument cluster and more time looking at the NDRT. The manipulation of introductory information resulted in medium differences in reported trust and influenced participants' reliance behavior. Participants of the Trust promoted group looked less at the road or instrument cluster and more at the NDRT. The odds of participants of the Trust promoted group to overrule the automated driving system in the non-critical situations were 3.65 times (Situation 1) to 5 times (Situation 3) higher. In Situation 2, the Trust promoted group's mean take-over time was extended by 1154 ms and the mean minimum time-to-collision was 933 ms shorter. Six participants from the Trust promoted group compared to no participant of the Trust lowered group collided with the obstacle. The results demonstrate that the individual trust level influences how much drivers monitor the environment while performing an NDRT. Introductory information influences this trust level, reliance on an automated driving system, and if a critical take-over situation can be successfully solved.

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Section: Discussioncontrasting

confidence: 82%

Section: Limitationsmentioning

confidence: 99%

Introduction matters: Manipulating trust in automation and reliance in automated driving

2018

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“…Pilots' trust in the system was evaluated with the German version (Gold et al, 2015) of the trust questionnaire originally developed by Jian et al (2000) and validated by Spain et al (2008). In the trust questionnaire, participants had to rate their agreement with 12 statements on a seven-point Likert scale from not at all to extremely.…”

Section: Trustmentioning

confidence: 99%

Are pilots prepared for a cyber-attack? A human factors approach to the experimental evaluation of pilots' behavior

Gontar

Homans

Rostalski

et al. 2018

Journal of Air Transport Management

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A B S T R A C TThe increasing prevalence of technology in modern airliners brings not just advantages, but also the potential for cyber threats. Fortunately, there have been no significant attacks on civil aircraft to date, which allows the handling of these emerging threats to be approached proactively. Although an ample body of research into technical defense strategies exists, current research neglects to take the human operator into account. In this study, we present an exploratory experiment focusing on pilots confronted with a cyber-attack. Results show that the occurrence of an attack affects all dependent variables: pilots' workload, trust, eye-movements, and behavior. Pilots experiencing an attack report heavier workload and weakened trust in the system than pilots whose aircraft is not under attack. Further, pilots who experienced an attack monitored basic flying instruments less and their performance deteriorated. A warning about a potential attack seems to moderate several of those effects. Our analysis prompts us to recommend incorporating cyber-awareness into pilots' recurrent training; we also argue that one has to consider all affected personnel when designing such training. Future research should target the development of appropriate procedures and training techniques to prepare pilots to correctly identify and respond to cyber-attacks.

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“…In order to the importance of the driver state, more recent TOR schemes such as [15] give as much emphasis on psychological and physiological aspects as to the time and motoric aspects. Examples of psycho-physiological states have been then widely explored such as distraction [16], trust [17], and drowsiness.…”

Section: A Driver State Role In Tormentioning

confidence: 99%

Drowsiness in Conditional Automation: Proneness, diagnosis and driving performance effects

Happee

Bengler

2016

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

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Abstract-Fatigue and drowsiness can play an important role in Conditional Automation (CA), as drowsy drivers may fail to properly recover control.In order to provide better insight in the effects of drowsy driving in Take Over Request (TOR), we designed a driving experiment that extends related literature in drowsiness research CA with self-rated subjective drowsiness, and analyze TOR performance adopting methods from recent TOR publications.Results show that under certain conditions, drivers are very prone to drowsiness. Specifically, in this study the majority of subjects reported a high level of drowsiness before 15 minutes. Furthermore, this self-perceived drowsiness was followed by a decrement in vehicle lateral control during TOR. In this time frame, remaining driving performance and eye-tracking related metrics did not show significant decrements traditionally associated with fatigue and drowsiness, suggesting self-report to be more indicative of drowsiness than eye-based metrics.

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Trust in Automation – Before and After the Experience of Take-over Scenarios in a Highly Automated Vehicle

Cited by 267 publications

References 18 publications

Introduction matters: Manipulating trust in automation and reliance in automated driving

Introduction matters: Manipulating trust in automation and reliance in automated driving

Are pilots prepared for a cyber-attack? A human factors approach to the experimental evaluation of pilots' behavior

Drowsiness in Conditional Automation: Proneness, diagnosis and driving performance effects

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