Fully Automated Driving

Payre, William; Cestac, Julien; Delhomme, Patricia

doi:10.1177/0018720815612319

Cited by 163 publications

(42 citation statements)

References 34 publications

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“…Moray and Inagaki claim that excessive trust in automation can compromise people's readiness to take over manual control [70]. Over-trust in AVs also leads to slower reaction times when people need to intervene in case of an emergency, so-called manual control recovery [71]. Abe et al discovered that reaction times to warnings increased with increasing trust in the vehicle [72].…”

Section: Discussionmentioning

confidence: 99%

Enhancing Trust in Autonomous Vehicles through Intelligent User Interfaces That Mimic Human Behavior

Ruijten

Terken

Chandramouli

2018

MTI

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Autonomous vehicles use sensors and artificial intelligence to drive themselves. Surveys indicate that people are fascinated by the idea of autonomous driving, but are hesitant to relinquish control of the vehicle. Lack of trust seems to be the core reason for these concerns. In order to address this, an intelligent agent approach was implemented, as it has been argued that human traits increase trust in interfaces. Where other approaches mainly use anthropomorphism to shape appearances, the current approach uses anthropomorphism to shape the interaction, applying Gricean maxims (i.e., guidelines for effective conversation). The contribution of this approach was tested in a simulator that employed both a graphical and a conversational user interface, which were rated on likability, perceived intelligence, trust, and anthropomorphism. Results show that the conversational interface was trusted, liked, and anthropomorphized more, and was perceived as more intelligent, than the graphical user interface. Additionally, an interface that was portrayed as more confident in making decisions scored higher on all four constructs than one that was portrayed as having low confidence. These results together indicate that equipping autonomous vehicles with interfaces that mimic human behavior may help increasing people’s trust in, and, consequently, their acceptance of them.

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Section: Discussionmentioning

confidence: 99%

Enhancing Trust in Autonomous Vehicles through Intelligent User Interfaces That Mimic Human Behavior

Ruijten

Terken

Chandramouli

2018

MTI

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“…For example, Payre, Cestac, and Delhomme (2016) found a higher take-over time with increasing trust in an emergency situation if training was insufficient. Consistent across different levels of automation, inappropriate levels of trust lead to extended reaction times or poorer reaction quality in hazardous situations (Abe, Itoh, & Tanaka, 2002;McGuirl & Sarter, 2006;Parasuraman & Riley, 1997).…”

Section: The Role Of Trust In Automated Drivingmentioning

confidence: 99%

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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“…Studies have shown that what is required is an appropriate level of trust (Lee and See, 2004;Parasuraman, Molloy, and Singh, 1993). More recently, Payre, Cestac, and Delhomme (2015) showed that in a driving simulator task, participants with higher trust in automation had longer reaction times to recover a manual control; they suggested that appropriate training is required to overcome such problems. Although our participants evaluated the system more positively through items relating to the trust dimension, we must check that providing the system's intentions could not lead to an inappropriate level of trust or mental workload.…”

Section: Priming and Allocation Of Attentionmentioning

confidence: 99%

Agency modulates interactions with automation technologies

et al. 2018

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The increasing presence of automation between operators and automated systems tends to disrupt operators from action outcomes, leading them to leave the control loop. The theoretical framework of agency suggests that priming the operator about the system's upcoming behaviour could help restore an appropriate sense of control and increase user acceptance of what the system is doing. In a series of two experiments, we test whether providing information about what the system is about to do next leads to an increase in the level of user acceptance, concomitant with an increase in control and performance. Using an aircraft supervision task, we demonstrated the benefit of prime messages regarding system acceptance and performance. Taken together, our results indicate that the principles proposed by this framework could be used to improve human-machine interaction and maintain a high level of sense of control in supervisory tasks. Practitioner Summary: The out-of-the-loop performance problem is a major potential consequence of automation, leaving operators helpless to takeover automation in case of failure. Using an aircraft supervision task, the following article illustrates how the psychological approach of agency can help improving human-system interactions by designing more acceptable and more controllable automated interfaces.

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Fully Automated Driving

Abstract: The practice format used in this study could be used for the first interaction with an FAD car when acquiring such a vehicle.

Cited by 163 publications

References 34 publications

Enhancing Trust in Autonomous Vehicles through Intelligent User Interfaces That Mimic Human Behavior

Enhancing Trust in Autonomous Vehicles through Intelligent User Interfaces That Mimic Human Behavior

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

Agency modulates interactions with automation technologies

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