Look who’s talking now: Implications of AV’s explanations on driver’s trust, AV preference, anxiety and mental workload

Du, Na; Haspiel, Jacob; Zhang, Qiaoning; Tilbury, Dawn M.; Pradhan, Anuj K.; Yang, X. Jessie; Robert, Lionel

doi:10.1016/j.trc.2019.05.025

Cited by 111 publications

(81 citation statements)

References 70 publications

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“…Also, in the context of automated driving, anxiety has been investigated as a dependent variable additional to trust in automation. Du et al (2019) report a significant negative relationship between trust and anxiety although this relationship was not in the focus of their research and anxiety was measured as an attitude instead of an emotional state.…”

Section: Anxiety and Trust In Automationmentioning

confidence: 99%

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Kraus¹,

Scholz²,

Meßner

et al. 2020

Front. Psychol.

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The advantages of automated driving can only come fully into play if these systems are used in an appropriate way, which means that they are neither used in situations they are not designed for (misuse) nor used in a too restricted manner (disuse). Trust in automation has been found to be an essential psychological basis for appropriate interaction with automated systems. Well-balanced system use requires a calibrated level of trust in correspondence with the actual ability of an automated system. As for these far-reaching implications of trust for safe and efficient system use, the psychological processes, in which trust is dynamically calibrated prior and during the use of automated technology, need to be understood. At this point, only a restricted body of research investigated the role of personality and emotional states for the formation of trust in automated systems. In this research, the role of the personality variables depressiveness, self-efficacy, self-esteem, and locus of control for the experience of anxiety before the first experience with a highly automated driving system were investigated. Additionally, the relationship of the investigated personality variables and anxiety to subsequent formation of trust in automation was investigated. In a driving simulator study, personality variables and anxiety were measured before the interaction with an automated system. Trust in the system was measured after participants drove with the system for a while. Trust in the system was significantly predicted by state anxiety and the personality characteristics self-esteem and selfefficacy. The relationships of self-esteem and self-efficacy were mediated by state anxiety as supported by significant specific indirect effects. While for depression the direct relationship with trust in automation was not found to be significant, an indirect effect through the experience of anxiety was supported. Locus of control did not show a significant association to trust in automation. The reported findings support the importance of considering individual differences in negative self-evaluations and anxiety when being introduced to a new automated system for individual differences in trust in automation. Implications for future research as well as implications for the design of automated technology in general and automated driving systems are discussed.

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Section: Anxiety and Trust In Automationmentioning

confidence: 99%

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Kraus¹,

Scholz²,

Meßner

et al. 2020

Front. Psychol.

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“…AV explanations are one approach to promoting trust in AVs, but driver age might undermine its impact. Explanations-reasoning or logic behind actions-have been shown to facilitate trust in automation [8]. Explanations reduce anxiety about the actions taken by automation [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Explanations are reasons that underlie why an action was or should be taken [8,16]. Explanations have been used to support a range of automation, such as automated decision aid, driving automation, and recommender systems.…”

Section: Introductionmentioning

confidence: 99%

Drivers’ Age and Automated Vehicle Explanations

2021

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Automated vehicles (AVs) have the potential to benefit our society. However, lack of trust is a major barrier to the adoption of AVs. Providing explanations is one approach to facilitating AV trust by decreasing uncertainty about AVs’ decision-making and action. However, explanations might increase drivers’ cognitive effort and anxiety. Because of differences in cognitive ability across age groups, it is not clear whether explanations are equally beneficial for drivers across age groups in terms of trust, effort, and anxiety. To examine this, we conducted a mixed-design experiment with 40 participants divided into three age groups (i.e., younger, middle-aged, and older). Participants were presented with: (1) no explanation, (2) explanation given before or (3) after the AV took action, or (4) explanation along with a request for permission to take action. Results suggest that the explanations provided before AVs take action produced the highest trust and lowest effort for all drivers regardless of age group. The request-for-permission condition led to the highest trust and lowest effort only for older drivers. Younger drivers had the lowest anxiety and effort under the AV-explanation-after-action condition; however, this condition produced the highest level of anxiety and effort in middle-aged and older drivers, respectively. These results have important implications in designing AV explanations and promoting trust.

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“…To address this issue, scholars studying human–AV interactions have begun to examine the topic of human trust in AVs (Verberne et al, 2012 ; Choi and Ji, 2015 ; Basu and Singhal, 2016 ; Ekman et al, 2016 ; Du et al, 2019 ). However, much of this research has been directed at human–AV interactions within the AV itself.…”

Section: Introductionmentioning

confidence: 99%

“…However, much of this research has been directed at human–AV interactions within the AV itself. This existing research focuses primarily on identifying and examining the factors promoting drivers' trust in AVs and the implications of drivers trusting AVs (Gold et al, 2015 ; Verberne et al, 2015 ; Petersen et al, 2018 ; Zhang et al, 2018 ; Du et al, 2019 ). Much less attention has been paid to pedestrians and other road users outside of the AV (Saleh et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Pedestrian Trust in Automated Vehicles: Role of Traffic Signal and AV Driving Behavior

et al. 2019

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Pedestrians' acceptance of automated vehicles (AVs) depends on their trust in the AVs. We developed a model of pedestrians' trust in AVs based on AV driving behavior and traffic signal presence. To empirically verify this model, we conducted a human-subject study with 30 participants in a virtual reality environment. The study manipulated two factors: AV driving behavior (defensive, normal, and aggressive) and the crosswalk type (signalized and unsignalized crossing). Results indicate that pedestrians' trust in AVs was influenced by AV driving behavior as well as the presence of a signal light. In addition, the impact of the AV's driving behavior on trust in the AV depended on the presence of a signal light. There were also strong correlations between trust in AVs and certain observable trusting behaviors such as pedestrian gaze at certain areas/objects, pedestrian distance to collision, and pedestrian jaywalking time. We also present implications for design and future research.

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Look who’s talking now: Implications of AV’s explanations on driver’s trust, AV preference, anxiety and mental workload

Cited by 111 publications

References 70 publications

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Drivers’ Age and Automated Vehicle Explanations

Pedestrian Trust in Automated Vehicles: Role of Traffic Signal and AV Driving Behavior

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