With automated vehicles becoming increasingly widespread, the modern transportation landscape is likely to change. Compared to manually operated vehicles, automated vehicles are expected to offer a...Show moreWith automated vehicles becoming increasingly widespread, the modern transportation landscape is likely to change. Compared to manually operated vehicles, automated vehicles are expected to offer a range of benefits, from reduced environmental impact to increased road safety. However, the success of this technology depends on whether human passengers can learn to interact with it appropriately. The process of trust calibration is important for this, as appropriately calibrated trust enables a passenger to rely on the vehicle when it is warranted but intervene in situations where the capabilities of automation fall short. Therefore, investigating factors affecting trust is crucial for developing systems that facilitate successful human–automated vehicle partnerships. To learn more about the dynamics of trust development during a drive in an automated vehicle, we conducted this experimental study. In it, two groups of participants underwent a driving simulation in a virtual reality environment, one being driven by an automated vehicle and the other by a human driver. Both groups experienced a dangerous traffic rule violation during the drive. We assessed the trust levels during the drive and found that trust significantly dropped after the rule violation with no full recovery afterwards. We observed a similar pattern in both groups, with no significant differences between the human and the automated vehicle conditions both in terms of mean trust scores and pattern of trust development. Furthermore, we assessed the relationship between trust and extroversion, but no significant correlation was found. Our findings suggest that trust calibration is a dynamic process, with participants continuously updating their expectations regarding the vehicle’s safety and capabilities. This knowledge contributes to the understanding of factors influencing human–automation relationships and can help aid the integration of automated vehicles in today’s transportation landscape.Show less
Previous research has shown that children’s art viewing behaviour is influenced by bottom-up factors, as opposed to top-down factors in adults. This study examines the influence of painting...Show morePrevious research has shown that children’s art viewing behaviour is influenced by bottom-up factors, as opposed to top-down factors in adults. This study examines the influence of painting descriptions tailored to children aged 10-12 on their visual attention and aesthetic appreciation of art. Sixty-two participants viewed a set of three painting in the halls of the Rijksmuseum in Amsterdam, while their eye movements were recorded. One group received a description tailored to their age-group before viewing each painting (Child Description Condition), while the two other groups either received the museum’s description (Adult Description Condition) or no description at all (Free-Viewing Condition). After viewing, each participant’s aesthetic appreciation was measured. Findings indicate significant differences in visual attention between conditions, where participants with child-tailored description viewed more areas of interest for a longer period compared to other conditions. However, no difference in aesthetic appreciation was found between conditions. These results highlight the importance of tailoring art descriptions to the knowledge level of specific demographics, children in particular. Furthermore, it shows that adult-level descriptions are just as effective at modulating children’s visual attention as giving no description or information at all. Going further, this knowledge can be applied to enhance children’s understanding and maintain engagement in various real-world settings, such as education and safety.Show less
Previous research has shown that children’s art viewing behaviour is influenced by bottom-up factors, as opposed to top-down factors in adults. This study examines the influence of painting...Show morePrevious research has shown that children’s art viewing behaviour is influenced by bottom-up factors, as opposed to top-down factors in adults. This study examines the influence of painting descriptions tailored to children aged 10-12 on their visual attention and aesthetic appreciation of art. Sixty-two participants viewed a set of three painting in the halls of the Rijksmuseum in Amsterdam, while their eye movements were recorded. One group received a description tailored to their age-group before viewing each painting (Child Description Condition), while the two other groups either received the museum’s description (Adult Description Condition) or no description at all (Free-Viewing Condition). After viewing, each participant’s aesthetic appreciation was measured. Findings indicate significant differences in visual attention between conditions, where participants with child-tailored description viewed more areas of interest for a longer period compared to other conditions. However, no difference in aesthetic appreciation was found between conditions. These results highlight the importance of tailoring art descriptions to the knowledge level of specific demographics, children in particular. Furthermore, it shows that adult-level descriptions are just as effective at modulating children’s visual attention as giving no description or information at all. Going further, this knowledge can be applied to enhance children’s understanding and maintain engagement in various real-world settings, such as education and safety.Show less
This study delves into the intricate dynamics of how students interact with ChatGPT, a new chatbot using machine learning algorithms, specifically examining whether they tend to place excessive...Show moreThis study delves into the intricate dynamics of how students interact with ChatGPT, a new chatbot using machine learning algorithms, specifically examining whether they tend to place excessive trust in the information it provides. The study, involving 169 student participants, uses an experimental design to explore biases, trust perceptions and decision-making processes related to both AI-generated and human expert answers. Two different groups are examined in this study - the labelled group, with knowledge about the answer source, and the unlabelled group, which operates without information about the answer source. The study reveals a preference for answers from human experts, both in the overall sample and in the labelled group. Interestingly, this preference is absent in the unlabelled group, where students do not show a preference when unaware of the answer source. Furthermore, participants in all groups consistently show a tendency to choose correct answers over incorrect ones, indicating an inherent ability to distinguish accurate, high-quality information regardless of their awareness of the source. In conclusion, this study offers valuable insights into how students navigate and interact with ChatGPT. The notable preference for answers from human experts in the labelled group indicates a possible source bias. However, the consistent selection of correct answers in both groups underscores students' skill in identifying high-quality information. As such, this study highlights the trust dynamics in an AI-influenced society and emphasises the need for educating the new generation about the transformative role of AI.Show less
Abstract Background: To date, automated vehicles (AVs) still require human drivers to take back control upon request. When a take-over request (TOR) is issued, efficient and safe interaction...Show moreAbstract Background: To date, automated vehicles (AVs) still require human drivers to take back control upon request. When a take-over request (TOR) is issued, efficient and safe interaction between the AV and the driver needs to be ensured. Visuo-respiratory synchronisation has been proposed as a novel technique to reduce reaction time (RT) to TORs. Objective: In this study, we manipulated visuo-respiratory synchronisation in an automated driving simulation study. We hypothesize that exposing drivers to synchronised ambient light reduces RT and crash rate. In an exploratory fashion, we investigate trust in automation and heart-rate variability (HRV) development. Methods: During a 15-min automated driving phase, drivers were exposed to different types of ambient light. 57 participants were assigned to one of three conditions of pulsing ambient light: synchronised with their breathing (synchronised), in a set frequency (repetitive), or absence of ambient light (no-light). The automation phase ended with the AV issuing a TOR. Drivers had to react as quickly as possible to avoid an obstacle. Results: No significant differences in RT or crash rate between groups were found. An exploratory analysis yielded a significant increase of trust in automation after the simulation compared to before. HRV analysis showed no clearly interpretable results. Conclusion: Our results are conflicting with the results of prior research on visuo-respiratory synchronisation. More research is needed to determine whether visuo-respiratory synchronisation is an effective technique to increase take-over speed in automated driving.Show less
Background: To date, automated vehicles (AVs) still require human drivers to take back control upon request. When a take-over request (TOR) is issued, efficient and safe interaction between the AV...Show moreBackground: To date, automated vehicles (AVs) still require human drivers to take back control upon request. When a take-over request (TOR) is issued, efficient and safe interaction between the AV and the driver needs to be ensured. Visuo-respiratory synchronisation has been proposed as a novel technique to reduce reaction time (RT) to TORs. Objective: In this study, we manipulated visuo-respiratory synchronisation in an automated driving simulation study. We hypothesize that exposing drivers to synchronised ambient light reduces RT and crash rate. In an exploratory fashion, we investigate trust in automation and heart-rate variability (HRV) development. Methods: During a 15-min automated driving phase, drivers were exposed to different types of ambient light. 57 participants were assigned to one of three conditions of pulsing ambient light: synchronised with their breathing (synchronised), in a set frequency (repetitive), or absence of ambient light (no-light). The automation phase ended with the AV issuing a TOR. Drivers had to react as quickly as possible to avoid an obstacle. Results: No significant differences in RT or crash rate between groups were found. An exploratory analysis yielded a significant increase of trust in automation after the simulation compared to before. HRV analysis showed no clearly interpretable results. Conclusion: Our results are conflicting with the results of prior research on visuo-respiratory synchronisation. More research is needed to determine whether visuo-respiratory synchronisation is an effective technique to increase take-over speed in automated driving.Show less
