Matching Items (3)
Filtering by
- All Subjects: Transportation
Description
Previous literature was reviewed in an effort to further investigate the link between notification levels of a cell phone and their effects on driver distraction. Mind-wandering has been suggested as an explanation for distraction and has been previously operationalized with oculomotor movement. Mind-wandering’s definition is debated, but in this research it was defined as off task thoughts that occur due to the task not requiring full cognitive capacity. Drivers were asked to operate a driving simulator and follow audio turn by turn directions while experiencing each of three cell phone notification levels: Control (no texts), Airplane (texts with no notifications), and Ringer (audio notifications). Measures of Brake Reaction Time, Headway Variability, and Average Speed were used to operationalize driver distraction. Drivers experienced higher Brake Reaction Time and Headway Variability with a lower Average Speed in both experimental conditions when compared to the Control Condition. This is consistent with previous research in the field of implying a distracted state. Oculomotor movement was measured as the percent time the participant was looking at the road. There was no significant difference between the conditions in this measure. The results of this research indicate that not, while not interacting with a cell phone, no audio notification is required to induce a state of distraction. This phenomenon was unable to be linked to mind-wandering.
ContributorsRadina, Earl (Author) / Gray, Robert (Thesis advisor) / Chiou, Erin (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2019
Description
Future autonomous vehicle systems will be diverse in design and functionality since they will be produced by different brands. In the automotive industry, trustworthiness of a vehicle is closely tied to its perceived safety. Trust involves dependence on another agent in an uncertain situation. Perceptions of system safety, trustworthiness, and performance are important because they guide people’s behavior towards automation. Specifically, these perceptions impact how reliant people believe they can be on the system to do a certain task. Over or under reliance can be a concern for safety because they involve the person allocating tasks between themselves and the system in inappropriate ways. If a person trusts a brand they may also believe the brand’s technology will keep them safe. The present study measured brand trust associations and performance expectations for safety between twelve different automobile brands using an online survey.
The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.
These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.
The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.
These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.
ContributorsCelmer, Natalie (Author) / Branaghan, Russell (Thesis advisor) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Vehicular automation and autonomy are emerging fields that are growing at an
exponential rate, expected to alter the very foundations of our transportation system within the next 10-25 years. A crucial interaction has been born out this new technology: Human and automated drivers operating within the same environment. Despite the well- known dangers of automobiles and driving, autonomous vehicles and their consequences on driving environments are not well understood by the population who will soon be interacting with them every day. Will an improvement in the understanding of autonomous vehicles have an effect on how humans behave when driving around them? And furthermore, will this improvement in the understanding of autonomous vehicles lead to higher levels of trust in them? This study addressed these questions by conducting a survey to measure participant’s driving behavior and trust when in the presence of autonomous vehicles. Participants were given several pre-tests to measure existing knowledge and trust of autonomous vehicles, as well as to see their driving behavior when in close proximity to autonomous vehicles. Then participants were presented with an educational intervention, detailing how autonomous vehicles work, including their decision processes. After examining the intervention, participants were asked to repeat post-tests identical to the ones administered before the intervention. Though a significant difference in self-reported driving behavior was measure between the pre-test and post- test, there was no significant relation found between improvement in scores on the education intervention knowledge check and driving behavior. There was also no significant relation found between improvement in scores on the education intervention knowledge check and the change in trust scores. These findings can be used to inform autonomous vehicle and infrastructure design as well as future studies of the effects of autonomous vehicles on human drivers in experimental settings.
exponential rate, expected to alter the very foundations of our transportation system within the next 10-25 years. A crucial interaction has been born out this new technology: Human and automated drivers operating within the same environment. Despite the well- known dangers of automobiles and driving, autonomous vehicles and their consequences on driving environments are not well understood by the population who will soon be interacting with them every day. Will an improvement in the understanding of autonomous vehicles have an effect on how humans behave when driving around them? And furthermore, will this improvement in the understanding of autonomous vehicles lead to higher levels of trust in them? This study addressed these questions by conducting a survey to measure participant’s driving behavior and trust when in the presence of autonomous vehicles. Participants were given several pre-tests to measure existing knowledge and trust of autonomous vehicles, as well as to see their driving behavior when in close proximity to autonomous vehicles. Then participants were presented with an educational intervention, detailing how autonomous vehicles work, including their decision processes. After examining the intervention, participants were asked to repeat post-tests identical to the ones administered before the intervention. Though a significant difference in self-reported driving behavior was measure between the pre-test and post- test, there was no significant relation found between improvement in scores on the education intervention knowledge check and driving behavior. There was also no significant relation found between improvement in scores on the education intervention knowledge check and the change in trust scores. These findings can be used to inform autonomous vehicle and infrastructure design as well as future studies of the effects of autonomous vehicles on human drivers in experimental settings.
ContributorsReagan, Taylor (Author) / Cooke, Nancy J. (Thesis advisor) / Chiou, Erin (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2019