Perceived benefits and constraints in vehicle automation: Data to assess the relationship between driver's features and their attitudes towards autonomous vehicles

Lijarcio, Ignacio; Useche, Sergio A.; Llamazares, Javier; Montoro, Luís

doi:10.1016/j.dib.2019.104662

Cited by 15 publications

(17 citation statements)

References 7 publications

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“…Previous studies on road vehicle automation have operationalized perceived safety and trust by generic items, such as: “Overall , AVs would help make my journeys safer than they are when I use conventional vehicles” [ 78 , p. 3; 79, p. 874], “I am worried that the general safety of using an AV is worse than that of driving a common vehicle” [ 80 , p. 109848], and “Overall , I can trust autonomous vehicles” [ 29 , p. 697]. Other studies asked respondents to rate their level of trust and safety or changes in these using items such as: “To what extent do you trust the driving automation according to the previous performance of the system ?…”

Section: Discussionmentioning

confidence: 99%

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Nordhoff

Stapel

et al. 2021

PLoS ONE

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The present online study surveyed drivers of SAE Level 2 partially automated cars on automation use and attitudes towards automation. Respondents reported high levels of trust in their partially automated cars to maintain speed and distance to the car ahead (M = 4.41), and to feel safe most of the time (M = 4.22) on a scale from 1 to 5. Respondents indicated to always know when the car is in partially automated driving mode (M = 4.42), and to monitor the performance of their car most of the time (M = 4.34). A low rating was obtained for engaging in other activities while driving the partially automated car (M = 2.27). Partial automation did, however, increase reported engagement in secondary tasks that are already performed during manual driving (i.e., the proportion of respondents reporting to observe the landscape, use the phone for texting, navigation, music selection and calls, and eat during partially automated driving was higher in comparison to manual driving). Unsafe behaviour was rare with 1% of respondents indicating to rarely monitor the road, and another 1% to sleep during partially automated driving. Structural equation modeling revealed a strong, positive relationship between perceived safety and trust (β = 0.69, p = 0.001). Performance expectancy had the strongest effects on automation use, followed by driver engagement, trust, and non-driving related task engagement. Perceived safety interacted with automation use through trust. We recommend future research to evaluate the development of perceived safety and trust in time, and revisit the influence of driver engagement and non-driving related task engagement, which emerged as new constructs related to trust in partial automation.

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Section: Discussionmentioning

confidence: 99%

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Nordhoff

Stapel

et al. 2021

PLoS ONE

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“…The literature emphasizes that all three independent variables of the research are related to each other. For example, although perceived safety seems to describe the reduction of accidents [40] and therefore the increase in life safety [49] at first glance, potential accidents will have heavy costs that will force third parties such as maintenance and insurance [50]. Therefore, perceived security becomes indirectly related to the perception of advantage [9].…”

Section: Hypothesis 3 (H3)mentioning

confidence: 99%

Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles

Meidutė‐Kavaliauskienė

Yıldız

Çiğdem

et al. 2021

Energies

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Only recently, smart cities are taking shape, thanks to the rapid development of Internet of Things (IoT), cloud computing, and other similar technologies. Given the high demands placed on advanced technologies such as autonomous driving, cloud data services, and high-precision sensors, smart cities are creating an intelligent transportation environment conducive to the introduction of autonomous vehicles (AVs). In this context, the use of AVs in transportation is also considered a form of transportation innovation. As a result, AVs are considered more favorable to people interested in new technologies because they appear to be technologically superior. Their association with the most up-to-date technology can serve as a symbol for those who wish to demonstrate their interest in new technologies through their appearance. The positive image of technological innovation projected by AVs may influence their acceptance among technology enthusiasts to a significant degree. In this context, this study investigates the effects of perceived advantage, perceived risk, and perceived safety on the intention to use autonomous vehicles. For this purpose, data were collected from vehicle users living in Turkey by survey method. Secondly, factor analyses and regression analyses were performed with the data set obtained from 611 participants. As a result of the analyses, it has been determined that the perceived advantage and perceived security increase the intention to use autonomous vehicles. In contrast, the perceived risk reduces this intention to use. According to these results, recommendations were made to the companies about the level of acceptance of this technology by the users to assess their investments in autonomous vehicles better.

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“…erefore, the efficiency problem caused by the dimension of the take-over interaction interface is very important, especially now that the aging phenomenon is more and more serious. Research showed that drivers from different age groups had significant differences in perceived safety and intention to use of automated driving and the score increased with age [26].…”

Section: Cognitive and Behavioral Problems In The Process Of Take-mentioning

confidence: 99%

Dimensional Evolution of Intelligent Cars Human-Machine Interface considering Take-Over Performance and Drivers’ Perception on Urban Roads

2020

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The study analyzed the drivers’ take-over behaviors in intelligent cars when driving on urban roads and tried to find reasonable dimensions of the human-machine interface. Firstly, the main driving assistance functions in the process of take-over were analyzed based on the entropy theory, and the weight values of each function for the consumer’s purchase intention were calculated. Secondly, we explored the perceived comfortable dimensions of the interactive components under typical interaction modes. By means of experiments using a within-subjects design, the initial population of the evolutionary computation was obtained. The evolutionary mechanism of dimensions driven by users’ perception was constructed with a genetic algorithm. After debugging the parameters of the model, we verified the rationality of the model and evolved appropriate dimensions. Finally, the validity of the evolved dimensions was proved by a controlled experiment and paired-sample t-test. The results indicated that the completion time of most take-over tasks under the HMI with the evolved dimensions was significantly shorter, which ensured the HMI could be more conducive to the take-over quality and traffic efficiency.

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Perceived benefits and constraints in vehicle automation: Data to assess the relationship between driver's features and their attitudes towards autonomous vehicles

Cited by 15 publications

References 7 publications

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles

Dimensional Evolution of Intelligent Cars Human-Machine Interface considering Take-Over Performance and Drivers’ Perception on Urban Roads

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