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

Nordhoff, Sina; Stapel, Jork; He, Xiaolin; Gentner, Alexandre; Happee, Riender

doi:10.1371/journal.pone.0260953

Cited by 20 publications

(9 citation statements)

References 75 publications

(73 reference statements)

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“…They reported being able to monitor the vehicle surroundings more, which they considered a key advantage of using Autopilot compared to manual driving. This reflects studies showing that respondents identified observing the scenery or landscape as one of their favorite activities during automated driving (Pfleging et al, 2016;Nordhoff et al, 2021). Furthermore, this corresponds with studies reporting increased situational awareness when automated driving was engaged (De Winter et al, 2014;Endsley, 2017).…”

Section: Situational Awarenesssupporting

confidence: 67%

“…Other unintended reported behavioral effects were mode confusion (Endsley, 2017;Banks et al, 2018;Wilson et al, 2020), testing the limits of the ODD (Banks et al, 2018), using Autopilot in ODDs for which it was not intended (Kim et al, 2021), driver distraction, drowsiness, and the difficulty of handling unanticipated automation failures (Endsley, 2017), an inadequate mental model of the capabilities of the automation, and skill degradation (i.e., loss of manual control skills due to automation) (Saffarian et al, 2012). Other studies provided evidence for little differences between the self-reported secondary task engagement during manual and partially automated driving (Shutko et al, 2018;Nordhoff et al, 2021). Evidence as to whether secondary task engagement deteriorates drivers' take over performance is inconclusive (Lin et al, 2019).…”

mentioning

confidence: 99%

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(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta

et al. 2023

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Tesla's Full Self-Driving Beta (FSD) program introduces technology that extends the operational design domain of standard Autopilot from highways to urban roads. This research conducted 103 in-depth semi-structured interviews with users of Tesla's FSD Beta and standard Autopilot to evaluate the impact on user behavior and perception. It was found that drivers became complacent over time with Autopilot engaged, failing to monitor the system, and engaging in safety-critical behaviors, such as hands-free driving, enabled by weights placed on the steering wheel, mind wandering, or sleeping behind the wheel. Drivers' movement of eyes, hands, and feet became more relaxed with experience with Autopilot engaged. FSD Beta required constant supervision as unfinished technology, which increased driver stress and mental and physical workload as drivers had to be constantly prepared for unsafe system behavior (doing the wrong thing at the worst time). The hands-on wheel check was not considered as being necessarily effective in driver monitoring and guaranteeing safe use. Drivers adapt to automation over time, engaging in potentially dangerous behaviors. Some behavior seems to be a knowing violation of intended use (e.g., weighting the steering wheel), and other behavior reflects a misunderstanding or lack of experience (e.g., using Autopilot on roads not designed for). As unfinished Beta technology, FSD Beta can introduce new forms of stress and can be inherently unsafe. We recommend future research to investigate to what extent these behavioral changes affect accident risk and can be alleviated through driver state monitoring and assistance.

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Section: Situational Awarenesssupporting

confidence: 67%

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confidence: 99%

(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta

et al. 2023

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“…Scientific evidence supporting the role of (perceived) safety as direct predictor of acceptance and use of automated cars is inconclusive. In our previous study, perceived safety did not influence actual use of partial automation ( Nordhoff et al, 2021 ), while in other studies it did influence the intention to use automated cars ( Montoro et al, 2019 ; Detjen et al, 2020 ; Koul and Eydgahi, 2020 ).…”

Section: Introductionmentioning

confidence: 59%

Do driver’s characteristics, system performance, perceived safety, and trust influence how drivers use partial automation? A structural equation modelling analysis

Nordhoff

Stapel

et al. 2023

Front. Psychol.

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The present study surveyed actual extensive users of SAE Level 2 partially automated cars to investigate how driver’s characteristics (i.e., socio-demographics, driving experience, personality), system performance, perceived safety, and trust in partial automation influence use of partial automation. 81% of respondents stated that they use their automated car with speed (ACC) and steering assist (LKA) at least 1–2 times a week, and 84 and 92% activate LKA and ACC at least occasionally. Respondents positively rated the performance of Adaptive Cruise Control (ACC) and Lane Keeping Assistance (LKA). ACC was rated higher than LKA and detection of lead vehicles and lane markings was rated higher than smooth control for ACC and LKA, respectively. Respondents reported to primarily disengage (i.e., turn off) partial automation due to a lack of trust in the system and when driving is fun. They rarely disengaged the system when they noticed they become bored or sleepy. Structural equation modelling revealed that trust had a positive effect on driver’s propensity for secondary task engagement during partially automated driving, while the effect of perceived safety was not significant. Regarding driver’s characteristics, we did not find a significant effect of age on perceived safety and trust in partial automation. Neuroticism negatively correlated with perceived safety and trust, while extraversion did not impact perceived safety and trust. The remaining three personality dimensions ‘openness’, ‘conscientiousness’, and ‘agreeableness’ did not form valid and reliable scales in the confirmatory factor analysis, and could thus not be subjected to the structural equation modelling analysis. Future research should re-assess the suitability of the short 10-item scale as measure of the Big-Five personality traits, and investigate the impact on perceived safety, trust, use and use of automation.

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“…Overall, similar (positive) affects are used to describe these concepts and also comfort, when discussing the effect of automated driving style on user experience. Hartwich et al (2018) suggest that feeling safe, relaxed and certain can all lead to a positive experience of automated driving, which will ultimately enhance acceptance of these new forms of mobility (see also acceptance models reported by Madigan et al, 2016;Motamedi et al, 2020;Nordhoff, Stapel, et al, 2021). Therefore, the original conceptual framework included these mostly investigated concepts (i.e., perceived safety, trust, and naturalness), in order to clarify the relationship between these, and establish if and how each contributes to comfort, based on different automated driving styles.…”

Section: The Link Between Driving Styles and Comfortmentioning

confidence: 99%

“…Here, a wide range of factors are considered relevant to user comfort when driven by AVs. For example, perceived safety and trust are thought to affect comfort (Diels et al, 2017;Hartwich et al, 2021;Nordhoff, Stapel, et al, 2021), with research showing that when users do not trust AVs, they will refrain from using automation, and not use the driving time for other (non-driving related) activities. Another concern is the prevalence of motion sickness.…”

Section: Introductionmentioning

confidence: 99%

Conceptualising user comfort in automated driving: Findings from an expert group workshop

Peng¹,

Horn²,

Madigan³

et al. 2023

Preprint

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Automated driving needs to be comfortable to encourage the broad acceptance and usage of automated vehicles (AVs). However, current research provides limited knowledge on the descriptions and influencing factors of user comfort in automated driving, especially from the perspective of an AV’s driving styles. This paper presents results from an online workshop, in which nine experts with hands-on experience of AVs, and a long track record of research in this context, brainstormed and discussed a series of topics related to user comfort in automated driving. Results showed that a wide range of terms were used to describe user comfort and discomfort, when the attendees considered being driven by either currently available transport modes (e.g., taxi/bus/train) or higher-level AVs (with neither requiring control of the vehicle by the user). All of the terms used for existing vehicles were found to apply to AVs, but additional aspects of comfort/discomfort were revealed for AVs. This suggests that what makes existing transport modes comfortable is not the same as that for higher-level AVs. Regarding the relationship between comfort and discomfort in automated driving, seven and ten categories of terms were identified for comfort and discomfort, respectively, with both the number and the nature of these categories differing across the two states. This suggests that, to ensure user comfort in automated driving, additional factors that affect comfort must be considered, rather than solely mitigating discomfort. By integrating these multiple aspects that affect user comfort, knowledge from the workshop was used to develop a conceptual framework, to explain how AV driving styles, as well as other, non-driving-related factors, affect user comfort, from both a physical and psychological perspective. This work provides an overview of experts’ insights on the factors that affect comfort in automated driving, and will facilitate a more comprehensive definition, and more accurate measurement, of user comfort, facilitating the design of more comfortable and acceptable automated driving for future vehicles.

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

Cited by 20 publications

References 75 publications

(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta

(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta

Do driver’s characteristics, system performance, perceived safety, and trust influence how drivers use partial automation? A structural equation modelling analysis

Conceptualising user comfort in automated driving: Findings from an expert group workshop

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