Factors that influence the acceptance of future shared automated vehicles – A focus group study with United Kingdom drivers

Dichabeng, Patrick; Merat, Natasha; Markkula, Gustav

doi:10.1016/j.trf.2021.08.009

Cited by 26 publications

(11 citation statements)

References 50 publications

(71 reference statements)

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“…User comfort has been considered as one vital factor affecting the public's acceptance of automated vehicles (AVs) (Dichabeng et al, 2021;Nordhoff et al, 2021;Siebert et al, 2013). Comfort is generally described as a subjective and personal experience, which is affected by physical, physiological, and psychological factors, in the users' interaction with AVs (De Looze et al, 2003;Hartwich et al, 2018;Peng et al, submitted).…”

Section: Introductionmentioning

confidence: 99%

Exploring user comfort in automated driving: A qualitative study with younger and older users using the Wizard-Of-Oz method

Peng,

Ozturk,

Nordhoff

et al. 2024

Preprint

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As the introduction of automated vehicles (AVs) into road traffic accelerates, establishing user acceptance is increasingly crucial. User comfort, largely influenced by the AVs’ driving styles, is one of the essential factors influencing acceptance. This video submission provides a methodological overview of a qualitative interview study, which used a Wizard-of-Oz method to investigate participants’ comfort levels during automated driving on real roads. By understanding the specific comfort experiences of both older and younger users, we can inform the design process for AVs, thereby enhancing user experience and facilitating broader acceptance of technology across a more diverse and inclusive demographic spectrum.

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Section: Introductionmentioning

confidence: 99%

Exploring user comfort in automated driving: A qualitative study with younger and older users using the Wizard-Of-Oz method

Peng,

Ozturk,

Nordhoff

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Comfort, as a positive user experience of automated driving, is essential for the broad acceptance of Automated Vehicles (AVs), (Dichabeng et al, 2021;Nordhoff, Malmsten, et al, 2021;Paddeu et al, 2020;Siebert et al, 2013). When being driven by a higher-level AV (SAE Level 4+, SAE International, 2021), automated driving styles, such as the vehicle's kinematic behaviour, the distance it keeps with other, roadbased, objects, and how it negotiates different road geometries, play an important role in user comfort (Beggiato et al, 2020;Bellem et al, 2016;Diels & Bos, 2015;Peng et al, 2022).…”

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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“…A range of terms have been used to describe comfort, including: "a subjective, pleasant state of relaxation given by confidence and an apparently safe vehicle operation" (Hartwich et al, 2018). It is argued that ensuring user comfort is important for enhancing the public acceptance and uptake of AVs (Dichabeng et al, 2021;Nordhoff, Malmsten, et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

User comfort and naturalness of automated driving: The effect of vehicle kinematics and proxemics on subjective response

Peng,

Wei,

Solernou

et al. 2023

Preprint

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Higher-level Automated Vehicles (AVs, SAE Level 4+) need to provide a comfortable user experience to enhance public acceptance. AV driving styles, characterised by vehicle kinematics and proxemics, affect user comfort, with “human-like” driving styles expected to provide natural feelings to further improve user comfort. This study investigated how the kinematic and proxemic characteristics of an AV’s driving style affect user comfort and naturalness of a ride. The similarities in automated and users’ own manual driving style, and how these similarities affect evaluations, was also investigated. Using a motion-based driving simulator, participants experienced three Level 4 automated driving styles (Defensive, Aggressive, and Machine-Learning based), and a manual drive. Participants provided ratings (separately) for comfort and naturalness of each automated controller, as it negotiated twenty-four UK road sections, with varying geometric and roadside features. Linear mixed-effects models were used to examine the effect of kinematics and proxemics of the AV’s driving style, on subjective evaluation of comfort and naturalness of the ride, and how similarities between users’ own driving style and that of the AV affected riders’ evaluation. Results showed that the AV controllers’ lateral and rotational kinematics significantly influenced both comfort and naturalness, while longitudinal jerk only affected comfort. The Euclidean distance in a range of kinematics, characterising similarities between manual and automated driving styles, had varied effects on subjective evaluations. This research facilitates understanding how control features of AVs affect user experience, which will contribute to designing more user-centred controllers, leading to better acceptance of higher-level AVs.

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Factors that influence the acceptance of future shared automated vehicles – A focus group study with United Kingdom drivers

Cited by 26 publications

References 50 publications

Exploring user comfort in automated driving: A qualitative study with younger and older users using the Wizard-Of-Oz method

Exploring user comfort in automated driving: A qualitative study with younger and older users using the Wizard-Of-Oz method

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

User comfort and naturalness of automated driving: The effect of vehicle kinematics and proxemics on subjective response

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