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Marjan P. Hagenzieker

dblp:74/7916 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0002-5884-4877ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 77% Usability and user experience research · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
automated vehicles
1.012026
How do older passengers of automated vehicles experience comfort on road? An interview study · Int. J. Hum. Comput. Stud. 2026
Usability and user experience research › user perception
user comfort
0.312026
How do older passengers of automated vehicles experience comfort on road? An interview study · Int. J. Hum. Comput. Stud. 2026

Methods — techniques the papers use, named apart from their topics

thematic analysis · 1.0semi-structured interviews · 1.0
YearPublicationVenuePosition
2026 How do older passengers of automated vehicles experience comfort on road? An interview study
abstract
Understanding older users’ comfort needs can inform the inclusive design of automated vehicles (AVs). Real-world experience with automated driving is crucial to elicit meaningful insights for older adults, who are expected to benefit from AVs in terms of enhanced mobility and autonomy. In this study, semi-structured interviews were conducted with 27 participants (aged over 60) who experienced a so-called automated ride, operated by a Wizard-of-Oz driver, in Delft, Netherlands. Following the ride, participants were interviewed about their comfort during the ride. Using thematic analysis, we identified three overarching factors associated with user comfort: (1) vehicle factors (including driving styles, AV capabilities, effect of AV exposure , and physical aspects ), (2) environment factors (including effect of external driving environment ), and (3) human factors (including affective experience, attitudes to AV/technology, engagement in non-driving related tasks [NDRTs] , and communication with the AV ). Our findings contribute to understanding comfort in automated driving, by offering a comprehensive list of factors associated with comfort, identifying affective reflections of psychological comfort, and discovering the co-existence of psychological comfort and physical discomfort. The study provides implications for designing comfortable AVs, such as the need for smooth, cautious, and anticipatory driving styles, and flexible and early reactions to unexpected events.
Ibrahim Öztürk, Ruth Madigan, Sina Nordhoff, Sascha Hoogendoorn-Lanser, Marjan P. Hagenzieker, Natasha Merat
Int. J. Hum. Comput. Stud.6
2025 How Testing Impacts Willingness to Use and Share Autonomous Shuttles with Strangers: The Mediating Effects of Trust and Optimism
abstract
This study investigates acceptance of shared autonomous shuttles (SASs) in a suburban area.A model where contextual variables were mediated through trust in SASs and technology optimism was tested.We examined intentions to use SASs without a steward and the significance of social distancing.Data were collected at the start and end of a 2020-2021 pilot involving 922 and 608 participants respectively, operating at SAE level 3. Findings indicate that trust and technological optimism significantly influence the willingness to use SASs, though contextual variables show minimal impact.Older adults and women displayed lower trust and optimism, reducing their usage intentions.These two groups also feel that it is more important to be able to keep social distance while riding SASs.The study suggests that future pilots should avoid negative impacts from using immature technology and address the social needs of specific groups.
Ole Aasvik, Marjan P. Hagenzieker, Pål Ulleberg, Torkel Bjørnskau
Int. J. Hum. Comput. Interact.2