Stefanie Carlowitz- Master of Science
- PhD Student at University of Leeds
Stefanie Carlowitz
- Master of Science
- PhD Student at University of Leeds
About
11
Publications
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Introduction
I'm a Human Factors researcher with industry experience and contributions to projects like Horizon 2020 interACT, HiDrive, and Rumba, funded by the German Federal Government. Currently, I'm pursuing a PhD at the University of Leeds in partnership with Robert Bosch GmbH. My focus is on the interaction between autonomous vehicles and users, particularly regarding driving styles and passenger comfort.
Current institution
Additional affiliations
June 2021 - present
Education
October 2016 - May 2020
October 2013 - October 2016
Publications
Publications (11)
The development of increasingly automated vehicles (AVs) is likely to lead to new challenges around how they will interact with other road users. In the future, it is envisaged that AVs, manually driven vehicles, and vulnerable road users such as cyclists and pedestrians will need to share the road environment and interact with one another. This pa...
The driving style of an automated vehicle (AV) needs to be comfortable to encourage the broad acceptance and use of this newly emerging transport mode. However, current research provides limited knowledge about what influences comfort, how this concept is described, and how it is measured. This knowledge is especially lacking when comfort is linked...
As automated vehicles advance and become more widespread, it is increasingly important to ensure optimal driving comfort for passengers. Recent research has focused on developing driving styles for automated vehicles that are perceived to be most comfortable. However, there is still little understanding of whether, and how, possible driving styles...
Understanding passenger comfort in automated vehicles (AVs) is critical for advancing highly automated driving systems. This test track study was conducted in 2023 with N = 41 participants who are accustomed to German driving norms. It examined how deceleration rates and environmental factors influence passenger perceptions in two scenarios: crossw...
Previous research has shown that the use of an eHMI can lead pedestrians to make earlier, and more, crossing decisions in front of an automated vehicle (AV). However, there has been little exploration of the impact of crossing infrastructure or AV approach direction on pedestrian behaviour. This CAVE-based pedestrian simulator study investigated th...
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 onlin...
The Motion Sickness Task Tolerance (MSTT) Scale measures the currently perceived symptoms of motion sickness. It includes criteria that relate discomfort categories to the ability to perform visual non-driving related tasks (NDRT).
This short questionnaire addresses motion-related aspects of ride comfort in automated vehicles. Is was developed and applied in several user studies in the publicly-funded project RUMBA (https://projekt-rumba.de/en/). A German version is also available for download.
Previous research has shown that the use of an eHMI can lead pedestrians to make earlier, and more, crossing decisions in front of an AV. However, there has been little exploration of the impact of crossing infrastructure or AV approach direction on pedestrian behaviour. This CAVE-based pedestrian simulator study investigated the individual, and co...
