Are you passionate about enhancing human-machine interaction in automated vehicles to ensure safety, trust, and usability? Join our PhD project to develop and validate an HMI assessment framework for automated mobility systems in collaboration with leading industry and research partners.
Information More than 1,350,000 people die in traffic every year. Automated vehicles (AVs) are expected to improve road safety and save lives and injuries. As a result, the pace of development of AVs is accelerating. However, despite the fact that technology is enhancing, there are still a lot of human factors that play a role. How can we ensure that these systems are safe to use, that users trust them, that there is no uncertainty, and that people are not confused?
Human Machine Interaction (HMI) is a potential solution for safe and comfortable interactions. However, a challenge is that
prototypes for
Human-Machine Interaction (HMI) between AVs, the people inside and other road users lack systematic assessment under diverse conditions. We are seeking a highly motivated PhD candidate to work on the development of a validated HMI assessment framework for Connected, Cooperative, and Automated Mobility (CCAM) systems. The project is part of a larger European collaboration CERTAIN with a focus on ensuring Safe, Trustworthy, Accepted, and Comfortable (STAC) human-machine interaction within automated transportation systems.
The aim of this PhD project is to contribute to the development of human-centred design specifications, experimental studies, and validation methods to assess HMI performance across diverse road users (including users with special needs) and automation levels. The results of the project will be used by academia, automotive manufacturers and governments to coordinate the actions of future traffic participants. There will be close interaction with the industry and such companies as IDIADA, DAF, Jaguar Land Rover, and Toyota, as well as universities and knowledge institutes, such as TNO, the University of Leeds, Karlsruher Institut für Technologie (KIT), and RWTH Aachen. There will be opportunities to conduct joint experiments with other PhD candidates. The candidate will work very closely with Dr. Pavlo Bazilinskyy, who has a background in Computer Science and Human Factors and Prof. Marieke Martens with a background in Psychology and Human Factors. The project presents a unique chance to conduct empirical design-driven research.
Research objectives - Develop an HMI assessment component with pass/fail criteria based on STAC principles.
- Investigate human-centric approaches, focusing on various road users (drivers, vulnerable road users, passengers, bystanders, and active interactors).
- Define key assessment variables (e.g., mode confusion, automation surprise, situational awareness, learnability) and validate them through experimental studies.
- Conduct design-driven empirical research using advanced testing facilities, including driving simulators, virtual reality setups, and on-road vehicles.
- Integrate inclusivity principles, considering age, cultural background, disabilities, and experience levels in HMI design.
- Contribute to the development of tools and methodologies that guide HMI developers in ensuring safe and effective interaction with CCAM systems.