How do people respond when automated vehicles become uncertain?
黑料福利网 researchers study how people perceive uncertainty around automated vehicles and drones, combining human factors, design, EEG, and eye tracking to support safer urban mobility.
Researchers Pavlo Bazilinskyy and Marieke Martens from the Department of Industrial Design are taking part in the research program Safety solutions for autonomous vehicle integration in urban mobility: efficient and reliable acting in an uncertain and unreliable world. The project is led by Anton Popov from Kyiv Polytechnic Institute and Sergiy Danylov from Anima, and is funded through the NWO Hop On Call for Researchers Based in Ukraine. This funding scheme enables Ukrainian researchers to join ongoing NWO projects in the Netherlands and supports knowledge exchange, mentoring, and stronger academic network.
Hidden signals
In traffic, people constantly read each other. A cyclist slows down after making eye contact with a driver. A pedestrian steps forward only after sensing that a vehicle will yield. A passenger relaxes when a car behaves in a way that feels understandable. Automated vehicles enter this world of split-second judgments and subtle social cues, especially in cities, where traffic is dense, movement is mixed, and behavior is not always easy to predict. That is exactly where uncertainty becomes important.
Inside doubt
Within this project, Bazilinskyy and Martens focus on how uncertainty can be observed and measured in people. Their contribution connects neurobiological methods such as EEG and eye tracking with behavioral research and human-centered design.
By linking these measurements to a broader framework on uncertainty in automated mobility, they aim to better understand what happens when people are confronted with incomplete, changing, or hard to interpret information. The goal is to identify when a traffic situation becomes mentally demanding or unclear, so that vehicles, interfaces, and mobility systems can be designed to respond in ways that people can understand and trust.
Street reality
This matters because the challenge of automated mobility is not only technical. Cities are working toward transport systems that are cleaner, more connected, and better suited to walking, cycling, and shared mobility, while urban roads remain places where vulnerable road users face significant risk. In that setting, a vehicle must do more than function correctly. It must also behave in ways that people can read. If a cyclist cannot tell whether a vehicle is about to stop, or if a passenger does not understand why an automated system suddenly slows down, uncertainty can quickly turn into hesitation, discomfort, or unsafe decisions. Understanding those moments is essential for making automated mobility work in everyday life.
Human first
The 黑料福利网 researchers bring expertise that fits this challenge closely. Martens studies automated vehicles and human interaction, with a strong focus on safety, usability, trust, and societal acceptance. Bazilinskyy examines AI-driven interaction between automated vehicles, people inside those vehicles, and other road users, including pedestrians and cyclists. Together, their work helps translate technical performance into something more fundamental: mobility systems that align with human expectations and the realities of public space.
Shared work
The collaboration with Popov and Danylov adds expertise in brain activity, signal analysis, visual attention, and eye movement research. This creates a joint approach in which measurement, interpretation, and design reinforce each other. The project also reflects the broader purpose of the NWO call, which is to support Ukrainian researchers in expanding their professional networks within Dutch academia. The team also thanks Sander Boht茅 from Centrum Wiskunde & Informatica for his help with the administrative side of the application.
What next
As automated vehicles move closer to real urban use, the key question is no longer only whether a system can act, but whether people around it can understand what it is doing. Research on uncertainty helps address that question at the level where mobility becomes truly social: on streets, at crossings, and in those brief moments when people need to decide whether a system feels safe enough to trust.