All Stories

  1. Is Users’ Trust during Automated Driving Different When Using an Ambient Light HMI, Compared to an Auditory HMI?
  2. Willingness to Pay for Conditional Automated Driving among Segments of Potential Buyers in Europe
  3. Usability testing of three visual HMIs for assisted driving: How design impacts driver distraction and mental models
  4. Physiological indicators of driver workload during car-following scenarios and takeovers in highly automated driving
  5. Profiling the Enthusiastic, Neutral, and Sceptical Users of Conditionally Automated Cars in 17 Countries: A Questionnaire Study
  6. Drivers’ Intentions to Use Different Functionalities of Conditionally Automated Cars: A Survey Study of 18,631 Drivers from 17 Countries
  7. Don't Worry, I'm in Control! Is Users’ Trust in Automated Driving Different When Using a Continuous Ambient Light HMI Compared to an Auditory HMI?
  8. Are multimodal travellers going to abandon sustainable travel for L3 automated vehicles?
  9. User-centred design evaluation of symbols for adaptive cruise control (ACC) and lane-keeping assistance (LKA)
  10. Do drivers change their manual car-following behaviour after automated car-following?
  11. The effect of motor control requirements on drivers’ eye-gaze pattern during automated driving
  12. Predicting takeover response to silent automated vehicle failures
  13. Managing Big Data for Addressing Research Questions in a Collaborative Project on Automated Driving Impact Assessment
  14. Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries
  15. Measuring Drivers’ Physiological Response to Different Vehicle Controllers in Highly Automated Driving (HAD): Opportunities for Establishing Real-Time Values of Driver Discomfort
  16. Predicting takeover response to silent automated vehicle failures
  17. Applicability of risky decision-making theory to understand drivers' behaviour during transitions of control in vehicle automation
  18. Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles
  19. Understanding interactions between Automated Road Transport Systems and other road users: A video analysis
  20. Using Markov Chains to Understand the Sequence of Drivers' Gaze Transitions During Lane-Changes in Automated Driving
  21. Engaging in NDRTs affects drivers’ responses and glance patterns after silent automation failures
  22. Applying participatory design to symbols for SAE level 2 automated driving systems
  23. Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations
  24. The “Out-of-the-Loop” concept in automated driving: proposed definition, measures and implications
  25. What externally presented information do VRUs require when interacting with fully Automated Road Transport Systems in shared space?
  26. The effect of varying levels of vehicle automation on drivers’ lane changing behaviour
  27. Coming back into the loop: Drivers’ perceptual-motor performance in critical events after automated driving
  28. What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems
  29. Are you in the loop? Using gaze dispersion to understand driver visual attention during vehicle automation
  30. Were they in the loop during automated driving? Links between visual attention and crash potential
  31. Acceptance of Automated Road Transport Systems (ARTS): An Adaptation of the UTAUT Model
  32. Engaging with Highly Automated Driving: To be or Not to be in the Loop?