News

AdaptIVe investigated modes of cooperation between drivers and automated applications in different driving scenarios. A large part of the Human Factors research has been conducted in experimental settings in different lab environments.

In total 18 experiments have been finalised including 12 simulator studies – see also previously published article on simulator studies - , 3 test track studies, international surveys, and benchmarking of vehicle automation systems on the market. More than 300 car drivers and professional truck drivers have participated in simulator and test-track studies, and 2700 people responded to the survey. Studies were conducted by AdaptIVe partners University of Leeds, Volvo Car Corporation, Volvo Technology, German Aerospace Center (DLR), Würzburg Institute for Traffic Sciences and Ford.

The studies have investigated several types of driving situations, for example different weather conditions, traffic and road conditions on highway roads, as well as parking scenarios, in order to explore research areas and questions identified through reviewing the state of the art.

Topics include:

• Driver-in/out of-the-loop: For example, what affects the driver’s situation awareness and mode awareness during interactions with automated vehicles?
  
  
• Driver state: How can driver state (e.g. drowsiness, boredom, fatigue) be detected and taken into account in the design of automated functions?
  
  
• Distraction and secondary tasks: Can drivers re-take control of the vehicle effectively when engaged with non-driving activities during automated driving?
  
  
• Transitions: What is required for safe and smooth transitions from manual control to automation, and from automation back to manual control?
  
  
• Arbitration and shared control: Can the driver and the automated vehicle execute parts of an action in parallel?
  
  
• HMI: How can the HMI be designed to facilitate the transitions and to enhance the situation awareness and mode awareness?

The project utilises the research results in different ways. The findings from the experiments contribute essentially to the Human Factors recommendations for automated vehicles, providing important input to the HMI solutions developed for the AdaptIVe demo-vehicles. See the figure below, visualising the iterative process used in the project.