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Kai Holländer, Gesa Wiegand, Katherina Rupp, Heinrich Hussmann
Strong Together: A Collaborative Driver Interface to Overcome Limitations of Automated Vehicle Systems
Proceedings of the 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 2020, Virtual Event, DC, USA; (bib)

Autonomous vehicles still face situations in which system boundaries are met or in which the driving behavior is unclear. If pedestrianswait at crosswalks without the intention of crossing, autonomous vehicles might wait unnecessarily, whereas a human driver wouldassess the situation within split seconds. We investigate how vehicles and drivers can collaborate to handle critical situations together,without one entity having full control. We compare autonomous driving, Take-Over Requests (TOR) and two collaborative drivingconditions by evaluating usability, user experience, workload, psychological needs, performance criteria and interview statements.We focus on increasing joy in driving and aim to give drivers competence and autonomy even when driving autonomously. Thecollaborative conditions significantly increase autonomy and competence compared to autonomous driving. Joy is highly representedin the qualitative data during TOR and collaboration. Collaboration proves to be a good alternative for situations in which easy andquick decisions are called for.