I Drive - You Trust: Explaining Driving Behavior Of Autonomous Cars

ABSTRACT

Driving in autonomous cars requires trust, especially in case of unexpected driving behavior of the vehicle. This work evaluates mental models that experts and non-expert users have of autonomous driving to provide an explanation of the vehicle's past driving behavior. We identified a target mental model that enhances the user's mental model by adding key components from the mental model experts have. To construct this target mental model and to evaluate a prototype of an explanation visualization we conducted interviews (N=8) and a user study (N=16). The explanation consists of abstract visualizations of different elements, representing the autonomous system's components. We explore the relevance of the explanation's individual elements and their influence on the user's situation awareness. The results show that displaying the detected objects and their predicted motion was most important to understand a situation. After seeing the explanation, the user's level of situation awareness increased significantly.

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Index Terms

• Computing methodologies

  • Artificial intelligence

    • Distributed artificial intelligence

      • Mobile agents

• Human-centered computing

  • Human computer interaction (HCI)

    • HCI design and evaluation methods

  • Visualization

    • Visualization design and evaluation methods