Description

Generative AI can rapidly produce complex driving scenarios, but these outputs are often difficult for users to understand, control, or evaluate. Scenario descriptions appear as text or parameter lists that lack narrative structure, visual clarity, and transparent causal reasoning. This creates barriers for researchers, designers, and other stakeholders who must interpret scenario logic, detect unrealistic elements, or communicate scenario details to others. Treating scenarios as stories, e.g. visual, temporal, and causal sequences, offers a more intuitive way to generate, refine, and understand AI-driven simulations.

In this project, students designed interactive interfaces that bridge natural-language generation, storyboard visualization, and explainable AI. They developed a prototype that integrates conversational scenario creation, storyboard-based scenario representation, and explanatory overlays or narratives. Students evaluated the impact of these interfaces on scenario comprehensibility, user control, trust, and error detection.

Student Project Details

Coming soon

Interested?

Contact me if you’d like me to teach this course to you or your audience.