AI-based tutor for driver assistance systems : Development and evaluation of an LLM-supported prototype

AI-based tutor for driver assistance systems : Development and evaluation of an LLM-supported prototype

16.10., Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten

Ever wondered how an AI tutor could transform the way drivers understand assistance systems? Join us in designing and developing a dialogic LLM-based tutor – from concept and integration to prototypical implementation and driving simulator evaluation.

Driver assistance systems (e.g. ACC, LKA) are complex and are often misunderstood by users. Previous work has developed static and adaptable tutorials that explain these systems and use quiz questions to test knowledge. The next step is to develop an AI-based, dialogic tutor and evaluate it in a driving simulator : An LLM-supported application that makes a personalized learning offer when entering the vehicle or in case of queries and suggests existing tutorial chapters appropriately.

Aims of the work :

• Conception and prototypical implementation of a moderated bot dialog that reacts to prior knowledge, experience and user input
• Utilization and integration of existing tutorial and quiz content (structured preparation)
• Development of a technology pipeline for the connection of an LLM (e.g. retrieval augmented generation, rule-based filters, logging)
• Evaluation of the prototype in the form of functional tests and possibly initial user studies (e.g. usability, comprehensibility, acceptance)

Possible subtasks :

Prerequisites :