A Data-driven framework for modelling and visualizing functions of software-based vehicles

  • Type:Bachelor Thesis
  • Date:01.09.2025 - 02.03.2026
  • Supervisor:

    Manuel Götz

    Prof. Sanja Lazarova-Molnar

  • Person in Charge:Philip Klusek
  • Add on:

    Ongoing

Description

Problem:

The embedded software in modern vehicles is becoming increasingly complex:

  • A growing number of interconnected software functions.
  • High coupling and dependencies between functions, signals, and hardware components.
  • Limited transparency for engineers and stakeholders, making it hard to understand, verify, and evolve the system.

Goal:

Develop a data-driven framework to model, visualize, and simulate vehicle software functions:

  • Extract and visualize  software functions based on component signals.
  • Enable simulation or “what-if” analysis to support design decisions, debugging, and impact analysis.

Required Skills and Knowledge:

  • Process Mining
  • Machine learning
  • Software development