Decision-Making in Autonomous Driving with Data- and Model-Based Methods Combination Ensuring Road Safety Aspects

In addition to transportation comfort and efficiency, autonomous vehicles provide a vital improvement in traffic safety by minimizing impact of human factor. In this project, the data- and model-based approaches will be combined to develop a safety-oriented decision-making algorithm for autonomous driving systems. The main assessment criteria for the vehicle performance actuation is traffic safety, which includes other road users and ego vehicle itself. The algorithm will be first evaluation in simulation with real driving data. Therefore, the method will be tested on an experimental vehicle.

People involved

  • Andrei Aksjonov (, postdoctoral researcher.
  • Kargar Eshagh (, doctoral candidate.
  • Ville Kyrki (, professor.

Project updates

Master Thesis on “Emergency Corridor Building by Autonomous Vehicles”

In this thesis, model predictive control-based emergency corridor building algorithms will be developed for autonomous vehicles in simulation. In this context, the thesis is expected to include varying simulated scenarios in terms of lane numbers, autonomous/human drivers amount, road types, traffic densities.