In the context of future mobility a testbed for development applications is necessary. Different problems such as intermodal vehicle routing, parking or speed recommendations systems have traffic as a common factor. A gym-like environment based on a popular traffic macro-simulation should be extended so that experiments with different methods and problems can be conducted. For the method reinforcement learning or other optimization approaches are possible.
The focus of the proposed thesis can lay in one or multiple topics such as:
RL Intro Book: Sutton, Richard S., and Andrew G. Barto. Reinforcement learning: An introduction. MIT press, 2018.
RL Intro Lecture: https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ
Traffic Marco-Simulation: https://www.eclipse.org/sumo/
Autonomous Driving Simulation: https://carla.org/
Traffic Forecasting Challenge: https://www.iarai.ac.at/traffic4cast/
Vehicle Routing Challenge: https://euro-neurips-vrp-2022.challenges.ortec.com/
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