Literature Database Entry

wilms2025plafogym

Leon Wilms, "PlaFoGym: Bridging Platoon Formation and Reinforcement Learning," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), April 2025. (Advisors: Julian Heinovski and Doğanalp Ergenç; Referees: Falko Dressler and Thomas Sikora)

Abstract

Recent advancements in Intelligent Transportation Systems (ITS) and autonomous driving have great potential for improving traffic flow, safety and fuel efficiency through vehicle platooning. However, developing and evaluating innovative reinforcement learning (RL)-based platooning algorithms remain challenging due to limitations in existing simulation environments. This thesis addresses the challenge of creating a flexible and efficient test and evaluation platform for RL-based dynamic platoon formation. The primary contribution was developing a versatile framework through direct modifications of the existing traffic simulator, PlaFoSim. Although external libraries like Gymnasium or Petting- Zoo were not integrated, their documentation and concepts were closely followed to create a multi-agent capable environment. This framework allows researchers to implement, test and optimize various RL approaches within a realistic, large-scale traffic simulation. A case study demonstrated the framework's capability to implement and compare both Deep Q-Network (DQN) and traditional Q-table approaches. Results confirm that the developed environment effectively supports multiple RL-controlled vehicles, facilitates dynamic platooning strategies and enables the comparative evaluation of different RL methods. The significance of this work lies in providing researchers with a powerful tool for quickly developing and evaluating RL-based platooning algorithms. Consequently, this contributes significantly to optimizing real-time platoon formations, improving traffic flow, reducing fuel consumption and enhancing highway safety under realistic conditions.

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@phdthesis{wilms2025plafogym,
    author = {Wilms, Leon},
    title = {{PlaFoGym: Bridging Platoon Formation and Reinforcement Learning}},
    advisor = {Heinovski, Julian and Ergen{\c{c}}, Do{\u{g}}analp},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {4},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Bachelor Thesis},
    year = {2025},
   }
   
   

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Last modified: 2026-04-15