Adaptive Autonomous Traffic Control Based on Neural Reinforcement Learning

The goal of the thesis is to demonstrate that reinforcement learning methods can be employed for traffic control of single road crossings. In particular, we utilize an artificial neural network as traffic controller and constantly adapt its control behavior by temporal difference learning to changing traffic conditions.

Master Student


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