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Abstract

Disclosed is a training method for the optimization of a traffic signal. The method includes segmenting a large-scale road network into intersection groups each including a plurality of intersections, training a reinforcement learning model by allocating a training agent to each intersection group, performing traffic signal control through the inference of an optimal signal based on the trained reinforcement learning model, evaluating whether the results of the execution of the traffic signal control satisfy a preset goal of learning for traffic signal optimization, and repeatedly training the reinforcement learning model based on the results of the evaluation.

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