| CPC G08G 1/0125 (2013.01) [G06N 3/08 (2013.01); G08G 1/08 (2013.01); G08G 1/083 (2013.01)] | 12 Claims |

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1. A method of controlling traffic signals of a plurality of traffic lights in a sub-area by using a neural network model, the method comprising:
configuring state information of the sub-area by using downstream information for a current cycle time, wherein the downstream information is configured for each of a plurality of intersections included in the sub-area;
obtaining action information including green times and offsets for the sub-area by inputting the state information to a trained neural network model;
determining whether an offset is set to within a preset absolute value range; and
generating a coordinated signal value for applying the action information to the plurality of traffic lights in the sub-area during a transition process configured with a plurality of subsequent cycle times, in response to determining that the offset is set to a value out of the preset absolute value range,
wherein the neural network model is trained using a reinforcement learning algorithm which is based on the action information, the state information, and reward information, and
wherein the reward information for each intersection is defined as an arithmetic mean of stop rate obtained at downstream of each of a plurality of links of intersection, each of the stop rates is a value obtained by diving a processed queue length by a processed traffic volume of the downstream of one of the plurality of links of the intersection.
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