The invention discloses a traffic signal lamp control method based on time distribution and reinforcement learning. The traffic signal lamp control method comprises the following steps: (1) configuring a simulated intersection environment and traffic flow data to a traffic simulator, and building an intelligent agent network; (2) an intelligent agent network generating the action of the next signal period according to the road condition state and transmitting the action to a traffic simulator to simulate one signal period; (3) storing the experience of the last signal period into a replay buffer; (4) sampling an experience from the replay buffer to train an intelligent agent network, judging whether the number of simulated steps reaches a preset value, and if not, returning to the step (2), otherwise, executing the next step; and (5) resetting the traffic simulator, testing the intelligent agent network, and performing traffic signal lamp control application after the test is finished.By adopting the traffic signal lamp control method of the invention, the traffic efficiency can be obviously improved, and the method can be more easily applied to actual roads.