City traffic signal optimization control method

Abstract

The invention discloses a city traffic signal optimization control method and belongs to the field of automatic control. The method comprises the following steps: 1, selecting a control scheme, and defining traffic states, an instantaneous crossing income and control motion; 2, a sampling phase employs induction control, and at each sampling time, sending images shot by traffic pick-up heads and phases to a servers; 3, the server extracting the traffic states from the images and calculating the instantaneous crossing income; 4, the server calculating the probability that each discrete traffic state occurs and the crossing income, obtaining an optimal control policy by maximizing an average crossing income and sending the policy to a crossing machine; 5, the crossing machine setting that a control policy of a traffic signal controller is the policy obtained in the fourth step, and setting that a decision period is equal to a sampling period; and 6, the traffic signal controller obtaining the discrete traffic states from the crossing machine, querying the control policy, and sending the control motion to the crossing machine for execution. According to the invention, the average performance index of crossing traffic in a quite long time period can be improved.

Description

technical field [0001] The invention relates to the technical field of automatic control. Background technique [0002] At present, the urban traffic signal control methods adopted in my country are timing control and induction control, but the timing control cannot switch control actions according to real-time traffic conditions, and the induction control strategy is not flexible enough, so the traffic signal control strategy still has great improvement room. [0003] Markov chains can be used for modeling and optimization of traffic signal control problems. If a short unit time step is set, the traffic state at the intersection at the current moment can be considered to be only related to the traffic state at the previous moment and the control action taken, so the transition of the traffic state can be regarded as a Markov chain. The intersection will be in a traffic state at every moment, and the income obtained in each traffic state is the reciprocal of the congestion ...

AI Technical Summary

Problems solved by technology

[0002] At present, the urban traffic signal control methods adopted in my country are timing control and induction control, but the timing control cannot switch control actions according to real-time traffic conditions, and the induction control strategy is not flexible enough, so the traffic signal control strategy still has great improvement room

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