The invention relates to the technical field of
traffic planning, and discloses an urban
traffic optimization and
planning method and
system based on
artificial intelligence data processing, and the method comprises the steps: collecting a
time sequence perception data flow of a target intersection, and carrying out the extraction of an occupancy state
tensor based on a time window, and obtaining the occupancy state
tensor of the target intersection in the time window; using the occupancy mode analysis model to output occupancy mode probability distribution of the target intersection in the time window; and outputting the lane
traffic capacity of the target intersection by using a lane
traffic capacity calculation function which is corrected by introducing dynamic factors of a temporary parking type occupation
reduction factor and a queuing type occupation
delay factor, and dynamically adjusting a short-time traffic control strategy of the target intersection. According to the invention, through
time sequence perception and occupation mode analysis, the temporary parking and queuing occupation
modes are distinguished, and the
traffic capacity of the lane is dynamically quantified and corrected, so that the short-time traffic control strategy is adjusted in real time, and refined and
adaptive traffic control and optimization under complex disturbance conditions in a city are realized.