Presenting a New Model with a Compilation Structure to Timely Estimate Urban Traffic Situation

A new type of hybrid structure model is presented by meeting the requirements for combining traffic data to estimate the traffic situation in urban areas. This model is a combination of both spatial and temporary combinations. We first use the averaging operator for spatial composition, and then we propose a temporary correlation algorithm based on data compression based on the linear regression algorithm. The extension of the simulation results indicates the effectiveness and accuracy of the temporary correlation algorithm based on data compression as well as the temporary correlation superiority based on data compression relative to linear cross-sectional regression in terms of overall performance.