An expressway traffic state estimation method based on parallel computing

Abstract

The invention discloses a novel expressway traffic state estimation method based on parallel computing. The method comprises a parallel computing framework and four sub-modules which are a data center module, a data unification processing module, an online traffic flow model parameter correction module and an improved Kalman filter optimization module; the data center module is used for collecting and storing historical and real-time data of a traffic detector; the data unification processing module unifies the different types of traffic data into the same format; the online traffic flow model parameter correction module is used for parameter correction of the traffic flow model; and the Kalman filter optimization module further optimizes corrected model results. The parallel computing framework brought forward by the invention is used for automatic processing of the execution sequence of the above modules. Compared with existing traffic state estimation methods based on Kalman filtering, the method of the invention has higher execution efficiency and precision, can support expressway fixed detector data of different types and has a very good application and popularization prospect.

Description

technical field [0001] The invention relates to the field of expressway traffic state estimation and identification, in particular to an expressway traffic state estimation method based on parallel computing and improved Kalman filter algorithm. Aiming at the problem of insufficient layout of fixed detectors for expressway traffic status, this method estimates the real-time traffic status of various locations on designated sections of expressway based on real-time and historical traffic detector data. Background technique [0002] In recent years, with the continuous growth of my country's economy and the rapid increase of motor vehicle ownership and utilization rate, the existing expressway operation and management methods can no longer fully meet the real-time management needs of expressways. Therefore, the implementation of active management and control of expressways It is the development trend of expressway management in the future. The expressway active management and ...

AI Technical Summary

Problems solved by technology

This method has a large amount of calculation and will generate approximate estimation errors, which will affect the accuracy and efficiency of the estimation method to a certain extent.

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