Signal control period automatic division method

Abstract

The invention relates to a signal control period automatic division method. First, historical traffic flow data acquisition is performed, then the acquired data are divided according to certain granularity, then the divided data are cleaned and averaged, then period division is performed on the processed data, period merging is performed after period division, and finally, an obtained result is uploaded to a corresponding signal machine. The invention provides the traffic signal control period automatic division method, which is high in efficiency and is more precise, saves both time and labor, improves traffic operation efficiency, and facilitates trips of people.

Description

technical field [0001] The invention relates to the field of traffic signal control, in particular to a method for automatically dividing signal control periods. Background technique [0002] At present, the signal control system has been upgraded from the traditional single-point control to the networked control system. Relevant brand signal machines represented by this have been widely used in major cities. Using the networked control system, multiple time periods can be set throughout the day to run multiple times. A plan to realize multi-period timing control. The specific principle is to divide a day into several time periods according to traffic information such as traffic flow, and use different signal optimization control schemes for different periods. The current period division technology mainly includes: traffic engineering technicians collect historical flow data, draw flow time curves, and manually divide traffic periods according to the characteristics of the c...

AI Technical Summary

Problems solved by technology

The current period division technology mainly includes: traffic engineering technicians collect historical flow data, draw flow time curves, and manually divide traffic periods according to the characteristics of the curves. In actual work, due to various reasons, most intersections are only divided into Three time periods or even one time period; the existing artificial time period division method has the following disadvantages: ① Difficult to process historical data, there are many flow historical data, and the actual processing is more complicated; ② It is difficult to find abnormal data, due to the characteristics of flow historical data, There are many invalid or even erroneous traffic data in the huge traffic data, it is difficult to find these abnormal data by manual processing; ③ It is difficult to fit the traffic characteristics, in the actual operation of the vehicle, the traffic characteristics of each day and every week are different In the process of manual processing of traffic data, it is difficult to fully consider these characteristics; ④ time period division is not accurate enough, the traditional time period division method has strong subjectivity, and it is easy to fail to fit the characteristics of real-time traffic changes Unreasonable division of time periods; ⑤ The traditional time division method is time-consuming and laborious, requiring a lot of time and manpower in actual operation, and the cost is high; The efficiency of traffic operation is relatively low, which can easily cause traffic congestion, which is not conducive to people's travel

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