Road segment traffic state distinguishing method based on multi-source data

Abstract

The invention discloses a road segment traffic state distinguishing method based on multi-source data. The road segment traffic state distinguishing method comprises the following steps: using traffic parameter values acquired by a fixed detector and a floating car as a data source; selecting historical traffic parameter values and historical traffic state grades in multiple time periods to build a sample database, and calculating an average velocity adjustment parameter of the fixed detector in the smooth traffic period of the road segment, and the road segment historical space average velocity of each period; training to obtain a support vector machine model; respectively adopting a direct judgment method, a K-nearest neighbor nonparametric regression method and a data state correlating analysis method to obtain the road segment space average velocity in the current period; adopting the direct judgment method and the support vector machine model to distinguish the road segment traffic state grade in the current period. According to the road segment traffic state discriminating method disclosed by the invention, the fixed detector and the floating car are used as the data source, and sufficient digging and complementary using are performed on the premise of completely considering the characteristics and the applicability of the data, so that the road segment traffic state discrimination precision is further improved.

Description

technical field [0001] The invention relates to a traffic state discrimination method based on two data sources of fixed detectors and floating vehicles, in particular to a traffic state discrimination method based on multi-source data, which belongs to the technical field of real-time road traffic information processing and application. Background technique [0002] Rapid and accurate identification of road traffic status is helpful to formulate reasonable road network traffic control and guidance strategies; at present, various detectors are mainly used to collect traffic flow parameters, and on this basis to calculate road traffic status. [0003] Invention patent CN103021176A proposes a method for judging urban road traffic status based on section detectors, which uses traffic flow parameters of a certain detected section on the road section to calculate the congestion index, and compares the traffic status with the threshold value; the invention only uses fixed detection...

AI Technical Summary

Problems solved by technology

[0003] Invention patent CN103021176A proposes a method for judging urban road traffic status based on section detectors, which uses traffic flow parameters of a certain detected section on the road section to calculate the congestion index, and compares the traffic status with the threshold value; the invention only uses fixed detection However, in general, the number of fixed detectors deployed on the road section is limited (usually 1-2 groups), and the calculated results can only reflect the traffic status within the limited range of the road section, and it is difficult to accurately judge Traffic status of the whole road segment

[0004] Invention patents CN102087789A and CN103942953A propose a method for judging traffic conditions based on floating car data; only floating car data is used in this invention, because the distribution of floating cars on the road network is uneven, when the number of samples of floating cars on a road section is low or When the satellite signal is blocked by infrastructure such as tall buildings and tunnels on the roadside, it is difficult to judge the traffic status of the road section through the data of the floating car

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