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Fine division and identification method of urban traffic status based on multi-source trajectory data

A traffic state and urban traffic technology, applied in the traffic control system of road vehicles, traffic control system, data processing application, etc., can solve the problem that it is difficult to flexibly reflect the actual difference of road traffic conditions, so as to improve the credibility and expand the The effect of data volume

Active Publication Date: 2022-03-25
FUZHOU UNIV
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Problems solved by technology

These studies are mainly based on the whole road section or the fixed-length section as the research unit to identify the traffic state. The identification results depend on the division method of the road section or sub-section, and it is difficult to flexibly reflect the actual difference of road traffic conditions.

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  • Fine division and identification method of urban traffic status based on multi-source trajectory data
  • Fine division and identification method of urban traffic status based on multi-source trajectory data
  • Fine division and identification method of urban traffic status based on multi-source trajectory data

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specific Embodiment approach

[0053] Please refer to figure 1 , the present invention provides a method for finely dividing and identifying urban traffic states based on multi-source trajectory data. The specific implementation is as follows:

[0054] Step S1: collect data;

[0055] In this embodiment, taking Xiamen Island as the research area, the experimental data used includes two types: floating car trajectory data and road network data.

[0056] The track data of the floating car, including the track data of taxis in Xiamen and the track data of buses in Xiamen, come from the regular records of the vehicle-mounted GPS positioning device. Trajectory data mainly comprises the basic information such as vehicle serial number, time, position, speed, taxi passenger status, bus belonging line, and present embodiment has chosen on June 15th, 2015 (Monday) morning rush hour (7:00-9 :00) of bus and taxi trajectory data after preprocessing, the trajectory data set reaches 511,401, including 147,331 bus trajec...

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Abstract

The present invention relates to a kind of fine division and identification method of urban traffic state based on multi-source trajectory data, comprising the following steps: Step S1: collecting the speed value and the spatial position value of urban bus and taxi trajectory points, and normalizing them ; Step S2: using the normalized spatial position value and velocity value as an attribute to carry out spatio-temporal clustering to the track points of different road sections in different time periods, and carry out secondary processing to the clusters by splitting and merging the clusters, Obtain the segmentation point of finely divided traffic state of each road section; Step S3: adopt the strategy of feature level fusion to fuse the bus and taxi track point speed normalization value after division on the same road section, obtain the traffic state of each road section finely divided Step S4: the speed value after normalization will be divided into 4 classes by fuzzy clustering; Step S5: the speed normalization mean value of the finely divided traffic state of each road section and 4 types of traffic states Compared with the threshold value, the fine state of urban traffic can be obtained.

Description

technical field [0001] The invention relates to a method for finely dividing and identifying urban traffic states based on multi-source trajectory data. Background technique [0002] Traffic congestion has become an urgent problem to be solved in large and medium-sized cities. The traffic status analysis is of great significance to the urban construction of the planning department and the traffic guidance of the government department. [0003] At present, there have been many researches on urban traffic state analysis. On the basis of the data, the GPS trajectory data of various floating vehicles are fused through data fusion technology, which effectively expands the amount of data and increases the credibility of the results. In terms of research methods, K-means, DBSCAN, fuzzy comprehensive evaluation and other methods are mainly used to calculate the speed, flow, density and other indicators of road sections, and then analyze the traffic status of urban road sections. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G06K9/62G06Q50/30
CPCG08G1/0125G06Q50/30G06F18/23
Inventor 邬群勇胡振华
Owner FUZHOU UNIV
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