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Vehicle track data indexing method based on space-time interpolation

A trajectory data and data indexing technology, applied in the field of big data, can solve the problems of no indexing method, etc., and achieve the effects of reducing storage cost, improving efficiency, optimizing query speed and storage cost

Active Publication Date: 2019-08-02
EAST CHINA NORMAL UNIV
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AI Technical Summary

Problems solved by technology

In the analysis of real-world trajectory data, different scenarios require different sampling time granularities, and currently there is no indexing method compatible with different application scenarios
At the same time, the storage cost of massive data is also a problem

Method used

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  • Vehicle track data indexing method based on space-time interpolation
  • Vehicle track data indexing method based on space-time interpolation
  • Vehicle track data indexing method based on space-time interpolation

Examples

Experimental program
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Embodiment

[0050] refer to figure 2 , this embodiment specifically includes:

[0051] Step 1: Input the original trajectory data, and extract the unique vehicle identifier set Array after trajectory preprocessing. Suppose the example trajectory data VT={vt_c|vt_c={carID,time,x,y,state}} is ["001,2016-08-01 00:01:00,20,20,Vacant","002,2016 -08-01 00:00:50,20,20,Vacant","001,2016-08-01 00:01:30,20,20,Vacant","002,2016-08-01 00:02: 50,40,30,Vacant","001,2016-08-01 00:02:30,30,40,Vacant","001,2016-08-01 00:03:10,30,40,Vacant" ], get Array["001","002"] after deduplication.

[0052]Step 2: Organize raw trajectories into ordered trajectory sequences by vehicle identifiers. Before interpolating the raw data, it is necessary to organize the raw data with a large amount of data, disorder, and different frequency sampling into an ordered trajectory sequence according to the vehicle identifier. First, open up storage space for different vehicles, that is, define the track sequence carIDwithInf...

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Abstract

The invention discloses a vehicle track data indexing method based on space-time interpolation. The vehicle track data indexing method comprises the following steps: 1) extracting an unduplicated vehicle identifier set; 2) organizing the original track into an ordered track sequence according to the vehicle identifier; and 3) performing space-time state interpolation on the ordered track sequenceof each vehicle. According to the time granularity specified by the user, the current track data is interpolated and then written into the index structure, so that the indexed data can be quickly inquired and occupies smaller space. According to the method, the original data can be better recombined, the time complexity is O(n), and the index creation time, the query time and the occupied space are superior to those of a MySQL commercial database.

Description

technical field [0001] The invention belongs to the technical field of big data, and in particular relates to a vehicle trajectory data indexing method based on spatio-temporal interpolation. Background technique [0002] Vehicle trajectory big data has the characteristics of huge data, disorder, and different frequency sampling. If it is not organized in an orderly manner, the query time will be uncontrollable. Therefore, the analysis of massive trajectory data needs to solve the problem of storage and retrieval efficiency. In the analysis of real-world trajectory data, different scenarios require different sampling time granularities, and currently there is no indexing method compatible with different application scenarios. At the same time, the storage cost of massive data is also a problem. Contents of the invention [0003] In order to better store and query massive trajectory data, the object of the present invention is to provide a vehicle trajectory data indexing...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/22G06F16/29
CPCG06F16/22G06F16/29
Inventor 朱延冰李响
Owner EAST CHINA NORMAL UNIV
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