A Traffic Data Quality Control Method Based on Crowdsourced Trajectory Data

A quality control method and trajectory data technology, applied in the field of intelligent transportation, can solve problems such as different data attributes, inapplicability of crowdsourcing trajectory data processing, and differences in processing requirements, so as to save storage space, avoid frequent and uneven data collection, The effect of the simplicity of the data cleaning process

Inactive Publication Date: 2020-10-09
BEIHANG UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Most of the existing domestic patents are based on the quality evaluation and control of road traffic flow data detected by traditional sensors, including traffic volume, average speed, road occupancy rate and other parameters. The control methods are generally based on the relationship between the three elements of traffic. However, the traffic data detected by traditional cross-section sensors and the crowdsourced trajectory data based on individual users have different data attributes, and the processing requirements are also different. Therefore, the existing traffic data quality control methods are not Not suitable for processing crowdsourced trajectory data

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Traffic Data Quality Control Method Based on Crowdsourced Trajectory Data
  • A Traffic Data Quality Control Method Based on Crowdsourced Trajectory Data
  • A Traffic Data Quality Control Method Based on Crowdsourced Trajectory Data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0059] The present invention will be further described in detail with reference to the accompanying drawings and embodiments.

[0060] Such as figure 1 As shown, the embodiment of the present invention provides a quality control method for crowdsourcing trajectory data, including:

[0061] Step 1. Data cleaning: Extract key information from the data collected by the detector, enter it into the database according to the agreed format, and detect the acquired data attribute format, field content, and data set size. The steps are:

[0062] Step 1.1. Assume that the field of the crowdsourcing track data set is G={VehicleID, OrderID, Time, Longitude, Latitude}, and the data of the order ID is not required for data analysis. This field is removed, and the format for entering the agreed time is: xxxx- xx-xx xx:xx:xx, longitude and latitude are input with 6 decimal places according to the agreement, if the format does not match, the data will be marked as 0, and it is judged as a dat...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a quality control method for crowd-sourcing trajectory data. The method comprises the first step of data cleaning, the second step of abnormal trajectory data recognition and processing, the third step of data set trajectory pre-generation and adjusting and the fourth step of complete trajectory displaying and historical database updating. A solution is provided for fault data and missing data in traffic data of the crowd-sourcing trajectory data, the completeness of the trajectory data is ensured, and accurate data support is provided for traffic planning and traffic predicting.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a traffic data quality control method based on crowdsourced trajectory data. Background technique [0002] With the rapid development of wireless sensing technology, information processing technology, mobile Internet technology and satellite positioning technology, traffic data acquisition methods are gradually diversified, from traditional geomagnetic induction coils and infrared video detection to mobile terminal-based Internet of Vehicles, traffic Data tends to be massive and diversified. In recent years, the proposal of crowdsourcing has provided a new low-cost method for traffic data collection. The scattered data on various vehicle-mounted devices and sensors, and the mobile devices of ordinary users as the basic perception unit are collected through communication. Perception data, vehicle-to-vehicle communication, and vehicle-to-road, interaction data between peo...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01
CPCG08G1/0125G08G1/0137
Inventor 于海洋杨阳任毅龙王飞张力王子睿
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products