Travel and activity mode identification method based on DBSCAN clustering algorithm

An activity pattern, clustering algorithm technology, applied in character and pattern recognition, calculation, computer parts and other directions, can solve the problems of labor and material resources, cumbersome, not getting survey results, etc., to achieve the effect of saving labor

Active Publication Date: 2016-07-06
SOUTHEAST UNIV
View PDF3 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, my country mainly adopts the manual survey method to obtain residents' travel information, which is cumbersome and consumes manpower and financial resources.
Moreover, the results

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
  • Travel and activity mode identification method based on DBSCAN clustering algorithm
  • Travel and activity mode identification method based on DBSCAN clustering algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. After reading the present invention, those skilled in the art all fall into the appended claims of the present application to the amendments of various equivalent forms of the present invention limited range.

[0027] like figure 1 As shown, the embodiment of the present invention discloses a travel and activity pattern recognition method based on the DBSCAN clustering algorithm. The method sequentially includes the steps of data cleaning, travel pattern recognition, activity pattern recognition and generating a travel schedule.

[0028] The data cleaning step is to clean the traveler spatio-temporal trajectory data collected continuously for 24 hours. Due to the lack of WIFI signal or the err...

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 present invention discloses a travel and activity mode identification method based on a BDSCAN clustering algorithm. The method comprises the following steps: cleaning traveler spatio-temporal track data sets that are continuously acquired; calculating an average speed of coordinate points of cleaned data sets, and classifying a position coordinate point whose average speed is higher than a set threshold into a travel mode; based on a DBSCAN clustering algorithm, performing clustering analysis on the cleaned data sets, and determining an activity starting point and an activity ending point according to a clustering result; and according to coordinates and time of data points of an identified travel mode and activity mode, generating a travel time table. According to the method disclosed by the present invention, based on the acquired traveler spatio-temporal track sequence sets, the behavior modes of the travelers are divided into the travel mode and the activity mode by using the density-based clustering algorithm (DBSCAN). The method disclosed by the present invention is convenient for calculation and actual operation and has strong practicality, and by the method, the behavior mode of the travelers can be determined more accurately, so as to facilitate subsequent researches, so that the method has important realistic significance.

Description

technical field [0001] The invention relates to the technical field of traffic travel information, in particular to a method for collecting travel and activity pattern recognition information based on a DBSCAN clustering algorithm. Background technique [0002] Resident travel data is the basis of transportation planning and management. The development of transportation demand modeling theory can be roughly classified into two types of theoretical systems: travel-based and activity-based demand modeling. Travel-based demand modeling is widely used in the practice of traditional "four-stage approach" transportation planning. Based on the travel demand modeling method, from a macro perspective, the independent travel unit is used as the object to analyze the travel demand of each traffic district as a whole. However, this method does not consider the connection between these individual trips, mainly in two aspects, one is the lack of consideration of individual travel behavi...

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
IPC IPC(8): G06K9/62G08G1/01
CPCG08G1/0137G06F18/23
Inventor 叶智锐施晓蒙汤斗南赵鑫玮陆加健吴运腾吴丽霞
Owner SOUTHEAST 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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap