Travel endpoint identificationmethod based on multi-layer condensation hierarchical clustering algorithm

Abstract

The invention discloses a travel endpoint identification method based on a multi-layer agglomeration hierarchical clustering algorithm. According to 4G communication signaling data of a user mobile phone collected by a communication operator, a three-layer algorithm model is proposed: an equal-time-distance interpolation algorithm, an agglomeration hierarchical clustering algorithm and a ping-pongdwell correction algorithm are used for extracting a user trip end point. Finally, the travel endpoint information of the user all day is further sorted out to form the travel time-space sequence completed by the individual. The invention utilizes the feature that the positioning frequency of 4G signaling data is higher than that of 2G signaling data, exerts the identification advantage of the multi-layer condensation hierarchical clustering algorithm, solves the shortcomings of the traditional single-layer algorithm in identifying actual travel endpoints, and realizes the intelligent identification of the endpoint information of residents' traffic travel by using the signaling data in the background of 3G / 4G-LTE technology. This method can be used for large-scale, automated information collection of residents' travel endpoints.

Description

technical field [0001] The invention belongs to the field of resident travel investigation in traffic data collection, and in particular relates to a flow and process for analyzing and processing 4G communication signaling data by using a multi-layer agglomerative hierarchical clustering algorithm to identify the time-space location information of traffic travel endpoints in individual traffic travel. method. Background technique [0002] With the continuous development of social economy, the types and frequency of daily traffic trips of residents are increasing. What follows is that the traffic congestion in major cities is becoming more and more serious, which directly affects the social and economic development and the quality of residents' traffic travel. The acquisition of residents' traffic travel endpoint information can provide an important basis for the analysis of the current situation of urban residents' traffic travel, including the number of trips per capita of...

AI Technical Summary

Problems solved by technology

Its main disadvantages are as follows: 1. Respondents are unwilling to participate in the survey or the survey is too random, subjective memory bias and errors are common, and a lot of short-distance or short-term travel information is often missed, and the data quality cannot be reliably guaranteed; 2. The investigation process is cumbersome and difficult to organize. Usually, the traffic bureau, public security bureau, and sub-district office are required to coordinate and complete the survey of residents’ travel. The survey organization is difficult, and the questionnaire design, investigator training, Personnel organization and division of labor are cumbersome and require a lot of manpower and material resources

However, the positioning frequency of signaling data generated by the new generation of mobile communication 3G / 4G-LTE technology is higher. This method may easily lead to the omission of travel endpoints, or the number of identification is too large. There is an urgent need for a more applicable algorithm for 4G signaling data. Travel endpoint mining and extraction

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