Resident travel survey comprehensive sample expanding and checking method based on combination of big data and traditional method

Abstract

The invention provides a resident travel survey comprehensive sample expanding and checking method based on the combination of big data and a traditional method. The method comprises the following steps: step 1, carrying out overall preliminary checking work by utilizing multi-source big data; step 2, carrying out the classified checking operation: carrying out the classified checking operation onpreliminarily corrected travel features according to two types of travel features, namely commuting travel and non-commuting travel; step 3, re-correcting the overall constraint: re-correcting the overall constraint of travel data after being subjected to the classified checking operation. According to the invention, based on the large-sample or quasi-full-sample characteristics of multi-source big data, the silent travel can be conveniently excavated, so that most real resident travel characteristics are restored. In addition, the real-time performance and the accuracy of big data are utilized, so that the comprehensive sample expansion of a resident travel survey is more accurate and more timely.

Description

technical field [0001] The invention relates to a method for comprehensive sample expansion and checking of residents' travel survey based on the combination of big data and traditional methods, and belongs to the technical field of traffic management statistics. Background technique [0002] Resident travel survey is an important measure to solve how to obtain the basic data of current traffic problems in major cities. The main purpose is to grasp the travel characteristics of urban residents and provide basic data for the establishment of urban traffic planning models, thereby providing support for scientific and reasonable urban traffic planning and policy formulation, and guiding the sound development of urban traffic. The most commonly used method of resident travel survey is household survey. Its working method is that the investigators make an appointment in advance with the interviewed households, and visit the households at the appointed time. investigation. The m...

AI Technical Summary

Problems solved by technology

[0005] 1) The travel rate is underestimated (silent travel) due to missing filling, which leads to misjudgment of the travel volume of the entire city, which in turn affects a series of major issues such as the planning and construction of urban transportation facilities

[0006] 2) Due to the time difference between non-commuter travel and commuter travel, the underreporting of non-commuter travel leads to inaccurate travel time distribution of combined expansion, such as figure 2 As shown, the scale of peak travel is expanded, and the scale of off-peak travel is reduced, which is not conducive to the balanced allocation of transportation resources.

[0007] 3) Non-commuting travel involves a variety of travel purposes, such as official business, visiting relatives and friends, life shopping, entertainment, etc. The underreporting of non-commuting travel directly leads to problems in the expansion of travel purposes

[0008] 4) The traffic survey flow of the verification line used in the verification step of the current situation model of traditional sample expansion is not accurate enough, and the timeliness and reliability are not high

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