Global dynamic travel demand estimation method based on multi-source traffic data

A technology of traffic data and travel demand, applied in the field of transportation, can solve problems such as inaccurate recorded information, inability to estimate residents in real time, large-scale acquisition of large-scale data, etc., to achieve the effect of reducing time and economic costs

Active Publication Date: 2018-11-23
CENT SOUTH UNIV
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AI Technical Summary

Problems solved by technology

[0003] 1) Traditional questionnaire surveys and other methods not only consume a lot of manpower, material and financial resources, but also obtain large-scale data and record information is not very accurate
[0004] 2) Since mobile phone base station data is coll

Method used

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  • Global dynamic travel demand estimation method based on multi-source traffic data
  • Global dynamic travel demand estimation method based on multi-source traffic data
  • Global dynamic travel demand estimation method based on multi-source traffic data

Examples

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[0043] The present invention will be further described below with reference to the drawings and embodiments.

[0044] The present invention proposes a dynamic traffic demand estimation method using multi-source traffic data, such as figure 1 It is shown and applied to the travel of residents in a megacity in the south.

[0045] First construct the city’s traffic area, extract the real travel information of the residents through the city’s mobile phone signaling data, extract the residents’ real-time travel information through the city’s taxi GPS data and subway card swipe data, and then use the β( The value of i, j, tp) is divided into two resident travel modes with δ as the critical value, and different methods are used to estimate the real-time real-time travel of residents for different resident travel modes.

[0046] In this example, a large-scale crowd gathering activity in the city was taken as an example to verify the effectiveness of the real-time resident travel perception ...

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Abstract

The present invention discloses a global dynamic travel demand estimation method based on multi-source traffic data. Dynamic traffic data and static mobile phone historical signaling data are fused, resident global historical travel data and real-time traffic travel data are combined to estimate resident global travel data in real time so as to greatly reduce the time and economic cost of OD survey. Besides, the Chi-square distance is introduced to measure the accuracy of a constructed fusion model to determine the optimal leading travel mode threshold value and obtain accurately estimated fusion model. The method combines the real-time data of the taxi travel and the subway travel with the mobile phone historical signaling data to effectively perceive the real-time travel state of the large-scale resident travel and perform timely perception and early warning for events of gathering of the crowd so as to have a very important reference meaning of city planning and management.

Description

technical field [0001] The invention belongs to the technical field of traffic, in particular to a global dynamic travel demand estimation method based on multi-source traffic data. Background technique [0002] The travel of urban residents is closely related to the development of society and economy. Understanding the travel needs of residents is not only beneficial to the rational layout of urban land, but also of great significance to the planning and management of urban traffic. For a long time, the travel OD survey of residents has been widely valued by governments and scientific researchers in various countries. From the perspective of government management, understanding the travel characteristics of residents is not only conducive to maintaining the safety and stability of the city, but also related to the macroscopic control of urban economic development by administrative personnel. control. From the perspective of scientific research development, scientific resea...

Claims

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Application Information

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IPC IPC(8): G08G1/01G06Q10/06G06Q50/26
CPCG06Q10/0639G06Q50/26G08G1/0129
Inventor 王璞黄智仁刘洋
Owner CENT SOUTH UNIV
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