Urban resident travel activity pattern acquisition method based on multi-source positioning data

Abstract

The invention discloses an urban resident travel activity pattern acquisition method based on multi-source positioning data. The urban resident travel activity pattern acquisition method comprises thesteps of: (1) performing denoising processing on mobile phone signaling data, and identifying a travel endpoint base station and a passing-by base station of a user; (2) matching the travel endpointbase station and the passing-by base station acquired in the step (1) to a road network map, so as to obtain a travel route of the user; (3) calculating a travel distance, travel time and an average travel speed of the user, and identifying a travel mode of the user; (4) and identifying a travel purpose of the user by utilizing social network information near the travel endpoint base station. Theurban resident travel activity pattern acquisition method can effectively utilize the mobile phone signaling data and the social network data to identify information in various aspects such as the travel origin and destination, travel time, travel distance, travel mode and travel purpose of urban resident travel activities, and provides a novel resident travel activity chain investigation method for the field of urban transportation planning.

Description

Technical field [0001] The invention relates to the technical field of traffic planning, in particular to a method for acquiring travel activity patterns of urban residents based on multi-source positioning data. Background technique [0002] Travel demand forecasting is the supporting foundation for urban transportation planning management and decision-making. With the continuous expansion of my country's large and medium-sized cities' construction scales driving the continuous inflow of migrants, the currently widely used travel survey-based demand forecasting methods cannot meet new challenges, and it is urgent to expand new travel information data sources and demand forecasting methods. [0003] Traditional transportation demand information acquisition relies on urban residents' transportation travel surveys. Generally, questionnaire surveys, telephone inquiries and other methods are mainly used to obtain relatively complete travel information such as residents' travel purpose ...

AI Technical Summary

Problems solved by technology

Mobile phone positioning data covers a wide range of people, almost close to the collection of all members. The real-time location information is high, and it can record the spatio-temporal characteristics of user activities objectively and on a large scale for a long time. The disadvantage is that it is difficult to obtain the purpose of user travel activities and the user's personal socioeconomic attribute information

Mobile social network data can provide information on land use types of travel destinations, but compared with mobile phone data, the sample size is not high, and it is difficult to obtain a complete travel chain of a single user.

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