Urban traffic track data set generation method based on taxi data and urban road network

Abstract

The invention discloses an urban traffic track data set generation method based on taxi data and an urban road network, and belongs to the field of traffic transportation. The model is composed of a preparation layer, a generation layer and a verification layer. Track data of private cars are generated based on taxi data and urban road network information for the first time, and meanwhile a complete verification method is provided for verifying the accuracy of a generated data set. The invention provides an urban functional region division method based on an adjacent road division method. Theurban functional region division method comprises the steps of dividing a city into different functional regions; meanwhile, providing a regional population weight opportunity model, and a populationmovement mode can be more accurately depicted. In order to verify the authenticity and the accuracy of the method, a macroscopic angle-based model and a microscopic angle-based model are respectivelyprovided on a verification layer to verify the authenticity and the accuracy of a data set generated by the model. Through verification of the verification layer, the track data of the private car generated according to the taxi GPS data and the urban vehicle network information are high in authenticity and accuracy.

Description

technical field [0001] The invention belongs to the field of transportation and relates to a method for generating a social vehicle trajectory data set based on floating vehicle trajectory data in the field of transportation big data. Background technique [0002] The Internet of Things is an important part of the new generation of information technology and an important stage of the development of the information age. As more and more vehicles are connected to the Internet of Things, the popularity and application of Internet of Vehicles technology is in the ascendant. Human movement trajectory data is the basis of vehicle communication in the Internet of Vehicles, which can reflect the individual movement patterns and social migration rules in the space-time environment. Through the trajectory data of social vehicles (such as private cars, etc.) and floating vehicles (such as taxis, buses, etc.), complex and diverse vehicle social networks (VSNs) can be constructed. Traj...

AI Technical Summary

Problems solved by technology

However, due to the protection of personal privacy and some related government policies, it is almost impossible for ordinary researchers to obtain the trajectory data of social vehicles, which greatly hinders researchers' in-depth research and the development and progress of related fields.

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