OD calibration method by use of mobile phone signaling big data and dynamic traffic distribution

Abstract

The invention relates to resident travel OD matrix calibration method by use of mobile phone signaling big data and dynamic traffic distribution. The method comprises the following major steps: a city road simulation network model is constructed, simulation parameters of each road in a constructed city road network are calibrated by use of microwave and bayonet data, a real traffic flow in an actual road network is obtained by use of a microwave detector, a traffic flow of an initial OD matrix is obtained by use of mobile phone signaling data, through a dynamic traffic distribution method, an initial traffic flow is dynamically adjusted so as to be enabled to be close to the real traffic flow in the road network, an error between a simulation estimation traffic flow and the real traffic flow is calculated, if the error satisfies a threshold, calibration ends, and otherwise, dynamic distribution based on simulation is continuously carried out until the calibration ends. According to the invention, a dynamic OD matrix of resident travel is calibrated by use of the mobile phone signaling big data, and the method has the advantages of stable and objective data information sources, large sample size, wide coverage scope, high data precision, high dynamic performance and the like.

Description

technical field [0001] The invention relates to the field of OD calibration methods for residents' travel, in particular to calibrate the OD matrix of residents' travel based on mobile phone signaling big data and using a dynamic traffic allocation method. Background technique [0002] The continuous development of economy and society has brought more and more pressure to urban traffic while improving the appearance of urban life. At present, the process of domestic urbanization and urban traffic motorization is becoming faster and faster. Under the joint action of urbanization and motorization, traffic congestion has become one of the main problems restricting urban development and affecting the quality of life of residents. In order to effectively solve the problem of traffic congestion under the existing road network conditions, the establishment of intelligent traffic information systems has become the key to solve the problem of urban traffic congestion, and the establi...

AI Technical Summary

Problems solved by technology

It overcomes the shortcomings of low data sample size and poor data accuracy obtained by traditional resident survey methods, and makes up for the shortcomings of static traffic allocation methods that cannot consider the time-varying characteristics of traffic demand

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