A method, system, and electronic device for analyzing and predicting traffic fusion

Abstract

Disclosed are a traffic fusion analysis and prediction method and system, and an electronic device. Vehicles are tracked and identified by means of combining an electronic image capture device at a fixed point and a mobile intelligent information collection device, thereby compensating for the limitation of fixed-point identification for video tracking and providing decision making support for traffic control and guidance in a key area. The method comprises: step a: acquiring vehicle data information by using an electronic image capture device at a fixed point in combination with a mobile intelligent information collection device (100), and acquiring mobile phone signaling data (200); step b: respectively extracting vehicle OD data and user OD data according to the vehicle data information and the mobile phone signaling data (300, 400); step c: constructing a network topology diagram according to the vehicle OD data and the user OD data (500), and performing a space-time convolution operation on the network topology diagram with a space-time correlation by using a deep learning model based on a space-time diagram convolutional network to establish a traffic flow prediction model (600); and step d: predicting a traffic flow and predicting a population distribution by means of the traffic flow prediction model (700).

Description

technical field [0001] The present application belongs to the technical field of intelligent transportation, and in particular relates to a traffic fusion analysis and prediction method, system and electronic equipment. Background technique [0002] With the rapid development of urban economy, the demand for vehicle travel is increasing day by day, and the traffic flow of motor vehicles in urban and regional road networks is increasing year by year. The continuous improvement of the level of motorization has not only increased the pressure on road traffic, but also brought severe challenges to traffic management. Difficulties in driving, supervision, and parking are one of the problems that urban traffic needs to solve urgently. [0003] As the basis of traffic information service, traffic data is of great value to solve traffic problems. The existing traffic data acquisition methods include fixed detection equipment data collection, GPS-based data collection and other meth...

AI Technical Summary

Problems solved by technology

However, the existing technologies only use a single traffic data for research, while ignoring those non-traffic data that will affect traffic

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