Traffic fusion analytical prediction method and system and electronic device

Abstract

The present application relates to a traffic fusion analytical prediction method and system and an electronic device. The method includes the following steps of a: acquiring vehicle data information by using a fixed-point electronic photographing device in combination with a mobile intelligent information acquisition device, and acquiring mobile phone signaling data; b: separately extracting vehicle OD data and user OD data according to the vehicle data information and the mobile phone signaling data; c: constructing a network topological graph according to the vehicle OD data and the user OD data, and performing a space-time convolution operation on the network topological graph with space-time correlation by using a deep learning model based on a space-time diagram convolution network to establish traffic flow prediction model; and d: predicting a traffic flow and population distribution through the traffic flow prediction model. The method tracks and identifies the vehicle by means of the fixed-point electronic photographing device and the mobile intelligent information acquisition device, compensates for the limitation of video tracking fixed point identification and provides decision support for traffic control and induction in key areas.

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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