Urban passing vehicle prediction method and system

Abstract

The invention discloses an urban passing vehicle prediction method and system. The method comprises the following steps: acquiring hybrid vehicle vibration signals of set detection points and set continuous time periods in a city to be detected; carrying out filtering and denoising; carrying out blind source separation on the denoised hybrid vehicle vibration signal by adopting an adaptive gradient algorithm; carrying out empirical mode decomposition and normalization processing; adopting a least square support vector machine method to perform classification; and performing prediction by usinga least square support vector machine method to obtain data of different types of vehicles passing through the next time period of the set continuous time period. According to the method, blind source separation is carried out by adopting an adaptive gradient algorithm; and the adaptive gradient algorithm has the characteristics of high convergence rate and good separation performance, so that after the denoised hybrid vehicle vibration signals are subjected to blind source separation, the obtained vibration signals of different vibration types are more accurate, and the prediction precisionof vehicles passing through set detection points of a city to be detected is improved.

Description

technical field [0001] The invention relates to the technical field of urban intelligent traffic planning and management, in particular to a method and system for predicting vehicles passing through the city. Background technique [0002] With the development of the economy and the development of the smart city process, people's requirements for the intelligent transportation of the city are also increasing. With the development of the economy, the number of motor vehicles in my country has exceeded 280 million, and the number of private cars has exceeded 124 million. This has brought enormous pressure to urban traffic. The increase in urban population and vehicles has become the main cause of urban traffic congestion. The direct problems caused by traffic jams are: fuel consumption, environmental pollution, increasing people's travel time, and even causing traffic chaos and causing traffic accidents. According to the statistics of relevant agencies, the economic losses dir...

AI Technical Summary

Problems solved by technology

The direct problems caused by traffic jams are: fuel consumption, environmental pollution, increasing people's travel time, and even causing traffic chaos and causing traffic accidents

[0003] In my country, in recent years, with the sustained and stable development of the national economy and the acceleration of urbanization, the population and spatial scale of cities have continued to expand, service vehicles on urban roads have increased, and traffic demand has experienced unprecedented rapid growth. The difficulty of predicting types of vehicles has increased, and the prediction accuracy needs to be improved

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