Method for classifying vehicle types by using multiple geomagnetic sensors

Abstract

The invention discloses a method for classifying vehicle types by using multiple geomagnetic sensors. The problems that existing vehicle type classification is high in cost, complex in processing process and difficult to deploy on a large scale are mainly solved. The method is implemented by the following scheme: sequentially arranging N geomagnetic sensors on the road sides at equal intervals d,wherein each geomagnetic sensor collects magnetic field data around the geomagnetic sensor and transmits the magnetic field data to a data processing module for storage, and judges whether a vehicle passes through the detection range of the sensor; calculating the time difference of the vehicle in passing by two adjacent sensors in the N sensors, and calculating the vehicle speed and the vehicle magnetic length according to the time difference; and setting a vehicle magnetic length double-threshold value and a Z-axis magnetic field intensity threshold value, obtaining Z-axis geomagnetic data and a magnetic length through which the vehicle passes, and comparing the Z-axis geomagnetic data and the magnetic length with the set threshold values to obtain a vehicle type judgment result. The method can accurately obtain the vehicle model information of the passing vehicles, is high in reliability, is low in cost, is easy to achieve large-scale deployment, and can be used for the highway intelligentization.

Description

Technical field [0001] The invention belongs to the technical field of intelligent transportation, and further relates to a method for classifying traffic vehicle types, which can be used for vehicle type detection of road motor vehicles to realize road intelligence. Background technique [0002] Transportation is the main driving force of urban development. With the current rapid increase in the number of cars in my country, it has caused increasingly severe problems such as traffic jams, traffic accidents and environmental pollution. At the same time, urban transportation is developing rapidly in the direction of intelligent transportation, and intelligent transportation systems are becoming more and more popular. In this context, the Chinese government has issued a number of national strategic documents that point out the development of smart highway technology as the country's future transportation development direction. Among them, vehicle type information is a basic attrib...

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Problems solved by technology

[0005] At present, most vehicle classification methods use expensive equipment such as distributed fiber optic acoustic sensors, millimeter-wave radars, and cameras, which are not conducive to large-scale deployment; on the other hand, they use machine vision or neural network training methods by extracting waveform features It is obtained that the processing process is complex and difficult to implement. At the same time, the sensing range of a single or a small number of geomagnetic sensors is limited, and it is difficult to realize comprehensive and systematic management and control of road vehicle model information.

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