Traffic flow detection induction method

Abstract

The invention discloses a traffic flow detection induction method, which belongs to the technical field of intelligent traffic. The method is characterized in that on the basis of the ultrasonic and road condition video collection cooperative work, the transport network information of different urban roads is centralizedly processed through a traffic cloud information service platform, and the traffic information release and traffic induction can be carried out in real time. By combining the three advanced technologies, the traveling difficulty caused by incomplete information of the road traffic network can be effectively solved; moreover, the route planning problem for the traveling of the particular user can be solved on purpose through the road condition video inquiry and request service function of the system, the compulsory information of the traditional induction method for the user can be avoided, the consciousness for the user to initiatively anticipate in the traffic adjusting process can be enhanced, the traffic coordinate capacity of the road network can be enhanced, the traffic pressure can be alleviated, and the traffic induction purpose can be maximally realized.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and relates to a traffic flow detection and induction method. Background technique [0002] With the rapid development of social economy and the continuous acceleration of urbanization, the number of urban population and the number of motor vehicles are increasing, resulting in increasingly serious urban traffic congestion. Unfavorable factors such as environmental pollution and energy waste accompanying traffic congestion restrict urban development and affect the quality of life of residents. Traffic congestion has become an important problem that countries all over the world face and urgently need to be solved. Therefore, it is of great practical significance to study the methods to solve the problem of traffic congestion. [0003] Under the premise that the number of traffic participants cannot be limited endlessly and the capacity of the traffic road network cannot be inc...

AI Technical Summary

Problems solved by technology

The disadvantage is that the magnetic induction detector is easily affected by the external environment such as vehicles, temperature, humidity, etc., and the reference frequency will drift, thus affecting the detection effect

Its disadvantages are: if there is an object blocking between the ultrasonic probe and the vehicle, the ultrasonic detection will lose its effect, compared with the video detector, the parameters do not have a visual effect, and it is difficult to supervise the feedback of road condition information

The disadvantages are: when the flow rate is large, the air switch is sensitive to temperature or the tires cause wear and damage to the air pressure tube, the accuracy will drop; the accuracy will be distorted when the vehicle stops on the air pressure tube

Its disadvantage is that it can only measure the speed of the vehicle, but cannot measure the number of moving vehicles. It needs to cooperate with other sensors to measure the number of vehicles. At the same time, when the vehicle is running slowly, the error of the radar measuring the vehicle speed is large.

Its disadvantages are: the single channel is too strong; it is too affected by the surrounding environment (such as atmospheric temperature and humidity); the ability to penetrate dust, fog, rain and snow is very weak

Its disadvantage is that it is susceptible to weather, lighting, shadows, and video image processing algorithms.

The disadvantages are: it cannot have a significant impact on the traffic volume of the road, the overall coordination ability of the road network is not good, the effect of improving traffic is not obvious, and it cannot actively guide the driver to actively participate in the traffic regulation process, and the process is passive for the driver

The disadvantages are: strong dependence on a large amount of historical traffic data, low effective mediation rate, not easy to respond to changes in traffic volume in a timely manner, and lack of active participation awareness of drivers

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