Tachymeter on-site verification system based on Internet of things

文档序号:9592 发布日期:2021-09-17 浏览:61次 中文

1. A velocimeter field verification system based on the Internet of things is characterized by comprising an unmanned automobile, a tested velocimeter and a cloud platform;

the unmanned automobile is provided with a main controller, and the main controller is communicated with the cloud platform through the Internet of things;

the detected velocimeter is installed on a road and is communicated with the cloud platform through the Internet of things;

the detected velocimeter acquires first data generated by the unmanned automobile in the detection area and sends the first data to the cloud platform;

the main controller acquires second data generated by the unmanned automobile in the detection area and sends the second data to the cloud platform;

and the cloud platform carries out field error detection on the detected velocimeter according to the first data and the second data.

2. The Internet of things-based velocimeter field verification system according to claim 1, wherein the first data comprises picture information and a first velocity value;

the picture information comprises first license plate information and first time information;

the second data includes second license plate information, second time information, and a second speed value.

3. The on-site verification system for the Internet of things-based tachymeter according to claim 1, wherein the tachymeter to be detected comprises a first Internet of things communication module;

the detected speed meter sends the first data to a cloud platform through the first internet of things communication module.

4. The IOT-based velocimeter field verification system according to claim 1, wherein a standard velocimeter, a GNSS module and a second networking communication module are installed on the unmanned vehicle;

the standard velocimeter, the GNSS module and the second internet of things communication module are respectively electrically connected with the master controller;

the standard speedometer is used for acquiring a second speed value;

the GNSS module is used for acquiring second time information;

and the master controller of the unmanned automobile acquires second license plate information, second time information and a second speed value, and sends the second license plate information, the second time information and the second speed value to the cloud platform through the second internet-of-things communication module.

5. The internet-of-things-based tachymeter field verification system according to claim 2, wherein the cloud platform performs field error verification on the detected tachymeter according to the first data and the second data specifically:

judging whether the first license plate information and the second license plate information are consistent, if so, executing the next step;

and judging whether the time difference between the first time information and the second time information is smaller than a preset value, if so, carrying out field error verification on the detected speed meter according to the first speed value and the second speed value.

Background

The method for calibrating the field speed measurement error of the velocimeter comprises two methods according to JJG527-2015 fixed motor vehicle radar velocimeter calibration procedures, JJG528-2015 mobile motor vehicle radar velocimeter calibration procedures, JJJG 1074-2012 motor vehicle laser velocimeter calibration procedures and JJG1122-2015 motor vehicle ground induction coil velocimetry system calibration procedures: (1) taking a normally running vehicle as a measured object in a real traffic flow state, simultaneously measuring the same measured object in a detection area by using a field speed measurement standard device and a detected speed meter, recording 30 groups of effective measurement values, and calculating the error of the two effective measurement values; (2) the test vehicle with the standard speedometer runs at a detected speed value at a constant speed, the standard speedometer measures and displays the speed value of the test vehicle when the test vehicle passes through the detection area, and meanwhile, the speedometer measures the test vehicle and calculates the error between the test vehicle and the test vehicle. The speed measuring places are mostly installed on dangerous road sections where traffic accidents easily occur, and drivers of verification parties are required to drive test vehicles to pass through a detection area at a constant speed of 100% of a speed limit value in field verification.

However, both of the above methods have the following disadvantages:

(1) the field verification requires a traffic police department to seal a detection area;

(2) the requirements on the driving technique of a driver are high;

(3) the working efficiency is low, and social resources are wasted;

(4) there is a safety risk, and traffic accidents are easily caused by high-speed running in the detection area to cause on-site verification casualties.

Disclosure of Invention

Technical problem to be solved

In order to solve the problems in the prior art, the invention provides the tachymeter field verification system based on the internet of things, which can improve the field verification efficiency of a tester and has high safety and accuracy.

(II) technical scheme

In order to achieve the purpose, the invention adopts the technical scheme that:

a velocimeter field verification system based on the Internet of things comprises an unmanned automobile, a tested velocimeter and a cloud platform;

the unmanned automobile is provided with a main controller, and the main controller is communicated with the cloud platform through the Internet of things;

the detected velocimeter is installed on a road and is communicated with the cloud platform through the Internet of things;

the detected velocimeter acquires first data generated by the unmanned automobile in the detection area and sends the first data to the cloud platform;

the main controller acquires second data generated by the unmanned automobile in the detection area and sends the second data to the cloud platform;

and the cloud platform carries out field error detection on the detected velocimeter according to the first data and the second data.

(III) advantageous effects

The invention has the beneficial effects that: acquiring first data generated by the driving of the unmanned vehicle in the detection area through the detected velocimeter, and sending the first data to the cloud platform; the method comprises the steps that a main controller obtains second data generated when an unmanned automobile runs in a detection area and sends the second data to a cloud platform; and the cloud platform carries out field error detection on the detected speed meter according to the first data and the second data, analyzes the traffic road condition in real time through internet of things connection, and passes through a detection area at a constant speed according to the detection regulation requirement. The road traffic jam caused by the closed detection area can be eliminated, social resources are saved, in addition, data measured by the unmanned vehicle and the detected velocimeter are transmitted to the cloud platform through the Internet of things connection for automatic analysis and calculation to obtain field speed measurement errors, the danger that personnel casualties may appear on the field of the verification personnel is avoided, and the working efficiency can be improved.

Drawings

Fig. 1 is a schematic overall structure diagram of a velocimeter field verification system based on the internet of things according to an embodiment of the present invention.

[ description of reference ]

1: a velocimeter field verification system based on the Internet of things;

2: an unmanned vehicle;

3: a tested velocimeter;

4: and (4) cloud platform.

Detailed Description

For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.

Example one

Referring to fig. 1, a velocimeter field verification system 1 based on the internet of things comprises an unmanned vehicle 2, a tested velocimeter 3 and a cloud platform 4;

the unmanned automobile 2 is provided with a main controller, and the main controller is communicated with the cloud platform 4 through the Internet of things;

the detected speed meter 3 is arranged on a road and is communicated with the cloud platform 4 through the Internet of things;

the detected velocimeter 3 acquires first data generated by the unmanned automobile 2 in the detection area and sends the first data to the cloud platform 4;

the main controller acquires second data generated by the driving of the unmanned automobile 2 in the detection area and sends the second data to the cloud platform 4;

and the cloud platform 4 carries out field error detection on the detected velocimeter 3 according to the first data and the second data.

The first data comprises picture information and a first speed value;

the picture information comprises first license plate information and first time information;

the second data includes second license plate information, second time information, and a second speed value.

The detected speed meter 3 comprises a first internet of things communication module;

the detected speed meter 3 sends the first data to the cloud platform 4 through the first internet of things communication module.

The unmanned automobile 2 is provided with a standard speed meter, a GNSS module and a second networking communication module;

the standard velocimeter, the GNSS module and the second internet of things communication module are respectively electrically connected with the master controller;

the standard speedometer is used for acquiring a second speed value;

the GNSS module is used for acquiring second time information;

and the master controller of the unmanned automobile 2 acquires second license plate information, second time information and a second speed value, and sends the second license plate information, the second time information and the second speed value to the cloud platform 4 through the second networking communication module.

The cloud platform 4 specifically performs field error detection on the detected velocimeter 3 according to the first data and the second data as follows:

judging whether the first license plate information and the second license plate information are consistent, if so, executing the next step;

and judging whether the time difference between the first time information and the second time information is smaller than a preset value, if so, carrying out field error verification on the detected speed meter 3 according to the first speed value and the second speed value.

Preferably, the preset value is 30 seconds, and the error detection calculation formula is as follows:

Δv=v-v0

Δ v: the field speed measurement error (km/h) of the tested speed meter 3 is represented;

v: representing a first speed value (km/h);

υ0: representing the second velocity value (km/h).

The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.

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