CN117864133A - Safety control system based on big data - Google Patents

Abstract

The invention discloses a safety control method based on big data, which comprises the following steps: step one: collecting external real-time environment data of a truck when the truck passes through a tunnel; step two: detecting surrounding moving object information when a truck is about to enter a tunnel based on vehicle system data, and calculating and analyzing detected surrounding moving objects; step three: judging collision trend of the truck and surrounding moving objects according to the analyzed result data, and identifying specific obstacle data information; step four: according to the external environment and specific data of the obstacle, automatically analyzing and controlling the speed and direction change which should be adopted by the truck under different conditions; the invention has the characteristics of reducing recognition errors and realizing safety control.

Description

Safety control system based on big data

Technical Field

The invention relates to the technical field of big data monitoring, in particular to a safety control system based on big data.

Background

With the continuous development of science and technology, automobiles have become one of the indispensable transportation means of home households, the living standard of people is continuously promoted, the specific gravity of automobiles is gradually increased, and various traffic accidents are also caused. In recent years, frequent occurrence of freight car rolling events is actually unable to judge blind areas during driving, safety distance between vehicles or between vehicles and pedestrians in the blind areas cannot be accurately mastered, although the new blind spot monitoring system provides great convenience for monitoring blind area conditions, problems exist, misinformation is often generated in the monitoring system, namely, because signal reception in a tunnel is weaker, and wall parts in the tunnel can be judged to be misinformation by light changes to different degrees, particularly, the infrared camera is utilized to assist the blind spot monitoring system, the blind spot monitoring system is also easily affected by weather, under the condition of low visibility in rainy and snowy days, night and the like, the effect of the camera is poor, the error and accuracy of the blind spot monitoring system are greatly reduced, a driver is required to carry out main observation judgment when using a central control display screen to prompt, whether the system prompts a vehicle is near to the bottom wall area of the tunnel or the rear is judged, the driver needs to pay attention to the display screen in real time, the driver brings the consequences of easy driving in a split manner, and driving safety cannot be obtained, and traffic accidents are guaranteed. Therefore, it is necessary to design a big data based security control system that reduces recognition errors and implements security control.

Disclosure of Invention

The present invention is directed to a security control system based on big data, so as to solve the problems set forth in the background art.

In order to solve the technical problems, the invention provides the following technical scheme: the safety control method based on big data comprises the following steps:

step one: collecting external real-time environment data when a truck passes through a tunnel;

step two: detecting surrounding moving object information when a truck is about to enter a tunnel based on vehicle system data, and calculating and analyzing detected surrounding moving objects;

step three: judging collision trend of the truck and surrounding moving objects according to the analyzed result data, and identifying specific obstacle data information;

step four: according to the external environment and specific data of the obstacle, the speed and direction change which should be adopted by the truck under different conditions is automatically analyzed and controlled.

According to the above technical scheme, the step of collecting the external real-time environmental data when the truck passes through the tunnel comprises the following steps:

the light sensor is arranged at the position of the front cover air grid, the light intensity of light in the tunnel passing through the truck is detected through the light sensor, the vehicle-mounted electronic equipment is controlled by utilizing the output voltage, and the light intensity data of the truck in the tunnel is obtained;

the optical sensor is arranged behind the front windshield, and the weather condition data before the truck enters the tunnel is detected by utilizing the refraction principle of light of the optical sensor.

According to the above technical scheme, the step of detecting surrounding moving object information when the truck is about to enter the tunnel comprises the following steps:

the method comprises the steps that a truck blind spot monitoring system is arranged on a left rearview mirror and a right rearview mirror, and whether obstacles exist in a truck blind spot is monitored by utilizing a camera visual image technology mode;

the ultrasonic sensor is arranged on the side face of the truck, and the distance L between the truck and the obstacle in the blind area is calculated by utilizing the time difference of ultrasonic reflection and reception of the ultrasonic sensor.

According to the above technical solution, the step of performing measurement and analysis on the detected moving objects approaching around includes:

the short wave radar is arranged at the side of a truck or at the position of a rear bumper, the distance, direction and speed information of an obstacle are analyzed by utilizing electromagnetic wave signals transmitted and received by the short wave radar, and specific azimuth data information of the obstacle in a dead zone of the truck is measured according to an antenna pattern of the radar.

According to the above technical solution, the step of identifying specific obstacle data information includes:

respectively carrying out comparison analysis according to the acquired data of the obstacle, and if the speed of the obstacle is relative to the speed of the truck, the obstacle is a tunnel wall without an execution unit; if the distance between the obstacle and the truck changes in real time along with time, the obstacle is a vehicle, an execution signal is transmitted to the execution unit, and the driver is reminded of safe driving by using the audible and visual alarm.

According to the technical scheme, the steps for analyzing and controlling the speed and direction change which should be adopted by the truck under different conditions comprise the following steps:

the information of the type, position and distance of the obstacle, the speed of the vehicle, an accelerator pedal and the like acquired by the sensor are taken as input, the established rule is utilized to analyze the speed control of the truck, and finally an execution signal is output to control the running speed and direction of the truck, so that the active safety control of the truck is realized.

According to the above technical solution, the system comprises:

the external environment collecting module is used for collecting real-time data of light intensity and weather conditions in a specific scene;

the sensing module is used for monitoring whether a moving object exists in a rear visual field blind area of the truck and collecting specific data information of the moving object in the blind area close to the truck;

the electronic control module is used for processing and judging the specific data information of the moving object transmitted by the perception information module and outputting a signal instruction to the execution module;

and the execution module is used for receiving and executing the signal instruction transmitted by the electronic control module.

According to the above technical scheme, the module for collecting external environment information includes:

the light intensity acquisition module is used for acquiring real-time data of light intensity in a specific scene;

the weather condition acquisition module is used for acquiring real-time data of weather conditions in specific scenes.

According to the above technical solution, the perception information module includes:

the camera data acquisition module is used for acquiring whether a moving object exists in a dead zone of a truck or not by adopting a technical mode of images;

the radar data acquisition module is used for monitoring moving objects in dead zones of the truck and acquiring specific data information of the moving objects around the truck by utilizing a method for transmitting and receiving electromagnetic waves;

and the ultrasonic sensor acquisition data module is used for calculating the real-time distance between the moving object and the truck by utilizing the time difference between the transmission and the reception of ultrasonic waves.

According to the above technical scheme, the electronic control module includes:

the data storage module is used for storing the moving object data information collected by the record sensing module and the collection external environment module and the tunnel real-time environment data information;

the data control module is used for storing the recorded data information of the moving object, judging the movement trend of the truck and the moving object and the data information of the moving object, and transmitting an execution signal to the execution unit;

the execution module comprises:

the sound alarm module is used for receiving the execution command of the electronic control unit and providing sound prompt for a driver;

the light alarm module is used for receiving the execution command of the electronic control module and displaying dangerous icons in the rearview mirror to a driver;

and the vehicle speed controller module is used for receiving the execution signal of the electronic control module and controlling the running speed and the brake of the truck according to the execution signal.

Compared with the prior art, the invention has the following beneficial effects: according to the method, the external real-time environment data of the tunnel are acquired when the truck passes through the tunnel; detecting surrounding moving object information when a truck is about to enter a tunnel based on vehicle system data, and calculating and analyzing detected surrounding moving objects; judging collision trend of the truck and surrounding moving objects according to the analyzed result data, and identifying specific obstacle data information; according to the external environment and specific data of the obstacle, automatically analyzing and controlling the speed and direction change which should be adopted by the truck under different conditions; and the established rule is utilized to analyze the speed control of the truck, and finally, an execution signal is output to control the running speed and direction of the truck, so that the active safety control of the truck is realized, and the recognition of the system against the obstacle of the truck in the tunnel is stronger.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:

FIG. 1 is a flowchart of a security control method based on big data according to an embodiment of the present invention;

fig. 2 is a schematic diagram of module composition of a safety control system based on big data according to a second embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Embodiment one:

fig. 1 is a flowchart of a safety control method based on big data according to an embodiment of the present invention, where the embodiment may be applied to a scenario of a truck blind spot monitoring control system, and the method may be performed by the safety control system based on big data according to the embodiment, as shown in fig. 1, and the method specifically includes the following steps:

step one: collecting external real-time environment data of a tunnel when a truck passes through the tunnel;

in the embodiment of the invention, a truck runs in a tunnel, a light sensor is arranged at the position of a front cover air grid, the light intensity of light in the tunnel passing through the truck is detected through the light sensor, the light sensor is an electronic sensor for detecting the light intensity of the surrounding environment, and the light intensity data of the truck in the tunnel is obtained by further controlling vehicle-mounted electronic equipment by detecting the light intensity of the surrounding environment and utilizing output voltage.

The optical sensor is installed behind the front windshield, the weather condition data before the truck enters the tunnel is detected by utilizing the refraction principle of light of the optical sensor, a beam of conical light is emitted through the light emitting diode in the optical sensor, and passes through the windshield; when the truck enters the tunnel, rain and snow exist in the windshield of the truck, a part of light rays deviate, the total quantity of light received by the sensor is reduced, and the weather condition before entering the tunnel is obtained; the size of rain and snow before the truck enters the tunnel can be obtained by utilizing the area size of the reflected light received by the optical sensor.

Step two: detecting surrounding moving object information when a truck is about to enter a tunnel based on vehicle system data, and calculating and analyzing detected surrounding moving objects;

in the embodiment of the invention, a truck blind spot monitoring system is arranged on left and right rearview mirrors or positions of sensors comprising cameras, short wave radars, ultrasonic sensors and the like to sense rear blind spot information, whether obstacles exist in a truck blind spot is monitored by using a technical mode of camera visual images, images in the blind spot are acquired by using a lens, and then the images are processed into digital signals by an internal photosensitive component and the like, so that moving objects in the truck blind spot are sensed;

the method for detecting the moving objects approaching the periphery comprises the following steps of: the ultrasonic sensor emits sound wave pulse through resonance work of the piezoelectric wafer, the ultrasonic sensor starts timing while emitting, ultrasonic waves propagate in the air and immediately reflect back when encountering obstacles, the ultrasonic receiver immediately stops timing after receiving the reflected waves, and the distance between a truck and the obstacles can be obtained according to the fact that the propagation speed of the ultrasonic waves in the air is 340m/s and the time recorded by the timer is tWherein L is the distance between the truck and the obstacle, 340 is the approximate speed of the ultrasonic wave propagating in the air, 1 is the time taken for the ultrasonic sensor to reflect and receive the acoustic wave;

the main working principle is that after the radar equipment transmits electromagnetic wave signals, if the radar signals are touched by the obstacles in the blind area, echo signals are reflected, the radar receiver receives the echo signals, and distance data, direction data and speed data of the related obstacles are extracted through the received reflected wave signals; the method comprises the steps of utilizing high pulse with a certain repetition period emitted by electromagnetic waves, and reflecting a reflected wave R after encountering an obstacle to obtain distance data of R=1/2 c R between a truck and the obstacle, wherein c is the speed of light, and R is the time difference between the emitted wave and the reflected wave; the carrier frequency of the echo signal received by the radar is shifted relative to the carrier frequency of the transmitted signal, so that speed data of an obstacle relative to the truck can be obtained,where ∈b is the frequency of the echo signal and ∈0 is the frequency up to the transmit signal; v is the radial velocity relative to the radar; let ∈a be the signal wavelength; and measuring specific azimuth data information of the obstacle in the dead zone of the truck according to the antenna pattern of the radar.

Step three: judging collision trend of the truck and surrounding moving objects according to the analyzed result data, and identifying specific obstacle data information;

in the embodiment of the invention, when a truck runs in a tunnel, as the running track of front and rear wheels is inconsistent, the inner wheel difference can appear, and the obstacles in the blind area of the inner wheel difference are difficult to observe, so that traffic accidents are easy to cause, the occurrence of the accidents of vehicles is prevented, the related information data of the vehicles and surrounding environment in the process of acquiring the data of the vehicles entering the tunnel, including the related information data of the perceived tunnel wall, the vehicles and the surrounding environment obstacles, is adopted, the obstacles in the blind area are tracked and identified when the truck runs, the detection tracking is carried out on the obstacles by adopting a particle filter algorithm, the speed of target tracking is improved by fusing low rank representation, the driver is warned according to the tracking result and the obstacle distance, and the driver is reminded of keeping the safe vehicle distance.

The information of the external environment when the truck runs in the tunnel, which is obtained through analysis, comprises light intensity data and weather condition data, and if the truck is limited to run in the tunnel with weak light intensity, the information of the external environment is obtained through analysis; judging whether a moving object exists around a truck or not by utilizing a technical mode of acquiring images by utilizing a camera, if the camera identifies the existence of the moving object in a truck blind area, calculating the distance between the truck and the moving object by utilizing the time difference of transmitting and receiving ultrasonic waves of an ultrasonic sensor, analyzing the specific azimuth and the running speed of the moving object by utilizing the transmitting and receiving electromagnetic wave signals of a short wave radar, when a tunnel lane is identified to be a bidirectional double channel by utilizing a navigator, knowing that the distance between the moving object and the truck in the tunnel is more than 100 meters according to the specificity of the external environment of the tunnel, respectively calculating the distance between the moving object and the truck, the specific azimuth and the running speed, dividing the distance between the moving object and the truck into a plurality of segments according to the distance between the surrounding moving object and the truck, utilizing a data storage control unit to record the obtained data information of the moving object, analyzing the continuous fluctuation of the distance between the moving object and the truck along with the time change when the distance between the moving object and the truck is less than 1.5 meters in the blind area, and even the trend of collision exists, and the identified moving object is the vehicle at the moment, and the executing signal acousto-optic reminding of the driver to give a corresponding solution to an executing unit immediately; when the speed of the moving object in the dead zone is in relative speed with the truck, and the distance between the moving object and the truck is hardly changed along with the linear movement of the truck, the identified moving object is a tunnel wall at the moment, and no response is needed;

exemplary, the method for identifying specific obstacle data information is as follows: the existence and fuzzy position of the obstacle are identified by the camera in the sensing unit, the electromagnetic wave signal emitted by the radar is utilized, and when the signal is touchedWhen the obstacle is touched, electromagnetic waves are reflected to the radar receiver, and the distance between the truck and the obstacle is calculated according to the back-and-forth difference between the emitted waves and the reflected waves; the moving state and the moving speed of the obstacle are determined according to the different phases of echo signals under the transmission of a plurality of pulses by utilizing electromagnetic waves with different frequencies and wavelengths transmitted by the radar,wherein v represents the speed of the obstacle, A identifies the amplitude of the vibration, +.>Representing phase; the specific positions of the obstacles are determined by establishing a radar coordinate system and a camera coordinate system, measuring points under the radar coordinate system are converted into pixel coordinate systems corresponding to the cameras through coordinates to realize synchronous operation of multiple sensors, accurate position data are obtained, and the difficulty in identifying different obstacles is reduced; the acquired data information is stored in a data storage module, comparison analysis is carried out according to the acquired data of the obstacle, if the speed of the obstacle is relative to the speed of the truck, the obstacle is a tunnel wall, and an execution unit is not needed; if the distance between the obstacle and the truck changes in real time along with time, the obstacle is a vehicle, an execution signal is transmitted to an execution unit, and an audible and visual alarm is used for reminding a driver of safe driving;

step four: according to the external environment and specific data of the obstacle, automatically analyzing and controlling the speed and direction change which should be adopted by the truck under different conditions;

in the embodiment of the invention, the length of a truck, the real-time running speed and the steering wheel angle are acquired through the vehicle-mounted electronic equipment, and the position, the distance and the running speed of the obstacle acquired by the sensor and the specific data of the truck acquired by the vehicle-mounted electronic equipment are transmitted to the electronic control module; according to the movement trend of the obstacle, different countermeasures are taken, when the length of the truck is smaller than 10 meters and the running speed is larger than 50km/h, and the steering wheel has a slight left angle, the truck approaches to the left lane line at the moment, the sensor recognizes that the obstacle appears in the left full blind area of the truck, the distance between the obstacle and the truck is smaller than 2 meters, the data control module analyzes the trend that the two sides can collide at the moment according to specific data of the obstacle and the truck, immediately calculates the speed direction change which the truck should take, sends an execution command to the execution module, the execution module immediately sends an alarm to remind a driver that an object approaches in the blind area, controls the steering wheel to deviate in a direction away from the obstacle while keeping the speed stable, and increases the distance between the steering wheel and the obstacle, and if the running speed of the truck is smaller than 30km/h, at the moment, the execution module also needs to control the steering wheel to accelerate as soon as possible, keep away from the obstacle and increase the safety distance; when the length of the truck is greater than 10 meters and the running speed is greater than 50km/h, if an obstacle appears in a dead zone and the truck has a tendency of deviation of the obstacle, the truck is controlled to be lower than 50km/h firstly according to data control analysis, the reverse rotation of the steering wheel within 20 degrees is maintained, the obstacle is kept away, and the collision of the tail of the truck to the obstacle caused by the rotation of the steering wheel when the speed is too high is prevented. According to different conditions, the data control module analyzes the calculated different results, and then outputs the results to the execution module in a mode of executing a command, so that the audible and visual alarm reminds and displays that objects in the blind area are close to a driver through the central control display screen, and the speed controller module automatically controls the speed and the steering wheel to enlarge the safety distance;

the information of the type, the position and the distance of the obstacle, the speed of the vehicle, the accelerator pedal and the like acquired by the sensor are taken as input, the established rule is utilized to analyze the speed control of the truck, finally the execution signal is output, the running speed and the running direction of the truck are controlled, and the active safety control of the truck is realized.

Embodiment two:

fig. 2 is a schematic diagram of module composition of a safety control system based on big data provided in the second embodiment of the present invention, where the truck blind area monitoring system includes:

the external environment collecting module is used for collecting real-time data of light intensity and weather conditions in a specific scene;

the perception information module is used for monitoring whether a moving object exists in a rear visual field blind area of the truck and collecting specific data information of the moving object in the blind area close to the truck;

the electronic control module is used for processing and judging the specific data information of the moving object transmitted by the perception information module and outputting a signal instruction to the execution module;

and the execution module is used for receiving and executing the signal instruction transmitted by the electronic control module.

In some embodiments of the invention, the collecting external environmental information module includes:

the light intensity acquisition module is used for acquiring real-time data of light intensity in a specific scene;

the weather condition acquisition module is used for acquiring real-time data of weather conditions in specific scenes.

In some embodiments of the invention, the perceptual information module comprises:

the camera data acquisition module is used for acquiring whether a moving object exists in a dead zone of a truck or not by adopting a technical mode of images;

the radar data acquisition module is used for monitoring moving objects in dead zones of the truck and acquiring specific data information of the moving objects around the truck by utilizing a method for transmitting and receiving electromagnetic waves;

and the ultrasonic sensor acquisition data module is used for calculating the real-time distance between the moving object and the truck by utilizing the time difference between the transmission and the reception of ultrasonic waves.

In some embodiments of the invention, the electronic control module:

the data storage module is used for storing the moving object data information collected by the record sensing module and the collection external environment module and the tunnel real-time environment data information;

and the data control module is used for storing the recorded data information of the moving object, judging the movement trend of the truck and the moving object and the data information of the moving object, and transmitting an execution signal to the execution unit.

In some embodiments of the invention, the execution module comprises:

the sound alarm module is used for receiving the execution command of the electronic control unit and providing sound prompt for a driver;

the light alarm module is used for receiving the execution command of the electronic control module and displaying dangerous icons in the rearview mirror to a driver;

and the vehicle speed controller module is used for receiving the execution signal of the electronic control module and controlling the running speed and the brake of the truck according to the execution signal.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The safety control method based on big data is characterized by comprising the following steps of: the method comprises the following steps:

step one: collecting external real-time environment data when a truck passes through a tunnel;

step two: detecting surrounding moving object information when a truck is about to enter a tunnel based on vehicle system data, and calculating and analyzing detected surrounding moving objects;

step three: judging collision trend of the truck and surrounding moving objects according to the analyzed result data, and identifying specific obstacle data information;

step four: according to the external environment and specific data of the obstacle, the speed and direction change which should be adopted by the truck under different conditions is automatically analyzed and controlled.

2. The big data based security control method of claim 1, wherein: the step of collecting the external real-time environment data when the truck passes through the tunnel comprises the following steps:

the light sensor is arranged at the position of the front cover air grid, the light intensity of light in the tunnel passing through the truck is detected through the light sensor, the vehicle-mounted electronic equipment is controlled by utilizing the output voltage, and the light intensity data of the truck in the tunnel is obtained;

the optical sensor is arranged behind the front windshield, and the weather condition data before the truck enters the tunnel is detected by utilizing the refraction principle of light of the optical sensor.

3. The big data based security control method of claim 1, wherein: the step of detecting surrounding moving object information when the truck is about to enter a tunnel comprises the following steps:

the method comprises the steps that a truck blind spot monitoring system is arranged on a left rearview mirror and a right rearview mirror, and whether obstacles exist in a truck blind spot is monitored by utilizing a camera visual image technology mode;

the ultrasonic sensor is arranged on the side face of the truck, and the distance L between the truck and the obstacle in the blind area is calculated by utilizing the time difference of ultrasonic reflection and reception of the ultrasonic sensor.

4. The big data based security control method of claim 1, wherein: the step of measuring and analyzing the detected moving objects approaching around comprises the following steps:

the short wave radar is arranged at the side of a truck or at the position of a rear bumper, the distance, direction and speed information of an obstacle are analyzed by utilizing electromagnetic wave signals transmitted and received by the short wave radar, and specific azimuth data information of the obstacle in a dead zone of the truck is measured according to an antenna pattern of the radar.

5. The big data based security control method of claim 1, wherein: the step of identifying specific obstacle data information includes:

transmitting the acquired data of the obstacle to a data storage module for comparison analysis, and if the speed of the obstacle is in relative speed with the truck, determining that the obstacle is a tunnel wall, and eliminating the need of continuous execution and releasing the alarm; if the distance between the obstacle and the truck changes in real time along with time, the obstacle is a vehicle, an execution command is transmitted to the execution unit, and the audible and visual alarm is used for reminding a driver of safe driving.

6. The big data based security control method of claim 1, wherein: the steps for analyzing and controlling the speed and direction change which the truck should take under different conditions comprise the following steps:

the method comprises the steps of taking information such as the type, position and distance of an obstacle acquired by a sensor, the speed and the length of a vehicle, the rotating angle of a steering wheel and the like acquired by vehicle-mounted electronic equipment as input, analyzing the speed control of a truck by utilizing established rules, and finally outputting an execution command to an execution module, so that an audible and visual alarm reminds and displays that objects are close to each other in a blind area to a driver through a central control display screen, a speed controller module automatically controls the speed and the steering wheel, and the safety distance is increased, thereby realizing active safety control of the truck.

7. Safety control system based on big data, its characterized in that: the system comprises:

the external environment collecting module is used for collecting real-time data of light intensity and weather conditions in a specific scene;

the sensing module is used for monitoring whether a moving object exists in a rear visual field blind area of the truck and collecting specific data information of the moving object in the blind area close to the truck;

the electronic control module is used for processing and judging the specific data information of the moving object transmitted by the perception information module and outputting a signal instruction to the execution module;

and the execution module is used for receiving and executing the signal instruction transmitted by the electronic control module.

8. The big data based security control system of claim 7, wherein: the module for collecting external environment information comprises:

the light intensity acquisition module is used for acquiring real-time data of light intensity in a specific scene;

the weather condition acquisition module is used for acquiring real-time data of weather conditions in specific scenes.

9. The big data based security control system of claim 7, wherein: the perception information module comprises:

the camera data acquisition module is used for acquiring whether a moving object exists in a dead zone of a truck or not by adopting a technical mode of images;

the radar data acquisition module is used for monitoring moving objects in dead zones of the truck and acquiring specific data information of the moving objects around the truck by utilizing a method for transmitting and receiving electromagnetic waves;

and the ultrasonic sensor acquisition data module is used for calculating the real-time distance between the moving object and the truck by utilizing the time difference between the transmission and the reception of ultrasonic waves.

10. The big data based security control system of claim 7, wherein: the electronic control module includes:

the data storage module is used for storing the moving object data information collected by the record sensing module and the collection external environment module and the tunnel real-time environment data information;

the data control module is used for storing the recorded data information of the moving object, judging the movement trend of the truck and the moving object and the data information of the moving object, and transmitting an execution signal to the execution unit;

the execution module comprises:

the sound alarm module is used for receiving the execution command of the electronic control unit and providing sound prompt for a driver;

the light alarm module is used for receiving the execution command of the electronic control module and displaying dangerous icons in the rearview mirror to a driver;

and the vehicle speed controller module is used for receiving the execution signal of the electronic control module and controlling the running speed and the brake of the truck according to the execution signal.