A vehicle operation safety control method, device and system

Abstract

The application relates to the technical field of monitoring program control, in particular to a vehicle operation safety control method, device and system, which obtains current attribute information of a to-be-monitored vehicle and public equipment attribute information in a smart operation area, clusters the public equipment according to the current attribute information; continuously feeds the public equipment attribute information into a neural network model which has been trained to predict the travel route of the to-be-monitored vehicle, and continuously evaluates the end point information of the travel route of each to-be-monitored vehicle; according to the probability that the end point information belongs to the corresponding public equipment cluster, adopts a corresponding processing strategy for the to-be-monitored vehicle. The application realizes operation area monitoring by combining path prediction and behavior detection on the basis of image detection, and adaptively selects a corresponding protection mechanism according to the type of the public equipment, so as to meet the monitoring demand of the smart operation area with an increasing number of functions.

Description

Technical Field

[0001] This application relates to the field of monitoring program control technology, and in particular to a method, device and system for vehicle operation safety control. Background Technology

[0002] Currently, car driving mainly relies on the driver's visual recognition and manual judgment. Due to limitations imposed by natural environmental factors such as poor visibility, rain, snow, fog, sandstorms, and nighttime, as well as individual differences among drivers, the recognition and judgment of the driving environment and vehicles ahead often go astray, leading to traffic accidents such as collisions and rear-end collisions.

[0003] With the rise in people's living standards and the development of automotive technology, people's requirements for operating areas have become more diversified. For example, they have added functions such as charging piles, automatic vehicle locks, directions for parked vehicles, and parking space availability indicators, rather than just parking. However, this has also revealed some drawbacks. People are not actually aware of some of the new functions added to operating areas and often act on their own understanding, which can actually damage the property of the operating area.

[0004] In response, we believe that traditional monitoring solutions are no longer sufficient to meet the monitoring needs of increasingly sophisticated smart operation areas, and a more intelligent and comprehensive monitoring solution is required. Summary of the Invention

[0005] To achieve the above objectives, this application provides the following technical solution: According to a first aspect of the present invention, the present invention claims protection for a vehicle operation safety control method, comprising: Obtain the current attribute information of the vehicle to be monitored, the attribute information of public equipment in the smart operation area, and other vehicle operation information, and cluster the public equipment based on the current attribute information; The public equipment attribute information is continuously fed into the pre-trained neural network model to predict the travel route of the vehicle to be monitored, and the destination information and passing vehicles of each vehicle to be monitored are continuously evaluated. Based on the probability that the destination information belongs to the corresponding public equipment cluster and the dangerous or abnormal situation of the passing vehicle, a corresponding processing strategy is adopted for the vehicle to be monitored.

[0006] Furthermore, acquiring the current attribute information of the vehicle to be monitored, the attribute information of public equipment in the smart operation area, and other vehicle operation information, and clustering the public equipment based on the current attribute information, also includes: The current attribute information of the vehicle to be monitored includes at least: Gender, age, method of entering the operating area, role in the method of entering the operating area, path moved within the operating area, and actions performed within the operating area; The public equipment attribute information includes at least the location information of the public equipment in the operating area and the metadata information of the public equipment; The other vehicle operation information includes at least the operating speed of the other vehicles and their real-time distance from the vehicle to be monitored; Based on the current attribute information, the public equipment is clustered into Class I public equipment, Class II public equipment, or Class III public equipment according to its hazard level. The first type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is greater than a first threshold. The second type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is no greater than the first threshold and greater than the second threshold; The third type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is no greater than the second threshold. The first threshold is greater than the second threshold.

[0007] Furthermore, based on the probability that the endpoint information belongs to the corresponding public equipment cluster, it also includes: The endpoint information is not from any public equipment; The endpoint information is for Class I public facilities; The endpoint information is for Class II public facilities; The endpoint information is for Class III public facilities.

[0008] Furthermore, when the destination information is not any public equipment, no processing is performed on the vehicle to be monitored; When the endpoint information is a Class I public equipment, the vehicle to be monitored is subjected to behavior recognition. When it is identified that the vehicle under monitoring is misoperating or damaging the first type of public equipment, a relevant prompt message is sent to the security personnel to stop the behavior of the vehicle under monitoring in a timely manner. When the endpoint information is a second type of public equipment, the distance between the vehicle to be monitored and the second type of public equipment is continuously determined. When the distance is lower than the distance threshold, the behavior of the vehicle to be monitored is identified. When it is identified that the vehicle under monitoring is misoperating or damaging the second type of public equipment, a relevant prompt message is sent to the security personnel to stop the behavior of the vehicle under monitoring in a timely manner. When the endpoint information is a third-class public equipment, the usage status of the third-class public equipment is obtained, and corresponding emergency handling measures are taken based on the usage status of the third-class public equipment.

[0009] Furthermore, when the endpoint information is a third type of public equipment and the third type of public equipment is in use, the distance between the vehicle to be monitored and the third type of public equipment is continuously determined. When the distance is lower than the distance threshold, the third type of public equipment is controlled to stop working. The monitoring vehicle is subjected to behavior recognition. When the monitoring vehicle is identified to be performing a harmful action, the third type of public equipment is controlled to operate in a safe state.

[0010] Furthermore, the dangerous abnormal situation of the passing vehicle also includes: The vehicle that was traveling in the distance braked suddenly. The vehicle was observed to skid and drift as it passed by. There is a risk of collision between the passing vehicle and the vehicle to be monitored; There is a risk of a rear-end collision between the passing vehicle and the vehicle to be monitored.

[0011] According to a second aspect of the present invention, the present invention claims protection for a vehicle operation safety control device, including a camera system, a central control center, and public equipment; The vehicle operation safety control device is used to execute the vehicle operation safety control method.

[0012] According to a third aspect of the present invention, the present invention claims protection for a vehicle operation safety control system, comprising: One or more processors; A memory that stores one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the vehicle operation safety control method.

[0013] This application relates to the field of monitoring program control technology, and more particularly to a vehicle operation safety control method, device, and system. The method involves acquiring the current attribute information of the vehicle to be monitored and the attribute information of public equipment in a smart operation area; clustering the public equipment based on the current attribute information; continuously feeding the public equipment attribute information into a pre-trained neural network model to predict the travel routes of the vehicles to be monitored, and continuously evaluating the destination information of each vehicle's travel route; and applying corresponding processing strategies to the vehicles to be monitored based on the probability that the destination information belongs to the corresponding public equipment cluster. This invention combines path prediction and behavior detection on the basis of image detection to achieve operation area monitoring, and adaptively selects corresponding protection mechanisms by classifying public equipment types, meeting the monitoring needs of increasingly functional smart operation areas. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating the process of a vehicle operation safety control method claimed in an embodiment of this application. Figure 2 A schematic diagram of the actual driving state of all vehicles for the vehicle operation safety control method claimed in this application embodiment; Figure 3 A schematic diagram of the actual driving state of a vehicle as claimed in an embodiment of this application for a vehicle operation safety control method; Figure 4 This is the actual display interface of a vehicle operation safety control method claimed in the embodiments of this application. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0016] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0017] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0018] According to the first embodiment of the present invention, referring to Figure 1 This invention claims protection for a vehicle operation safety control method, comprising: Obtain the current attribute information of the vehicle to be monitored, the attribute information of public equipment in the smart operation area, and other vehicle operation information, and cluster the public equipment based on the current attribute information; The public equipment attribute information is continuously fed into the pre-trained neural network model to predict the travel route of the vehicle to be monitored, and the destination information and passing vehicles of each vehicle to be monitored are continuously evaluated. Based on the probability that the destination information belongs to the corresponding public equipment cluster and the dangerous or abnormal situation of the passing vehicle, a corresponding processing strategy is adopted for the vehicle to be monitored.

[0019] In this embodiment, vehicle parameter and vehicle location transmitters are installed on all vehicles to continuously transmit the vehicle's own status parameters in real time. The transmitted information includes relevant parameters that have a significant impact on driving safety, such as vehicle type, vehicle weight, speed, and location.

[0020] The preferred radio wave transmission method for communication is one with a transmission distance of about 500m (based on existing road design speed, vehicle speed, vehicle braking distance and other technical conditions, and considering appropriate improvement of safety assurance, a transmission distance of about 500m can meet the requirements of vehicle operation safety control). Existing mature, stable and anti-interference-capable radio communication technology is selected.

[0021] Furthermore, the step of acquiring the current attribute information of the vehicle to be monitored, the attribute information of public equipment in the smart operation area, and other vehicle operation information, and clustering the public equipment based on the current attribute information, further includes: The current attribute information of the vehicle to be monitored includes at least: Gender, age, method of entering the operating area, role in the method of entering the operating area, path moved within the operating area, and actions performed within the operating area; The public equipment attribute information includes at least the location information of the public equipment in the operating area and the metadata information of the public equipment; The other vehicle operation information includes at least the operating speed of the other vehicles and their real-time distance from the vehicle to be monitored; Each vehicle in operation receives information from other vehicles within its surrounding area, including vehicle type, weight, speed, and location. The range of information received is the same as the transmission distance of the radio waves used to send the information.

[0022] Based on the current attribute information, the public equipment is clustered into Class I public equipment, Class II public equipment, or Class III public equipment according to its hazard level. The first type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is greater than a first threshold. The second type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is no greater than the first threshold and greater than the second threshold; The third type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is no greater than the second threshold. The first threshold is greater than the second threshold.

[0023] Each vehicle analyzes and processes the information received from other vehicles, and combines it with precise positioning analysis to retain only the information of vehicles related to its own direction of travel, while filtering out the information of vehicles unrelated to its own direction of travel; at the same time, it analyzes the trajectory information of vehicles related to its own direction of travel.

[0024] Reference Figure 2 and 3In this embodiment, by analyzing the running trajectory of the vehicle to be monitored, the actual driving status of all vehicles within the signal receiving range can be obtained, and the actual driving status of vehicles related to the direction of travel of this vehicle can be analyzed.

[0025] In this embodiment, the central control system first performs facial recognition on the images returned by the camera system to identify all individuals in the smart operation area. Then, it continuously identifies relevant information for each individual based on the images. The relevant information mainly includes: gender (male / female), age (adult / child / elderly), mode of entry into the operation area (walking / driving), role in the mode of entry into the operation area (this mainly classifies passengers and drivers in the case of driving), the path moved in the operation area, and the actions performed in the operation area.

[0026] Based on each individual's relevant information, all public equipment in the smart operation area is categorized into three levels according to their hazard level. The first category consists of equipment the individual is highly likely to encounter, such as charging stations and warning devices next to their parking space. The second category consists of equipment the individual would normally not touch, such as car locks on other people's parking spaces. The third category consists of equipment the individual would have virtually no motivation to actively touch under normal circumstances; this mainly includes other public equipment currently in use and equipment permitted only under specific conditions.

[0027] These three categories of public facilities are all relative to an individual; that is, the classification of these three types of facilities will be different for different individuals.

[0028] Furthermore, the probability of belonging to the corresponding public equipment cluster based on the endpoint information also includes: The endpoint information is not from any public equipment; The endpoint information is for Class I public facilities; The endpoint information is for Class II public facilities; The endpoint information is for Class III public facilities.

[0029] In this embodiment, the location information of all public equipment in the operating area and the relevant information of individuals are continuously fed into a pre-trained neural network model to predict the individual's travel route and continuously evaluate the probability that the destination of each individual's travel route is various public equipment. For example, for an individual who has just gotten out of the driver's seat of an electric vehicle and needs to charge the vehicle, the probability that the destination of the travel route is a charging pile near the parking space is theoretically the highest, while the probability of going to a charging pile that is charging in another parking space should be zero.

[0030] Furthermore, when the destination information is not any public equipment, no processing is performed on the vehicle to be monitored.

[0031] In this embodiment, no action is taken when it is determined that the individual's journey destination is not any public facility. This typically occurs when the individual directly passes through or exits the operating area, or when there are service areas such as shops or parcel racks within the operating area, and the individual is simply there to buy something or pick up a package.

[0032] The system displays information about vehicles ahead of the vehicle on the screen, providing the driver with intuitive identification and judgment. This display system integrates with existing electronic maps and navigation systems, showing relevant vehicles as red dots (or other prominent forms) on the electronic map.

[0033] Reference Figure 4 The system comprehensively analyzes and judges information about vehicles related to the direction of travel of the vehicle. If the vehicle in front exhibits abnormal trajectory (sudden lateral change, lateral instability, longitudinal instability), rapid deceleration, or abnormal vehicle density on the road (greater than normal driving density, high density, slow movement, or stopping), the system will issue an alarm to the driver. The alarm can be issued simultaneously using multiple forms such as sound, light, text, and voice, and the urgency of the sound and light alarm can be adjusted according to the distance between the vehicle and the abnormal information.

[0034] Based on the information displayed by the information and alarm systems, the driver makes judgments and takes corresponding driving actions. When there are no abnormalities in the information about vehicles ahead, the driver controls the vehicle normally and safely controls the vehicle according to the information about vehicles ahead displayed on the electronic map. When there are abnormalities in the information about vehicles ahead, the driver controls the vehicle to slow down or brake, and safely controls the vehicle according to the information about vehicles ahead displayed on the electronic map and the urgency of the alarm. If necessary, emergency braking measures should be taken to ensure safety.

[0035] Furthermore, when the endpoint information is a first-class public equipment, behavior recognition is performed on the vehicle to be monitored; When it is identified that the vehicle under monitoring is misoperating or damaging the first type of public equipment, a relevant prompt message is sent to the security personnel to stop the behavior of the vehicle under monitoring in a timely manner.

[0036] In this embodiment, when an individual's travel route is identified as ending at a Class I public facility, it indicates that the area is relatively safe. There is no need to judge the distance; only behavioral recognition is performed. When misoperation or damage to the public facility is detected, relevant prompts are sent to security personnel to promptly stop the individual's behavior, thereby protecting the Class I public facility.

[0037] Furthermore, when the endpoint information is a second type of public equipment, the distance between the vehicle to be monitored and the second type of public equipment is continuously determined. When the distance is lower than the distance threshold, behavior recognition is performed on the vehicle to be monitored. When it is identified that the vehicle under monitoring is misoperating or damaging the second type of public equipment, a relevant prompt message is sent to the security personnel to stop the behavior of the vehicle under monitoring in a timely manner.

[0038] In this embodiment, when an individual's travel route is identified as ending at a second-class public facility, indicating low security, a distance judgment is added to the above logic. The central control center continuously judges the distance between the individual and the public facility based on the images returned by the camera. When the distance is below a threshold, behavior recognition is performed based on the image. When misoperation or damage to the public facility is detected, relevant prompts are sent to security personnel to stop the individual's behavior in a timely manner, thereby protecting the second-class public facility.

[0039] Furthermore, when the endpoint information is a third type of public equipment, the usage status of the third type of public equipment is obtained, and corresponding emergency handling measures are taken based on the usage status of the third type of public equipment.

[0040] Furthermore, when the endpoint information is a third type of public equipment and the third type of public equipment is in use, the distance between the vehicle to be monitored and the third type of public equipment is continuously determined. When the distance is lower than the distance threshold, the third type of public equipment is controlled to stop working. The monitoring vehicle is subjected to behavior recognition. When the monitoring vehicle is identified to be performing a harmful action, the third type of public equipment is controlled to operate in a safe state.

[0041] In this embodiment, when an individual's travel route is identified as ending at a third-class public device, and the public device at the end point is locked, the central control center will select different processing mechanisms based on the category of the end-point device.

[0042] If the public equipment at the destination is one that the individual is currently using, such as a charging station, the system continuously determines the individual's distance from the public equipment based on the images returned by the camera. If the distance is below a threshold, the central control center immediately issues a command to the public equipment to stop operating, in order to prevent the individual from performing dangerous operations on the operating public equipment and posing a risk of electric shock. At the same time, the system begins to perform motion recognition on the individual based on the images to determine whether the individual is continuing to perform harmful actions on the public equipment. If it is determined that the individual is performing harmful actions, the system continues to issue commands to control the public equipment to return to its initial state. This is to prevent the individual from forcibly changing the state of the public equipment and damaging it.

[0043] If the public equipment at the destination is public equipment that is only allowed to be used under specific circumstances, the distance between the individual and the public equipment will be continuously judged based on the images returned by the camera. If the judgment result is that the distance is lower than the threshold, all images returned by the cameras will be traversed to determine whether the specific situation, such as a fire, has occurred in the operating area. If the specific situation does not exist, a prompt message will be sent to the relevant security personnel in a timely manner to stop the individual's behavior. If the specific situation exists, a prompt message for the specific situation will be sent to the security personnel, such as a prompt that there is a fire.

[0044] Furthermore, the dangerous abnormal situation of the passing vehicle also includes: The vehicle that was traveling in the distance braked suddenly. The vehicle was observed to skid and drift as it passed by. There is a risk of collision between the passing vehicle and the vehicle to be monitored; There is a risk of a rear-end collision between the passing vehicle and the vehicle to be monitored.

[0045] According to a second embodiment of the present invention, the present invention claims protection for a vehicle operation safety control device, including a camera system, a central control center, and public equipment; The public facilities include at least: smart car locks, smart fire protection systems, parked vehicle route indication devices, vacant parking space indication devices, and charging piles; The vehicle operation safety control device is used to execute the vehicle operation safety control method.

[0046] In this embodiment, the camera system mainly includes multiple cameras, which are set up in various corners of the smart operation area to monitor the situation in various parts of the smart operation area and transmit the corresponding images back to the central control center.

[0047] The central control center mainly communicates and interacts with various public devices set up in the smart operation area. The diagram only shows some of the commonly used public devices in the smart operation area (smart car lock, smart fire extinguishing system, parked vehicle route indication device, empty parking space indication device, charging pile). In fact, there can be many more types of public devices.

[0048] According to a third embodiment of the present invention, the present invention claims protection for a vehicle operation safety control system, comprising: One or more processors; A memory that stores one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the vehicle operation safety control method.

[0049] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0050] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0051] The specific embodiments of the invention have been described in detail above, but they are only examples, and this application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this application. Therefore, all equivalent changes, modifications, and improvements made without departing from the spirit and principles of this application should be covered within the scope of this application.

Claims

1. A method for controlling vehicle operation safety, characterized in that, include: Obtain the current attribute information of the vehicle to be monitored, the attribute information of public equipment in the smart operation area, and other vehicle operation information, and cluster the public equipment based on the current attribute information; The public equipment attribute information is continuously fed into the pre-trained neural network model to predict the travel route of the vehicle to be monitored, and the destination information and passing vehicles of each vehicle to be monitored are continuously evaluated. Based on the probability that the destination information belongs to the corresponding public equipment cluster and the dangerous or abnormal situation of the passing vehicle, a corresponding processing strategy is adopted for the vehicle to be monitored.

2. The vehicle operation safety control method as described in claim 1, characterized in that, Acquiring the current attribute information of the vehicle to be monitored, the attribute information of public equipment in the smart operation area, and other vehicle operation information, and clustering the public equipment based on the current attribute information, the method further includes: The current attribute information of the vehicle to be monitored includes at least: Gender, age, method of entering the operating area, role in the method of entering the operating area, path moved within the operating area, and actions performed within the operating area; The public equipment attribute information includes at least the location information of the public equipment in the operating area and the metadata information of the public equipment; The other vehicle operation information includes at least the operating speed of other vehicles and their real-time distance from the vehicle to be monitored; Based on the current attribute information, the public equipment is clustered into Class I public equipment, Class II public equipment, or Class III public equipment according to its hazard level. The first type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is greater than a first threshold. The second type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is no greater than the first threshold and greater than the second threshold; The third type of public equipment refers to public equipment whose contact probability with the vehicle under normal circumstances is no greater than the second threshold. The first threshold is greater than the second threshold.

3. The vehicle operation safety control method as described in claim 1, characterized in that, Based on the probability that the endpoint information belongs to the corresponding public equipment cluster, it also includes: The endpoint information is not from any public equipment; The endpoint information is for Class I public facilities; The endpoint information is for Class II public facilities; The endpoint information is for Class III public facilities.

4. The vehicle operation safety control method as described in claim 3, characterized in that, When the destination information is not any public equipment, no processing is performed on the vehicle to be monitored; When the endpoint information is a first-class public equipment, the vehicle to be monitored is subjected to behavior recognition. When it is identified that the vehicle under monitoring is misoperating or damaging the first type of public equipment, a relevant prompt message is sent to the security personnel to stop the behavior of the vehicle under monitoring in a timely manner. When the endpoint information is a second type of public equipment, the distance between the vehicle to be monitored and the second type of public equipment is continuously determined. When the distance is lower than the distance threshold, the behavior of the vehicle to be monitored is identified. When it is identified that the vehicle under monitoring is misoperating or damaging the second type of public equipment, a relevant prompt message is sent to the security personnel to stop the behavior of the vehicle under monitoring in a timely manner. When the endpoint information is a third-class public equipment, the usage status of the third-class public equipment is obtained, and corresponding emergency handling measures are taken based on the usage status of the third-class public equipment.

5. The vehicle operation safety control method as described in claim 4, characterized in that, When the endpoint information is a third-class public device and the third-class public device is in use, the distance between the vehicle to be monitored and the third-class public device is continuously determined. When the distance is lower than the distance threshold, the third-class public device is controlled to stop working. The monitoring vehicle is subjected to behavior recognition. When the monitoring vehicle is identified to be performing a harmful action, the third type of public equipment is controlled to operate in a safe state.

6. The vehicle operation safety control method as described in claim 4, characterized in that, The dangerous and abnormal situations involving the passing vehicles also include: The vehicle that was traveling in the distance braked suddenly. The vehicle was observed to skid and drift as it passed by. There is a risk of collision between the passing vehicle and the vehicle to be monitored; There is a risk of a rear-end collision between the passing vehicle and the vehicle to be monitored.

7. A vehicle operation safety control device, characterized in that, Including camera systems, central control center, and public equipment; The vehicle operation safety control device is used to execute the vehicle operation safety control method as described in any one of claims 1-6.

8. A vehicle operation safety control system, characterized in that, include: One or more processors; A memory having stored one or more programs that, when executed by one or more processors, cause the one or more processors to implement a vehicle operation safety control method according to any one of claims 1 to 6.

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