Road traffic protection facility control method and system, server and medium

Abstract

The invention discloses a road traffic protection facility control method and system, a server and a medium, and relates to the technical field of data processing systems. The method comprises the steps that when an abnormal vehicle exists on a target road, a first variable signboard is controlled to display early warning information; when the abnormal reason of the abnormal vehicle belongs to a preset reason set and the abnormal vehicle is not stopped within a preset stop duration, performing simulation through a digital twin model to obtain a predicted vehicle moving route and a vehicle personnel safety value of each control scheme; when the vehicle personnel safety value exceeds a preset threshold value, a target control scheme and a target predicted vehicle moving route are obtained; under the condition that the target protection facility executes the target control scheme, when the actual vehicle moving route is not matched with the target predicted vehicle moving route, a new control scheme is determined; and after the new control scheme is executed, determining a replacement scheme of the target movable protection facility. By implementing the technical scheme, the overall safety of the road traffic system is improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing systems, and particularly to a control method, system, server, and medium for highway traffic protection facilities. Background Art

[0002] In the modern highway traffic system, traffic protection facilities play a crucial role. It not only concerns the life safety of road users but also has a profound impact on ensuring the smooth operation of the traffic system. With the continuous growth of traffic flow and the continuous increase in vehicle driving speed, more stringent requirements are put forward for the effectiveness and reliability of highway traffic protection facilities.

[0003] Currently, when a vehicle's braking system fails and it cannot stop relying on its own braking ability, in order to quickly stop the vehicle, the vehicle driver generally scratches or collides with the surrounding protection facilities to decelerate the vehicle until it stops.

[0004] However, when the vehicle driver is in a state of extreme tension and panic due to vehicle failure and inability to stop, it is impossible to accurately control the angle, force, and position of scratching or colliding with the protection facilities. As a result, when the vehicle contacts the protection facilities, unpredictable dangerous situations such as rollover and out-of-control rotation are likely to occur, which not only pose a great threat to the driver's own life safety but also are very likely to affect the normal vehicles and pedestrians around, causing serious traffic accidents and affecting the safety and operation efficiency of highway traffic. Summary of the Invention

[0005] This application provides a control method, system, server, and medium for highway traffic protection facilities, which can improve the overall safety of the highway traffic system.

[0006] In a first aspect, the present application provides a method for controlling highway traffic protection facilities. The protection facilities include intelligent guardrails, automatic roadblocks, and variable signboards. The method includes: when an abnormal vehicle is detected on a target highway, controlling a first variable signboard on the target section where the abnormal vehicle is located to display a warning message, where the warning message is the location of the abnormal vehicle, and the target section is one of multiple sections of the target highway; when the abnormal reason of the abnormal vehicle belongs to a preset reason set and the abnormal vehicle has not stopped within a preset stop duration, inputting the current position, driving speed, and driving direction of the abnormal vehicle into a pre-established digital twin model of highway traffic to obtain predicted vehicle movement routes and vehicle personnel safety values corresponding to each control scheme, where the control scheme is used to control the target protection facilities on the target highway to generate friction with the abnormal vehicle so that the abnormal vehicle stops; when there is a vehicle personnel safety value exceeding a preset threshold, obtaining the target control scheme and the target predicted vehicle movement route corresponding to the highest vehicle personnel safety value; when controlling the target protection facilities to execute the target control scheme, when it is detected that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route, re-determining a new control scheme and a new predicted vehicle movement route; after detecting that the target protection facilities have executed the new control scheme, determining a replacement scheme for the target movable protection facilities according to the real-time facility images of each target movable protection facility on the target highway and the historical usage records of all movable protection facilities on the highway.

[0007] By adopting the above technical solution, when an abnormal vehicle is detected, the warning message is timely displayed through the first variable signboard, which can quickly transmit the location of the abnormal vehicle to surrounding vehicles, enabling the drivers of surrounding vehicles to react in advance and effectively avoiding collision accidents such as rear-end collisions caused by untimely information, thereby reducing potential safety hazards at the source. When it is detected that the abnormal vehicle cannot stop on its own, the predicted vehicle movement routes and vehicle personnel safety values based on different control schemes are obtained through simulation by the digital twin model, which can accurately simulate various situations of protection facilities intervention. Then, the target control scheme with the highest vehicle personnel safety value is selected to maximize the safety of the personnel in the abnormal vehicle. At the same time, controlling the protection facilities to execute the target control scheme, without the operation of the vehicle driver, the protection facilities automatically approach the abnormal vehicle and generate scratches or collisions with the abnormal vehicle to make the vehicle stop in time, avoiding more serious accidents caused by improper operation of the vehicle driver, reducing the interference of traffic accidents on the normal traffic flow, and improving the overall safety and operation efficiency of the highway traffic system. After the vehicle stops, the damage problems of the protection facilities that have scratched and collided with the abnormal vehicle are timely obtained, and maintenance and replacement are reasonably arranged to ensure that the protection facilities are always in the best operating state, providing continuous and reliable guarantee for highway traffic safety.

[0008] In some embodiments in combination with some embodiments of the first aspect, when the abnormal cause of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within a preset stop duration, the current position, driving speed, and driving direction of the abnormal vehicle are input into a pre-established digital twin model of road traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control scheme. Specifically, it includes: when the abnormal cause of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within a preset stop duration, obtaining the driving speed, driving direction, and current position of the abnormal vehicle; determining one or more control schemes according to the target protection facilities on the target road and the relative position information between the target protection facilities and the abnormal vehicle; inputting the driving speed, driving direction, current position, and the control scheme into the pre-established digital twin model of road traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control scheme.

[0009] By adopting the above technical solution, the vehicle information and the control scheme are input into the digital twin model to simulate the predicted vehicle movement routes and vehicle personnel safety values corresponding to each scheme. It is like conducting multiple rehearsals in a virtual environment, enabling the system to evaluate the effects of the schemes in advance, screening out the best scheme that can not only ensure the safety of vehicle personnel but also effectively guide the abnormal vehicle to stop, improving the safety and reliability during the handling of abnormal vehicles, accelerating the handling speed of abnormal vehicles, reducing the interference to the normal traffic flow, and enhancing the overall traffic operation efficiency.

[0010] In some embodiments in combination with some embodiments of the first aspect, after detecting that the target protection facility has executed the new control scheme, according to the real-time facility images of each target movable protection facility on the target road and the historical usage records of all movable protection facilities on all roads, determine the replacement scheme for the target movable protection facility. Specifically, it includes: after detecting that the target protection facility has executed the new control scheme, determining the first current health status value of the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road; according to the historical usage records of all movable protection facilities on all roads, counting the total number of repairs and replacements and the second current health status value of other movable protection facilities corresponding to the target movable protection facility except the target movable protection facility among all movable protection facilities on all roads; determining the replacement scheme for each protection facility in the target movable protection facility according to the first current health status value, the total number, and the second current health status value. The replacement scheme includes not replacing the movable protection facility, replacing the other movable protection facility with the target movable protection facility, and replacing with a new movable protection facility.

[0011] Adopting the above technical solution, by determining the first current health status value of the target movable protection facility through the real-time facility image, it can intuitively reflect the actual current situation of the protection facility, providing a basis for judging whether the protection facility needs to be replaced. The replacement plan is determined by comprehensively considering the first current health status value, the total number of times, and the second current health status value, fully taking into account various factors such as the status of the target facility itself and the historical performance of similar facilities. If the health status of the target facility is good, it can be chosen not to be replaced, avoiding unnecessary waste of resources; if the target facility is severely damaged and there is no new facility to replace it, then the movable protection facility on other roads with relatively good status, low usage, and corresponding to the target movable protection facility is allocated for replacement, maximizing the use of existing resources, ensuring that the protection facility is always in the best operating state, continuously providing solid and reliable protection for highway traffic safety, while reducing maintenance costs, improving the utilization efficiency of traffic management resources, and enhancing the overall stability and reliability of the highway traffic system.

[0012] Combined with some embodiments of the first aspect, in some embodiments, after the step of determining the replacement plan of the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road and the historical usage records of the movable protection facilities on all roads after detecting that the target protection facility has executed the new control plan, the method further includes: when the abnormal vehicle stops, acquiring the vehicle image data and the vehicle real-time operation data of the abnormal vehicle; determining the explosion risk value of the abnormal vehicle according to the vehicle image data and the vehicle real-time operation data; when the explosion risk value is greater than or equal to a preset explosion risk threshold, controlling the second variable sign corresponding to the section within the first preset range from the abnormal vehicle on the target road to display a warning message, and the warning message is used to warn other vehicles on the target road except the abnormal vehicle to keep an explosion safety distance from the abnormal vehicle; when the explosion risk value is less than the preset explosion risk threshold, calculating the predicted processing time for moving the abnormal vehicle onto the target trailer according to the driving duration of the target trailer reaching the current position of the abnormal vehicle and the preset vehicle movement duration; determining the display content of the third variable sign corresponding to each section of the target road according to the predicted processing time and the obstacle conditions of each lane in the target section, and the display content is the first content or the second content, the first content is the lanes that can be passed and the lanes that cannot be passed in the target section, and the second content is that the target section is not passable.

[0013] With the above technical solution, when the explosion risk value exceeds the preset threshold, the second variable sign within a specific range is immediately controlled to display a warning message, timely reminding other vehicles to keep a safe distance from the abnormal vehicle, effectively preventing possible explosion accidents, and ensuring the life and property safety of surrounding vehicles and personnel. When the explosion risk value is low, the predicted processing duration is calculated based on the arrival duration of the target trailer and the preset vehicle movement duration, and the display content of the third variable sign is determined in combination with the obstacle conditions of each lane on the target road section. By the display content, the drivers of other vehicles are informed in advance of the time required for handling the abnormal vehicle and the traffic conditions of each lane, helping them plan their driving routes in advance, avoiding congestion or delays caused by ignorance, and reducing the impact on normal traffic order.

[0014] Combined with some embodiments of the first aspect, in some embodiments, after the step of controlling the second variable sign corresponding to the road section within the first preset range from the abnormal vehicle in the target road to display a warning message when the explosion risk value is greater than or equal to the preset explosion risk threshold, the method further includes: obtaining fire extinguisher information within the second preset range from the abnormal vehicle, where the fire extinguisher information includes the position information of the fire extinguisher; controlling the sound playback device closest to the fire extinguisher to play the fire extinguisher information and the position information of the abnormal vehicle.

[0015] With the above technical solution, when it is detected that a vehicle is extremely likely to explode, the fire extinguisher information around the vehicle is obtained in a timely manner, and the fire extinguisher information and the position information of the abnormal vehicle are played through the sound playback device, so that surrounding users can quickly find the fire extinguisher and bring the fire extinguisher to the vicinity of the abnormal vehicle at the first time they hear the information. In the initial stage when the abnormal vehicle explodes or catches fire, fire extinguishing measures are quickly taken to effectively contain the spread of the fire and reduce the possibility and harm degree of the explosion.

[0016] Combined with some embodiments of the first aspect, in some embodiments, determining the display content of the third variable sign corresponding to each road section in the target road according to the predicted processing duration and the obstacle conditions of each lane in the target road section specifically includes: determining the predicted duration for the vehicle to travel from each road section to the target road section according to the average vehicle speed and the road section length corresponding to each road section in the target road; if there is a target predicted duration less than the predicted processing duration in the predicted durations, determining the traffic states of each target lane in the target road section according to the obstacle conditions of each lane in the target road section, where the traffic states include passable and non-passable; if there is a passable target lane, determining the display content of the third variable sign corresponding to the road section with the target predicted duration as the first content; if there is no passable target lane, determining the display content of the third variable sign corresponding to the road section with the target predicted duration as the second content.

[0017] Adopting the above technical solution, by calculating the average vehicle speed and road section length of each section of the target road, the time required for the vehicle to drive towards the target section is accurately estimated, laying a solid time foundation for traffic guidance. When there is a vehicle that will arrive at the target section in a short time and the section is dealing with an abnormal vehicle, the lane traffic status is determined in combination with the lane obstacle situation. If there is a passable lane, the information of the passable and prohibited lanes is displayed through a sign to assist the driver in planning the lane selection in advance and avoid congestion; if there is no passable lane, the driver is informed through a sign that the section is not passable, prompting the driver to detour in advance, improving traffic safety and convenience, optimizing resource allocation, and ensuring the efficient and orderly operation of the highway traffic system.

[0018] Combined with some embodiments of the first aspect, in some embodiments, after the steps of obtaining the target control scheme corresponding to the highest vehicle personnel safety value and the target predicted vehicle movement route when the vehicle personnel safety value exceeds the preset threshold, the method further includes: when there is a traffic light intersection in the target predicted vehicle movement route, obtaining the real-time position of the abnormal vehicle; when the distance between the real-time position and the stop line of the traffic light intersection is within the preset distance range, controlling the traffic light corresponding to the driving direction of the traffic light intersection and the abnormal vehicle to be green.

[0019] Adopting the above technical solution, the real-time position of the abnormal vehicle is obtained. When it is detected that the abnormal vehicle is about to approach the stop line of the traffic light intersection, the traffic light in the corresponding direction is immediately switched to green, allowing the abnormal vehicle to pass through without obstruction. This avoids the situation where the abnormal vehicle collides with the vehicles and pedestrians driving normally in other directions when the traffic light is red and it cannot stop, causing traffic accidents, and improves the overall safety of the highway traffic system.

[0020] Second aspect, an embodiment of the present application provides a protection facility control system, which is characterized by including: a sign control module, configured to control a first variable sign on a target road section where the abnormal vehicle is located to display a warning message when an abnormal vehicle is detected on the target road; a model input module, configured to input the current position, traveling speed, and traveling direction of the abnormal vehicle into a pre-established digital twin model of road traffic to obtain predicted vehicle movement routes and vehicle personnel safety values corresponding to each control plan when the cause of the abnormality of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within a preset stop duration; a target control plan determination module, configured to obtain a target control plan and a target predicted vehicle movement route corresponding to the highest vehicle personnel safety value when there is a vehicle personnel safety value exceeding a preset threshold; a new control plan determination module, configured to re-determine a new control plan and a new predicted vehicle movement route when it is detected that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route while controlling the target protection facility to execute the target control plan; a replacement plan determination module, configured to determine a replacement plan for the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road and the historical usage records of the movable protection facilities of all roads after it is detected that the target protection facility has executed the new control plan.

[0021] Third aspect, an embodiment of the present application provides a protection facility control server, including: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the protection facility control server to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0022] Fourth aspect, an embodiment of the present application provides a computer-readable storage medium, including instructions, when the above instructions run on the protection facility control server, enabling the protection facility control server to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0023] It can be understood that the protection facility control system provided in the second aspect above, the protection facility control server provided in the third aspect, and the storage medium provided in the fourth aspect are all used to execute the method provided by the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, and will not be elaborated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application uses a digital twin model to simulate and obtain the predicted vehicle movement routes and vehicle personnel safety values based on different control schemes. It can accurately simulate various situations of protective facility interventions, select the target control scheme with the highest vehicle personnel safety value, and maximize the safety of personnel in abnormal vehicles. At the same time, it controls the protective facilities to execute the target control scheme without the operation of the vehicle driver. The protective facilities automatically approach the abnormal vehicle and scrape or collide with the abnormal vehicle to stop the vehicle in time, avoiding more serious accidents caused by improper operation of the vehicle driver, reducing the interference of traffic accidents to the normal traffic flow, and improving the overall safety and operation efficiency of the highway traffic system.

[0025] 2. This application uses variable signs to display warning information. When it detects that a vehicle is extremely likely to explode, it promptly reminds other vehicles to keep a safe distance from the abnormal vehicle, effectively preventing possible explosion accidents and ensuring the life and property safety of surrounding vehicles and personnel. At the same time, it plays the information of the fire extinguisher and the location information of the abnormal vehicle through a sound playback device, enabling surrounding users to quickly find the fire extinguisher and bring it to the vicinity of the abnormal vehicle as soon as they hear the information. In the initial stage of an explosion or fire in the abnormal vehicle, they can quickly take fire extinguishing measures, effectively containing the spread of the fire and reducing the possibility and harm degree of the explosion.

[0026] 3. This application obtains the position of the abnormal vehicle in real time. When it detects that the abnormal vehicle is about to approach the stop line of a traffic light intersection, it immediately switches the corresponding traffic light to green, allowing the abnormal vehicle to pass unobstructed. This avoids the situation where the abnormal vehicle collides with normal vehicles and pedestrians in other directions when the traffic light is red and it cannot stop, causing traffic accidents, and improves the overall safety of the highway traffic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a schematic structural diagram of a system architecture to which the highway traffic protection facility control method in an embodiment of this application can be applied; Figure 2 is a schematic flowchart of a highway traffic protection facility control method in an embodiment of this application; Figure 3 is another schematic flowchart of a highway traffic protection facility control method in an embodiment of this application; Figure 4 is a schematic module diagram of a protection facility control system in an embodiment of this application; Figure 5 is a schematic exemplary hardware structure diagram of a protection facility control server in an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular forms "a", "an", "the", "above", "said", "this" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0029] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and should not be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0030] Figure 1 It is a schematic structural diagram of a system architecture to which the highway traffic protection facility control method in the embodiments of the present application can be applied.

[0031] Please refer to Figure 1 , the highway traffic protection facility control system includes protection facilities, traffic lights, and a protection facility control server.

[0032] The protection facility control server, as the core component of the system, is used to analyze and process data such as vehicle driving video image data and real-time operation data obtained by communicating with systems such as the traffic system and the vehicle-mounted system, obtain a control plan for controlling the protection facilities, and send control instructions to the protection equipment and the traffic control system. The traffic lights are used to receive the control instructions forwarded by the server through the traffic control system and change the display state of the traffic lights according to the control instructions. The protection facilities are used to receive the control instructions sent by the server and execute the corresponding control plan according to the control instructions.

[0033] Among them, the protection facilities include intelligent guardrails, automatic roadblocks, collision buffer facilities, variable signs, etc. When the intelligent guardrail detects an abnormal vehicle approaching, it can extend scraping arms with buffer materials but certain rigidity from both sides of the guardrail. When the abnormal vehicle passes by, the scraping arms contact the side of the vehicle, and the vehicle speed is gradually reduced by using the frictional force, and the vehicle is gradually guided to stop. When the automatic roadblock detects an abnormal vehicle approaching, it can quickly rise from the ground. The surface of the roadblock has special anti-slip textures, like densely arranged speed bumps, which will cause a strong bumping feeling when the vehicle passes by, forcing the vehicle speed to drop. The collision buffer facility consists of an intelligent sensing unit, a hydraulic buffer device, and a flexible protection net. When it detects an abnormal vehicle approaching, it can transmit a warning signal to the hydraulic buffer device. The hydraulic device then starts the hydraulic pump and automatically adjusts the force and angle to deploy the protection net according to the vehicle speed. The high-damping rubber coating and memory foam of the protection net cooperate with the damping valve of the hydraulic device to convert the collision kinetic energy into heat energy, making the vehicle stop smoothly. The variable sign can display different warning messages to remind passing vehicles to pay attention to the abnormal vehicle.

[0034] Through the above system architecture, the highway traffic protection facility control system can control the scraping or collision between the protection facilities and the abnormal vehicle according to the generated control plan, so that the abnormal vehicle can stop in time and avoid serious traffic accidents.

[0035] In the related art, when the braking system of a vehicle fails and it cannot stop relying on its own braking ability, in order to quickly stop the vehicle, the vehicle driver generally scrapes or collides with the surrounding protection facilities to decelerate the vehicle until it stops. However, since the vehicle driver will be in an extremely tense and flustered state when the vehicle breaks down and cannot stop, it is impossible to accurately control the angle, force, and position of scraping or colliding with the protection facilities. As a result, when the vehicle contacts the protection facilities, dangerous situations such as unpredictable rollovers and out-of-control rotations are likely to occur, which not only pose a great threat to the life safety of the driver himself, but also are very likely to endanger the vehicles and pedestrians driving normally around, causing serious traffic accidents and affecting the safety and operation efficiency of highway traffic.

[0036] By using the highway traffic protection facility control method in the embodiment of the present application, when it is detected that an abnormal vehicle breaks down and cannot stop relying on its own braking ability, a control plan for the protection facilities is simulated through a pre-established digital twin model of highway traffic, and the protection facilities are controlled to execute the control plan. Without the operation of the vehicle driver, the protection facilities automatically approach the abnormal vehicle and scrape or collide with the abnormal vehicle to make the vehicle stop in time, avoiding more serious accidents caused by improper operation of the vehicle driver, and improving the overall safety and operation efficiency of the highway traffic system.

[0037] The following is combined with Figure 2to illustrate the method of the embodiments of the present application.

[0038] Please refer to Figure 2 , which is a schematic flowchart of a highway traffic protection facility control method in an embodiment of the present application.

[0039] S201. When an abnormal vehicle is detected on the target highway, control the first variable sign on the target section where the abnormal vehicle is located to display a warning message.

[0040] Among them, the warning message is the location of the abnormal vehicle, and the target section is one of multiple sections on the target highway.

[0041] Specifically, first communicate with the traffic monitoring system through the real-time data interaction interface of the traffic management department to obtain the vehicle driving video data on the target highway.

[0042] Then, based on the vehicle driving video data, use an image recognition algorithm to analyze the video data frame by frame. First, split the video data into frames of images in chronological order. Then, use an image recognition algorithm (such as a target detection algorithm based on deep learning, etc.) to process each frame of the image. In the algorithm training stage, a large amount of image data containing normal vehicles and abnormal vehicles (such as vehicles in situations of illegal parking, reverse driving, speeding, turning on the hazard warning flashers, etc.) has been used to train the algorithm, so that the algorithm can accurately identify the characteristics of various abnormal vehicles. During the frame-by-frame analysis process, the algorithm will extract the characteristics of each vehicle in the image and compare and match the extracted characteristics with the characteristics of abnormal vehicles to determine whether the vehicle is an abnormal vehicle. When an abnormal vehicle is detected, in order to ensure the accuracy of the detection result, the algorithm will perform tracking analysis on the abnormal vehicle in multiple consecutive frames of images. When a certain vehicle is detected to meet the characteristics of an abnormal vehicle in several consecutive frames of images, confirm that the vehicle is an abnormal vehicle. After determining the existence of an abnormal vehicle, the algorithm will further determine the specific position coordinates of the abnormal vehicle on the target highway through information such as road signs, markings in the image, and the relative position of the vehicle, in combination with the pre-stored electronic map data of the target highway.

[0043] Next, according to the specific position coordinates of the abnormal vehicle on the target highway and the section division information of the target highway (this information is pre-stored in the storage device and includes information such as the starting point, ending point coordinates, and section numbers of each section), locate the target section where the abnormal vehicle is located.

[0044] Finally, according to the specific position coordinates of the abnormal vehicle, determine the control instruction. Send the control instruction to the variable sign through the wireless communication module. After receiving the control instruction, the variable sign will display the specific position coordinates of the abnormal vehicle on the sign according to the preset display template and font style, reminding passing vehicles to pay attention to avoiding and taking corresponding safety measures.

[0045] S202. When the abnormal cause of the abnormal vehicle belongs to the preset cause set and the abnormal vehicle has not stopped within the preset stop duration, input the current position, driving speed, and driving direction of the abnormal vehicle into the digital twin model of highway traffic established in advance to obtain the predicted vehicle movement route and vehicle personnel safety value corresponding to each control plan.

[0046] Among them, the control plan is used to control the generation of friction between the target protection facilities on the target road and the abnormal vehicle, so that the abnormal vehicle stops. The preset cause set includes abnormal causes such as brake system failures that cause the vehicle to be unable to stop normally. The vehicle personnel safety value refers to the safety value of the user in the abnormal vehicle.

[0047] Specifically, establish a communication connection with the in-vehicle device of the abnormal vehicle through the wireless communication module to obtain the real-time operation data of the vehicle, including but not limited to information such as the vehicle speed, braking state, and vehicle control instructions issued by the driver. Among them, the vehicle control instructions are generated by the vehicle control system. For example, when the driver turns the steering wheel, the steering wheel angle sensor transmits a signal to the control system, and the system generates corresponding steering control instructions based on this signal and information such as the current driving state of the vehicle.

[0048] Determine the abnormal cause based on the real-time operation data provided by the in-vehicle device. For the real-time operation data related to the brake system, compare the pressure value in the brake system in the real-time operation data with the pressure value within the normal working range. If the real-time braking pressure value is lower than the normal range and the vehicle speed has not decreased due to the deceleration instruction issued by the driver, it is determined that the abnormal cause may be a brake system failure. For the vehicle driving direction data, extract the vehicle driving direction data in the real-time operation data. If the driving direction of the vehicle shows an abnormal deviation and does not match the steering operation instruction issued by the driver, it is determined that the vehicle has a steering system failure. For the vehicle driving speed, extract the vehicle real-time speed data in the real-time operation data. If the vehicle speed shows an abnormal rapid increase or decrease without the driver actively issuing an acceleration instruction or a deceleration instruction, it is determined that the vehicle may have a power system failure.

[0049] If communication cannot be established with the in-vehicle system of the abnormal vehicle, the position, speed, driving direction, and other information of the abnormal vehicle are monitored in real time through traffic cameras, radars, or other sensor devices on the road. These devices can capture the driving trajectory, speed changes, and direction offsets of the vehicle. Then, data fusion algorithms (such as the Kalman filter algorithm, Bayesian estimation method, etc.) are used to integrate different types of data obtained from multiple sensors. Next, an abnormal behavior pattern library is constructed by combining historical data with machine learning models (such as decision tree models, neural network models, etc.). Historical data includes various past vehicle abnormal situations and their corresponding operation data. The machine learning model learns and analyzes these historical data to extract the characteristics and rules of vehicle operation data under different abnormal causes. Finally, the operation data of the currently monitored abnormal vehicle is compared with the established abnormal behavior pattern library to determine the abnormal cause of the abnormal vehicle. For example, if the vehicle speed decreases abnormally, the radar detects that the braking distance is significantly shortened, and the road sensor shows that the wheel pressure distribution is uniform, referring to historical data, it is inferred that the vehicle may have a mechanical failure in the braking system.

[0050] When the abnormal cause of the abnormal vehicle belongs to the preset cause set, a timer with a preset stop duration is started. When the timer stops timing, it is determined whether the abnormal vehicle has stopped driving. If so, the steps of S205 below are executed to determine the replacement plan for the movable protection facility. If not, the current position, driving speed, and driving direction of the abnormal vehicle are obtained. It can be obtained by establishing a connection with the in-vehicle system of the abnormal vehicle; it can also be obtained by identifying the driving video data of the abnormal vehicle through an image recognition algorithm. The video data of the section where the abnormal vehicle is located is obtained from the traffic monitoring system, and an advanced image recognition algorithm (such as the object detection and tracking algorithm based on deep learning) is used to analyze each frame of the abnormal vehicle in the video. The driving direction is calculated based on the position change of the vehicle in the image, the driving speed is estimated according to the change in the size of the vehicle in the image and the time interval, and the current position of the vehicle is determined by combining the traffic map data.

[0051] According to the current position, driving direction of the abnormal vehicle, and the relative position relationship between the abnormal vehicle and each protection facility on the road, one or more control plans are determined. According to the current position and driving direction of the abnormal vehicle, the driving lane of the abnormal vehicle is determined. The protection facility correspondence table corresponding to the target road is obtained. The first protection facility set corresponding to the driving lane is found in the correspondence table. According to the current position of the abnormal vehicle and the position coordinates of each protection facility in the first protection facility set, the target protection facilities in the first protection facility set that are directly in front of or on the side of the abnormal vehicle are extracted. One or more control plans matching the target protection facilities are found in the preset control plan set.

[0052] Input the vehicle model, current location, driving speed, driving direction, and control plan of the abnormal vehicle into the pre-established digital twin model of road traffic. The digital twin model of road traffic is constructed based on various data such as the actual geographical information of the target road, specific parameters of protective facilities (such as location, size, material, service life, etc.), real-time status, and the dynamic model of vehicles. Based on a large amount of pre-collected data, this model uses Geographic Information System (GIS) technology to construct a three-dimensional virtual model of the target road, accurately restoring the actual geographical environment of the road. Combining the parameter data of protective facilities, accurately arrange the location and form of protective facilities in the virtual model. Introduce a vehicle dynamic model that can describe the motion state of vehicles under different driving conditions, such as acceleration, deceleration, turning, etc. Combine the vehicle dynamic model with the road virtual model to form a basic model architecture that can simulate the driving of vehicles on the road. After the basic model architecture is constructed, train the model based on a large amount of pre-collected training data. By continuously adjusting the parameters of the model, make the model accurately predict the driving dynamics of the vehicle and the response of protective facilities according to the input vehicle information and road environment parameters. During the training process, adopt the method of supervised learning, compare the prediction results of the model with the actual training data, calculate the error, and update the parameters of the model through the backpropagation algorithm to minimize the prediction error. At the same time, use reinforcement learning technology to enable the model to conduct autonomous learning and decision-making in a simulated traffic environment. By continuously trying different strategies and obtaining rewards based on environmental feedback, optimize the decision-making ability of the model so that it can simulate the actual operation of road traffic, including the driving dynamics of vehicles on the road and the real-time status of protective facilities.

[0053] Based on the input vehicle model, the model retrieves and calls the detailed parameters corresponding to this model vehicle from the built-in vehicle dynamic parameter database. These parameters include but are not limited to the mass, center of gravity position, moment of inertia, friction coefficient between the tire and the ground, suspension system characteristics, etc. of the vehicle. These parameters are the basis for accurately simulating the motion state of the vehicle in various situations.

[0054] Based on the current location of the input abnormal vehicle, the model accurately locates the vehicle's position in the virtual target road scene. The model will refer to the actual geographical information data of the target road, including the road alignment, slope, curvature, etc., and place the vehicle on the corresponding road section and lane.

[0055] Based on the input driving speed and driving direction, the model sets the initial motion state of the vehicle. The model calculates the velocity vector of the vehicle at the initial moment, including the magnitude and direction of the speed. At the same time, combining the dynamic parameters of the vehicle, calculate the force acting on the vehicle in this initial state, such as air resistance, rolling friction, etc.

[0056] Based on the input control scheme, the model will conduct a detailed analysis of it. The control scheme may include various operation instructions for the target protection facility, such as the deformation, opening or closing of the protection facility, etc. The model will perform corresponding simulation operations on the target protection facility in the virtual scenario according to these instructions.

[0057] After the model sets the initial state of the vehicle and the target protection facility needs to execute the control scheme, it starts to simulate the movement process of the vehicle. The model will calculate the position, speed, acceleration and other parameters of the vehicle at each time step in real time according to the vehicle's dynamic equation. At the same time, the model will continuously perform collision detection to determine whether the vehicle collides or rubs against the target protection facility or other objects. When a collision or rubbing event is detected, the model will calculate physical quantities such as the impact force and energy transfer generated during the collision or rubbing process according to the material, shape, speed and other parameters of the vehicle and the protection facility.

[0058] Based on the vehicle's motion simulation and collision detection results, the model will generate a predicted vehicle movement route. The model will record the position changes of the vehicle during the entire simulation process to form a continuous trajectory, that is, the predicted vehicle movement route. This route takes into account the interaction between the vehicle and the protection facility, as well as the changes in the vehicle's motion state after collision or rubbing.

[0059] In order to obtain the safety situation of vehicle occupants under different control schemes, the model will calculate the safety value of vehicle occupants according to the physical quantities during the collision or rubbing process. The model will refer to the vehicle's safety design standards and ergonomic principles to convert parameters such as the impact force and acceleration during the collision process into injury indicators for vehicle occupants. For example, the model will calculate the peak acceleration received by the driver's head during the collision of the vehicle and determine whether the acceleration exceeds the safety threshold according to relevant safety standards, so as to evaluate the risk of the driver's head injury. By comprehensively considering multiple injury indicators, the model will calculate a comprehensive safety value of vehicle occupants to measure the safety level of vehicle occupants under this control scheme.

[0060] For multiple input control schemes, the model will repeat the above steps, simulate and evaluate each control scheme in turn, and obtain the predicted vehicle movement route and the safety value of vehicle occupants corresponding to each control scheme.

[0061] S203. When there is a safety value of vehicle occupants exceeding the preset threshold, obtain the target control scheme and the target predicted vehicle movement route corresponding to the highest safety value of vehicle occupants.

[0062] Specifically, when there is a vehicle personnel safety value exceeding the preset threshold, sort all vehicle personnel safety values from high to low. After the sorting is completed, obtain the target control plan and the target predicted vehicle movement route corresponding to the vehicle personnel safety value ranked first, and send the end position of the target predicted vehicle movement route to the traffic police personnel closest to this end position and the trailer driver of the idle target trailer.

[0063] S204. When the target protection facility is controlled to execute the target control plan, if it is detected that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route, re-determine the new control plan and the new predicted vehicle movement route.

[0064] Specifically, according to the target control plan, determine the control instructions for each facility in the target protection facility, and send the control instructions to the corresponding target protection facility. After receiving the control instructions, the target protection facility performs corresponding operations according to the control instructions to execute the target control plan.

[0065] When the driving state of the abnormal vehicle obtained in real time is driving (that is, when the target protection facility is controlled to execute the target control plan), determine the real-time movement route of the abnormal vehicle according to the real-time position of the abnormal vehicle. By communicating with the traffic monitoring system, obtain the real-time vehicle driving video data on the target road. Identify the position of the abnormal vehicle in each frame of the image through an image recognition algorithm (such as a target detection and tracking algorithm based on deep learning, etc.). Then, through continuous tracking of multiple frames of images, combined with the pixel coordinate changes of the vehicle in the image and the scale information of the image, calculate the position coordinates of the vehicle on the actual road. According to a series of real-time position coordinates of the determined abnormal vehicle, connect these coordinate points in chronological order to generate the real-time movement route of the abnormal vehicle.

[0066] Use a similarity calculation algorithm (such as a similarity calculation method based on Euclidean distance) to calculate the similarity between the real-time movement route and the target predicted vehicle movement route. If the similarity between the real-time movement route and the target predicted vehicle movement route is lower than the preset threshold, it is determined that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route.

[0067] If the actual movement route does not match the target predicted vehicle movement route, execute the steps of S202 - S203 above, and re-determine the new control plan and the new predicted vehicle movement route according to the real-time position, real-time driving direction, and real-time driving speed of the abnormal vehicle.

[0068] S205. After detecting that the target protection facility has executed the new control plan, determine the replacement plan for the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road and the historical usage records of all movable protection facilities on the road.

[0069] Among them, the historical usage records include the replacement times of the movable protection facilities at each installation location on each road, the usage data of the currently used movable protection facilities, etc. The usage data includes detailed information such as the cumulative usage duration of the protection facilities since they were installed and put into use, the number of times of being collided or damaged in the past, the number of repairs, the degree and type of damage for each damage, the average frequency of regular maintenance, the real-time health status value, the installation location, and the facility model.

[0070] Specifically, when the driving state of the abnormal vehicle obtained in real time is stopped (i.e., after the target protection facility executes the new control plan), the real-time facility images of each target movable protection facility on the target road are obtained through the protection facility monitoring system. These images are from cameras or other image acquisition devices installed near the protection facilities.

[0071] Based on the real-time facility images, the damage degree and type of the protection facilities are identified by using image recognition technology based on deep learning (such as a convolutional neural network (CNN) model, etc.). This model is trained with a large amount of protection facility image data and can accurately identify various features of the protection facilities. Taking the convolutional neural network model as an example, after the image is input into the trained model, the convolutional layer of the model will perform convolutional operations on the image to generate a series of feature maps, which can capture different detailed information of the protection facilities, such as damage features like cracks, deformations, and fading. The pooling layer will perform downsampling on the feature maps, reducing the data dimension while retaining the key features and improving the calculation efficiency. The fully connected layer integrates the feature maps after convolution and pooling processing and outputs a feature vector, which contains the comprehensive feature information of the protection facility image. After extracting the features, the model will compare the extracted feature vector with the pre-established normal state feature library of the protection facilities. This feature library stores a large number of feature vectors of the protection facilities in the normal usage state. By calculating the similarity between the current feature vector and the feature vectors in the library (such as using the cosine similarity algorithm to calculate the similarity, etc.), the current damage degree (including no damage, minor, moderate, and severe, etc.) and the current damage type of the target movable protection facility are determined.

[0072] When the current damage degree of the target movable protection facility is not undamaged, calculate the current health status value of the target movable protection facility according to the usage data, current damage degree, and current damage type of the target movable protection facility, and update the real-time health status value in the usage data of this protection facility. Search for the usage data of the currently used movable protection facility corresponding to the target road in the historical usage records. Based on the cumulative usage duration in the usage data, obtain the cumulative usage duration score value corresponding to this cumulative usage duration in the preset cumulative usage duration score table. Based on the damage degree and damage type of each damage in the usage data, obtain the score value corresponding to the damage type and damage degree in the preset damage situation score table, and subtract the sum of all score values from the full score value of the preset damage situation score to obtain the past damage situation score value of the target movable protection facility. Based on the average frequency of regular maintenance and repair in the usage data, obtain the regular maintenance and repair situation score value corresponding to the average frequency in the preset maintenance and repair situation score table. According to the cumulative usage duration score value, past damage situation score value, regular maintenance and repair situation score value, and preset weights, calculate the current health status value of the target movable protection facility through weighted calculation, and update the real-time health status value in the usage data of this protection facility to the current health status value.

[0073] If the current health status value of the target movable protection facility is less than the preset health status threshold, obtain the preset importance level of the target movable protection facility to be replaced. This importance level includes level one, level two, and level three. The higher the level, the more important it is, and it is used to represent the guarantee degree of the movable protection facility for highway traffic safety and its key degree in the traffic protection system.

[0074] According to the warehouse inventory information, determine whether there is a protection facility in the warehouse with the same facility model as the target movable protection facility. If so, retrieve the protection facility in the warehouse for replacement. If not, and the importance level of this protection facility is level one, temporarily do not replace it and wait for the procurement personnel to purchase it before replacement. If not, and the importance level of this protection facility is level two or level three, according to the historical usage of the movable protection facilities on all roads, search for the first movable protection facility with the same protection facility model as this protection facility, a health status score value higher than the preset health status threshold, and an importance level of level one, and replace this protection facility with the first protection facility.

[0075] In the embodiments of the present application, when it is detected that an abnormal vehicle cannot stop by itself, the digital twin model is used to simulate and obtain the predicted vehicle movement routes and vehicle personnel safety values based on different control schemes, which can accurately simulate various situations of protective facility intervention. Then, the target control scheme with the highest vehicle personnel safety value is selected to maximize the safety of the personnel in the abnormal vehicle. At the same time, the protective facilities are controlled to execute the target control scheme without the operation of the vehicle driver. The protective facilities automatically approach the abnormal vehicle and scrape or collide with the abnormal vehicle to stop the vehicle in time, avoiding more serious accidents caused by improper operation of the vehicle driver, reducing the interference of traffic accidents on the normal traffic flow, and improving the overall safety and operation efficiency of the highway traffic system.

[0076] The following Figure 3 is used to further illustrate the method of the embodiments of the present application.

[0077] Please refer to Figure 3 , which is another process schematic diagram of the highway traffic protection facility control method in the embodiments of the present application.

[0078] S301. When an abnormal vehicle is detected on the target highway, control the first variable sign on the target section where the abnormal vehicle is located to display a warning message.

[0079] S302. When the abnormal cause of the abnormal vehicle belongs to the preset cause set and the abnormal vehicle has not stopped within the preset stop duration, obtain the driving speed, driving direction, and current position of the abnormal vehicle.

[0080] S303. Determine one or more control schemes according to the target protection facilities on the target highway and the relative position information between the target protection facilities and the abnormal vehicle.

[0081] S304. Input the driving speed, driving direction, current position, and control scheme into the pre-established digital twin model of highway traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control scheme.

[0082] S305. When there is a vehicle personnel safety value exceeding the preset threshold, obtain the target control scheme and the target predicted vehicle movement route corresponding to the highest vehicle personnel safety value.

[0083] Steps S301 - S305 are similar to Figure 2 Steps S201 - S203 in the illustrated embodiment, and reference can be made to the descriptions in Steps S201 - S203, which will not be elaborated here.

[0084] S306. When there is a traffic light intersection in the target predicted vehicle movement route, obtain the real-time position of the abnormal vehicle.

[0085] Specifically, obtain the positions of each traffic light intersection on the preset target road. Traverse the positions of each moving point on the target predicted vehicle movement route, match the position of the moving point with the positions of each traffic light intersection. If there is a match between the position of a certain moving point and the position of a certain traffic light intersection, it is determined that there is a traffic light intersection on the target predicted vehicle movement route, and obtain the position of the preset stop line corresponding to the traffic light intersection with which the match is successful.

[0086] When there is a traffic light intersection on the target predicted vehicle movement route, obtain the real-time position of the abnormal vehicle by establishing a connection with the on-vehicle system of the abnormal vehicle. If it is impossible to connect to the on-vehicle system of the abnormal vehicle, identify the real-time position of the abnormal vehicle by recognizing the driving video data of the abnormal vehicle through an image recognition algorithm. Obtain the video data of the section where the abnormal vehicle is located from the traffic monitoring system, use an advanced image recognition algorithm (such as a target detection and tracking algorithm based on deep learning) to identify the abnormal vehicle in the video data, and determine the real-time position of the abnormal vehicle on the target road based on information such as road signs, markings, and the relative position of the vehicle in the image, in combination with the pre-stored electronic map data of the target road.

[0087] S307. When the distance between the real-time position and the stop line of the traffic light intersection is within the preset distance range, control the traffic light corresponding to the driving direction of the abnormal vehicle at the traffic light intersection to be green.

[0088] Specifically, calculate the distance between the real-time position and the stop line of the traffic light intersection according to the real-time position and the preset stop line position corresponding to the traffic light intersection. When this distance is within the preset distance range, determine the target traffic light device corresponding to the driving direction of the abnormal vehicle according to the driving direction of the abnormal vehicle. Establish a communication connection with the traffic signal control system, and send a control instruction to the system. After receiving the instruction, the traffic signal control system sends a corresponding instruction to the target traffic light device. After receiving the instruction, the target traffic light device switches the display status of the traffic light device to display green, so that the abnormal vehicle can directly pass through the traffic light intersection.

[0089] S308. When controlling the target protection facility to execute the target control plan, when it is detected that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route, re-determine a new control plan and a new predicted vehicle movement route.

[0090] Step S308 is similar to Figure 2 Step S204 in the embodiment shown, and reference can be made to the description in Step S204, which will not be elaborated here.

[0091] S309. After detecting that the target protection facility has executed the new control plan, determine the first current health status value of the target movable protection facility.

[0092] After detecting that the target protection facility has executed the new control plan, determine the first current health status value of the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road.

[0093] Among them, the real-time facility status includes the cumulative usage duration, the current damage degree (including no damage, slight, general, and severe, etc.), the current damage type, and the current health status value, etc.

[0094] Step S309 is similar to Figure 2 identifying the current damage degree, the current damage type of the target movable protection facility, and calculating the current health status value in step S205 in the illustrated embodiment. For details, refer to the description in step S205 and will not be elaborated here.

[0095] S310. Statistically calculate the total number of repairs and replacements and the second current health status value of other movable protection facilities corresponding to the target movable protection facility among all movable protection facilities on all roads except the target movable protection facility.

[0096] According to the historical usage records of all movable protection facilities on all roads, statistically calculate the total number of repairs and replacements and the second current health status value of other movable protection facilities corresponding to the target movable protection facility among all movable protection facilities on all roads except the target movable protection facility.

[0097] Specifically, obtain the historical usage records. Extract the usage data of the currently in-use movable protection facilities whose facility models are the same as that of the target movable protection facility from the historical usage records to obtain the first set of movable protection facilities and their corresponding usage data. According to the usage data, obtain the repair times of each protection facility in the first set of movable protection facilities.

[0098] Then, according to the historical usage records, obtain the facility replacement times at the installation positions corresponding to each protection facility in the first set of movable protection facilities.

[0099] Finally, calculate the sum of the repair times and the facility replacement times to obtain the total number of repairs and replacements of each protection facility in the first set of movable protection facilities. At the same time, extract the real-time health status value in the usage data corresponding to each protection facility in the first set of movable protection facilities as the second current health status value of each protection facility.

[0100] S311. Determine the replacement plan for each protection facility in the target movable protection facility.

[0101] According to the first current health status value, the total number of times, and the second current health status value, determine the replacement plan for each protection facility in the target movable protection facility.

[0102] Among them, the replacement solutions include not replacing the movable protection facility, replacing the target movable protection facility with other movable protection facilities, and replacing with a new movable protection facility.

[0103] Specifically, if the first current health state value of the target movable protection facility is within the preset normal health state value range, it is determined that the replacement solution is not to replace the movable protection facility. If the first current health state value of the target movable protection facility is not within the preset normal health state value range, it is determined whether there is a protection facility of the same model in the inventory. If so, it is determined that the replacement solution is to replace the new movable protection facility in the inventory; if not, the total target number of repairs and replacements of the target movable protection facility is counted. If the total target number is less than the preset threshold, the movable protection facility is not replaced and waiting for the purchaser to purchase and then replace. If the total target number is greater than or equal to the preset threshold, search for the first movable protection facility in the first set of movable protection facilities whose second current health state value is within the normal health state value range corresponding to the target movable protection facility and the total number of repairs and replacements is less than the preset threshold to obtain the second set of movable protection facilities. According to the installation positions of each second movable protection facility in the second set of movable protection facilities and the installation position of the target movable protection facility, calculate the distances between each second movable protection facility and the target movable protection facility. Select the second movable protection facility corresponding to the shortest distance to replace the target movable protection facility.

[0104] S312. When the abnormal vehicle stops, obtain the vehicle image data and vehicle real-time operation data of the abnormal vehicle.

[0105] Specifically, when the driving state of the abnormal vehicle obtained in real time is stopped, communicate with the traffic monitoring system to obtain the vehicle image data of the abnormal vehicle. At the same time, establish a communication connection with the in-vehicle device of the abnormal vehicle through the wireless communication module to obtain the vehicle real-time operation data of the vehicle.

[0106] S313. Determine the explosion risk value of the abnormal vehicle.

[0107] Determine the explosion risk value of the abnormal vehicle according to the vehicle image data and vehicle real-time operation data.

[0108] Specifically, based on vehicle image data, a pre-trained deep learning model (such as a convolutional neural network, CNN) is used to identify whether there are abnormal features in the vehicle image, such as damage, deformation, liquid leakage, or smoke on the vehicle appearance. This deep learning model is trained on a large amount of image data containing various normal states of vehicles and abnormal states at different degrees. During the training process, each image is carefully annotated to clarify the specific abnormal features of the vehicle in the image and their corresponding categories. By continuously adjusting the parameters of the model, the model can accurately identify various abnormal features. After inputting the vehicle image data into this pre-trained deep learning model, the model will extract and analyze the features of the image, and compare each part of the image with the learned feature patterns. When a pattern matching an abnormal feature such as damage, deformation, liquid leakage, or smoke is detected, the model will output the corresponding recognition result.

[0109] Input the vehicle image data into this pre-trained deep learning model to obtain the recognition result output by the model. According to various abnormal features in the recognition result, look up the scores corresponding to the abnormal features in the preset abnormal feature score table, and add up all the scores to obtain the risk score of the vehicle image data.

[0110] Meanwhile, extract the key parameters related to vehicle explosion in the vehicle real-time operation data, such as engine temperature, fuel pressure, battery voltage, coolant temperature, etc. Based on the preset normal parameter operation range, determine whether there are key parameters exceeding the corresponding normal parameter operation range. If so, obtain the abnormal parameters exceeding the normal parameter operation range and their corresponding deviation values. Look up the scores corresponding to the abnormal parameters and the deviation values of the abnormal parameters in the preset abnormal parameter score table. Add up all the scores to obtain the risk score of the vehicle real-time operation data.

[0111] Finally, comprehensively evaluate the risk score of the vehicle image data and the risk score of the vehicle real-time operation data. Through the preset weight allocation, calculate the final explosion risk value through weighted calculation. This risk value is represented in numerical form, and the higher the value, the greater the explosion risk.

[0112] S314. When the explosion risk value is greater than or equal to the preset explosion risk threshold, control the second variable sign to display a warning message.

[0113] When the explosion risk value is greater than or equal to the preset explosion risk threshold, control the second variable signs corresponding to the sections within the first preset range from the abnormal vehicle on the target road to display warning messages.

[0114] Among them, the warning message is used to warn other vehicles on the target road except the abnormal vehicle to keep an explosion safety distance from the abnormal vehicle.

[0115] Specifically, when the explosion risk value is greater than or equal to the preset explosion risk threshold, a control instruction is determined based on the specific position coordinates of the abnormal vehicle and the preset warning information template. The control instruction is sent to the second variable sign corresponding to the section within the first preset range from the abnormal vehicle on the target road. After receiving the control instruction, the second variable sign clearly displays the specific position coordinates of the abnormal vehicle and the warning content on the sign according to the preset warning information template and font style, reminding passing vehicles to keep an explosion safety distance from the abnormal vehicle.

[0116] S315. Obtain the fire extinguisher information within the second preset range from the abnormal vehicle.

[0117] Among them, the fire extinguisher information includes the position information of the fire extinguisher.

[0118] Specifically, obtain the facility layout information of the target road and the specific position coordinates of the abnormal vehicle. According to the position of the abnormal vehicle, combined with the preset second preset range (for example, a certain distance range centered on the abnormal vehicle), search for the fire extinguisher information within this range in the facility database of the target road. This information is usually stored in the traffic facility management system, and relevant data is obtained by communicating with this system.

[0119] S316. Control the sound playback device closest to the fire extinguisher to play the fire extinguisher information and the position information of the abnormal vehicle.

[0120] Specifically, according to the position information of each fire extinguisher in the fire extinguisher information and the position information of each sound playback device preset, calculate the distance between each sound playback device and each fire extinguisher. According to the distance between each sound playback device and each fire extinguisher, determine the sound playback device closest to each fire extinguisher.

[0121] According to the position information of each fire extinguisher and the position information of the abnormal vehicle, generate a control instruction for the sound playback device corresponding to each fire extinguisher. Send the control instruction to the corresponding sound playback device. After receiving the control instruction, the sound playback device automatically plays the position information of the fire extinguisher closest to the device and the position information of the abnormal vehicle.

[0122] S317. When the explosion risk value is less than the preset explosion risk threshold, calculate the predicted processing duration for moving the abnormal vehicle to the target trailer.

[0123] When the explosion risk value is less than the preset explosion risk threshold, calculate the predicted processing duration for moving the abnormal vehicle to the target trailer according to the driving duration of the target trailer to reach the current position of the abnormal vehicle and the preset vehicle movement duration.

[0124] Specifically, when the explosion risk value is less than the preset explosion risk threshold, obtain the current position of the target trailer and the current position of the abnormal vehicle. Calculate the distance between the target trailer and the abnormal vehicle based on the current positions of the target trailer and the abnormal vehicle. Then, obtain the average driving speed of the target trailer, and calculate the driving duration required for the target trailer to reach the current position of the abnormal vehicle based on the average driving speed and the distance. Finally, add the driving duration to the preset vehicle movement duration to obtain the predicted processing duration for the abnormal vehicle to move onto the target trailer. The preset vehicle movement duration is set based on historical data or experience and is used to estimate the average time required to move the abnormal vehicle from the current position to the target trailer.

[0125] S318. Determine the predicted duration for a vehicle to travel from each section of the road to the target section.

[0126] Based on the average vehicle speed corresponding to each section of the target road and the length of each section, determine the predicted duration for a vehicle to travel from each section to the target section.

[0127] Specifically, find the section information of all sections between each section of the target road and the target section from the road traffic database. The road traffic database stores detailed information about all sections of all roads, including the starting point, ending point, length, and connection relationships with other sections of each section. The section information corresponding to a section includes one or more first sections and their corresponding section lengths. A vehicle starts traveling from this section and can reach the target section only after passing through these first sections.

[0128] Obtain the average vehicle speed preset for each section. According to the average vehicle speed of each section and the section information, calculate the first passing duration of each first section in the section information corresponding to each section in sequence. Add up all the first passing durations corresponding to each section in sequence to obtain the predicted duration for a vehicle to travel from each section to the target section.

[0129] S319. If there is a target predicted duration in the predicted durations that is less than the predicted processing duration, determine the traffic states of each target lane in the target section.

[0130] If there is a target predicted duration in the predicted durations that is less than the predicted processing duration, determine the traffic states of each target lane in the target section according to the obstacle conditions of each lane in the target section.

[0131] Among them, the traffic states include passable and non-passable.

[0132] Specifically, if there is a target prediction duration in the prediction duration that is less than the prediction processing duration, communicate with the traffic monitoring system to obtain the road image data of the target section. Then, use an image recognition algorithm, such as an object detection algorithm based on deep learning (e.g., YOLO, Faster R-CNN, etc.) to identify obstacles in the road image. These algorithms are trained with a large amount of road image data containing various obstacles (such as accident vehicles, protective facilities, etc.) and can accurately detect the obstacles (vehicles and protective facilities) in the image and their corresponding position ranges.

[0133] After identifying the obstacles, based on the lane division information of the target section (this information can be pre-stored in the database or obtained from the road information system of the traffic management department), determine the lane where each obstacle is located.

[0134] For each lane, if there are no obstacles in the lane, determine the traffic state of the lane as passable; if there are obstacles in the lane, determine the traffic state of the lane as impassable.

[0135] S320: If there is a passable target lane, determine the display content of the third variable sign as the first content.

[0136] If there is a passable target lane, then determine the display content of the third variable sign of the section corresponding to the target prediction duration as the first content.

[0137] Among them, the first content is the passable lanes and impassable lanes of the target section.

[0138] Specifically, according to the traffic states of each target lane in the target section, determine whether there is a passable target lane.

[0139] If so, generate the first content according to the traffic states of each target lane. Determine the control instruction according to the first content and the preset lane prompt information template corresponding to the first content. Send this control instruction to the third variable sign of the section corresponding to the target prediction duration. After receiving the control instruction, the third variable sign displays the passable lanes and impassable lanes in the target section on the sign according to the first content, the preset lane prompt information template, and the font style, reminding passing vehicles to pay attention to whether they can pass through the passable lanes in the target section. If not, execute the steps of S321 below.

[0140] S321: If there is no passable target lane, determine the display content of the third variable sign as the second content.

[0141] If there is no passable target lane, then determine the display content of the third variable sign of the section corresponding to the target prediction duration as the second content.

[0142] Among them, the second content is that the target road section is impassable.

[0143] Specifically, according to the second content and the preset no - passage prompt information template corresponding to the second content, a control instruction is determined. The control instruction is sent to the third variable sign of the road section corresponding to the target prediction duration. After receiving the control instruction, the third variable sign displays the no - passage of the target road section on the sign according to the preset no - passage prompt information template and font style, reminding passing vehicles that the target road section is impassable and to pay attention to changing lanes in time.

[0144] In the embodiment of the present application, when the explosion risk value exceeds the preset threshold, the fire extinguisher information around the vehicle is obtained, and the fire extinguisher information and the location information of the abnormal vehicle are played through the sound playback device, so that surrounding users can quickly find the fire extinguisher and bring the fire extinguisher to the vicinity of the abnormal vehicle at the first time they hear the information. In the initial stage when the abnormal vehicle explodes or catches fire, fire - fighting measures can be quickly taken to effectively contain the spread of the fire and reduce the possibility and harm degree of the explosion. At the same time, by obtaining the location of the abnormal vehicle in real - time, when it is detected that the abnormal vehicle is about to approach the stop line of the traffic light intersection, the corresponding traffic light in that direction is immediately switched to green, allowing the abnormal vehicle to pass unobstructed, avoiding the situation where when the abnormal vehicle cannot stop and encounters a red traffic light, it collides with vehicles and pedestrians traveling normally in other directions, causing traffic accidents, and improving the overall safety of the highway traffic system.

[0145] The control method of the highway traffic protection facilities in the embodiment of the present application is described above. Below, in combination with the above - mentioned control method of the highway traffic protection facilities, the protection facility control system in the embodiment of the present application is described in detail.

[0146] Please refer to Figure 4 , which is a module architecture diagram of the protection facility control system in the embodiment of the present application.

[0147] In some embodiments, the protection facility control system includes: A sign control module 401, configured to control the first variable sign of the target road section where the abnormal vehicle is located to display a warning message when an abnormal vehicle is detected on the target highway; A model input module 402, configured to input the current position, traveling speed, and traveling direction of the abnormal vehicle into a pre - established digital twin model of highway traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control scheme when the abnormal cause of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within the preset stop duration; A target control scheme determination module 403, configured to obtain the target control scheme and the target predicted vehicle movement route corresponding to the highest vehicle personnel safety value when there is a vehicle personnel safety value exceeding the preset threshold; A new control scheme determination module 404 is configured to, when it is detected that the actual movement route of an abnormal vehicle does not match the target predicted vehicle movement route while the target protection facility is executing the target control scheme, re-determine a new control scheme and a new predicted vehicle movement route. A replacement scheme determination module 405 is configured to, after detecting that the target protection facility has executed the new control scheme, determine a replacement scheme for the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road and the historical usage records of the movable protection facilities on all roads.

[0148] An embodiment of the present application also provides a protection facility control server. The protection facility control server in the embodiment of the present application will be described below with reference to the schematic hardware structure diagram of the protection facility control server provided by the present application.

[0149] Please refer to Figure 5 , which is an exemplary schematic hardware structure diagram of the protection facility control server in the embodiment of the present application.

[0150] In some embodiments, the protection facility control server 500 includes a computer device, and the computer device may be a terminal device. The computer device includes a processor 501, a memory 502, a communication module 503, an input device 504, and an output device 505 connected through a system bus. Among them, the processor 501 of the computer device is used to provide computing and control capabilities. The memory 502 of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database is used to store data. The communication module 503 of the computer device is used to communicate with each system to obtain corresponding image data and vehicle operation data, etc. The input device 504 of the computer device is used to receive image data, vehicle operation data, etc. transmitted by other systems. The output device 505 of the computer device is used to display data such as control schemes. When the computer program is executed by the processor 501, it realizes the highway traffic protection facility control method in the embodiment of the present application.

[0151] Those skilled in the art can understand that Figure 5 the structure shown in

[0152] In some embodiments of the present application, a computer-readable storage medium is provided, including instructions that, when running on the protection facility control server 500, can cause the protection facility control server 500 to execute the highway traffic protection facility control method in the embodiments of the present application.

[0153] In some embodiments of the present application, a computer program product is also provided that, when running on the protection facility control server 500, causes the protection facility control server 500 to execute the highway traffic protection facility control method in the embodiments of the present application.

[0154] As described above, the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0155] As used in the above embodiments, depending on the context, the term "when..." can be interpreted to mean "if...", or "after...", or "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if detecting (the stated condition or event)" can be interpreted to mean "if determining...", or "in response to determining...", or "when detecting (the stated condition or event)", or "in response to detecting (the stated condition or event)".

[0156] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state drive), etc.

[0157] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware with a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The aforementioned storage medium includes: various media that can store program codes such as ROM or random access memory RAM, magnetic disks, or optical discs.

Claims

1. A control method for highway traffic protection facilities, characterized in that, The described protective facilities include intelligent guardrails, automatic roadblocks, and variable signboards. The method includes: When an abnormal vehicle is detected on the target road, control the first variable signboard on the target section where the abnormal vehicle is located to display a warning message, where the warning message is the location of the abnormal vehicle, and the target section is one of multiple sections on the target road; When the abnormal cause of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within a preset stop duration, input the current position, driving speed, and driving direction of the abnormal vehicle into a pre-established digital twin model of road traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control plan. The control plan is used to control the target protective facilities on the target road to generate friction with the abnormal vehicle so that the abnormal vehicle stops; When there is a vehicle personnel safety value exceeding a preset threshold, obtain the target control plan and the target predicted vehicle movement route corresponding to the highest vehicle personnel safety value; When controlling the target protective facilities to execute the target control plan, when it is detected that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route, re-determine a new control plan and a new predicted vehicle movement route; After detecting that the target protective facilities have executed the new control plan, determine the replacement plan for the target movable protective facilities according to the real-time facility images of each target movable protective facility on the target road and the historical usage records of all movable protective facilities on the road; 2. The method according to claim 1, characterized in that, The step of when the abnormal cause of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within a preset stop duration, input the current position, driving speed, and driving direction of the abnormal vehicle into a pre-established digital twin model of road traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control plan specifically includes: When the abnormal cause of the abnormal vehicle belongs to a preset cause set and the abnormal vehicle has not stopped within a preset stop duration, obtain the driving speed, driving direction, and current position of the abnormal vehicle; Determine one or more control plans according to the target protective facilities on the target road and the relative position information between the target protective facilities and the abnormal vehicle; Input the driving speed, the driving direction, the current position, and the control plan into a pre-established digital twin model of road traffic to obtain the predicted vehicle movement routes and vehicle personnel safety values corresponding to each control plan.

3. The method according to claim 1, characterized in that The step of after detecting that the target protective facilities have executed the new control plan, determine the replacement plan for the target movable protective facilities according to the real-time facility images of each target movable protective facility on the target road and the historical usage records of all movable protective facilities on the road specifically includes: After detecting that the target protective facilities have executed the new control plan, determine the first current health state value of the target movable protective facilities according to the real-time facility images of each target movable protective facility on the target road; According to the historical use records of the movable protection facilities on all roads, the total number of repairs and replacements of other movable protection facilities corresponding to the target movable protection facilities, except the target movable protection facilities, and the second current health status value are counted among the movable protection facilities on all roads; Based on the first current health status value, the total number of times and the second current health status value, a replacement plan for each protective facility in the target movable protective facility is determined, and the replacement plan includes not replacing the movable protective facility, replacing the other movable protective facilities with the target movable protective facility and replacing with a new movable protective facility.

4. The method according to claim 1, characterized in that After the step of determining a replacement scheme for the target movable protective facility based on the real-time facility images of each target movable protective facility on the target highway and the historical usage records of the movable protective facilities on all highways after detecting that the target protective facility has completed the execution of the new control scheme, the method further includes: When the abnormal vehicle stops, acquiring vehicle image data and vehicle real-time operation data of the abnormal vehicle; Determining an explosion risk value of the abnormal vehicle according to the vehicle image data and the real-time operation data of the vehicle; When the explosion risk value is greater than or equal to a preset explosion risk threshold, a second variable sign corresponding to a section of the target highway within a first preset range from the abnormal vehicle is controlled to display a warning message, wherein the warning message is used to warn other vehicles on the target highway except the abnormal vehicle to maintain an explosion safety distance from the abnormal vehicle; When the explosion risk value is less than a preset explosion risk threshold, the predicted processing time for moving the abnormal vehicle to the target trailer is calculated according to the driving time for the target trailer to reach the current position of the abnormal vehicle and the preset vehicle moving time; According to the predicted processing time and the obstacle conditions of each lane in the target section, the display content of the third variable sign corresponding to each section in the target highway is determined, and the display content is the first content or the second content, the first content is the passable lanes and the impassable lanes of the target section, and the second content is that the target section is impassable.

5. The method according to claim 4, characterized in that, After the step of controlling the second variable sign corresponding to the section of the target highway within the first preset range from the abnormal vehicle to display warning information when the explosion risk value is greater than or equal to the preset explosion risk threshold, the method further includes: Acquire fire extinguisher information within a second preset range from the abnormal vehicle, the fire extinguisher information including location information of the fire extinguisher; The sound playing device closest to the fire extinguisher is controlled to play the fire extinguisher information and the position information of the abnormal vehicle.

6. The method according to claim 4, wherein Determining the display content of the third variable sign corresponding to each road section in the target highway according to the predicted processing time and the obstacle conditions of each lane in the target road section specifically includes: Determining the predicted time for a vehicle to travel from each road section to the target road section according to the average vehicle speed corresponding to each road section in the target highway and the road section length of each road section; If there is a target prediction duration less than the prediction processing duration in the predicted duration, determine the traffic states of the target lanes in the target road section according to the obstacle conditions of each lane in the target road section, where the traffic states include passable and impassable; If there is a passable target lane, determine that the display content of the third variable sign of the road section corresponding to the target prediction duration is the first content; If there is no passable target lane, determine that the display content of the third variable sign of the road section corresponding to the target prediction duration is the second content.

7. The method according to claim 1, wherein After the step of, when there is a vehicle personnel safety value exceeding a preset threshold, obtaining a target control scheme corresponding to the highest vehicle personnel safety value and a target predicted vehicle movement route, the method further includes: When there is a traffic light intersection in the target predicted vehicle movement route, obtain the real-time position of the abnormal vehicle; When the distance between the real-time position and the stop line of the traffic light intersection is within a preset distance range, control the traffic light corresponding to the driving direction of the abnormal vehicle at the traffic light intersection to be green.

8. A protective facility control system, characterized in that, Including: A sign control module, configured to control the first variable sign of the target road section where the abnormal vehicle is located to display a warning message when an abnormal vehicle is detected on the target road; A model input module, configured to input the current position, driving speed, and driving direction of the abnormal vehicle into a digital twin model of highway traffic established in advance when the abnormal reason of the abnormal vehicle belongs to a preset reason set and the abnormal vehicle has not stopped within a preset stop duration, to obtain a predicted vehicle movement route and a vehicle personnel safety value corresponding to each control scheme; A target control scheme determination module, configured to obtain a target control scheme corresponding to the highest vehicle personnel safety value and a target predicted vehicle movement route when there is a vehicle personnel safety value exceeding a preset threshold; A new control scheme determination module, configured to re-determine a new control scheme and a new predicted vehicle movement route when it is detected that the actual movement route of the abnormal vehicle does not match the target predicted vehicle movement route under the condition of controlling the target protection facility to execute the target control scheme; A replacement scheme determination module, configured to determine a replacement scheme for the target movable protection facility according to the real-time facility images of each target movable protection facility on the target road and the historical usage records of all movable protection facilities on the road after detecting that the target protection facility has executed the new control scheme.

9. A protective facility control server, characterized in that, Including: One or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program code, where the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the protection facility control server to execute the method according to any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions, characterized in that, When the computer instructions run on the protection facility control server, cause the protection facility control server to execute the method according to any one of claims 1-7.

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