Tunnel management method, device and equipment for two-passenger-and-dangerous-goods vehicles

Abstract

The application relates to a management method and device for two-passenger-one-hazardous vehicle in a tunnel, and computer equipment. When a vehicle drives into the tunnel, the vehicle is bound with information of a multi-source system in the tunnel to obtain binding information. When the vehicle drives into an identification area, a laser radar is used to obtain position information, a notch camera is triggered to obtain license plate information of the vehicle, a preset two-passenger-one-hazardous vehicle management library is searched according to the license plate information, if the two-passenger-one-hazardous vehicle management library contains the license plate information, the vehicle is determined as a two-passenger-one-hazardous vehicle, and when the vehicle is determined as the two-passenger-one-hazardous vehicle, the vehicle is tracked by the multi-source system based on the license plate information and the binding information, so that the vehicle is managed according to the tracking result of the vehicle. In the application, the two-passenger-one-hazardous vehicle is detected by using the collected information of the multi-source system, and the two-passenger-one-hazardous vehicle is monitored, tracked and rescued according to the tracking result, so that the traffic safety of the road is improved.

Description

Technical Field

[0001] This application relates to the field of traffic safety technology, and in particular to a management method, device and equipment for passenger vehicles and dangerous goods vehicles in tunnels. Background Technology

[0002] As people's living standards gradually improve, more and more vehicles are appearing on the road. While vehicles bring great convenience to people's travel, the sharp increase in the number of vehicles has also made the road traffic environment more complex, resulting in frequent traffic accidents. This has aroused great concern among people about road traffic safety issues, especially the road traffic safety issues caused by passenger vehicles and dangerous goods vehicles.

[0003] To address the aforementioned road traffic safety issues, it is necessary to accurately identify and locate passenger vehicles and hazardous material transport vehicles on the road, thereby ensuring road traffic safety. Summary of the Invention

[0004] Therefore, it is necessary to provide a management method, device, and equipment for passenger and hazardous goods vehicles in tunnels that can improve road traffic safety, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a management method for passenger and hazardous goods vehicles within a tunnel, the method comprising:

[0006] When a vehicle enters a tunnel, information binding information is performed on the vehicle using the information from the multi-source system within the tunnel. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0007] When the vehicle enters the identification area, the checkpoint camera is triggered to acquire the vehicle's license plate information based on the location information obtained by the lidar.

[0008] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is in the management database of passenger vehicles and dangerous goods vehicles, then the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0009] When the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, the vehicle is tracked using the multi-source system based on the license plate information and the binding information.

[0010] The vehicle is managed based on the tracking results.

[0011] In one embodiment, the method further includes:

[0012] If the license plate information is not found in the vehicle management database for passenger and hazardous goods vehicles, the vehicle model information is determined based on the information collected by the multi-view camera group and the lidar.

[0013] Based on the vehicle model information, determine whether the vehicle is one of the two types of passenger vehicles and one type of dangerous goods vehicle.

[0014] In one embodiment, determining whether the vehicle is a passenger vehicle or a dangerous goods vehicle based on the vehicle model information includes:

[0015] If the vehicle type information is a bus, then the vehicle is identified as one of the two passenger vehicles and one dangerous goods vehicle.

[0016] In one embodiment, the method further includes:

[0017] If the vehicle is determined to be a passenger vehicle or a hazardous materials vehicle based on the vehicle model information, the passenger vehicle and hazardous materials vehicle management database is updated according to the vehicle's license plate information.

[0018] In one embodiment, determining whether the vehicle is a passenger vehicle or a dangerous goods vehicle based on the vehicle model information includes:

[0019] If the vehicle type information is a truck, then the vehicle front hazardous materials sign detection algorithm is used to identify the vehicle front hazardous materials sign information and determine the first confidence level of the vehicle front hazardous materials sign;

[0020] A vehicle body hazardous materials sign detection algorithm is used to identify the vehicle body image and determine the second confidence level of the vehicle body hazardous materials sign;

[0021] Based on the first confidence level and the second confidence level, determine whether the vehicle is one of the two passenger vehicles and one dangerous goods vehicle.

[0022] In one embodiment, determining whether the vehicle is one of the two-passenger-one-dangerous-goods vehicles based on the second confidence level includes:

[0023] If the second confidence level is greater than the vehicle body confidence level threshold, then the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, and the vehicle's sub-type is determined.

[0024] In one embodiment, managing the vehicle based on the vehicle tracking results includes:

[0025] Based on the vehicle tracking results, determine whether the vehicle has been involved in an accident;

[0026] If the vehicle is involved in an accident, the vehicle shall be managed according to its specific sub-type.

[0027] In one embodiment, managing the vehicle based on the vehicle tracking results includes:

[0028] Based on the tracking results, the speed information of the vehicle is determined;

[0029] If the speed information is greater than the preset speed, or if it is determined based on the speed information that the vehicle is stationary, then a first prompt message is output, and the acquisition information from the multi-view camera group is obtained.

[0030] In one embodiment, the method further includes:

[0031] Based on the information collected by the multi-source system, the number and location of the two passenger vehicles and one dangerous goods vehicle in the tunnel are determined;

[0032] Based on the number and location of the two passenger vehicles and one dangerous goods vehicle in the tunnel, a second prompt message is output.

[0033] Secondly, this application also provides a management device for passenger and hazardous goods vehicles within a tunnel, the device comprising:

[0034] The binding module is used to bind the vehicle to the information of the multi-source system in the tunnel when the vehicle enters the tunnel, and obtain binding information. The binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera and a lidar.

[0035] The acquisition module is used to trigger the checkpoint camera to acquire the vehicle's license plate information based on the location information obtained by the lidar when the vehicle enters the recognition area.

[0036] The first determining module is used to search a preset passenger and hazardous materials vehicle management database based on the license plate information. If the license plate information is in the database, the vehicle is determined to be a passenger and hazardous materials vehicle.

[0037] The tracking module is used to track the vehicle using the multi-source system based on the license plate information and the binding information when it is determined that the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0038] The management module is used to manage the vehicle based on the vehicle tracking results.

[0039] Thirdly, this application also provides a computer device, the computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0040] When a vehicle enters a tunnel, information binding information is performed on the vehicle using the information from the multi-source system within the tunnel. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0041] When the vehicle enters the identification area, the checkpoint camera is triggered to acquire the vehicle's license plate information based on the location information obtained by the lidar.

[0042] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is in the management database of passenger vehicles and dangerous goods vehicles, then the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0043] When the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, the vehicle is tracked using the multi-source system based on the license plate information and the binding information.

[0044] The vehicle is managed based on the tracking results.

[0045] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0046] When a vehicle enters a tunnel, information binding information is performed on the vehicle using the information from the multi-source system within the tunnel. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0047] When the vehicle enters the identification area, the checkpoint camera is triggered to acquire the vehicle's license plate information based on the location information obtained by the lidar.

[0048] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is in the management database of passenger vehicles and dangerous goods vehicles, then the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0049] When the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, the vehicle is tracked using the multi-source system based on the license plate information and the binding information.

[0050] The vehicle is managed based on the tracking results.

[0051] Fifthly, this application also provides a computer program product, which includes a computer program that, when executed by a processor, performs the following steps:

[0052] When a vehicle enters a tunnel, information binding information is performed on the vehicle using the information from the multi-source system within the tunnel. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0053] When the vehicle enters the identification area, the checkpoint camera is triggered to acquire the vehicle's license plate information based on the location information obtained by the lidar.

[0054] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is in the management database of passenger vehicles and dangerous goods vehicles, then the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0055] When the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, the vehicle is tracked using the multi-source system based on the license plate information and the binding information.

[0056] The vehicle is managed based on the tracking results.

[0057] The aforementioned management method, device, and equipment for passenger and hazardous materials vehicles within tunnels involves binding information to a multi-source system within the tunnel when a vehicle enters. Upon entering the identification zone, the system uses location information obtained from LiDAR to trigger a checkpoint camera to acquire the vehicle's license plate information. Further, based on the license plate information, a pre-set management database for passenger and hazardous materials vehicles is searched. If the license plate information is found in the database, the vehicle is identified as such. Once identified, the vehicle is tracked using the multi-source system based on the license plate and binding information. Management is then based on the tracking results. This application utilizes a multi-source system to collect real-time image and point cloud information for targeted detection of passenger and hazardous materials vehicles, ensuring high accuracy in tunnel vehicle detection. Furthermore, after identification, the system tracks the vehicle and manages it based on the tracking results, ensuring targeted monitoring, tracking, and rescue of passenger and hazardous materials vehicles within the tunnel, thus improving road traffic safety. Attached Figure Description

[0058] Figure 1 This is an application environment diagram of a management method for passenger and hazardous goods vehicles within a tunnel, as shown in one embodiment.

[0059] Figure 2 This is a flowchart illustrating a management method for passenger and hazardous goods vehicles within a tunnel in one embodiment.

[0060] Figure 3This is a flowchart illustrating the process of determining whether a vehicle is a passenger vehicle or a dangerous goods vehicle in one embodiment.

[0061] Figure 4 This is a schematic diagram of a vehicle vehicle hazardous materials sign in one embodiment;

[0062] Figure 5 This is a schematic diagram of the process for managing vehicles in one embodiment;

[0063] Figure 6 This is a schematic diagram of the process for managing vehicles in another embodiment;

[0064] Figure 7 This is a flowchart illustrating the management method for passenger and hazardous goods vehicles within a tunnel in another embodiment.

[0065] Figure 8 This is a schematic diagram of the process for detecting dangerous goods labels in one embodiment;

[0066] Figure 9 This is a structural block diagram of a management device for passenger and hazardous goods vehicles inside a tunnel in one embodiment.

[0067] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0069] The management method for passenger and hazardous goods vehicles within tunnels provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, the multi-source system 1 communicates with computer device 2 via a network. A data storage system can store the data that computer device 2 needs to process. The data storage system can be integrated onto computer device 2 or located in the cloud or on other network servers. Multi-source system 1 includes a multi-view camera group, a bayonet camera, and a LiDAR. Computer device 2 can be a server, which can be a standalone server or a server cluster consisting of multiple servers.

[0070] In one embodiment, such as Figure 2 As shown, a management method for passenger and hazardous goods vehicles within a tunnel is provided, which is then applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0071] S201, when a vehicle enters the tunnel, the vehicle is bound to information from the multi-source system within the tunnel to obtain binding information. The binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0072] The tunnel is equipped with multiple multi-source systems, each including a multi-view camera group, a checkpoint camera, and a lidar. Optionally, the multi-source systems can be installed at 150-meter intervals.

[0073] In this embodiment, when a vehicle enters the tunnel, a fusion algorithm is used to bind the same vehicle based on multi-frame image information acquired by the checkpoint camera at the tunnel entrance, video data acquired by the multi-view camera group, and point cloud data acquired by the LiDAR, thus obtaining binding information. For example, the multi-frame image information of the target vehicle acquired by the checkpoint camera is 'a', the video data of the target vehicle acquired by the multi-view camera group is 'b', and the point cloud data of the target vehicle acquired by the LiDAR is 'c'. Based on the multi-frame image information 'a', video data 'b', and point cloud data 'c', the fusion algorithm is used to bind the target vehicle, thus obtaining binding information. That is, the target vehicle is set as vehicle A. Based on the binding information, the data collected by each device of the multi-source system on vehicle A can be indexed.

[0074] S202: When a vehicle enters the recognition area, the checkpoint camera is triggered to obtain the vehicle's license plate information based on the location information obtained by the LiDAR.

[0075] In this embodiment, when a vehicle enters the recognition area, the vehicle's location information is determined using a point cloud detection algorithm based on the point cloud data of the vehicle obtained by the LiDAR. When the vehicle enters a specific area of ​​the recognition area (such as an area where the front and rear images of the vehicle can be obtained relatively comprehensively) based on the location information, the recognition area checkpoint camera is triggered to obtain the vehicle's front image information. The image recognition algorithm is then used to identify the front image information to obtain the vehicle's license plate information.

[0076] S203: Based on the license plate information, search the preset management database of passenger and hazardous goods vehicles. If the license plate information is found in the management database of passenger and hazardous goods vehicles, then the vehicle is determined to be a passenger and hazardous goods vehicle.

[0077] In this embodiment, the license plate information is compared one by one with the preset passenger and hazardous materials vehicle management database to determine whether the license plate information of the vehicle exists in the database. If the license plate information exists in the database, the vehicle is determined to be a passenger and hazardous materials vehicle.

[0078] S204: When a vehicle is identified as a passenger vehicle or a dangerous goods vehicle, a multi-source system is used to track the vehicle based on the license plate information and binding information.

[0079] In this embodiment, the vehicle is tracked using a multi-source system based on license plate information and binding information. That is, the target vehicle is determined based on the license plate information and binding information, and the target vehicle is collected in real time by the multi-source system in the tunnel to obtain the collected information of the target vehicle in the tunnel.

[0080] S205 manages vehicles based on vehicle tracking results.

[0081] In this embodiment, vehicles are managed based on the tracking results. This involves acquiring vehicle location information based on collected data, and furthermore, binding the location information with latitude and longitude coordinates. This allows for real-time tracking of passenger and hazardous materials transport vehicles within the tunnel, providing a warning to other vehicles to give way.

[0082] It can also obtain vehicle information collected by a multi-source system within the tunnel based on license plate information and binding information, thereby obtaining vehicle speed information and issuing early warnings based on the speed information.

[0083] In one possible implementation, the tracking results can also be used to obtain information such as the number of passenger vehicles and dangerous goods vehicles, and whether any accidents have occurred, thereby enabling appropriate rescue operations to be carried out based on the vehicle tracking results.

[0084] In the aforementioned management method for passenger and hazardous goods vehicles within tunnels, when a vehicle enters the tunnel, information is bound to the vehicle using a multi-source system within the tunnel to obtain binding information. Upon entering the identification zone, the vehicle's location information, obtained from LiDAR, triggers a checkpoint camera to acquire the vehicle's license plate information. Further, based on the license plate information, a pre-set management database for passenger and hazardous goods vehicles is searched. If the license plate information exists in the database, the vehicle is identified as a passenger or hazardous goods vehicle. Once identified, the vehicle is tracked using the multi-source system based on the license plate and binding information, and managed according to the tracking results. This application utilizes a multi-source system to collect real-time image and point cloud information for targeted detection of passenger and hazardous goods vehicles, ensuring the accuracy of vehicle detection within the tunnel. Furthermore, after identifying a vehicle as a passenger or hazardous goods vehicle, tracking is implemented, and management is based on the tracking results, ensuring targeted monitoring, tracking, and rescue of passenger and hazardous goods vehicles within the tunnel, thus improving road traffic safety.

[0085] For example, based on the above embodiments, if the license plate information is not found in the vehicle management database for passenger vehicles and hazardous materials vehicles, the vehicle model information is determined based on the information collected by the multi-view camera group and LiDAR; based on the vehicle model information, it is determined whether the vehicle is a passenger vehicle or a hazardous materials vehicle.

[0086] In this embodiment, if the vehicle license plate information is not available in the vehicle management database for passenger and hazardous goods vehicles, the vehicle length information can be obtained based on the information collected by the multi-view camera group and LiDAR, and the vehicle model information can be determined based on the length information.

[0087] It can also obtain specific details about the vehicle based on information collected by multi-view camera groups and lidar, such as the proportion of the vehicle's front length and cargo box length in the vehicle, and determine the vehicle model information based on the detailed information.

[0088] In this embodiment, the vehicle type is determined based on the vehicle model information. Specifically, if the vehicle model information is a bus, the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle; if the vehicle model information is a truck, it is necessary to further determine whether the truck is a passenger vehicle or a dangerous goods vehicle; if the vehicle model information is a sedan, the vehicle is determined not to be a passenger vehicle or a dangerous goods vehicle.

[0089] Furthermore, if the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle based on the vehicle model information, the passenger vehicle and dangerous goods vehicle management database is updated according to the vehicle's license plate information.

[0090] In this embodiment, the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle based on the vehicle type information. That is, if there is no license plate information in the preset passenger vehicle and dangerous goods vehicle management database, and the vehicle is a passenger vehicle and a dangerous goods vehicle, then the license plate information is added to the passenger vehicle and dangerous goods vehicle management database, and the database is updated so that it can be determined more quickly whether the vehicle is a passenger vehicle or a dangerous goods vehicle in subsequent vehicle identification.

[0091] In this embodiment, when the license plate information is not found in the passenger and hazardous materials vehicle management database, the vehicle model information is determined based on information collected by a multi-view camera group and LiDAR. Based on the model information, it is determined whether the vehicle is a passenger or hazardous materials vehicle. This embodiment uses a multi-view camera group to capture vehicle image information and LiDAR to collect vehicle point cloud information, making full use of the environmental perception capability of the multi-source system. This makes the vehicle model information determined by the information collected by the multi-view camera group and LiDAR more accurate, thereby improving the accuracy of identifying passenger and hazardous materials vehicles.

[0092] Figure 3 This is a flowchart illustrating the process of determining whether a vehicle is a passenger vehicle or a dangerous goods vehicle in one embodiment. Figure 3 As shown, this application embodiment relates to a feasible method for determining whether a vehicle is a passenger vehicle or a dangerous goods vehicle based on vehicle model information when the license plate information is not found in the passenger vehicle and dangerous goods vehicle management database. The method includes the following steps:

[0093] S301. If the vehicle type information is a truck, the dangerous goods sign detection algorithm on the front of the vehicle is used to identify the dangerous goods sign information on the front of the vehicle and determine the first confidence level of the dangerous goods sign on the front of the vehicle.

[0094] Optionally, the algorithm for detecting hazardous materials signs on the front of a vehicle can be any image detection algorithm, such as neural networks like convolutional neural networks and deep belief networks, or algorithms like principal component analysis and decision trees.

[0095] In this embodiment, when the vehicle type information is a truck, the checkpoint camera acquires an image of the front of the vehicle. A hazardous materials sign detection algorithm is used to identify triangular and rectangular signs in the front of the vehicle image. First, it detects whether triangular and / or rectangular hazardous materials signs exist in the front of the vehicle image. If hazardous materials signs are present, a first confidence level for the vehicle's hazardous materials signs is determined based on the type and corresponding location of the triangular and / or rectangular signs. For example, if no triangular or rectangular hazardous materials signs are found in the front of the vehicle image, the first confidence level for the vehicle's hazardous materials signs is determined to be 0.

[0096] If the vehicle front image contains both triangular and rectangular hazard signs, the triangular hazard sign on the truck is positioned above the rectangular hazard sign, and the triangular sign is located in the upper half of the front of the truck, while the rectangular sign is located in the lower half. Optionally, the triangular hazard sign can be placed on the roof of the truck, and the rectangular sign near the license plate. If, according to the vehicle front hazard sign detection algorithm, the triangular hazard sign is located in the upper half of the front of the truck, and the rectangular sign is located in the lower half, then the first confidence level of the vehicle front hazard signs is determined to be 2. If only one hazard sign is detected, and that sign is located in its designated area, then the first confidence level of the vehicle front hazard signs is determined to be 1. If the triangular hazard sign is detected in the upper half of the front of the truck, but the rectangular sign is not located in the lower half, then the first confidence level of the vehicle front hazard signs is determined to be 1.5.

[0097] In one possible implementation, the rule "the triangular hazard sign is located in the upper half of the vehicle's front, and the rectangular hazard sign is located in the lower half of the vehicle's front" can be used as a rule condition to set an initial confidence level. If the vehicle's front recognition and detection result meets the rule condition, the initial confidence level is multiplied by a weight value greater than 1. If the vehicle's front recognition and detection result does not meet the rule condition, the initial confidence level is multiplied by a weight value less than 1 corresponding to each recognition result, based on the specific recognition result, to obtain a first confidence level.

[0098] S302 uses a vehicle body hazardous materials sign detection algorithm to identify the vehicle body image and determine the second confidence level of the vehicle body hazardous materials sign.

[0099] The algorithm for detecting hazardous materials signs on the vehicle body can be the same as or different from the algorithm for detecting hazardous materials signs on the front of the vehicle.

[0100] In this embodiment, based on the side-view images of the vehicle acquired by a multi-view camera group, firstly, a deep learning algorithm is used to identify the area where the vehicle is located in the side-view image, thus obtaining the target vehicle image. Then, a vehicle hazard sign detection algorithm is used to identify the vehicle hazard signs in the target vehicle image, thus obtaining the number of vehicle hazard signs.

[0101] In one possible implementation, a vehicle vehicle hazardous materials sign detection algorithm is used to identify the number of vehicle vehicle hazardous materials signs. If no vehicle vehicle hazardous materials signs are found, the second confidence level of the vehicle vehicle hazardous materials signs is determined to be 0. If vehicle vehicle hazardous materials signs are found, the second confidence level of the vehicle vehicle hazardous materials signs can be determined based on the number of vehicle vehicle hazardous materials signs.

[0102] S303, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle based on the first confidence level and / or the second confidence level.

[0103] In this embodiment, if the first confidence level is greater than the front confidence level threshold, the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle; if the first confidence level is not greater than the front confidence level threshold and the second confidence level is greater than the vehicle body confidence level threshold, the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle; if the first confidence level is not greater than the front confidence level threshold and the second confidence level is not greater than the vehicle body confidence level threshold (dangerous goods markings are present on the vehicle body), the vehicle is determined to be a suspected passenger vehicle and a dangerous goods vehicle; if the first confidence level is not greater than the front confidence level threshold and the second confidence level is 0 (dangerous goods markings are not present on the vehicle body), the vehicle is determined not to be a passenger vehicle and a dangerous goods vehicle.

[0104] Specifically, this can be expressed as follows: if the confidence level of the hazardous materials sign on the front of the vehicle is greater than the confidence threshold for the front of the vehicle, the number of hazardous materials signs on the vehicle body is greater than 0, and the confidence level of the hazardous materials signs on the vehicle body is greater than the confidence threshold for the vehicle body, then the vehicle is determined to be a passenger vehicle with one hazardous materials sign; if the confidence level of the hazardous materials sign on the front of the vehicle is greater than the confidence threshold for the front of the vehicle, the number of hazardous materials signs on the vehicle body is greater than 0, and the confidence level of the hazardous materials signs on the vehicle body is less than the confidence threshold for the vehicle body, then the vehicle is determined to be a passenger vehicle with one hazardous materials sign; if the confidence level of the hazardous materials sign on the front of the vehicle is greater than the confidence threshold for the front of the vehicle, the number of hazardous materials signs on the vehicle body is 0, and the confidence level of the hazardous materials signs on the vehicle body is less than the confidence threshold for the vehicle body, then the vehicle is determined to be a passenger vehicle with one hazardous materials sign; If a passenger vehicle is classified as a dangerous goods vehicle, and the confidence level of the dangerous goods sign on the front of the vehicle is less than the confidence threshold for the front of the vehicle, the number of dangerous goods signs on the body of the vehicle is greater than 0, and the confidence level of the dangerous goods signs on the body of the vehicle is greater than the confidence threshold for the body of the vehicle, then the vehicle is determined to be a passenger vehicle classified as a dangerous goods vehicle. If the confidence level of the dangerous goods sign on the front of the vehicle is less than the confidence threshold for the front of the vehicle, the number of dangerous goods signs on the body of the vehicle is greater than 0, and the confidence level of the dangerous goods signs on the body of the vehicle is less than the confidence threshold for the body of the vehicle, then the vehicle is determined to be neither a passenger vehicle nor a dangerous goods vehicle.

[0105] Furthermore, based on the second confidence level, it is determined whether the vehicle is a passenger vehicle or a dangerous goods vehicle, including: if the second confidence level is greater than the vehicle body confidence threshold, then the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, and the vehicle sub-type is determined.

[0106] In this embodiment, the specific type of vehicle hazard sign is determined based on the vehicle body hazard sign detection algorithm, thereby obtaining the vehicle's sub-type. The circular hazard signs include symbols for "flammable," "corrosive," "explosive," "heat-producing," and "toxic," such as... Figure 4 As shown, different types of vehicle vehicle hazard symbols are displayed.

[0107] In this embodiment, when the vehicle type information is a truck, a first confidence level for the hazardous materials sign on the front of the vehicle and a second confidence level for the hazardous materials sign on the body of the vehicle are determined respectively. Based on the first and second confidence levels, it is determined whether the vehicle is a passenger vehicle or a hazardous materials transport vehicle. This embodiment combines both the hazardous materials sign on the body and the hazardous materials sign on the front to determine whether a truck is a passenger vehicle or a hazardous materials transport vehicle, avoiding the identification difficulties caused by obscured hazardous materials signs on the body or front, and improving the accuracy of identifying passenger vehicles and hazardous materials transport vehicles.

[0108] Figure 5 This is a schematic diagram of a vehicle management process in one embodiment, such as... Figure 5 As shown, this application embodiment relates to a possible implementation of how to manage vehicles based on vehicle tracking results, including the following steps:

[0109] S501 determines whether a vehicle has been involved in an accident based on the vehicle tracking results.

[0110] In this embodiment, the multi-view camera group, checkpoint camera, and lidar of the multi-source system inside the tunnel continuously acquire vehicle information to obtain vehicle tracking results. For example, it can be determined whether a vehicle has been involved in an accident based on the image and video information acquired by the multi-view camera group, or based on the point cloud data of the lidar; or it can be determined whether a vehicle has been involved in an accident based on a combination of multiple acquired information.

[0111] S502: If a vehicle is involved in an accident, the vehicle will be managed according to its specific sub-type.

[0112] In this embodiment, if a vehicle is involved in an accident, targeted rescue operations can be carried out based on the type of passenger vehicle and dangerous goods vehicle and the different types of dangerous goods signs, thereby achieving vehicle management.

[0113] In this embodiment, based on the vehicle tracking results, it is determined whether a vehicle has been involved in an accident. If an accident occurs, the vehicle is managed according to its sub-type, which can effectively improve road traffic safety.

[0114] Figure 6 This is a schematic diagram of the process for managing vehicles in another embodiment, such as... Figure 6 As shown, this application embodiment relates to another possible implementation of how to manage vehicles based on vehicle tracking results, including the following steps:

[0115] S601 determines the vehicle's speed information based on the tracking results.

[0116] In this embodiment, vehicle speed information is obtained based on the point cloud data acquired by the lidar device in the tracking results.

[0117] S602, if the speed information is greater than the preset speed, or if it is determined that the vehicle is stationary based on the speed information, then the first prompt information is output and the acquisition information of the multi-view camera group is obtained.

[0118] In this embodiment, when the speed information is greater than the preset speed, it proves that the vehicle is speeding, or the speed information determines that the vehicle is stationary. A first warning message is output to warn of the dangerous driving behavior. The warning can be given through a warning light, a buzzer, or information output. At the same time, the information collected by the multi-view camera group is used to take pictures for evidence.

[0119] In this embodiment, the vehicle speed information is determined based on the tracking results. If the speed information is greater than a preset speed, or if the vehicle is determined to be stationary based on the speed information, a first warning message is output to prevent traffic accidents from occurring.

[0120] For example, based on the above embodiments, the number and location of passenger and hazardous materials vehicles in the tunnel can be determined according to the information collected by the multi-source system; and a second prompt message can be output according to the number and location of passenger and hazardous materials vehicles in the tunnel.

[0121] In this embodiment, based on the information collected by the multi-source system, the number and location of passenger and hazardous materials vehicles in the tunnel are counted in real time. The number and location of passenger and hazardous materials vehicles are output to remind vehicles entering the tunnel to maintain a safe distance and pay attention to avoid them, thereby alleviating congestion and reducing the occurrence of accidents.

[0122] In one embodiment, such as Figure 7 As shown, this application also provides a specific embodiment of a management method for passenger and hazardous goods vehicles in tunnels, including the following steps: when a vehicle enters the tunnel detection area, point cloud data from a lidar, image data from a checkpoint camera and a multi-view camera group are acquired, and the point cloud data and image data are fused using a fusion algorithm to achieve the binding of vehicle information.

[0123] Further, the license plate information obtained from the checkpoint camera is compared with the data of passenger and hazardous goods vehicles. If the license plate information exists in the passenger and hazardous goods vehicle database, the vehicle is tracked using a multi-source system, and vehicle management is carried out based on the tracking results.

[0124] If the license plate information does not exist in the passenger and hazardous materials transport database, determine whether the vehicle is a bus. If the vehicle is a bus, determine that the vehicle is a passenger and hazardous materials transport vehicle, and update the passenger and hazardous materials transport database according to the bus's license plate information. Use a multi-source system to track the vehicle, and then manage the vehicle based on the tracking results.

[0125] If the vehicle type is not a bus, then determine whether the vehicle is a truck. If the vehicle type is a truck, then determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle based on the detection of dangerous goods signs on the vehicle body and the front of the vehicle. After confirming that the truck is a passenger vehicle or a dangerous goods vehicle, update the passenger vehicle or dangerous goods vehicle database according to the truck's license plate information, use a multi-source system to track the vehicle, and then manage the vehicle based on the tracking results.

[0126] In one embodiment, such as Figure 8As shown, this application also provides a flowchart for detecting hazardous materials signs on the front and body of a truck, including the following steps: using a deep learning algorithm to detect the area of ​​the target truck in the front image acquired by a checkpoint camera to obtain a first target truck image; and using a deep learning algorithm to detect the area of ​​the target truck in the body image acquired by a multi-view camera group to obtain a second target truck image. A front detection algorithm is used to identify the hazardous materials signs on the front of the first target truck image to obtain a first quantity of hazardous materials on the front, and a first confidence level of the hazardous materials on the front is determined based on the first quantity and the position of the hazardous materials signs. A body detection algorithm is used to identify a second quantity of hazardous materials signs in the second target truck image, and a second confidence level of the hazardous materials signs on the body is obtained based on the second quantity. Based on the first confidence level of the hazardous materials signs on the front and / or the second confidence level of the hazardous materials signs on the body, it is determined whether the truck is a passenger vehicle or a hazardous materials vehicle. Furthermore, a body detection algorithm can be used to identify the color, characters, etc., of the hazardous materials signs on the body, thereby obtaining the specific sub-type of the passenger vehicle or hazardous materials vehicle based on the color, characters, etc., of the hazardous materials signs on the body.

[0127] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0128] Based on the same inventive concept, this application also provides a tunnel management device for two-passenger-one-dangerous-vehicles, used to implement the aforementioned management method for two-passenger-one-dangerous-vehicles in tunnels. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of the one or more tunnel management device embodiments provided below can be found in the above-described limitations of the tunnel management method for two-passenger-one-dangerous-vehicles, and will not be repeated here.

[0129] In one embodiment, such as Figure 9 As shown, a management device for passenger and hazardous goods vehicles in a tunnel is provided, comprising: a binding module 11, an acquisition module 12, a first determination module 13, a tracking module 14, and a management module 15, wherein:

[0130] The binding module 11 is used to bind the vehicle to the information of the multi-source system in the tunnel when the vehicle enters the tunnel. The binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera and a lidar.

[0131] The acquisition module 12 is used to trigger the checkpoint camera to acquire the vehicle's license plate information based on the location information obtained by the lidar when the vehicle enters the recognition area.

[0132] The first determining module 13 is used to search the preset two-passenger-one-dangerous-vehicle management database based on the license plate information. If the license plate information is found in the two-passenger-one-dangerous-vehicle management database, the vehicle is determined to be a two-passenger-one-dangerous-vehicle.

[0133] Tracking module 14 is used to track a vehicle based on license plate information and binding information using a multi-source system when the vehicle is identified as a passenger vehicle or a dangerous goods vehicle.

[0134] The management module 15 is used to manage vehicles based on the vehicle tracking results.

[0135] In one embodiment, the management device for passenger and hazardous goods vehicles within the tunnel further includes:

[0136] The second determination module is used to determine the vehicle type information based on the information collected by the multi-view camera group and lidar if the license plate information is not found in the vehicle management database for passenger vehicles and dangerous goods vehicles.

[0137] The judgment module is used to determine whether a vehicle is a passenger vehicle or a dangerous goods vehicle based on the vehicle type information.

[0138] In one embodiment, the determination module includes:

[0139] The first determining unit is used to determine that if the vehicle's vehicle type information is a bus, then the vehicle is a passenger vehicle and a dangerous goods vehicle.

[0140] In one embodiment, the determination module further includes:

[0141] The update unit is used to update the passenger and hazardous materials vehicle management database based on the vehicle's license plate information when the vehicle is determined to be a passenger vehicle or hazardous materials vehicle based on the vehicle type information.

[0142] In one embodiment, the determination module further includes:

[0143] The identification unit is used to identify the vehicle's front hazardous materials sign information and determine the first confidence level of the vehicle's front hazardous materials sign if the vehicle's model information is a truck.

[0144] The second determining unit is used to identify the vehicle body image using a vehicle body hazardous materials sign detection algorithm and determine the second confidence level of the vehicle body hazardous materials sign.

[0145] The judgment unit is used to determine whether a vehicle is a passenger vehicle or a dangerous goods vehicle based on a first confidence level and / or a second confidence level.

[0146] In one embodiment, the determining unit is further configured to determine that the vehicle belongs to the category of passenger vehicles and dangerous goods vehicles, and to determine the vehicle's sub-type, if the second confidence level is greater than the vehicle body confidence level threshold.

[0147] In one embodiment, the tracking module includes:

[0148] The third determining unit is used to determine whether a vehicle has been involved in an accident based on the vehicle tracking results;

[0149] The management unit is used to manage vehicles based on their specific sub-types in the event of an accident.

[0150] In one embodiment, the tracking module further includes:

[0151] The fourth determining unit is used to determine the vehicle's speed information based on the tracking results;

[0152] The output unit is used to output a first prompt message and acquire the data collected by the multi-view camera group if the speed information is greater than the preset speed or if the vehicle is determined to be stationary based on the speed information.

[0153] In one embodiment, the management device for passenger and hazardous goods vehicles within the tunnel further includes:

[0154] The third determination module is used to determine the number and location of passenger and hazardous goods vehicles in the tunnel based on the information collected by the multi-source system.

[0155] The output module is used to output a second prompt message based on the number and location of passenger and hazardous goods vehicles in the tunnel.

[0156] The various modules in the management device for passenger and hazardous goods vehicles within the aforementioned tunnel can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0157] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data related to traffic safety. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a management method for passenger and hazardous goods vehicles within a tunnel.

[0158] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0159] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0160] When a vehicle enters the tunnel, information binding is performed on the vehicle by the multi-source system within the tunnel to obtain binding information. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0161] When a vehicle enters the recognition area, the checkpoint camera is triggered to obtain the vehicle's license plate information based on the location information obtained by the lidar.

[0162] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is found in the management database of passenger vehicles and dangerous goods vehicles, the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0163] When a vehicle is identified as a passenger vehicle or a dangerous goods vehicle, it is tracked using a multi-source system based on the license plate information and binding information.

[0164] Vehicles are managed based on the tracking results.

[0165] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0166] If the vehicle license plate information is not found in the vehicle management database for passenger vehicles and hazardous materials vehicles, the vehicle model information will be determined based on the information collected by the multi-view camera group and LiDAR.

[0167] Based on vehicle type information, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0168] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0169] If the vehicle type information is a bus, then the vehicle is identified as a passenger vehicle and a dangerous goods vehicle.

[0170] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0171] If a vehicle is identified as a passenger vehicle or a hazardous materials vehicle based on its vehicle model information, the passenger vehicle and hazardous materials vehicle management database is updated according to the vehicle's license plate information.

[0172] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0173] If the vehicle type information is a truck, the dangerous goods sign detection algorithm on the front of the vehicle is used to identify the dangerous goods sign information on the front of the vehicle and determine the first confidence level of the dangerous goods sign on the front of the vehicle.

[0174] A vehicle body hazardous materials sign detection algorithm is used to identify the vehicle body image and determine the second confidence level of the vehicle body hazardous materials sign;

[0175] Based on the first confidence level and / or the second confidence level, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0176] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0177] If the second confidence level is greater than the vehicle body confidence threshold, then the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, and the vehicle's sub-type is determined.

[0178] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0179] Based on the vehicle tracking results, determine whether the vehicle has been involved in an accident;

[0180] If a vehicle is involved in an accident, the vehicle is managed according to its specific classification. In one embodiment, the processor, when executing the computer program, also performs the following steps:

[0181] Based on the tracking results, determine the vehicle's speed information;

[0182] If the speed information is greater than the preset speed, or if the vehicle is determined to be stationary based on the speed information, the first prompt message will be output, and the data collected by the multi-view camera group will be acquired.

[0183] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0184] Based on the information collected by the multi-source system, the number and location of two passenger vehicles and one dangerous goods vehicle in the tunnel were determined;

[0185] Based on the number and location of passenger and hazardous materials vehicles inside the tunnel, a second prompt message is output.

[0186] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0187] When a vehicle enters the tunnel, information binding is performed on the vehicle by the multi-source system within the tunnel to obtain binding information. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0188] When a vehicle enters the recognition area, the checkpoint camera is triggered to obtain the vehicle's license plate information based on the location information obtained by the lidar.

[0189] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is found in the management database of passenger vehicles and dangerous goods vehicles, the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0190] When a vehicle is identified as a passenger vehicle or a dangerous goods vehicle, it is tracked using a multi-source system based on the license plate information and binding information.

[0191] Vehicles are managed based on the tracking results.

[0192] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0193] If the vehicle license plate information is not found in the vehicle management database for passenger vehicles and hazardous materials vehicles, the vehicle model information will be determined based on the information collected by the multi-view camera group and LiDAR.

[0194] Based on vehicle type information, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0195] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0196] If the vehicle type information is a bus, then the vehicle is identified as a passenger vehicle and a dangerous goods vehicle.

[0197] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0198] If a vehicle is identified as a passenger vehicle or a hazardous materials vehicle based on its vehicle model information, the passenger vehicle and hazardous materials vehicle management database is updated according to the vehicle's license plate information.

[0199] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0200] If the vehicle type information is a truck, the dangerous goods sign detection algorithm on the front of the vehicle is used to identify the dangerous goods sign information on the front of the vehicle and determine the first confidence level of the dangerous goods sign on the front of the vehicle.

[0201] A vehicle body hazardous materials sign detection algorithm is used to identify the vehicle body image and determine the second confidence level of the vehicle body hazardous materials sign;

[0202] Based on the first confidence level and / or the second confidence level, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0203] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0204] If the second confidence level is greater than the vehicle body confidence threshold, then the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, and the vehicle's sub-type is determined.

[0205] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0206] Based on the vehicle tracking results, determine whether the vehicle has been involved in an accident;

[0207] If a vehicle is involved in an accident, it will be managed according to its specific type.

[0208] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0209] Based on the tracking results, determine the vehicle's speed information;

[0210] If the speed information is greater than the preset speed, or if the vehicle is determined to be stationary based on the speed information, the first prompt message will be output, and the data collected by the multi-view camera group will be acquired.

[0211] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0212] Based on the information collected by the multi-source system, the number and location of two passenger vehicles and one dangerous goods vehicle in the tunnel were determined;

[0213] Based on the number and location of passenger and hazardous materials vehicles inside the tunnel, a second prompt message is output.

[0214] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0215] When a vehicle enters the tunnel, information binding is performed on the vehicle by the multi-source system within the tunnel to obtain binding information. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar.

[0216] When a vehicle enters the recognition area, the checkpoint camera is triggered to obtain the vehicle's license plate information based on the location information obtained by the lidar.

[0217] Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is found in the management database of passenger vehicles and dangerous goods vehicles, the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle.

[0218] When a vehicle is identified as a passenger vehicle or a dangerous goods vehicle, it is tracked using a multi-source system based on the license plate information and binding information.

[0219] Vehicles are managed based on the tracking results.

[0220] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0221] If the vehicle license plate information is not found in the vehicle management database for passenger vehicles and hazardous materials vehicles, the vehicle model information will be determined based on the information collected by the multi-view camera group and LiDAR.

[0222] Based on vehicle type information, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0223] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0224] If the vehicle type information is a bus, then the vehicle is identified as a passenger vehicle and a dangerous goods vehicle.

[0225] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0226] If a vehicle is identified as a passenger vehicle or a hazardous materials vehicle based on its vehicle model information, the passenger vehicle and hazardous materials vehicle management database is updated according to the vehicle's license plate information.

[0227] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0228] If the vehicle type information is a truck, the dangerous goods sign detection algorithm on the front of the vehicle is used to identify the dangerous goods sign information on the front of the vehicle and determine the first confidence level of the dangerous goods sign on the front of the vehicle.

[0229] A vehicle body hazardous materials sign detection algorithm is used to identify the vehicle body image and determine the second confidence level of the vehicle body hazardous materials sign;

[0230] Based on the first confidence level and / or the second confidence level, determine whether the vehicle is a passenger vehicle or a dangerous goods vehicle.

[0231] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0232] If the second confidence level is greater than the vehicle body confidence threshold, then the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, and the vehicle's sub-type is determined.

[0233] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0234] Based on the vehicle tracking results, determine whether the vehicle has been involved in an accident;

[0235] If a vehicle is involved in an accident, it will be managed according to its specific type.

[0236] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0237] Based on the tracking results, determine the vehicle's speed information;

[0238] If the speed information is greater than the preset speed, or if the vehicle is determined to be stationary based on the speed information, the first prompt message will be output, and the data collected by the multi-view camera group will be acquired.

[0239] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0240] Based on the information collected by the multi-source system, the number and location of two passenger vehicles and one dangerous goods vehicle in the tunnel were determined;

[0241] Based on the number and location of passenger and hazardous materials vehicles inside the tunnel, a second prompt message is output.

[0242] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0243] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0244] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A management method for passenger and hazardous goods vehicles within a tunnel, characterized in that, The method includes: When a vehicle enters a tunnel, information binding information is performed on the vehicle using the information from the multi-source system within the tunnel. This binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera, and a lidar. When the vehicle enters the identification area, the checkpoint camera is triggered to acquire the vehicle's license plate information based on the location information obtained by the lidar. Based on the license plate information, search the preset management database of passenger vehicles and dangerous goods vehicles. If the license plate information is in the management database of passenger vehicles and dangerous goods vehicles, then the vehicle is determined to be a passenger vehicle and a dangerous goods vehicle. When the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, the vehicle is tracked using the multi-source system based on the license plate information and the binding information. The vehicle is managed based on the tracking results. If the license plate information is not found in the vehicle management database for passenger and hazardous goods vehicles, the vehicle model information is determined based on the information collected by the multi-view camera group and the lidar. If the vehicle type information is a truck, then the vehicle front hazardous materials sign detection algorithm is used to identify the vehicle front hazardous materials sign information and determine the first confidence level of the vehicle front hazardous materials sign; the vehicle body hazardous materials sign detection algorithm is used to identify the vehicle body image and determine the second confidence level of the vehicle body hazardous materials sign; based on the first confidence level and the second confidence level, it is determined whether the vehicle is the two-passenger-one-hazardous-materials vehicle.

2. The method according to claim 1, characterized in that, The step of determining whether the vehicle is one of the two types of passenger vehicles and one type of dangerous goods vehicle based on the vehicle model information includes: If the vehicle type information is a bus, then the vehicle is identified as one of the two passenger vehicles and one dangerous goods vehicle.

3. The method according to claim 1, characterized in that, The method further includes: If the vehicle is determined to be a passenger vehicle or a hazardous materials vehicle based on the vehicle model information, the passenger vehicle and hazardous materials vehicle management database is updated according to the vehicle's license plate information.

4. The method according to claim 1, characterized in that, Determining whether the vehicle is one of the two passenger and one dangerous goods vehicles based on the second confidence level includes: If the second confidence level is greater than the vehicle body confidence level threshold, then the vehicle is determined to be a passenger vehicle or a dangerous goods vehicle, and the vehicle's sub-type is determined.

5. The method according to claim 4, characterized in that, The step of managing the vehicle based on the vehicle tracking results includes: Based on the vehicle tracking results, determine whether the vehicle has been involved in an accident; If the vehicle is involved in an accident, the vehicle shall be managed according to its specific sub-type.

6. The method according to claim 1, characterized in that, The step of managing the vehicle based on the vehicle tracking results includes: Based on the tracking results, the speed information of the vehicle is determined; If the speed information is greater than the preset speed, or if it is determined based on the speed information that the vehicle is stationary, then a first prompt message is output, and the acquisition information from the multi-view camera group is obtained.

7. The method according to claim 1, characterized in that, The method further includes: Based on the information collected by the multi-source system, the number and location of the two passenger vehicles and one dangerous goods vehicle in the tunnel are determined; Based on the number and location of the two passenger vehicles and one dangerous goods vehicle in the tunnel, a second prompt message is output.

8. A management device for passenger and hazardous goods vehicles within a tunnel, characterized in that, The device includes: The binding module is used to bind the vehicle to the information of the multi-source system in the tunnel when the vehicle enters the tunnel, and obtain binding information. The binding information is used to index the information collected by each device in the multi-source system on the vehicle using the identity identifier assigned by the multi-source system. The multi-source system includes a multi-view camera group, a checkpoint camera and a lidar. The acquisition module is used to trigger the checkpoint camera to acquire the vehicle's license plate information based on the location information obtained by the lidar when the vehicle enters the recognition area. The first determining module is used to search a preset passenger and hazardous materials vehicle management database based on the license plate information. If the license plate information is in the database, the vehicle is determined to be a passenger and hazardous materials vehicle. The tracking module is used to track the vehicle using the multi-source system based on the license plate information and the binding information when it is determined that the vehicle is a passenger vehicle or a dangerous goods vehicle. The management module is used to manage the vehicle based on the tracking results. The second determining module is used to determine the vehicle model information based on the information collected by the multi-view camera group and the lidar if the license plate information is not found in the two-passenger-one-dangerous-vehicle management database. The judgment module is used to, if the vehicle model information is a truck, use a front hazardous materials sign detection algorithm to identify the vehicle's front hazardous materials sign information and determine the first confidence level of the vehicle's front hazardous materials sign; use a body hazardous materials sign detection algorithm to identify the vehicle's body image and determine the second confidence level of the vehicle's body hazardous materials sign; and determine whether the vehicle is a passenger vehicle or a hazardous materials vehicle based on the first confidence level and the second confidence level.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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