A highway vehicle monitoring method and system, and storage medium

Abstract

The present invention discloses a highway vehicle monitoring method and system, and a storage medium, and relates to the technical field of road management. The method comprises: for each monitoring device on a target highway, the vehicle information of the target vehicle acquired by the monitoring device is saved in the monitoring node corresponding to the monitoring device; the node transmission path of the target vehicle is acquired from the monitoring knowledge graph corresponding to the target highway; and the driving track of the target vehicle on the target highway is determined according to the node transmission path. The present invention can realize the structured description of all monitoring devices on the target highway based on the monitoring knowledge graph, and then determine the driving track of the target vehicle on the target highway according to the node transmission path on the monitoring knowledge graph. Thereby, the vehicle information acquired on the highway is efficiently analyzed and managed, and the efficiency of vehicle monitoring on the highway is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of road management, and in particular to a highway vehicle monitoring method and system, and a storage medium. Background Art

[0002] Expressways greatly facilitate people's lives, and monitoring vehicles on them helps improve the efficiency of highway management. Existing technologies primarily rely on methods such as video surveillance, radar speed measurement, and ETC monitoring to obtain vehicle information on highways, and then monitor vehicle status on the highway based on this information. Practice has shown that existing technologies for monitoring vehicle status on highways often rely solely on analyzing data from one of these methods, such as video surveillance, radar speed measurement, or ETC monitoring. This results in inefficient analysis and management of vehicle information acquired on highways, leading to inefficient vehicle monitoring on highways. Therefore, how to efficiently analyze and manage vehicle information acquired on highways, thereby improving the efficiency of vehicle monitoring on highways, is a major challenge that highway managers need to address. Summary of the Invention

[0003] The present invention provides a method and system for monitoring vehicles on a highway, and a storage medium, which can efficiently analyze and manage vehicle information acquired on the highway, thereby improving the efficiency of vehicle monitoring on the highway.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a method for monitoring vehicles on a highway, the method comprising:

[0005] For each monitoring device on the target highway, the vehicle information of the target vehicle acquired by the monitoring device is saved in the monitoring node corresponding to the monitoring device; wherein the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is the node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway;

[0006] Obtain the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway; and determine the driving trajectory of the target vehicle on the target highway based on the node transmission path.

[0007] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0008] Acquire monitoring device category information and monitoring device location information of each monitoring device on the target highway;

[0009] Obtaining an association relationship between each of the monitoring devices and other monitoring devices on the target highway;

[0010] A monitoring knowledge graph corresponding to the target highway is generated based on the monitoring device category information and the monitoring device location information of each monitoring device on the target highway and the association relationship between each monitoring device and other monitoring devices.

[0011] As an optional embodiment, in the first aspect of the present invention, for each monitoring device on the target highway, saving the vehicle information of the target vehicle acquired by the monitoring device to the monitoring node corresponding to the monitoring device includes:

[0012] For each of the monitoring devices on the target highway, determining the vehicle identity of the target vehicle based on the vehicle information of the target vehicle acquired by the monitoring device, and saving the vehicle identity of the target vehicle and the monitoring time point at which the vehicle information was acquired by the monitoring device to the monitoring node corresponding to the monitoring device;

[0013] Furthermore, obtaining the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway includes:

[0014] Traversing the monitoring knowledge graph corresponding to the target highway, obtaining all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle;

[0015] The node transmission path of the target vehicle is determined according to all the target monitoring nodes and the monitoring time point corresponding to the target vehicle in each of the target monitoring nodes.

[0016] As an optional embodiment, in the first aspect of the present invention, determining the node transmission path of the target vehicle based on all the target monitoring nodes and the monitoring time point corresponding to the target vehicle in each target monitoring node includes:

[0017] Constructing a sub-monitoring knowledge graph corresponding to the target vehicle according to the node relationship between each target monitoring node and other target monitoring nodes;

[0018] According to the monitoring time point corresponding to the target vehicle in each of the target monitoring nodes, the target node transmission path that matches the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, and the target node transmission path is determined to be the node transmission path of the target vehicle.

[0019] As an optional implementation manner, in the first aspect of the present invention, after determining the driving trajectory of the target vehicle on the target highway, the method further includes:

[0020] Determine all desired nodes corresponding to the target vehicle based on all the target monitoring nodes, where the desired node is a monitoring node corresponding to the next monitoring device that the target vehicle may pass through in the monitoring knowledge graph;

[0021] For each of the desired nodes corresponding to the target vehicle, the desired driving trajectory of the target vehicle on the target highway is determined based on the node transmission path and the desired node, and the cost information of the target vehicle corresponding to the desired node is determined based on the desired driving trajectory and the vehicle information.

[0022] As an optional embodiment, in the first aspect of the present invention, the monitoring device includes an image monitoring device, a video monitoring device, a radar monitoring device, an ETC monitoring device, and a wireless signal monitoring device; the monitoring knowledge graph corresponding to the target expressway includes an image monitoring node, a video monitoring node, a radar monitoring node, an ETC monitoring node, and a wireless signal monitoring node;

[0023] The obtaining of the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway includes:

[0024] According to the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, respectively obtain the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all the target vehicles;

[0025] The node transmission path of the target vehicle is determined based on the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all the target vehicles.

[0026] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0027] For each of the monitoring devices on the target highway, the vehicle characteristic information of the unidentified vehicle acquired by the monitoring device is stored in the monitoring node corresponding to the monitoring device; the unidentified vehicle is a vehicle whose identity cannot be uniquely determined, and the vehicle characteristic information includes one or more of photo information, video information, radar speed measurement information, ETC information, and wireless signal information of the unidentified vehicle;

[0028] According to the vehicle feature information of all the unidentified vehicles stored in the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, determine the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph corresponding to all the unidentified vehicles;

[0029] According to the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph, identifiable vehicles are screened out from all the unidentified vehicles and the target node transmission path corresponding to the identifiable vehicle is determined.

[0030] A second aspect of the present invention discloses a highway vehicle monitoring system, the system comprising:

[0031] a node updating module configured to, for each monitoring device on a target highway, save the vehicle information of a target vehicle acquired by the monitoring device to a monitoring node corresponding to the monitoring device; wherein the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is the node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway;

[0032] The trajectory analysis module is used to obtain the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway; and determine the driving trajectory of the target vehicle on the target highway based on the node transmission path.

[0033] As an optional embodiment, in the second aspect of the present invention, the system further includes:

[0034] a first acquisition module, configured to acquire monitoring device category information and monitoring device location information of each monitoring device on the target highway;

[0035] A second acquisition module is used to obtain the association relationship between each monitoring device and other monitoring devices on the target highway;

[0036] The graph construction module is used to generate a monitoring knowledge graph corresponding to the target highway based on the monitoring device category information and the monitoring device location information of each monitoring device on the target highway and the association relationship between each monitoring device and other monitoring devices.

[0037] As an optional embodiment, in the second aspect of the present invention, the specific manner in which the node update module saves the vehicle information of the target vehicle acquired by each monitoring device on the target highway to the monitoring node corresponding to the monitoring device includes:

[0038] For each of the monitoring devices on the target highway, determining the vehicle identity of the target vehicle based on the vehicle information of the target vehicle acquired by the monitoring device, and saving the vehicle identity of the target vehicle and the monitoring time point at which the vehicle information was acquired by the monitoring device to the monitoring node corresponding to the monitoring device;

[0039] Furthermore, the specific manner in which the trajectory analysis module obtains the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway includes:

[0040] Traversing the monitoring knowledge graph corresponding to the target highway, obtaining all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle;

[0041] The node transmission path of the target vehicle is determined according to all the target monitoring nodes and the monitoring time point corresponding to the target vehicle in each of the target monitoring nodes.

[0042] As an optional embodiment, in the second aspect of the present invention, the trajectory analysis module determines the node transmission path of the target vehicle based on all the target monitoring nodes and the monitoring time point corresponding to the target vehicle in each target monitoring node, including:

[0043] Constructing a sub-monitoring knowledge graph corresponding to the target vehicle according to the node relationship between each target monitoring node and other target monitoring nodes;

[0044] According to the monitoring time point corresponding to the target vehicle in each of the target monitoring nodes, the target node transmission path that matches the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, and the target node transmission path is determined to be the node transmission path of the target vehicle.

[0045] As an optional embodiment, in the second aspect of the present invention, the system further includes:

[0046] a node prediction module, configured to determine, after the trajectory analysis module determines the driving trajectory of the target vehicle on the target highway, all expected nodes corresponding to the target vehicle based on all the target monitoring nodes, wherein the expected nodes are monitoring nodes corresponding to the next monitoring device that the target vehicle may pass through in the monitoring knowledge graph;

[0047] The cost prediction module is used to determine, for each expected node corresponding to the target vehicle, an expected driving trajectory of the target vehicle on the target highway based on the node transmission path and the expected node, and determine the cost information of the target vehicle corresponding to the expected node based on the expected driving trajectory and the vehicle information.

[0048] As an optional embodiment, in the second aspect of the present invention, the monitoring device includes an image monitoring device, a video monitoring device, a radar monitoring device, an ETC monitoring device, and a wireless signal monitoring device; the monitoring knowledge graph corresponding to the target expressway includes an image monitoring node, a video monitoring node, a radar monitoring node, an ETC monitoring node, and a wireless signal monitoring node;

[0049] The specific method of the trajectory analysis module obtaining the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway includes:

[0050] According to the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, respectively obtain the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all the target vehicles;

[0051] The node transmission path of the target vehicle is determined based on the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all the target vehicles.

[0052] As an optional embodiment, in the second aspect of the present invention, the system further includes:

[0053] an unidentified updating module configured to, for each monitoring device on the target highway, store vehicle characteristic information of an unidentified vehicle acquired by the monitoring device to a monitoring node corresponding to the monitoring device; the unidentified vehicle being a vehicle whose identity cannot be uniquely determined, the vehicle characteristic information including one or more of photographic information, video information, radar speed measurement information, ETC information, and wireless signal information of the unidentified vehicle;

[0054] a sub-graph construction module, configured to determine the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph, and wireless signal monitoring sub-knowledge graph corresponding to all the unidentified vehicles based on the vehicle feature information of all the unidentified vehicles stored in the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes, and wireless signal monitoring nodes on the monitoring knowledge graph;

[0055] The vehicle identification module is used to filter out identifiable vehicles from all the unidentified vehicles and determine the target node transmission path corresponding to the identifiable vehicles based on the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph.

[0056] A third aspect of the present invention discloses another highway vehicle monitoring system, the system comprising:

[0057] a memory storing executable program code;

[0058] a processor coupled to the memory;

[0059] The processor calls the executable program code stored in the memory to execute the highway vehicle monitoring method disclosed in the first aspect of the present invention.

[0060] A fourth aspect of the present invention discloses a computer storage medium, wherein the computer storage medium stores computer instructions. When the computer instructions are called, they are used to execute the highway vehicle monitoring method disclosed in the first aspect of the present invention.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] In the present invention, for each monitoring device on the target highway, the vehicle information of the target vehicle obtained by the monitoring device is saved in the monitoring node corresponding to the monitoring device; wherein the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is the node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway; the node transmission path of the target vehicle is obtained from the monitoring knowledge graph corresponding to the target highway; and the driving trajectory of the target vehicle on the target highway is determined based on the node transmission path. It can be seen that the present invention can realize the structured description of all monitoring devices on the target highway based on the monitoring knowledge graph, and then determine the driving trajectory of the target vehicle on the target highway based on the node transmission path on the monitoring knowledge graph. In this way, the vehicle information obtained on the highway can be efficiently analyzed and managed, and the efficiency of vehicle monitoring on the highway can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0064] Figure 1This is a flow chart of a highway vehicle monitoring method disclosed in an embodiment of the present invention;

[0065] Figure 2 This is a flow chart of another highway vehicle monitoring method disclosed in an embodiment of the present invention;

[0066] Figure 3 This is a schematic structural diagram of a highway vehicle monitoring system disclosed in an embodiment of the present invention;

[0067] Figure 4 1 is a schematic structural diagram of another highway vehicle monitoring system disclosed in an embodiment of the present invention;

[0068] Figure 5 This is a structural diagram of another highway vehicle monitoring system disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0070] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or end.

[0071] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0072] This invention discloses a highway vehicle monitoring method, system, and storage medium. The main inventive concept is to achieve a structured description of all monitoring devices on a target highway based on a monitoring knowledge graph. Then, based on the node transmission paths in the monitoring knowledge graph, the target vehicle's travel trajectory on the target highway is determined. This allows for efficient analysis and management of vehicle information acquired on the highway, improving the efficiency of highway vehicle monitoring.

[0073] Example 1

[0074] See also Figure 1 , Figure 1 This is a flow chart of a highway vehicle monitoring method disclosed in an embodiment of the present invention. Figure 1 The highway vehicle monitoring method described can be applied to a highway vehicle monitoring system, which can be integrated into a cloud server or a local server, and the embodiment of the present invention does not limit this. Figure 1 As shown, the highway vehicle monitoring method may include the following operations:

[0075] Step 101: For each monitoring device on a target highway, the vehicle information of the target vehicle acquired by the monitoring device is saved in a monitoring node corresponding to the monitoring device.

[0076] In the embodiment of the present invention, specifically, the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is a node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway.

[0077] In an embodiment of the present invention, the monitoring devices on the target highway may include image monitoring devices, video monitoring devices, radar monitoring devices, ETC monitoring devices, and wireless signal monitoring devices, etc. A knowledge graph is a structured semantic knowledge base used to quickly describe concepts in the physical world and their relationships. Specifically, a knowledge graph is a graphical structure used to describe entities, attributes, and various relationships between entities. It achieves rapid response and reasoning of knowledge by processing data into triples of "entity-relationship-entity". The embodiment of the present invention uses a knowledge graph to perform a structured description of all monitoring devices on the target highway, thereby enabling efficient management of target vehicle data.

[0078] In an optional embodiment, the method may further include a step of monitoring the construction of the knowledge graph:

[0079] Obtain monitoring device category information and monitoring device location information of each monitoring device on the target highway;

[0080] Obtaining the association relationship between each monitoring device and other monitoring devices on the target highway;

[0081] Based on the monitoring device category information and monitoring device location information of each monitoring device on the target highway and the association relationship between each monitoring device and other monitoring devices, a monitoring knowledge graph corresponding to the target highway is generated.

[0082] In this optional embodiment, the "entity-relationship-entity" triple form in the knowledge graph can be used to construct a monitoring device network on the target highway, which can efficiently represent the attributes of each monitoring device and the relationship between any two monitoring devices.

[0083] Step 102: Obtain the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway; and determine the driving trajectory of the target vehicle on the target highway based on the node transmission path.

[0084] In an embodiment of the present invention, a node transmission path of a target vehicle is obtained from a monitoring knowledge graph corresponding to the target highway, and the node transmission path includes a driving trajectory of the target vehicle on the target highway.

[0085] As can be seen, the implementation of the highway vehicle monitoring method in this embodiment of the present invention enables a structured description of all monitoring devices on a target highway based on the monitoring knowledge graph. The target vehicle's trajectory on the target highway is then determined based on the node transmission paths in the monitoring knowledge graph. This allows for efficient analysis and management of vehicle information acquired on the highway, improving the efficiency of vehicle monitoring on the highway.

[0086] In an optional embodiment, for each monitoring device on the target highway, saving the vehicle information of the target vehicle acquired by the monitoring device to the monitoring node corresponding to the monitoring device may include:

[0087] For each monitoring device on the target highway, the target vehicle's identity is determined based on the vehicle information of the target vehicle acquired by the monitoring device, and the target vehicle's identity and the monitoring time point at which the monitoring device acquired the vehicle information are stored in the monitoring node corresponding to the monitoring device;

[0088] Furthermore, the node transmission path of the target vehicle is obtained from the monitoring knowledge graph corresponding to the target highway, including:

[0089] Traverse the monitoring knowledge graph corresponding to the target highway and obtain all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle;

[0090] The node transmission path of the target vehicle is determined based on all target monitoring nodes and the monitoring time point corresponding to the target vehicle in each target monitoring node.

[0091] In this optional embodiment, the vehicle identity of the target vehicle and the monitoring time point at which the monitoring device obtains the vehicle information are saved in the monitoring node corresponding to the monitoring device, thereby organizing all vehicle data monitored on the target highway into a monitoring knowledge graph. Based on the efficient data management and preservation mechanism of the knowledge graph, the efficiency of the monitoring data management of the entire target highway is improved. For the monitoring knowledge graph, more than one possible node transmission path is obtained only through a number of nodes and the relationship between the nodes. For example, there are multiple possible paths between two monitoring devices, and if the other monitoring devices between the two monitoring devices do not obtain the specific information of the target vehicle, it is difficult to determine which specific path the target vehicle has passed through. Therefore, in this optional embodiment, it is necessary to combine the monitoring time point to determine the node transmission path of the target vehicle based on all target monitoring nodes.

[0092] This optional embodiment is illustrated as follows:

[0093] Traverse the monitoring knowledge graph corresponding to the target highway and obtain all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle: A1, A7, B2, B5, D9. If only the relationship between each node is considered, there are many possible path relationships.

[0094] The monitoring time points corresponding to the target vehicle in each target monitoring node are A1-1:00, A7-2:50, B2-1:40, B5-3:00, and D9-3:20; based on all target monitoring nodes and the monitoring time points corresponding to the target vehicle in each target monitoring node, the node transmission path of the target vehicle is determined to be A1->B2->A7->B5->D9.

[0095] It can be seen that this optional embodiment can quickly determine the node transmission path of the target vehicle by analyzing the monitoring knowledge graph; when it is necessary to retrieve the driving trajectory of the target vehicle, only an application needs to be submitted to the server of the monitoring knowledge graph, which can quickly obtain the result without the need to analyze the data obtained by all monitoring devices. In particular, when it is necessary to analyze the driving trajectories of multiple vehicles in a short period of time, this optional embodiment can respond quickly, thereby improving the efficiency of vehicle monitoring on highways.

[0096] In another optional embodiment, determining the node transmission path of the target vehicle based on all target monitoring nodes and the monitoring time point corresponding to the target vehicle in each target monitoring node may include:

[0097] According to the node relationship between each target monitoring node and other target monitoring nodes, a sub-monitoring knowledge graph corresponding to the target vehicle is constructed;

[0098] According to the monitoring time point corresponding to the target vehicle in each target monitoring node, the target node transmission path that matches the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, and the target node transmission path is determined to be the node transmission path of the target vehicle.

[0099] In this optional embodiment, the management of the monitoring data of the target vehicle can be achieved by constructing a sub-monitoring knowledge graph corresponding to the target vehicle from the monitoring knowledge graph. The sub-monitoring knowledge graph represents various information about the target vehicle traveling on the target highway. The monitoring data of the target vehicle can be analyzed based on the sub-knowledge graph. For example, according to the monitoring time point corresponding to the target vehicle in each target monitoring node, the target node transmission path that matches the sub-monitoring knowledge graph is determined from the monitoring knowledge graph. It is also possible to analyze whether the target vehicle has any driving abnormalities based on the sub-knowledge graph.

[0100] It can be seen that this optional embodiment can construct a sub-monitoring knowledge graph corresponding to the target vehicle based on the node relationship between each target monitoring node and other target monitoring nodes, thereby realizing a more detailed monitoring data analysis of each target vehicle; in addition, according to the monitoring time point corresponding to the target vehicle in each target monitoring node, the target node transmission path matching the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, which can more accurately analyze the node transmission path corresponding to the target vehicle.

[0101] In yet another optional embodiment, after determining the driving trajectory of the target vehicle on the target highway, the method may further include:

[0102] Based on all target monitoring nodes, determine all expected nodes corresponding to the target vehicle. The expected node is the monitoring node corresponding to the next monitoring device that the target vehicle may pass through in the monitoring knowledge graph.

[0103] For each desired node corresponding to the target vehicle, the desired driving trajectory of the target vehicle on the target highway is determined based on the node transmission path and the desired node. The cost information of the target vehicle corresponding to the desired node is determined based on the desired driving trajectory and vehicle information.

[0104] In this optional embodiment, a key function of monitoring vehicles on highways is calculating the target vehicle's toll information based on its driving trajectory. While prior art often calculates tolls based on the target vehicle's entry and exit locations, the reality is that the target vehicle's driving trajectory can vary. Therefore, from a cost-refining perspective, it would be more reasonable to comprehensively calculate tolls based on the target vehicle's driving trajectory. In practical applications, when a target vehicle reaches an highway exit, the corresponding toll information needs to be quickly calculated. Calculating toll information based on the driving path, for complex routes, may not be timely enough if the driving path calculation begins only after the target vehicle reaches the exit.

[0105] Therefore, this optional embodiment determines all desired nodes corresponding to the target vehicle based on all target monitoring nodes. The desired node is the monitoring node corresponding to the next monitoring device that the target vehicle may pass through in the monitoring knowledge graph. For example, every time a monitoring node obtains monitoring information about the target vehicle, it updates the sub-monitoring knowledge graph corresponding to the target vehicle and determines the possible exit location of the target vehicle. The driving trajectory corresponding to each possible exit location is calculated in advance, so that the highway toll can be quickly determined based on the driving trajectory when the target vehicle reaches the exit location.

[0106] It can be seen that this optional embodiment can analyze in advance the driving trajectory of the target vehicle when it appears at each possible exit, so as to quickly determine the highway fee based on the vehicle's driving trajectory, thereby improving the meticulousness of the vehicle highway fee calculation while improving the timeliness of the vehicle highway fee calculation.

[0107] Example 2

[0108] See also Figure 2 , Figure 2 This is a flow chart of another highway vehicle monitoring method disclosed in an embodiment of the present invention. Figure 2 The highway vehicle monitoring method described can be applied to a highway vehicle monitoring system, which can be integrated into a cloud server or a local server, and the embodiment of the present invention does not limit this. Figure 2 As shown, the highway vehicle monitoring method may include the following operations:

[0109] Step 201: For each monitoring device on the target highway, the vehicle information of the target vehicle acquired by the monitoring device is saved in the monitoring node corresponding to the monitoring device.

[0110] In this embodiment of the present invention, the monitoring device includes an image monitoring device, a video monitoring device, a radar monitoring device, an ETC monitoring device, and a wireless signal monitoring device. The monitoring knowledge graph corresponding to the target highway includes image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes, and wireless signal monitoring nodes. The wireless signal monitoring device is a device that recognizes vehicle information through specific wireless signals, such as Bluetooth signals, Wi-Fi signals, and signals from the vehicle owner's mobile phone.

[0111] Step 202: According to the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all target vehicles are obtained respectively.

[0112] In an embodiment of the present invention, the monitoring knowledge graph is divided more finely, and the monitoring nodes are divided into image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes according to the different monitoring devices corresponding to each node, so that the vehicle monitoring data can be managed more finely through the monitoring knowledge graph.

[0113] Step 203: Determine the node transmission path of the target vehicle based on the image node transmission paths, video node transmission paths, radar node transmission paths, ETC node transmission paths, and wireless signal node transmission paths of all target vehicles.

[0114] In an embodiment of the present invention, the information of the target vehicle obtained by different types of monitoring devices may be erroneous, but the information of the target vehicle obtained by the same type of monitoring device is likely to be consistent. Therefore, the accuracy of the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of the target vehicle alone is higher than the node transmission path of the target vehicle directly obtained from the monitoring knowledge graph corresponding to the target highway. The embodiment of the present invention determines the node transmission path of the target vehicle after comprehensive analysis based on the above-mentioned independent image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path. Once any two independent transmission paths do not match, it means that an error has occurred and the transmission path needs to be determined again based on other transmission paths, which can improve the accuracy of the path analysis.

[0115] It can be seen that the implementation of the highway vehicle monitoring method in this optional embodiment can divide the monitoring nodes into image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes according to the different monitoring devices corresponding to each node, thereby performing more detailed management of vehicle monitoring data through the monitoring knowledge graph; in addition, the node transmission path of the target vehicle is determined based on the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all target vehicles, which can improve the accuracy of path analysis.

[0116] In an optional embodiment, the method may further include:

[0117] For each monitoring device on the target highway, the vehicle characteristic information of the unidentified vehicle acquired by the monitoring device is stored in the monitoring node corresponding to the monitoring device; the unidentified vehicle is a vehicle whose identity cannot be uniquely determined, and the vehicle characteristic information includes one or more of the following: photo information, video information, radar speed measurement information, ETC information, and wireless signal information of the unidentified vehicle;

[0118] According to the vehicle feature information of all unidentified vehicles stored in the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph corresponding to all unidentified vehicles are determined;

[0119] According to the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph, identifiable vehicles are screened out from all unidentified vehicles and the target node transmission path corresponding to the identifiable vehicles is determined.

[0120] In this optional embodiment, the monitoring knowledge graph can also be used to analyze unidentified vehicles, so that identifiable vehicles can be determined from the unidentified vehicles based on the information of the unidentified vehicles obtained. Among them, an unidentified vehicle is a vehicle whose identity cannot be uniquely determined, and the vehicle feature information includes one or more of the photo information, video information, radar speed information, ETC information and wireless signal information of the unidentified vehicle. An identified vehicle is a vehicle whose driving trajectory can be determined. An unidentified vehicle generally refers to a vehicle whose license plate number, temporary license plate number, frame number or engine number is not identified. However, on the basis of not identifying the above information, the driving trajectory of each unidentified vehicle can also be determined based on a series of unidentified vehicle information that has been obtained. At this time, although the license plate number and other information of the unidentified vehicle are not obtained, the driving status of the vehicle can be analyzed based on the determined driving trajectory information.

[0121] In this optional embodiment, an unidentified vehicle is detected by an image monitoring device, a video monitoring device, a radar monitoring device, an ETC monitoring device, and a wireless signal monitoring device. Based on the scattered data above, it is difficult to determine the driving trajectory of the unidentified vehicle. Therefore, it is necessary to filter out all image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes, and wireless signal monitoring nodes that store the characteristic information of unidentified vehicles, and construct image monitoring sub-knowledge graphs, video monitoring sub-knowledge graphs, radar monitoring sub-knowledge graphs, ETC monitoring sub-knowledge graphs, and wireless signal monitoring sub-knowledge graphs corresponding to all unidentified vehicles. Each sub-knowledge graph stores all unidentified vehicle data recorded by the same monitoring device. These data record the characteristic information of the unidentified vehicle and the time of monitoring. Although it is difficult to accurately determine the driving path of an unidentified vehicle by analyzing it alone, by analyzing all unidentified vehicles together, it is possible to filter out identifiable vehicles.

[0122] In this optional embodiment, based on the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph, and wireless signal monitoring sub-knowledge graph, identifiable vehicles are screened from all unidentified vehicles and the target node transmission path corresponding to the identifiable vehicles is determined. This can be accomplished using a pre-trained graph analysis model. For example, there are three unidentified vehicles on the target highway, which are detected by the image monitoring device, video monitoring device, radar monitoring device, ETC monitoring device, and wireless signal monitoring device, respectively. However, it is impossible to distinguish these three unidentified vehicles and determine their respective driving paths. In actual scenarios, the image monitoring device can roughly distinguish different vehicles based on the color and appearance of the vehicles, but vehicles with the same appearance color cannot be distinguished. On the other hand, different drivers have different driving habits, so the speed of the vehicles varies. Radar monitoring can assist in distinguishing vehicles that the image monitoring device cannot distinguish by the difference in speed. Especially when the amount of data is large enough, this distinction also has a high accuracy rate. Therefore, through the pre-trained graph analysis model, according to the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph, identifiable vehicles can be screened out from all unidentified vehicles and the target node transmission path corresponding to the identifiable vehicles can be determined.

[0123] It can be seen that this optional embodiment can filter out identifiable vehicles from all unidentified vehicles and determine the target node transmission path corresponding to the identifiable vehicles based on the image monitoring sub-knowledge graph, the video monitoring sub-knowledge graph, the radar monitoring sub-knowledge graph, the ETC monitoring sub-knowledge graph and the wireless signal monitoring sub-knowledge graph, thereby realizing the monitoring of unidentified vehicles.

[0124] Example 3

[0125] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of a highway vehicle monitoring system disclosed in an embodiment of the present invention. Figure 3 As shown, the highway vehicle monitoring system may include:

[0126] A node updating module 301 is configured to store, for each monitoring device on the target highway, the vehicle information of the target vehicle acquired by the monitoring device to the monitoring node corresponding to the monitoring device; wherein the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is the node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway;

[0127] The trajectory analysis module 302 is used to obtain the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway; and determine the driving trajectory of the target vehicle on the target highway based on the node transmission path.

[0128] As can be seen, the implementation of the highway vehicle monitoring system in this embodiment of the present invention can achieve a structured description of all monitoring devices on a target highway based on the monitoring knowledge graph. It can then determine the target vehicle's trajectory on the target highway based on the node transmission paths in the monitoring knowledge graph. This allows for efficient analysis and management of vehicle information acquired on the highway, improving the efficiency of vehicle monitoring on the highway.

[0129] In an optional embodiment, if Figure 4 As shown, the system may also include:

[0130] A first acquisition module 303 is configured to acquire monitoring device category information and monitoring device location information of each monitoring device on the target highway;

[0131] The second acquisition module 304 is used to obtain the association relationship between each monitoring device and other monitoring devices on the target highway;

[0132] The graph construction module 305 is used to generate a monitoring knowledge graph corresponding to the target highway based on the monitoring device category information and monitoring device location information of each monitoring device on the target highway and the association relationship between each monitoring device and other monitoring devices.

[0133] It can be seen that this optional embodiment can use the "entity-relationship-entity" triple form in the knowledge graph to construct a monitoring device network on the target highway, and can efficiently represent the attributes of each monitoring device and the relationship between any two monitoring devices.

[0134] In an optional embodiment, the node updating module 301 saves the vehicle information of the target vehicle acquired by each monitoring device on the target highway to the monitoring node corresponding to the monitoring device in a specific manner, which may include:

[0135] For each monitoring device on the target highway, the target vehicle's identity is determined based on the vehicle information of the target vehicle acquired by the monitoring device, and the target vehicle's identity and the monitoring time point at which the monitoring device acquired the vehicle information are stored in the monitoring node corresponding to the monitoring device;

[0136] Furthermore, the specific method for the trajectory analysis module 302 to obtain the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway may include:

[0137] Traverse the monitoring knowledge graph corresponding to the target highway and obtain all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle;

[0138] The node transmission path of the target vehicle is determined based on all target monitoring nodes and the monitoring time point corresponding to the target vehicle in each target monitoring node.

[0139] It can be seen that this optional embodiment can quickly determine the node transmission path of the target vehicle by analyzing the monitoring knowledge graph; when it is necessary to retrieve the driving trajectory of the target vehicle, only an application needs to be submitted to the server of the monitoring knowledge graph, which can quickly obtain the result without the need to analyze the data obtained by all monitoring devices. In particular, when it is necessary to analyze the driving trajectories of multiple vehicles in a short period of time, this optional embodiment can respond quickly, thereby improving the efficiency of vehicle monitoring on highways.

[0140] In another optional embodiment, the trajectory analysis module 302 determines the node transmission path of the target vehicle based on all target monitoring nodes and the monitoring time point corresponding to the target vehicle in each target monitoring node, which may include:

[0141] According to the node relationship between each target monitoring node and other target monitoring nodes, a sub-monitoring knowledge graph corresponding to the target vehicle is constructed;

[0142] According to the monitoring time point corresponding to the target vehicle in each target monitoring node, the target node transmission path that matches the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, and the target node transmission path is determined to be the node transmission path of the target vehicle.

[0143] It can be seen that this optional embodiment can construct a sub-monitoring knowledge graph corresponding to the target vehicle based on the node relationship between each target monitoring node and other target monitoring nodes, thereby realizing a more detailed monitoring data analysis of each target vehicle; in addition, according to the monitoring time point corresponding to the target vehicle in each target monitoring node, the target node transmission path matching the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, which can more accurately analyze the node transmission path corresponding to the target vehicle.

[0144] In another optional embodiment, Figure 4 As shown, the system may also include:

[0145] The node prediction module 306 is used to determine all expected nodes corresponding to the target vehicle based on all target monitoring nodes after the trajectory analysis module 302 determines the target vehicle's driving trajectory on the target highway. The expected node is the monitoring node corresponding to the next monitoring device that the target vehicle may pass through in the monitoring knowledge graph;

[0146] The cost prediction module 307 is used to determine the expected driving trajectory of the target vehicle on the target highway for each expected node corresponding to the target vehicle based on the node transmission path and the expected node, and to determine the cost information of the target vehicle corresponding to the expected node based on the expected driving trajectory and vehicle information.

[0147] It can be seen that this optional embodiment can analyze in advance the driving trajectory of the target vehicle when it appears at each possible exit, so as to quickly determine the highway fee based on the vehicle's driving trajectory, thereby improving the meticulousness of the vehicle highway fee calculation while improving the timeliness of the vehicle highway fee calculation.

[0148] In another optional embodiment, the monitoring device includes an image monitoring device, a video monitoring device, a radar monitoring device, an ETC monitoring device, and a wireless signal monitoring device; the monitoring knowledge graph corresponding to the target highway includes an image monitoring node, a video monitoring node, a radar monitoring node, an ETC monitoring node, and a wireless signal monitoring node;

[0149] The specific method of the trajectory analysis module 302 obtaining the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway may include:

[0150] According to the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all target vehicles are obtained respectively;

[0151] The node transmission path of the target vehicle is determined based on the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all target vehicles.

[0152] It can be seen that the highway vehicle monitoring device in this optional embodiment can divide the monitoring nodes into image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes according to the different monitoring devices corresponding to each node, so as to manage the vehicle monitoring data more carefully through the monitoring knowledge graph; in addition, the node transmission path of the target vehicle is determined according to the image node transmission path, video node transmission path, radar node transmission path, ETC node transmission path and wireless signal node transmission path of all target vehicles, which can improve the accuracy of path analysis.

[0153] In another optional embodiment, Figure 4 As shown, the system may also include:

[0154] The unidentified updating module 308 is configured to store, for each monitoring device on the target highway, the vehicle characteristic information of the unidentified vehicle acquired by the monitoring device to the monitoring node corresponding to the monitoring device. An unidentified vehicle is a vehicle whose identity cannot be uniquely determined. The vehicle characteristic information includes one or more of the following: photograph information, video information, radar speed measurement information, ETC information, and wireless signal information of the unidentified vehicle.

[0155] The sub-graph construction module 309 is used to determine the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph, and wireless signal monitoring sub-knowledge graph corresponding to all unidentified vehicles based on the vehicle feature information of all unidentified vehicles stored in the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes, and wireless signal monitoring nodes on the monitoring knowledge graph;

[0156] The vehicle identification module 310 is used to filter out identifiable vehicles from all unidentified vehicles and determine the target node transmission path corresponding to the identifiable vehicles based on the image monitoring sub-knowledge graph, the video monitoring sub-knowledge graph, the radar monitoring sub-knowledge graph, the ETC monitoring sub-knowledge graph and the wireless signal monitoring sub-knowledge graph.

[0157] It can be seen that this optional embodiment can filter out identifiable vehicles from all unidentified vehicles and determine the target node transmission path corresponding to the identifiable vehicles based on the image monitoring sub-knowledge graph, the video monitoring sub-knowledge graph, the radar monitoring sub-knowledge graph, the ETC monitoring sub-knowledge graph and the wireless signal monitoring sub-knowledge graph, thereby realizing the monitoring of unidentified vehicles.

[0158] Example 4

[0159] See also Figure 5 , Figure 5 This is a structural diagram of another highway vehicle monitoring system disclosed in an embodiment of the present invention. Figure 5 As shown, the highway vehicle monitoring system may include:

[0160] A memory 401 storing executable program code;

[0161] a processor 402 coupled to the memory 401;

[0162] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the highway vehicle monitoring method described in the first embodiment or the second embodiment of the present invention.

[0163] Example 5

[0164] An embodiment of the present invention discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the steps of the highway vehicle monitoring method described in the first embodiment or the second embodiment of the present invention.

[0165] Example 6

[0166] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the highway vehicle monitoring method described in embodiment 1 or embodiment 2.

[0167] The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present embodiment without inventive effort.

[0168] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0169] Finally, it should be noted that the highway vehicle monitoring method, system, and storage medium disclosed in the embodiments of the present invention are only preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for monitoring vehicles on a highway, characterized in that: The method comprises: Generate a monitoring knowledge graph corresponding to the target highway according to the monitoring device category information and monitoring device location information of each monitoring device on the target highway and the association relationship between each monitoring device and other monitoring devices; For each of the monitoring devices on the target highway, the vehicle identity of the target vehicle is determined according to the vehicle information of the target vehicle acquired by the monitoring device, and the vehicle identity of the target vehicle and the monitoring time point at which the vehicle information is acquired by the monitoring device are saved in the monitoring node corresponding to the monitoring device; wherein the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is the node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway; Traversing the monitoring knowledge graph corresponding to the target highway, obtaining all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle; According to the node relationship between each of the target monitoring nodes and other target monitoring nodes, a sub-monitoring knowledge graph corresponding to the target vehicle is constructed; According to the monitoring time point corresponding to the target vehicle in each of the target monitoring nodes, the target node transmission path matching the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, and the target node transmission path is determined to be the node transmission path of the target vehicle; according to the node transmission path, the driving trajectory of the target vehicle on the target highway is determined.

2. The highway vehicle monitoring method according to claim 1, characterized in that: The method further comprises: Acquire monitoring device category information and monitoring device location information of each of the monitoring devices on the target highway; Obtain the association relationship between each of the monitoring devices and other monitoring devices on the target highway.

3. The highway vehicle monitoring method according to claim 1, characterized in that: After determining the driving trajectory of the target vehicle on the target highway, the method further includes: Determine all expected nodes corresponding to the target vehicle according to all the target monitoring nodes, wherein the expected node is a monitoring node corresponding to the next monitoring device that the target vehicle may pass through in the monitoring knowledge graph; For each of the expected nodes corresponding to the target vehicle, the expected driving trajectory of the target vehicle on the target highway is determined based on the node transmission path and the expected node, and the cost information of the target vehicle corresponding to the expected node is determined based on the expected driving trajectory and the vehicle information.

4. The highway vehicle monitoring method according to claim 1, characterized in that: The monitoring device includes an image monitoring device, a video monitoring device, a radar monitoring device, an ETC monitoring device and a wireless signal monitoring device; the monitoring knowledge graph corresponding to the target expressway includes an image monitoring node, a video monitoring node, a radar monitoring node, an ETC monitoring node and a wireless signal monitoring node; The step of obtaining the node transmission path of the target vehicle from the monitoring knowledge graph corresponding to the target highway includes: According to the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, the image node transmission paths, video node transmission paths, radar node transmission paths, ETC node transmission paths and wireless signal node transmission paths of all the target vehicles are respectively obtained; The node transmission path of the target vehicle is determined based on the image node transmission paths, video node transmission paths, radar node transmission paths, ETC node transmission paths and wireless signal node transmission paths of all the target vehicles.

5. The highway vehicle monitoring method according to claim 4, characterized in that: The method further comprises: For each of the monitoring devices on the target highway, the vehicle characteristic information of the unidentified vehicle acquired by the monitoring device is saved in the monitoring node corresponding to the monitoring device; the unidentified vehicle is a vehicle whose identity cannot be uniquely determined, and the vehicle characteristic information includes one or more of the photo information, video information, radar speed measurement information, ETC information and wireless signal information of the unidentified vehicle; According to the vehicle feature information of all the unidentified vehicles stored in the image monitoring nodes, video monitoring nodes, radar monitoring nodes, ETC monitoring nodes and wireless signal monitoring nodes on the monitoring knowledge graph, determine the image monitoring sub-knowledge graph, video monitoring sub-knowledge graph, radar monitoring sub-knowledge graph, ETC monitoring sub-knowledge graph and wireless signal monitoring sub-knowledge graph corresponding to all the unidentified vehicles; According to the image monitoring sub-knowledge graph, the video monitoring sub-knowledge graph, the radar monitoring sub-knowledge graph, the ETC monitoring sub-knowledge graph and the wireless signal monitoring sub-knowledge graph, identifiable vehicles are screened out from all the unidentified vehicles and the target node transmission path corresponding to the identifiable vehicles is determined.

6. A highway vehicle monitoring system, characterized in that: The system comprises: A graph construction module is used to generate a monitoring knowledge graph corresponding to the target highway according to the monitoring device category information and monitoring device location information of each monitoring device on the target highway and the association relationship between each monitoring device and other monitoring devices; A node updating module is used to determine the vehicle identity of the target vehicle for each monitoring device on the target highway according to the vehicle information of the target vehicle acquired by the monitoring device, and save the vehicle identity of the target vehicle and the monitoring time point when the monitoring device acquires the vehicle information to the monitoring node corresponding to the monitoring device; wherein the vehicle information includes information that can uniquely identify the target vehicle, and the monitoring node is the node corresponding to the monitoring device on the monitoring knowledge graph corresponding to the target highway; A trajectory analysis module, used to traverse the monitoring knowledge graph corresponding to the target highway, and obtain all target monitoring nodes in the monitoring knowledge graph that contain the vehicle identity of the target vehicle; According to the node relationship between each of the target monitoring nodes and other target monitoring nodes, a sub-monitoring knowledge graph corresponding to the target vehicle is constructed; According to the monitoring time point corresponding to the target vehicle in each of the target monitoring nodes, the target node transmission path matching the sub-monitoring knowledge graph is determined from the monitoring knowledge graph, and the target node transmission path is determined to be the node transmission path of the target vehicle; according to the node transmission path, the driving trajectory of the target vehicle on the target highway is determined.

7. A highway vehicle monitoring system, characterized in that: The system comprises: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the highway vehicle monitoring method as described in any one of claims 1-5.

8. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the highway vehicle monitoring method as described in any one of claims 1-5.

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