A traffic knowledge graph construction method, device and equipment and a storage medium

Abstract

The application provides a traffic knowledge graph construction method and device, equipment and a storage medium, relates to the intelligent traffic technical field, and can construct a traffic knowledge graph for the traffic signal control field, facilitating practitioners to cope with various traffic signal control problems. The method comprises the following steps: acquiring phase sequences of multiple traffic signals; for the phase sequence of each traffic signal in the multiple traffic signals, determining a directional phase sequence of the phase sequence, acquiring a traffic phenomenon existing under the directional phase sequence, a cause leading to the traffic phenomenon, and a solution strategy of the cause; constructing a traffic knowledge graph according to the phase sequence of each traffic signal, the directional phase sequence of the phase sequence, the directional phase sequence existing under the directional phase sequence, the cause leading to the traffic phenomenon, and the solution strategy of the cause; and the traffic knowledge graph is used for analyzing traffic signal control problems between nodes or between nodes and edges. The application can be used in the process of diagnosing traffic signal control problems.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation technology, and in particular to a method, apparatus, device and storage medium for constructing a traffic knowledge graph. Background Technology

[0002] Nowadays, with the continuous expansion of major transportation arteries and the increasing number of vehicles, various traffic problems have emerged. Knowledge graph technology can be used to construct a knowledge network that reflects the numerous entities existing in the objective world, the attributes of each entity, and the relationships between them. Knowledge graphs used in the transportation field, such as traffic knowledge graphs, can reflect entities such as people, vehicles, roads, and the environment in the transportation network, their attributes, and the relationships between them, and can be used to diagnose various traffic problems. Therefore, further research on traffic knowledge graphs is a hot topic today.

[0003] Existing traffic knowledge graph construction primarily focuses on automating the process, covering a relatively broad range of traffic domains. Current traffic knowledge graph technologies do not address traffic signal control problems (or simply traffic signal control problems) within specific traffic sub-domains, thus failing to provide solutions for existing traffic signal control issues in conjunction with traffic knowledge graphs. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for constructing a traffic knowledge graph, which can be used to construct a traffic knowledge graph for the field of traffic signal control, making it easier for practitioners to deal with various traffic signal control problems.

[0005] Firstly, this application provides a method for constructing a traffic knowledge graph. The method includes: acquiring the phase sequence of multiple traffic signals; determining the directional phase sequence of each traffic signal's phase sequence, acquiring the traffic phenomena existing under the directional phase sequence, the causes of the traffic phenomena, and solutions to the causes; constructing a traffic knowledge graph based on the phase sequence of each traffic signal, the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, the causes of the traffic phenomena, and solutions to the causes; the traffic knowledge graph is used to analyze traffic signal control problems between nodes or between nodes and edges.

[0006] The traffic knowledge graph construction method provided in this application acquires the phase sequence of multiple traffic signals, determines the directional phase sequence based on the phase sequence, and identifies the traffic phenomena existing under the directional phase sequence, the causes of these traffic phenomena, and the solutions to these causes. This allows for the construction of a traffic knowledge graph for analyzing various traffic signal control problems. The traffic knowledge graph constructed in this solution eliminates the inefficiency of manually diagnosing traffic signal control problems in traditional methods. Furthermore, the phase sequence required for constructing the traffic knowledge graph is a fundamental control mechanism in the field of traffic signal control; therefore, a traffic knowledge graph constructed based on the directional phase sequence is more consistent with the optimization logic of traffic signal control problems. Moreover, the construction of the traffic knowledge graph is based on data such as the traffic phenomena existing under the directional phase sequence, the causes of these traffic phenomena, and the solutions to these causes. This data can intuitively provide causal analysis and corresponding solutions for traffic signal control problems, facilitating users to analyze traffic signal control problems based on the traffic knowledge graph and thus significantly improving the processing efficiency of traffic signal control problems.

[0007] In one possible implementation, in the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are the nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy is the edge of the traffic knowledge graph.

[0008] In another possible implementation, a traffic knowledge graph is constructed based on the phase sequence of each traffic signal, the direction phase sequence of the phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes. This includes: for each traffic signal's phase sequence, constructing a set of triples for the phase sequence; the set of triples includes one or more triples, each triple containing any two entities from the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, as well as the relationship between the two entities, used to indicate the nodes and edges of the traffic knowledge graph; and constructing the traffic knowledge graph based on the set of triples for each traffic signal's phase sequence.

[0009] In another possible implementation, the set of triplets for the phase sequence of each traffic signal includes one or more of the following: a first triplet, a second triplet, a third triplet, a fourth triplet, a fifth triplet, and a sixth triplet; wherein, the first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relation between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes in the traffic knowledge graph, and the first relation is an edge in the traffic knowledge graph; the second triplet includes: the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, and a second relation between the direction phase sequence and the traffic phenomenon existing under the direction phase sequence, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the cause of the traffic phenomenon exist in the traffic knowledge graph. The first triplet consists of nodes in the traffic knowledge graph, indicating the traffic phenomena existing under the given direction phase sequence and the causes of the traffic phenomena. The third relation is the edge of the traffic knowledge graph. The fourth triplet consists of the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fifth triplet consists of the direction phase sequence, the traffic phenomena existing under the given direction phase sequence, and the cause of the traffic phenomenon. The sixth triplet consists of the direction phase sequence, the cause of the traffic phenomenon existing under the given direction phase sequence, and the solution strategy for the cause. The sixth triplet consists of nodes in the traffic knowledge graph, indicating the direction phase sequence and the solution strategy for the cause.

[0010] In another possible implementation, the phase sequence includes one or more phases; determining the directional phase sequence includes: dividing the phase sequence according to a preset rule to obtain the directional phase sequence; the preset rule is that phases with the same direction constitute a directional phase sequence.

[0011] Secondly, this application provides a traffic problem analysis method, which includes: obtaining a query request; the query request includes: information of a first node and information of a target location; the first node is any one of phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy; the target location is a node or an edge; when the target location is an edge, according to the query request, a traffic knowledge graph is queried to obtain a second node or a first chain; the second node is a node that satisfies the relationship indicated by the target location with the first node, and the first chain is a chain in the traffic knowledge graph that includes the first node, the second node, and the target location; when the target location is a node, according to the query request, a traffic knowledge graph is queried to obtain a second chain, the second chain is a chain in the traffic knowledge graph that includes the first node, the target location, and an edge indicating the relationship between the second node and the target location; the second node, the first chain, or the second chain is used to indicate the traffic signal control status between the first node and the target location.

[0012] The traffic problem analysis method provided in this application supports not only node queries but also chain queries, which helps in providing causal analysis and experience sharing for traffic signal control problems, enabling knowledge empowerment for frontline practitioners. This solution can promote the application of knowledge graphs in the transportation field and provide a solid foundation for the future development of knowledge graphs in the transportation sector.

[0013] In one possible implementation, in the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes and solution strategy is the edge of the traffic knowledge graph.

[0014] In another possible implementation, the traffic knowledge graph is constructed from a set of triplets of the phase sequence of each traffic signal; the set of triplets includes one or more triplets, each triplet including the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon and the solution strategy of the cause, any two entities in the triplet set, and the relationship between the two entities, which are used to indicate the nodes and edges of the traffic knowledge graph.

[0015] In another possible implementation, the set of triplets for the phase sequence of each traffic signal includes one or more of the following: a first triplet, a second triplet, a third triplet, a fourth triplet, a fifth triplet, and a sixth triplet; wherein, the first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relation between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes in the traffic knowledge graph, and the first relation is an edge in the traffic knowledge graph; the second triplet includes: the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, and a second relation between the direction phase sequence and the traffic phenomenon existing under the direction phase sequence, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the cause of the traffic phenomenon exist in the traffic knowledge graph. The first triplet consists of nodes in the traffic knowledge graph, indicating the traffic phenomena existing under the given direction phase sequence and the causes of the traffic phenomena. The third relation is the edge of the traffic knowledge graph. The fourth triplet consists of the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fifth triplet consists of the direction phase sequence, the traffic phenomena existing under the given direction phase sequence, and the cause of the traffic phenomenon. The sixth triplet consists of the direction phase sequence, the cause of the traffic phenomenon existing under the given direction phase sequence, and the solution strategy for the cause. The sixth triplet consists of nodes in the traffic knowledge graph, indicating the direction phase sequence and the solution strategy for the cause.

[0016] In another possible implementation, the directional phase sequence is obtained by dividing the phase sequence according to a preset rule; the preset rule is that phases with the same direction constitute a directional phase sequence.

[0017] Thirdly, this application provides a construction apparatus, comprising: an acquisition module, a determination module, and a construction module; the acquisition module is used to acquire the phase sequence of multiple traffic signals; the determination module is used to determine the direction phase sequence of the phase sequence for each traffic signal, acquire the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes; the construction module is used to construct a traffic knowledge graph based on the phase sequence of each traffic signal, the direction phase sequence of the phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes; the traffic knowledge graph is used to analyze the relationships between nodes or between nodes and edges for diagnosing traffic signal control problems.

[0018] In one possible implementation, in the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are the nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy is the edge of the traffic knowledge graph.

[0019] In another possible implementation, a construction module is specifically used for the phase sequence of each traffic signal: based on the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, a set of triples for the phase sequence is constructed; the set of triples includes one or more triples, and each triple includes any two entities in the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, as well as the relationship between the two entities, which is used to indicate the nodes and edges of the traffic knowledge graph; based on the set of triples for the phase sequence of each traffic signal, a traffic knowledge graph is constructed.

[0020] In another possible implementation, the set of triplets for the phase sequence of each traffic signal includes one or more of the following: a first triplet, a second triplet, a third triplet, a fourth triplet, a fifth triplet, and a sixth triplet; wherein, the first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relation between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes in the traffic knowledge graph, and the first relation is an edge in the traffic knowledge graph; the second triplet includes: the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, and a second relation between the direction phase sequence and the traffic phenomenon existing under the direction phase sequence, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the cause of the traffic phenomenon exist in the traffic knowledge graph. The first triplet consists of nodes in the traffic knowledge graph, indicating the traffic phenomena existing under the given direction phase sequence and the causes of the traffic phenomena. The third relation is the edge of the traffic knowledge graph. The fourth triplet consists of the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fifth triplet consists of the direction phase sequence, the traffic phenomena existing under the given direction phase sequence, and the cause of the traffic phenomenon. The sixth triplet consists of the direction phase sequence, the cause of the traffic phenomenon existing under the given direction phase sequence, and the solution strategy for the cause. The sixth triplet consists of nodes in the traffic knowledge graph, indicating the direction phase sequence and the solution strategy for the cause.

[0021] In another possible implementation, the determining module is specifically used to divide the phase sequence according to a preset rule to obtain the directional phase sequence; the preset rule is that phases with the same direction constitute a directional phase sequence.

[0022] Fourthly, this application provides a traffic problem analysis device, which includes: an acquisition module and a query module; the acquisition module is used to acquire a query request; the query request includes: information of a first node and information of a target location; the first node is any one of phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy; the target location is a node or an edge; the query module is used to query a traffic knowledge graph according to the query request when the target location is an edge, to obtain a second node or a first chain; the second node is a node that satisfies the relationship indicated by the target location with the first node, and the first chain is a chain in the traffic knowledge graph that includes the first node, the second node, and the target location; the query module is also used to query a traffic knowledge graph according to the query request when the target location is a node, to obtain a second chain, the second chain is a chain in the traffic knowledge graph that includes the first node, the target location, and an edge indicating the relationship between the second node and the target location; the second node, the first chain, or the second chain is used to indicate the traffic signal control status between the first node and the target location.

[0023] In one possible implementation, in the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes and solution strategy is the edge of the traffic knowledge graph.

[0024] In another possible implementation, the traffic knowledge graph is constructed from a set of triplets of the phase sequence of each traffic signal; the set of triplets includes one or more triplets, each triplet including the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon and the solution strategy of the cause, any two entities in the triplet set, and the relationship between the two entities, which are used to indicate the nodes and edges of the traffic knowledge graph.

[0025] In another possible implementation, the set of triplets for the phase sequence of each traffic signal includes one or more of the following: a first triplet, a second triplet, a third triplet, a fourth triplet, a fifth triplet, and a sixth triplet; wherein, the first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relation between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes in the traffic knowledge graph, and the first relation is an edge in the traffic knowledge graph; the second triplet includes: the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, and a second relation between the direction phase sequence and the traffic phenomenon existing under the direction phase sequence, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the traffic phenomenon existing under the direction phase sequence are nodes in the traffic knowledge graph, and the second relation is an edge in the traffic knowledge graph; the third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the direction phase sequence and the cause of the traffic phenomenon exist in the traffic knowledge graph. The first triplet consists of nodes in the traffic knowledge graph, indicating the traffic phenomena existing under the given direction phase sequence and the causes of the traffic phenomena. The third relation is the edge of the traffic knowledge graph. The fourth triplet consists of the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fifth triplet consists of the direction phase sequence, the traffic phenomena existing under the given direction phase sequence, and the cause of the traffic phenomenon. The sixth triplet consists of the direction phase sequence, the cause of the traffic phenomenon existing under the given direction phase sequence, and the solution strategy for the cause. The sixth triplet consists of nodes in the traffic knowledge graph, indicating the direction phase sequence and the solution strategy for the cause.

[0026] In another possible implementation, the directional phase sequence is obtained by dividing the phase sequence according to a preset rule; the preset rule is that phases with the same direction constitute a directional phase sequence.

[0027] Fifthly, this application provides a server comprising: a processor and a memory; the memory storing processor-executable instructions; when the processor is configured to execute the instructions, causing the server to implement the methods of the first or second aspect described above.

[0028] Sixthly, this application provides a computer-readable storage medium comprising: computer software instructions; and, when the computer software instructions are executed in a computer, causing the computer to implement the method of the first aspect or the second solution described above.

[0029] In a seventh aspect, this application provides a computer program product that, when run on a computer, causes the computer to perform the steps of the relevant methods described in the first or second aspect above, so as to implement the methods of the first or second aspect above.

[0030] The beneficial effects of the third to seventh aspects mentioned above can be referred to the corresponding descriptions of the first or second aspects, and will not be repeated here. Attached Figure Description

[0031] Figure 1 A schematic diagram illustrating the application environment of the traffic knowledge graph construction method provided in this application; Figure 2 A flowchart illustrating a method for constructing a traffic knowledge graph provided in this application; Figure 3 A schematic diagram illustrating another method for constructing a traffic knowledge graph provided in this application; Figure 4 A schematic diagram illustrating another method for constructing a traffic knowledge graph provided in this application; Figure 5 This application provides a partial traffic knowledge graph diagram. Figure 6 This is another partial traffic knowledge graph diagram provided in this application; Figure 7 This application provides yet another partial traffic knowledge graph diagram. Figure 8 A flowchart illustrating a traffic problem analysis method provided in this application; Figure 9 A schematic diagram of the composition of a construction device provided in this application; Figure 10 A schematic diagram of the composition of an analytical apparatus provided in this application; Figure 11 This is a schematic diagram of the composition of a server provided in this application. Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0033] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0034] To facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish the same or similar items with essentially the same function and effect. Those skilled in the art can understand that the terms "first" and "second" are not intended to limit the quantity or execution order.

[0035] As described in the background section, with the continuous development of society, the number of transportation vehicles is increasing. The complexity of the movement of motor vehicles, non-motor vehicles, and pedestrians easily leads to various traffic problems. How to deal with this phenomenon is an important issue that urgently needs to be addressed in the field of transportation.

[0036] Various traffic monitoring devices are deployed along urban arterial roads, collecting traffic data such as road flow and direction. This data can be used to analyze various traffic problems. Currently, there are solutions that build knowledge graphs based on traffic data to analyze traffic issues using these graphs.

[0037] A knowledge graph is a semantic network that reflects the objective world. Essentially, a knowledge graph is a large-scale data model that constructs a knowledge network to reflect a large number of entities in the objective world, the attributes of each entity, and the relationships between them, providing people with a fast and convenient way to retrieve and reason about knowledge.

[0038] Existing knowledge graphs for the transportation field (such as transportation knowledge graphs) primarily focus on how the knowledge graph extracts and identifies entities from technical documents and mines relationships between entities, rather than the correspondence between entities within the knowledge graph. Furthermore, existing transportation knowledge graphs cover a relatively broad range of content and a wide scope within the transportation field. There is a lack of suitable knowledge graphs for specific subfields within transportation, such as traffic signal control (or simply traffic signal management). The business barriers in traffic signal control are relatively high, leaving general practitioners at a loss when encountering traffic signal control problems. Therefore, there is an urgent need for a transportation knowledge graph specifically for traffic signal control to assist practitioners in solving various traffic signal control problems.

[0039] Against this background, embodiments of this application provide a method for constructing a traffic knowledge graph. This method can be used to construct a traffic knowledge graph for the field of traffic signal control, so that practitioners can query and solve various traffic signal control problems based on the traffic knowledge graph.

[0040] The method for constructing a traffic knowledge graph provided in this application can be applied to, for example... Figure 1 The application environment shown. For example... Figure 1 As shown, the application environment may include a construction device 101 and a user-side device 102. The construction device 101 and the user-side device 102 can communicate via a network to transmit information such as images, videos, text, audio, or other data. This network may be the Internet, a cellular network, or other networks. The network may also be a network composed of interconnected devices such as routers or switches.

[0041] The construction device 101 can be applied to a server. The server referred to here can be a server cluster consisting of multiple servers, a single server, or a computer. Specifically, the construction device 101 can be a processor or processing chip within the server. This application embodiment does not limit the specific device form of the server described above. Figure 1 The example of the application of the Sino-Israeli construction device 101 to a single server is shown.

[0042] The aforementioned user-side device 102 can be an electronic device such as a mobile terminal, computer, or tablet computer. This application embodiment does not limit the specific device form of the user-side device 102. Figure 1 The example shown is a computer, with user-side device 102 as an example.

[0043] In some embodiments, when it is necessary to construct a traffic knowledge graph, the construction device 101 can acquire the phase sequence of multiple traffic signals and determine the directional phase sequence based on the phase sequence of each traffic signal. Furthermore, the construction device 101 can also acquire the traffic phenomena existing under the directional phase sequence of the phase sequence, the causes of the traffic phenomena, and the solutions to the causes, so as to construct a traffic knowledge graph for analyzing traffic signal control problems based on the above data.

[0044] In addition, the construction device 101 can also be called a traffic problem analysis device, which can obtain query requests from the user-side device 102 and assist the user in analyzing traffic signal control problems based on the query requests and the pre-constructed traffic knowledge graph.

[0045] The above embodiments illustrate how a user queries the traffic knowledge graph constructed by the construction device 101 through the user-side device 102 to assist in diagnosing traffic signal control problems. In other embodiments, the construction device 101 may also provide a search entry point for the user, such as a search engine, so that the user can directly query the traffic knowledge graph through the construction device 101 to assist in analyzing traffic signal control problems.

[0046] The above embodiments illustrate the example where the construction device and the traffic problem analysis device share the same server. In other embodiments, the construction device and the traffic problem analysis device may be two different servers. The construction device is used to construct a traffic knowledge graph, and the traffic problem analysis device can obtain the traffic knowledge graph from the construction device, query the traffic knowledge graph according to a query request, and output the results for the user to analyze traffic signal control problems. This application does not impose specific limitations on this aspect.

[0047] Figure 2 This is a flowchart illustrating a method for constructing a traffic knowledge graph, as provided in an embodiment of this application. Figure 2 As shown, the method for constructing the traffic knowledge graph provided in this application can be implemented using the aforementioned construction device, and may specifically include the following steps: S201. Obtain the phase sequence of multiple traffic signals.

[0048] Traffic signal control problems in the field of traffic signal control can generally be solved by analyzing the phase sequence of traffic signals. Phase sequence, which uses the changing states of traffic lights to allocate right-of-way to pedestrians, vehicles, and other traffic flows, is a fundamental control mechanism ensuring the safety and efficiency of signalized intersections. In intersection traffic signal control, the selection and arrangement of the phase sequence significantly impacts the intersection's traffic efficiency. Therefore, analyzing traffic signal control problems can be considered an optimization analysis of the phase sequence of traffic signals. In actual traffic signal control projects, a large amount of historical project-related data, such as phase sequence information, is available. Therefore, based on this historical data, data extraction and cleaning can be performed to obtain data for constructing a traffic knowledge graph.

[0049] In some embodiments, the construction apparatus can obtain the phase sequence of multiple traffic signals from historical data of traffic signal control.

[0050] The acquisition method can employ algorithms from the field of artificial intelligence, such as language processing and text analysis, to extract and clean relevant data from historical projects to obtain the phase sequence of multiple traffic signals. Specific methods for obtaining phase sequence from historical projects can be found in relevant technical documents; these will not be detailed further in this application's embodiments.

[0051] For example, the device obtains the phase sequence of multiple traffic signals from historical projects, such as: "North-South Straight - North-South Left Turn - East-West Mixed Traffic", "East-West Straight - East-West Left Turn - North-South Mixed Traffic", etc.

[0052] For the phase sequence of each traffic signal among the multiple traffic signals obtained in S201, execute the following S202-S203.

[0053] S202. Determine the direction phase sequence, obtain the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes.

[0054] As described in the foregoing embodiments, the process of handling traffic signal control problems can be described as an optimization process of phase sequence. Phase sequence optimization is generally performed by adjusting and optimizing in a fixed direction. Therefore, after acquiring the phase sequence of a traffic signal, the device can determine the directional phase sequence and, based on the directional phase sequence, obtain the traffic phenomena existing under that directional phase sequence, the causes of those traffic phenomena, and the solutions to those causes.

[0055] As an example, such as Figure 3 As shown, S202 may specifically include the following S202a-S202b.

[0056] S202a. Divide the phase sequence according to the preset rules to obtain the directional phase sequence.

[0057] The preset rule is that phases with the same direction constitute a directional phase sequence.

[0058] In some embodiments, the constructing device can divide the phase sequence according to the direction using a preset rule to obtain the directional phase sequence. The preset rule is that phases with the same direction are grouped into one type of directional phase sequence.

[0059] For example, taking the phase sequence "North-South Straight - North-South Left Turn - East-West Mixed" as an example, and referring to the examples in the above embodiments, there are three phases in the phase sequence "North-South Straight - North-South Left Turn - East-West Mixed": "North-South Straight", "North-South Left Turn", and "East-West Mixed". "North-South Straight" and "North-South Left Turn" share the same direction "North-South", and are therefore divided into one directional phase sequence "North-South Straight - North-South Left Turn". The other directional phase sequence, divided according to the "East-West" direction, is "East-West Mixed". It can be understood that each directional phase sequence in the above example contains only one direction, facilitating subsequent optimization of the phase sequence based on direction.

[0060] S202b. Based on the direction phase sequence, obtain the traffic phenomena existing under that direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes.

[0061] In some embodiments, after determining the directional phase sequence, the construction device can acquire, based on the directional phase sequence, the traffic phenomena existing under that directional phase sequence, the causes of those traffic phenomena, and the solutions to those causes. The acquisition method can be based on the accumulation of expert experience. For example, the construction device can display the directional phase sequence to a traffic signal control expert, who can then input data such as the traffic phenomena existing under that directional phase sequence, the corresponding causes, and the solutions to the construction device. This allows the construction device to acquire the data input by the traffic signal control expert and subsequently construct a traffic knowledge graph based on this data.

[0062] For example, continuing with the examples in the above embodiments, the device can determine the traffic phenomenon under the direction phase sequence "North-South Straight - North-South Left Turn" as "North-South Straight - North-South Left Turn with queuing and empty lanes," based on the phase sequence. The cause of this traffic phenomenon is "uneven flow of traffic in the same phase between North-South Straight and North-South Left Turn, with large differences in the flow coefficients of the directions." The solution to this problem is "symmetrical North-South Straight and Left Turn overlap." Similarly, the device can determine the traffic phenomenon under the direction phase sequence "East-West Mixed Traffic" as "low traffic efficiency of East-West Mixed Traffic," based on the phase sequence. The cause of this traffic phenomenon is "symmetrical East-West Straight and Left Turn traffic conflicts," and the solution to this problem is "East-West phase splitting" or "releasing the main phase first and then allowing mixed traffic."

[0063] It should be noted that the historical projects of traffic signal control include a large number of historical cases of handling traffic signal control problems. These cases contain numerous intuitive phenomena related to direction phase sequence, as well as the root causes of these phenomena and the solutions to address these intuitive phenomena and root causes. Therefore, in some other embodiments, the construction device can also extract and clean data from the historical projects of traffic signal control based on the direction phase sequence, using the aforementioned language processing or text analysis methods. This allows for the acquisition of data such as the traffic phenomena existing under that direction phase sequence, the causes of those traffic phenomena, and the solutions to those causes. Subsequently, this data can be used to construct a traffic knowledge graph.

[0064] S203. Based on the phase sequence of each traffic signal, the directional phase sequence of that phase sequence, the traffic phenomena existing under that directional phase sequence, the causes of those traffic phenomena, and the solutions to those causes, construct a traffic knowledge graph.

[0065] Among them, the traffic knowledge graph is used to analyze traffic signal control problems between nodes or between nodes and edges.

[0066] The construction device can construct a traffic knowledge graph for diagnosing traffic signal control problems based on the phase sequence of each traffic signal, the directional phase sequence, the traffic phenomena existing under that directional phase sequence, the causes of those traffic phenomena, and the solutions to those causes. In the traffic knowledge graph, phase sequence, directional phase sequence, traffic phenomena, causes, and solutions are the nodes; the relationships between phase sequence, directional phase sequence, traffic phenomena, causes, and solutions are the edges.

[0067] As described in the preceding embodiments, the traffic knowledge graph mainly consists of nodes and edges representing the relationships between nodes. After obtaining the nodes required to construct the traffic knowledge graph, namely entities such as phase sequence, direction phase sequence, traffic phenomena, causes, and solutions, the relationships between any two of these entities can also be obtained.

[0068] Determining the relationship between any two entities can be done by the construction device based on a preset correspondence set by expert experience input, or by using an algorithm training method. This application does not impose specific limitations on this.

[0069] After obtaining the entities and relationships between them needed to construct a traffic knowledge graph, the graph can be built based on these entities and relationships. As an example, triples can be constructed to represent entities and their relationships, indicating the nodes and edges in the traffic knowledge graph. For instance, a triple can consist of a node and a relation, such as a head node (represented by the letter 'h'), a relation (represented by the letter 'r'), and a tail node (represented by the letter 't'). The head and tail nodes correspond to nodes in the traffic knowledge graph, and the relations correspond to edges. The traffic knowledge graph can then be further constructed based on these triples. Figure 4 As shown, S203 may specifically include the following S203a-S203b.

[0070] S203a. For each traffic signal's phase sequence, based on the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, construct a set of triplets for the phase sequence.

[0071] The set of triples can include one or more triples. A triple includes a phase sequence, a directional phase sequence, a traffic phenomenon under the directional phase sequence, any two entities in the cause of the traffic phenomenon and the solution strategy for the cause, and the relationship between the two entities, which are used to indicate the nodes and edges of the traffic knowledge graph.

[0072] The set of triples mentioned above may include one or more of the first triple, the second triple, the third triple, the fourth triple, the fifth triple, and the sixth triple.

[0073] The first triplet may include: phase sequence, direction phase sequence of phase sequence, and a first relationship between phase sequence and direction phase sequence, used to indicate that phase sequence and direction phase sequence are nodes of the traffic knowledge graph, and the first relationship is an edge of the traffic knowledge graph.

[0074] The second triplet may include: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence. The second relationship is used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is the edge of the traffic knowledge graph.

[0075] The third triplet may include: a traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon. The third relation is used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relation is the edge of the traffic knowledge graph.

[0076] The fourth triple can include: the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy, which indicates that the cause of the traffic phenomenon and the solution strategy are nodes in the traffic knowledge graph, and the fourth relation is an edge in the traffic knowledge graph.

[0077] The fifth triplet may include: the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, and the cause of the traffic phenomenon. The directional phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph.

[0078] The sixth triplet may include: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon existing under the directional phase sequence, and the solution strategy for the cause. The directional phase sequence of the phase sequence and the solution strategy for the cause are nodes of the traffic knowledge graph, and the cause of the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph.

[0079] In some embodiments, for each traffic signal phase sequence, the constructing device can construct a set of triplets of the phase sequence based on the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena and the solutions to the causes.

[0080] For example, the construction device can construct a first triplet based on the phase sequence and the directional phase sequence; construct a second triplet based on the directional phase sequence and the traffic phenomena existing under that directional phase sequence; construct a third triplet based on the traffic phenomena existing under that directional phase sequence and the causes of those traffic phenomena; and construct a fourth triplet based on the causes of those traffic phenomena and the solutions to those causes.

[0081] For example, taking the traffic signal phase sequence "North-South Straight - North-South Left Turn - East-West Mixed Traffic" as an example, the device can construct a first triplet with the phase sequence "North-South Straight - North-South Left Turn - East-West Mixed Traffic" as the head node, the direction phase sequence "North-South Straight - North-South Left Turn" as the tail node, and "inclusion" as the relation. This first triplet can be represented as (North-South Straight - North-South Left Turn - East-West Mixed Traffic, including, North-South Straight - North-South Left Turn).

[0082] Similarly, the construction device can take the traffic phenomenon "North-South Straight - North-South Left Turn with queues and empty lanes" under the direction phase sequence as the head node, "North-South Straight - North-South Left Turn" as the tail node, and "phenomenon to" as the relation to construct a second triplet. The second triplet can be represented as (North-South Straight - North-South Left Turn with queues and empty lanes, phenomenon to, North-South Straight - North-South Left Turn).

[0083] The device can construct a third tripartite based on the traffic phenomena existing under the direction phase sequence and the causes of these traffic phenomena. This third tripartite can be represented as (the uneven flow of north-south straight traffic and north-south left-turn traffic in the same phase, with large differences in the directional flow coefficients, resulting in both north-south straight traffic and north-south left-turn traffic queuing and empty lanes).

[0084] The device can construct a fourth triplet based on the cause of the traffic phenomenon and the solution strategy for that cause. The fourth triplet can be represented as (the flow coefficients of the north-south straight-through and north-south left-turn traffic are unbalanced in the same phase, and the solution strategy is to overlap the north-south straight-through and left-turn traffic).

[0085] Among them, the first triplet, the second triplet, the third triplet, and the fourth triplet constructed above can satisfy the requirement of querying the tail node based on the head node and the relationship.

[0086] In this embodiment, considering the correlation between phenomena and causes under a certain phase sequence, and the correlation between causes and solutions, which are also core requirements in the optimization process of traffic signal control, the construction device can also construct a fifth triplet and a sixth triplet to represent the correlation between phenomena and causes, and causes and solutions under a certain phase sequence. That is, the construction device can construct a fifth triplet based on the directional phase sequence, the traffic phenomena existing under that directional phase sequence, and the causes leading to those traffic phenomena; and construct a sixth triplet based on the directional phase sequence, the causes leading to those traffic phenomena under that directional phase sequence, and the solutions to those causes.

[0087] For example, the device can construct a fifth triplet with the directional phase sequence "north-south straight - north-south left turn" as the head node, the traffic phenomenon "queuing on one side and empty parking on the other" as the relationship, and the cause of this traffic phenomenon "uneven flow of north-south straight - north-south left turn in the same phase with large differences in flow coefficients" as the tail node. The fifth triplet can be represented as (north-south straight - north-south left turn, queuing on one side and empty parking on the other, uneven flow of north-south straight - north-south left turn in the same phase with large differences in flow coefficients).

[0088] Similarly, the construction device can also use the directional phase sequence "north-south straight - north-south left turn" as the head node, the cause of the traffic phenomenon "uneven flow in the same phase between north-south straight and north-south left turn with large differences in flow coefficients in the direction" as the relationship, and the solution strategy for this cause "symmetrical north-south straight-left overlap" as the tail node to construct a sixth triplet. The sixth triplet can be represented as (north-south straight - north-south left turn, uneven flow in the same phase with large differences in flow coefficients in the direction, symmetrical north-south straight-left overlap).

[0089] The above example phase sequence "North-South Straight-North-South Left Turn-East-West Mixed Traffic" also includes the directional phase sequence "East-West Mixed Traffic". The traffic phenomena existing under this directional phase sequence, the causes of these traffic phenomena, and the solutions to these causes are described in the above example. The process of constructing a triplet is as described in the example above and will not be repeated here.

[0090] In summary, the set of triplets for the traffic signal phase sequence "north-south straight - north-south left turn - east-west mixed traffic" constructed in the above example is shown in Table 1 below: Table 1

[0091] Similarly, the constructing device can also acquire a set of triplets of other phase sequences of multiple traffic signals obtained in S201.

[0092] S203b constructs a traffic knowledge graph based on the set of triplets of phase sequence for each traffic signal.

[0093] In some embodiments, after obtaining the set of triplets of the phase sequence of each traffic signal, the construction device can construct a traffic knowledge graph for analyzing traffic signal control problems based on the set of triplets of the phase sequence of multiple traffic signals, and store the traffic knowledge graph.

[0094] For example, the construction device can construct a traffic knowledge graph by connecting any two triples with the same nodes (including the head node and the tail node) in the triple set, based on the head node-relationship-tail node expressed by the triples.

[0095] For example, in conjunction with the examples in the above embodiments, such as Figure 4 As shown, the construction device connects the first ternary group (north-south straight - north-south left turn - east-west mixed traffic, including north-south straight - north-south left turn), the second ternary group (north-south straight - north-south left turn, queuing and emptying simultaneously, the phenomenon belongs to north-south straight - north-south left turn), the third ternary group (north-south straight - north-south left turn, unbalanced flow in the same phase, large difference in flow coefficient in the direction, resulting in north-south straight - north-south left turn, queuing and emptying simultaneously), and the fourth ternary group (north-south straight - north-south left turn, unbalanced flow in the same phase, large difference in flow coefficient in the direction, solution strategy: north-south symmetrical straight-left overlap), end to end, constructing as follows. Figure 5 Part of the traffic knowledge graph in the text.

[0096] In addition, the construction device can also be based on the fifth triplet (north-south straight-north-south left turn, queuing on one side and emptying on the other, north-south straight-north-south left turn, unbalanced flow rate and large difference in flow coefficient between the same phase of the flow), with "queuing on one side and emptying on the other" as the edge connection. Figure 4 The nodes in the middle section are "North-South Straight - North-South Left Turn" and "North-South Straight - North-South Left Turn with Uneven Flow Coefficients and Large Differences in Phase Flow Coefficients". Based on the sixth triplet (North-South Straight - North-South Left Turn, Uneven Flow Coefficients and Large Differences in Phase Flow Coefficients, Symmetrical North-South Straight-Left Crossover), the nodes are connected with the edge "Uneven Flow Coefficients and Large Differences in Phase Flow Coefficients and Large Differences in Phase Flow Coefficients". Figure 5 The nodes of "north-south straight - north-south left turn" and "north-south symmetrical straight-left overlap" are constructed as follows: Figure 6 The image shows a portion of the traffic knowledge graph.

[0097] The construction device can also be used in Figure 6 The traffic knowledge graph shown is supplemented by adding relevant nodes and relationships corresponding to other directional phase sequences according to the steps described above, thus enriching the traffic knowledge graph. Figure 7 As shown. Among them, "East-West mixed lanes" is a subset of "East-West symmetrical direction", so "East-West symmetrical direction" is also connected with the two solutions for "East-West mixed lanes", "East-West phase splitting" and "first release the main phase and then mix them".

[0098] Similarly, the construction device can further update and improve the traffic knowledge graph based on the set of triplets of phase sequence of other traffic signals.

[0099] As mentioned above, knowledge graphs can provide a fast and convenient way to retrieve and reason about knowledge. Therefore, the traffic knowledge graph established above has a query function, providing causal analysis and solution strategies for traffic signal control problems for professionals in the field. Therefore, this application also provides a traffic problem analysis method, applied to a traffic problem analysis device (or simply analysis device). For example, this traffic problem analysis method is as follows: Figure 8As shown, it may include the following S801-S802.

[0100] S801, Get query request.

[0101] The query request includes: information about the first node and information about the target location; the first node is any entity among phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy; the target location is a node or edge.

[0102] S802. Based on the query request, retrieve the query results from the traffic knowledge graph.

[0103] In the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are the nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes and solution strategy is the edge of the traffic knowledge graph.

[0104] The traffic knowledge graph can be constructed from a set of triplets of the phase sequence of each traffic signal; the set of triplets includes one or more triplets, and each triplet includes any two entities in the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomenon under the direction phase sequence, the cause of the traffic phenomenon and the solution strategy of the cause, as well as the relationship between the two entities, which are used to indicate the nodes and edges of the traffic knowledge graph.

[0105] The set of triplets for the phase sequence of each traffic signal includes one or more of the following: first triplet, second triplet, third triplet, fourth triplet, fifth triplet, and sixth triplet; wherein... The first triplet includes: phase sequence, direction phase sequence of phase sequence, and first relation between phase sequence and direction phase sequence, used to indicate that phase sequence and direction phase sequence are nodes of the traffic knowledge graph, and the first relation is an edge of the traffic knowledge graph.

[0106] The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence. It is used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is the edge of the traffic knowledge graph.

[0107] The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and the third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon. It is used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relation is the edge of the traffic knowledge graph.

[0108] The fourth triplet includes: the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fourth relation is used to indicate that the cause of the traffic phenomenon and the solution strategy are nodes in the traffic knowledge graph, and the fourth relation is an edge in the traffic knowledge graph.

[0109] The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the cause of the traffic phenomena. The directional phase sequence and the cause of the traffic phenomena are nodes of the traffic knowledge graph, and the traffic phenomena existing under the directional phase sequence are edges of the traffic knowledge graph.

[0110] The sixth triplet includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon under the directional phase sequence, and the solution strategy for the cause. The directional phase sequence and the solution strategy for the cause are nodes in the traffic knowledge graph, and the cause of the traffic phenomenon under the directional phase sequence is an edge in the traffic knowledge graph.

[0111] The directional phase sequence of the above phase sequence is obtained by dividing the phase sequence according to a preset rule. The preset rule is that phases with the same direction constitute a directional phase sequence.

[0112] In some embodiments, the analysis device can acquire a query request to obtain query results from a traffic knowledge graph. These results indicate the traffic signal control status between the first node and the target location and can be used to analyze traffic signal control issues. The query request can be sent by a user through a user-side device or entered directly by the user on the query interface provided by the analysis device.

[0113] The traffic knowledge graph supports two query schemes: querying nodes and querying chains. The specific query scheme selection depends on the target location in the query request. The following sections provide a detailed explanation of the two query schemes with concrete examples.

[0114] For example, when the target location is an edge, the query request includes information about the first node and the edge. For instance, the first node could be any entity among phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy. Further, the analysis device can query the traffic knowledge graph based on this query request to obtain a second node or a first chain. The second node is a node that satisfies the relationship indicated by the first edge with the first node, and the first chain is a chain in the traffic knowledge graph that includes the first node, the second node, and the target location.

[0115] For example, if the construction device obtains information about the first node in the first query request as "north-south straight - north-south left turn" and the edge information as "one side queues while the other is empty", then the construction device will proceed according to... Figure 6 The traffic knowledge graph shown shows that the information obtained for the corresponding second node is "uneven flow of north-south straight traffic - north-south left turn traffic in the same phase with large differences in flow coefficients in the direction"; or, the obtained first chain can be represented as ("north-south straight traffic - north-south left turn", "queuing on one side and empty on the other", "uneven flow of north-south straight traffic - north-south left turn traffic in the same phase with large differences in flow coefficients in the direction").

[0116] For example, when the target location is a node, the query request includes information about a first node and information about any other node (such as a third node). For instance, the first node is any entity among phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy. The third node is any entity among phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy, but is different from the entity indicated by the first node. Further, the analysis device can query the traffic knowledge graph according to this query request to obtain a second chain, which is a chain in the traffic knowledge graph that includes the first node, the target location (i.e., the third node), and edges indicating the relationship between the first node and the target location.

[0117] For example, the analysis device can obtain a query request. This query request includes information from two nodes: the first node's information is "North-South Straight - North-South Left Turn," and the third node's information is "North-South Symmetrical Straight-Left Overlap." The analysis device can then obtain the corresponding second chain based on the traffic knowledge graph. This second chain can be called chain 1, and chain 1 can be represented as "North-South Straight - North-South Left Turn" - "Queuing on one side while leaving empty on the other" - "Uneven flow of traffic in the same phase for North-South Straight and North-South Left Turn, with large differences in flow coefficients" - "Solution Strategy" - "North-South Symmetrical Straight-Left Overlap."

[0118] It should be noted that, according to the traffic knowledge graph query chain, there may be multiple chains that satisfy the query request. For example, in the above example, the information of the first node in the query request is "North-South Straight - North-South Left Turn" and the information of the third node is "North-South Symmetrical Straight-Left Overlap". In the traffic knowledge graph, chain 2 also satisfies the above second query request. Chain 2 can be represented as "North-South Straight - North-South Left Turn" - "Phenomenon" - "North-South Straight - North-South Left Turn, one side queues while the other is empty" - "Cause" - "North-South Straight and North-South Left Turn, the same phase flow is unbalanced and the flow coefficient difference is large" - "Solution Strategy" - "North-South Symmetrical Straight-Left Overlap". It can be seen that chain 1 is shorter than chain 2. For users, the analysis of traffic signal control problems provided by the shorter chain is more intuitive and it is easier for users to find the content they want. Therefore, the shortest chain can be displayed to users first. When multiple chains are satisfied, multiple chains can also be displayed to provide users with the most complete causal analysis and solution strategy for traffic signal control problems. This application embodiment does not limit the specific scheme of displaying chains.

[0119] The technical solutions provided by the above embodiments bring at least the following beneficial effects. The traffic knowledge graph construction method provided in this application acquires the phase sequence of multiple traffic signals, determines the direction phase sequence based on the phase sequence, and identifies the traffic phenomena existing under the direction phase sequence, the causes of these traffic phenomena, and the solutions to these causes. This allows for the construction of a traffic knowledge graph for analyzing various traffic signal control problems based on the aforementioned data. The traffic knowledge graph constructed in this solution can alleviate the inefficiency of manually diagnosing traffic signal control problems in traditional solutions. Furthermore, the phase sequence required for constructing the traffic knowledge graph is a fundamental control mechanism in the field of traffic signal control. Therefore, a traffic knowledge graph constructed based on the direction phase sequence is more in line with the optimization logic of traffic signal control problems. Moreover, the construction of the traffic knowledge graph is based on data such as the traffic phenomena existing under the direction phase sequence, the causes of these traffic phenomena, and the solutions to these causes. This data can intuitively provide causal analysis and corresponding solutions for traffic signal control problems, facilitating the analysis of traffic signal control problems based on the traffic knowledge graph, thereby significantly improving the processing efficiency of traffic signal control problems.

[0120] Furthermore, this solution continuously improves the traffic knowledge graph by accumulating and refining expert experience. This not only frees up manpower for handling traffic signal control issues but also significantly improves the efficiency and accuracy of problem-solving. In addition, the traffic knowledge graph supports not only node queries but also chain queries, which helps in providing causal analysis and experience sharing for traffic signal control problems, empowering frontline practitioners with knowledge. This solution can promote the application of knowledge graphs in the transportation field and provide a solid foundation for the future development of knowledge graphs in transportation.

[0121] In an exemplary embodiment, this application also provides a construction apparatus. The construction apparatus may include one or more functional modules for implementing the traffic knowledge graph construction method of the above method embodiments.

[0122] For example, Figure 9 This is a schematic diagram illustrating the composition of a construction apparatus provided in an embodiment of this application. Figure 9 As shown, the construction device includes an acquisition module 901, a determination module 902, and a construction module 903. The acquisition module 901, the determination module 902, and the construction module 903 are interconnected.

[0123] The acquisition module 901 is used to acquire the phase sequence of multiple traffic signals.

[0124] The determination module 902 is used to determine the direction phase sequence of each traffic signal among multiple traffic signals, obtain the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes.

[0125] Module 903 is used to construct a traffic knowledge graph based on the phase sequence of each traffic signal, the direction phase sequence, the traffic phenomena under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes. The traffic knowledge graph is used to analyze the relationships between nodes or between nodes and edges for diagnosing traffic signal control problems.

[0126] In some embodiments, in a traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy is the edge of the traffic knowledge graph.

[0127] In some embodiments, the construction module 903 is specifically used for the phase sequence of each traffic signal: based on the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, a set of triples for the phase sequence is constructed; the set of triples includes one or more triples, and each triple includes any two entities in the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, as well as the relationship between the two entities, which is used to indicate the nodes and edges of the traffic knowledge graph; a traffic knowledge graph is constructed based on the set of triples for the phase sequence of each traffic signal.

[0128] In some embodiments, the set of triplets for the phase sequence of each traffic signal includes one or more of the following: a first triplet, a second triplet, a third triplet, a fourth triplet, a fifth triplet, and a sixth triplet; wherein... The first triplet includes: phase sequence, direction phase sequence of phase sequence, and first relation between phase sequence and direction phase sequence, used to indicate that phase sequence and direction phase sequence are nodes of the traffic knowledge graph, and the first relation is an edge of the traffic knowledge graph. The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence. It is used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is the edge of the traffic knowledge graph.

[0129] The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and the third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon. It is used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relation is the edge of the traffic knowledge graph.

[0130] The fourth triplet includes: the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fourth relation is used to indicate that the cause of the traffic phenomenon and the solution strategy are nodes in the traffic knowledge graph, and the fourth relation is an edge in the traffic knowledge graph.

[0131] The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the cause of the traffic phenomena. The directional phase sequence and the cause of the traffic phenomena are nodes of the traffic knowledge graph, and the traffic phenomena existing under the directional phase sequence are edges of the traffic knowledge graph.

[0132] The sixth triplet includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon under the directional phase sequence, and the solution strategy for the cause. The directional phase sequence and the solution strategy for the cause are nodes in the traffic knowledge graph, and the cause of the traffic phenomenon under the directional phase sequence is an edge in the traffic knowledge graph.

[0133] In some embodiments, the determining module 902 is specifically used to divide the phase sequence according to a preset rule to obtain the directional phase sequence of the phase sequence; the preset rule is that phases with the same direction constitute a directional phase sequence.

[0134] In an exemplary embodiment, this application also provides an analysis apparatus. This analysis apparatus may include one or more functional modules for implementing the traffic problem analysis method of the above method embodiments.

[0135] For example, Figure 10 This is a schematic diagram illustrating the composition of an analytical apparatus provided in an embodiment of this application. Figure 10 As shown, the analysis device includes an acquisition module 1001 and a query module 1002. The acquisition module 1001 and the query module 1002 are interconnected.

[0136] The acquisition module 1001 is used to acquire query requests; the query requests include: information of the first node and information of the target location; the first node is any entity among phase sequence, direction phase sequence, traffic phenomenon, cause and solution strategy; the target location is a node or edge.

[0137] The query module 1002 is used to query the traffic knowledge graph according to the query request when the target location is an edge, so as to obtain the second node or the first chain; the second node is a node that satisfies the relationship indicated by the target location with the first node, and the first chain is a chain in the traffic knowledge graph that includes the first node, the second node and the target location.

[0138] The query module 1002 is also used to query the traffic knowledge graph according to the query request when the target location is a node, so as to obtain a second chain. The second chain is a chain in the traffic knowledge graph that includes the first node, the target location and the edge indicating the relationship between the second node and the target location. The second node, the first chain or the second chain is used to indicate the traffic signal control status between the first node and the target location.

[0139] In some embodiments, in a traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes and solution strategy is the edge of the traffic knowledge graph.

[0140] In some embodiments, the traffic knowledge graph is constructed from a set of triplets of the phase sequence of each traffic signal; the set of triplets includes one or more triplets, each triplet including any two entities in the phase sequence, the direction phase sequence of the phase sequence, the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon and the solution strategy of the cause, and the relationship between the two entities, which are used to indicate the nodes and edges of the traffic knowledge graph.

[0141] In some embodiments, the set of triplets for the phase sequence of each traffic signal includes one or more of the following: a first triplet, a second triplet, a third triplet, a fourth triplet, a fifth triplet, and a sixth triplet; wherein... The first triplet includes: phase sequence, direction phase sequence of phase sequence, and first relation between phase sequence and direction phase sequence, used to indicate that phase sequence and direction phase sequence are nodes of the traffic knowledge graph, and the first relation is an edge of the traffic knowledge graph. The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence. It is used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is the edge of the traffic knowledge graph.

[0142] The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and the third relation between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon. It is used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relation is the edge of the traffic knowledge graph.

[0143] The fourth triplet includes: the cause of the traffic phenomenon, the solution strategy for the cause, and the fourth relation between the cause of the traffic phenomenon and the solution strategy. The fourth relation is used to indicate that the cause of the traffic phenomenon and the solution strategy are nodes in the traffic knowledge graph, and the fourth relation is an edge in the traffic knowledge graph.

[0144] The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and the cause of the traffic phenomena. The directional phase sequence and the cause of the traffic phenomena are nodes of the traffic knowledge graph, and the traffic phenomena existing under the directional phase sequence are edges of the traffic knowledge graph.

[0145] The sixth triplet includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon under the directional phase sequence, and the solution strategy for the cause. The directional phase sequence and the solution strategy for the cause are nodes in the traffic knowledge graph, and the cause of the traffic phenomenon under the directional phase sequence is an edge in the traffic knowledge graph.

[0146] In some embodiments, the directional phase sequence of the phase sequence is obtained by dividing the phase sequence according to a preset rule; the preset rule is that phases with the same direction constitute a directional phase sequence.

[0147] In an exemplary embodiment, this application also provides a server, which may be the construction apparatus or analysis apparatus in the above method embodiments. Figure 11 This is a schematic diagram illustrating the composition of a server provided in an embodiment of this application. For example... Figure 11As shown, the server may include a processor 1101 and a memory 1102; the memory 1102 stores instructions executable by the processor 1101; when the processor 1101 is configured to execute instructions, the server implements the method described in the foregoing method embodiments.

[0148] In exemplary embodiments, this application also provides a computer-readable storage medium storing computer program instructions thereon; when the computer program instructions are executed by a computer, the computer causes the computer to implement the method described in the foregoing embodiments. The computer may be the aforementioned electronic device. The computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0149] In an exemplary embodiment, this application also provides a computer program product that, when run on a computer, causes the computer to execute the aforementioned related method steps to implement the traffic knowledge graph construction method or traffic problem analysis method in the above embodiments.

[0150] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for constructing a traffic knowledge graph, characterized in that, The method includes: The phase sequence of multiple traffic signals is acquired; the phase sequence includes one or more phases. For the phase sequence of each traffic signal among the multiple traffic signals, the phase sequence is divided according to a preset rule to obtain the directional phase sequence of the phase sequence; the preset rule is that phases with the same direction constitute a directional phase sequence; the traffic phenomena existing under the directional phase sequence are obtained, the causes of the traffic phenomena are identified, and the solutions to the causes are proposed. For each traffic signal's phase sequence: Based on the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, a set of triples for the phase sequence is constructed; the set of triples includes one or more triples, each triple including any two entities from the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, as well as the relationship between the two entities, used to indicate the nodes and edges of the traffic knowledge graph; The traffic knowledge graph is constructed based on the set of triples of the phase sequence of each traffic signal; the traffic knowledge graph is used to analyze traffic signal control problems between nodes or between nodes and edges.

2. The method according to claim 1, characterized in that, In the aforementioned traffic knowledge graph: Phase sequence, direction phase sequence, traffic phenomena, causes of traffic phenomena, and solutions are the nodes of the traffic knowledge graph. The relationship between phase sequence, direction phase sequence, traffic phenomena, causes of traffic phenomena, and solutions is the edge of the traffic knowledge graph.

3. The method according to claim 1, characterized in that, The set of triplets for the phase sequence of each traffic signal includes one or more of the following: first triplet, second triplet, third triplet, fourth triplet, fifth triplet, and sixth triplet; wherein... The first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relationship between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes of the traffic knowledge graph, and the first relationship is an edge of the traffic knowledge graph; The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and a second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence, used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is an edge of the traffic knowledge graph; The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relationship between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relationship is an edge of the traffic knowledge graph. The fourth triple includes: the cause of the traffic phenomenon, the solution strategy of the cause, and a fourth relation between the cause of the traffic phenomenon and the solution strategy of the cause, used to indicate that the cause of the traffic phenomenon and the solution strategy of the cause are nodes of the traffic knowledge graph, and the fourth relation is an edge of the traffic knowledge graph; The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, and the cause of the traffic phenomenon, used to indicate that the directional phase sequence of the phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph. The sixth triple includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon existing under the directional phase sequence, and the solution strategy for the cause, used to indicate that the directional phase sequence of the phase sequence and the solution strategy for the cause are nodes of the traffic knowledge graph, and the cause of the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph.

4. A traffic problem analysis method, characterized in that, The method includes: Obtain a query request; the query request includes: information of a first node and information of a target location; the first node is any one of the following entities: phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy; the target location is a node or an edge; When the target location is an edge, the traffic knowledge graph is queried according to the query request to obtain a second node or a first chain; the second node is a node that satisfies the relationship indicated by the target location with the first node, and the first chain is a chain in the traffic knowledge graph that includes the first node, the second node and the target location; When the target location is a node, the traffic knowledge graph is queried according to the query request to obtain a second chain. The second chain is a chain in the traffic knowledge graph that includes the first node, the target location, and an edge indicating the relationship between the second node and the target location. The second node, the first chain, or the second chain is used to indicate the traffic signal control status between the first node and the target location; Wherein, the traffic knowledge graph is a traffic knowledge graph constructed according to the method described in any one of claims 1-3, wherein: the directional phase sequence of the phase sequence is obtained by dividing the phase sequence according to a preset rule, the preset rule being that phases with the same direction constitute a directional phase sequence; the traffic knowledge graph is constructed from a set of triplets of the phase sequence of each traffic signal, the set of triplets includes one or more triplets, the triplets including the phase sequence, the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, the cause of the traffic phenomenon and the solution strategy of the cause, any two entities, and the relationship between the two entities, are used to indicate the nodes and edges of the traffic knowledge graph.

5. The method according to claim 4, characterized in that, In the aforementioned traffic knowledge graph: Phase sequence, direction phase sequence, traffic phenomena, causes of traffic phenomena, and solutions are the nodes of the traffic knowledge graph. The relationships between phase sequence, direction phase sequence, traffic phenomena, causes, and solutions form the edges of the traffic knowledge graph.

6. The method according to claim 5, characterized in that, The set of triplets for the phase sequence of each traffic signal includes one or more of the following: first triplet, second triplet, third triplet, fourth triplet, fifth triplet, and sixth triplet; wherein... The first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relationship between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes of the traffic knowledge graph, and the first relationship is an edge of the traffic knowledge graph; The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and a second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence, used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is an edge of the traffic knowledge graph; The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relationship between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relationship is an edge of the traffic knowledge graph. The fourth triple includes: the cause of the traffic phenomenon, the solution strategy of the cause, and a fourth relation between the cause of the traffic phenomenon and the solution strategy of the cause, used to indicate that the cause of the traffic phenomenon and the solution strategy of the cause are nodes of the traffic knowledge graph, and the fourth relation is an edge of the traffic knowledge graph; The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, and the cause of the traffic phenomenon, used to indicate that the directional phase sequence of the phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph. The sixth triple includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon existing under the directional phase sequence, and the solution strategy for the cause, used to indicate that the directional phase sequence of the phase sequence and the solution strategy for the cause are nodes of the traffic knowledge graph, and the cause of the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph.

7. A construction apparatus, characterized in that, The device includes: an acquisition module, a determination module, and a construction module; The acquisition module is used to acquire the phase sequence of multiple traffic signals; the phase sequence includes one or more phases. The determining module is used to divide the phase sequence of each traffic signal among the plurality of traffic signals according to a preset rule to obtain the directional phase sequence of the phase sequence; the preset rule is that phases with the same direction constitute a directional phase sequence; to obtain the traffic phenomena existing under the directional phase sequence, the causes of the traffic phenomena, and the solutions to the causes. The construction module is used to construct a set of triples for each traffic signal's phase sequence based on the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes. The set of triples includes one or more triples, each triple containing any two entities from the phase sequence, the direction phase sequence, the traffic phenomena existing under the direction phase sequence, the causes of the traffic phenomena, and the solutions to the causes, as well as the relationship between the two entities, used to indicate the nodes and edges of the traffic knowledge graph. The traffic knowledge graph is constructed based on the set of triples for each traffic signal's phase sequence. The traffic knowledge graph is used to analyze traffic signal control problems between nodes or between nodes and edges.

8. The apparatus according to claim 7, characterized in that, In the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are the nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy is the edge of the traffic knowledge graph. The set of triplets for the phase sequence of each traffic signal includes one or more of the following: first triplet, second triplet, third triplet, fourth triplet, fifth triplet, and sixth triplet; wherein... The first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relationship between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes of the traffic knowledge graph, and the first relationship is an edge of the traffic knowledge graph; The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and a second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence, used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is an edge of the traffic knowledge graph; The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relationship between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relationship is an edge of the traffic knowledge graph. The fourth triple includes: the cause of the traffic phenomenon, the solution strategy of the cause, and a fourth relation between the cause of the traffic phenomenon and the solution strategy of the cause, used to indicate that the cause of the traffic phenomenon and the solution strategy of the cause are nodes of the traffic knowledge graph, and the fourth relation is an edge of the traffic knowledge graph; The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, and the cause of the traffic phenomenon, used to indicate that the directional phase sequence of the phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph. The sixth triple includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon existing under the directional phase sequence, and the solution strategy for the cause, used to indicate that the directional phase sequence of the phase sequence and the solution strategy for the cause are nodes of the traffic knowledge graph, and the cause of the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph.

9. A traffic problem analysis device, characterized in that, The device includes: an acquisition module and a query module; The acquisition module is used to acquire a query request; the query request includes: information of a first node and information of a target location; the first node is any one of the following entities: phase sequence, direction phase sequence, traffic phenomenon, cause, and solution strategy; the target location is a node or an edge; The query module is used to query the traffic knowledge graph according to the query request when the target location is an edge, so as to obtain a second node or a first chain; the second node is a node that satisfies the relationship indicated by the target location with the first node, and the first chain is a chain in the traffic knowledge graph that includes the first node, the second node and the target location; The query module is further configured to, when the target location is a node, query the traffic knowledge graph according to the query request to obtain a second chain, wherein the second chain is a chain in the traffic knowledge graph that includes the first node, the target location, and an edge indicating the relationship between the second node and the target location; The second node, the first chain, or the second chain is used to indicate the traffic signal control status between the first node and the target location; Wherein, the traffic knowledge graph is a traffic knowledge graph constructed according to the method described in any one of claims 1-3, wherein: the directional phase sequence of the phase sequence is obtained by dividing the phase sequence according to a preset rule, the preset rule being that phases with the same direction constitute a directional phase sequence; the traffic knowledge graph is constructed from a set of triplets of the phase sequence of each traffic signal, the set of triplets includes one or more triplets, the triplets including the phase sequence, the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, the cause of the traffic phenomenon and the solution strategy of the cause, any two entities, and the relationship between the two entities, are used to indicate the nodes and edges of the traffic knowledge graph.

10. The apparatus according to claim 9, characterized in that, In the traffic knowledge graph: phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy are the nodes of the traffic knowledge graph; the relationship between phase sequence, direction phase sequence, traffic phenomenon, causes of traffic phenomenon and solution strategy is the edge of the traffic knowledge graph. The set of triplets for the phase sequence of each traffic signal includes one or more of the following: first triplet, second triplet, third triplet, fourth triplet, fifth triplet, and sixth triplet; wherein... The first triplet includes: the phase sequence, the direction phase sequence of the phase sequence, and a first relationship between the phase sequence and the direction phase sequence, used to indicate that the phase sequence and the direction phase sequence are nodes of the traffic knowledge graph, and the first relationship is an edge of the traffic knowledge graph; The second triplet includes: the directional phase sequence of the phase sequence, the traffic phenomena existing under the directional phase sequence, and a second relationship between the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence, used to indicate that the directional phase sequence of the phase sequence and the traffic phenomena existing under the directional phase sequence are nodes of the traffic knowledge graph, and the second relationship is an edge of the traffic knowledge graph; The third triplet includes: the traffic phenomenon existing under the direction phase sequence, the cause of the traffic phenomenon, and a third relationship between the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon, used to indicate that the traffic phenomenon existing under the direction phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the third relationship is an edge of the traffic knowledge graph. The fourth triple includes: the cause of the traffic phenomenon, the solution strategy of the cause, and a fourth relation between the cause of the traffic phenomenon and the solution strategy of the cause, used to indicate that the cause of the traffic phenomenon and the solution strategy of the cause are nodes of the traffic knowledge graph, and the fourth relation is an edge of the traffic knowledge graph; The fifth triplet includes: the directional phase sequence of the phase sequence, the traffic phenomenon existing under the directional phase sequence, and the cause of the traffic phenomenon, used to indicate that the directional phase sequence of the phase sequence and the cause of the traffic phenomenon are nodes of the traffic knowledge graph, and the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph. The sixth triple includes: the directional phase sequence of the phase sequence, the cause of the traffic phenomenon existing under the directional phase sequence, and the solution strategy for the cause, used to indicate that the directional phase sequence of the phase sequence and the solution strategy for the cause are nodes of the traffic knowledge graph, and the cause of the traffic phenomenon existing under the directional phase sequence is an edge of the traffic knowledge graph.

11. A server, characterized in that, The server includes: a processor and memory; The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, the server implements the method as described in any one of claims 1-3, or any one of claims 4-6.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: computer software instructions; When the computer software instructions are executed in the computer, the computer causes the computer to perform the method as described in any one of claims 1-3, or any one of claims 4-6.

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