Mining Method and Device, Equipment and Medium for Invalid Traffic Restriction Information at Road Intersections

Abstract

The present disclosure provides a method, apparatus, device, and medium for mining invalid traffic restriction information at an intersection, which relates to the field of computer technology, and particularly to the fields of intelligent transportation, intelligent cockpit, and vehicle networking technologies. The implementation solution is as follows: obtain a target intersection from a road network topology, where the target intersection is associated with traffic restriction information for restricting traffic on multiple target road segments; obtain multiple vehicle travel trajectory data within a preset duration before the current moment that is associated with the target intersection, and the travel trajectory data includes multiple road segments and multiple intersections in the road network topology; for each vehicle travel trajectory data, determine the trajectory form type of the vehicle travel trajectory data, and the trajectory form type can indicate the driving direction of the vehicle at each intersection among the corresponding multiple intersections; and based on the trajectory form types of the multiple vehicle travel trajectory data, determine whether the traffic restriction information of the target intersection is invalid.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and in particular to the fields of intelligent transportation, intelligent cockpits, and vehicle networking. Specifically, the present disclosure relates to a method, apparatus, electronic device, computer-readable storage medium, and computer program product for mining invalid traffic restriction information at intersections. Background Art

[0002] With the popularization of mobile electronic map applications, electronic maps are increasingly used by users, and users can use the road network topology displayed by the electronic map applications to plan travel routes.

[0003] The methods described in this section are not necessarily methods that have been previously conceived or adopted. Unless otherwise specified, any method described in this section should not be considered prior art solely because it is included in this section. Similarly, unless otherwise specified, the problems mentioned in this section should not be considered to have been recognized in any prior art. Summary of the Invention

[0004] The present disclosure provides a method, apparatus, electronic device, computer-readable storage medium, and computer program product for mining invalid traffic restriction information at intersections.

[0005] According to one aspect of the present disclosure, there is provided a method for mining invalid traffic restriction information at intersections, including: obtaining a target intersection from a road network topology, where the target intersection is associated with traffic restriction information for restricting the traffic of a plurality of target road segments associated with the target intersection; obtaining a plurality of vehicle travel trajectory data within a preset time period before the current moment and associated with the target intersection, where the travel trajectory data includes a plurality of road segments and a plurality of intersections in the road network topology; for each vehicle travel trajectory data among the plurality of vehicle travel trajectory data, determining the trajectory form type of the vehicle travel trajectory data, where the trajectory form type can indicate the travel direction of the vehicle at each intersection among the corresponding plurality of intersections; and determining whether the traffic restriction information of the target intersection is invalid based on the trajectory form types of the plurality of vehicle travel trajectory data.

[0006] According to another aspect of the present disclosure, there is provided a method for displaying an electronic map, where the electronic map includes a road network topology, and at least one intersection included in the road network topology is associated with traffic restriction information. The method includes: determining at least one invalid traffic restriction information from the traffic restriction information associated with the at least one intersection by using the method for mining invalid traffic restriction information at intersections as described above; updating the road network topology based on the at least one invalid traffic restriction information; and displaying the updated road network topology in response to receiving a user's opening request.

[0007] According to another aspect of the present disclosure, there is provided a device for mining invalid traffic restriction information of an intersection, including: a first acquisition unit configured to acquire a target intersection from a road network topology, where the target intersection is associated with traffic restriction information for restricting traffic on a plurality of target road segments associated with the target intersection; a second acquisition unit configured to acquire a plurality of vehicle travel trajectory data within a preset duration before the current moment associated with the target intersection, where the travel trajectory data includes a plurality of road segments and a plurality of intersections in the road network topology; a first determination unit configured to determine, for each of the plurality of vehicle travel trajectory data, a trajectory form type of the travel trajectory data, where the trajectory form type can indicate the driving direction of the vehicle at each of the corresponding plurality of intersections; and a second determination unit configured to determine whether the traffic restriction information of the target intersection is invalid based on the trajectory form types of the plurality of vehicle travel trajectory data.

[0008] According to another aspect of the present disclosure, there is also provided a display device for an electronic map, where the electronic map includes a road network topology, and at least one intersection included in the road network topology is associated with traffic restriction information. The method includes: the above-mentioned device for mining invalid traffic restriction information of an intersection configured to determine at least one invalid traffic restriction information from the traffic restriction information associated with the at least one intersection; an update unit configured to update the road network topology based on the at least one invalid traffic restriction information; and a display unit configured to display the updated road network topology in response to receiving a user's opening request.

[0009] According to another aspect of the present disclosure, there is also provided a vehicle including the above-mentioned display device for an electronic map.

[0010] According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively connected to the at least one processor; where the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned method for mining invalid traffic restriction information of an intersection.

[0011] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to cause the computer to execute the above-mentioned method for mining invalid traffic restriction information of an intersection.

[0012] According to another aspect of the present disclosure, there is provided a computer program product including a computer program, where the computer program can implement the above-mentioned method for mining invalid traffic restriction information of an intersection when executed by a processor.

[0013] According to one or more embodiments of the present disclosure, the efficiency and accuracy of mining invalid traffic restriction information can be improved.

[0014] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings exemplarily illustrate embodiments and form a part of the specification, and are used together with the written description of the specification to explain the exemplary embodiments of the embodiments. The illustrated embodiments are for illustrative purposes only and do not limit the scope of the claims. In all the drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0016] Figure 1 A schematic diagram of an exemplary system in which various methods described herein can be implemented according to an exemplary embodiment of the present disclosure;

[0017] Figure 2 A flowchart of a method for mining invalid traffic restriction information at an intersection according to an exemplary embodiment of the present disclosure;

[0018] Figure 3 A flowchart of a partial example process in a method for mining invalid traffic restriction information at an intersection according to an exemplary embodiment of the present disclosure;

[0019] Figures 4 - 5 A topological schematic diagram of a target intersection and associated road segments according to an exemplary embodiment of the present disclosure;

[0020] Figure 6 A flowchart of a method for displaying an electronic map according to an exemplary embodiment of the present disclosure;

[0021] Figure 7 A block diagram of a device for mining invalid traffic restriction information at an intersection according to an exemplary embodiment of the present disclosure;

[0022] Figure 8 A block diagram of a device for displaying an electronic map according to an exemplary embodiment of the present disclosure;

[0023] Figure 9 A block diagram of an exemplary electronic device capable of implementing the embodiments of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, descriptions of well-known functions and structures are omitted in the following description for clarity and conciseness.

[0025] In the present disclosure, unless otherwise specified, the terms "first", "second", etc. are used to describe various elements and are not intended to limit the positional relationship, temporal relationship, or importance relationship of these elements. Such terms are only used to distinguish one element from another. In some examples, the first element and the second element may refer to the same instance of the element, and in certain cases, based on the context description, they may also refer to different instances.

[0026] The terms used in the description of various examples in the present disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element may be one or more. In addition, the term "and / or" used in the present disclosure covers any one of the listed items and all possible combinations.

[0027] The collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information involved in the present disclosure comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0028] The main content of the electronic map is the road network topology, which includes multiple intersections and multiple road segments for connecting the multiple intersections, and each intersection and road segment includes attribute information. It should be understood that the intersections and road segments in the road network topology do not necessarily correspond one-to-one to the roads and intersections in the real world. For example, a road in the real world may include multiple lanes or sidewalks, and each lane or sidewalk can be referred to as a road segment. On this basis, the intersection of every two or more road segments can be referred to as an intersection.

[0029] In an actual application scenario, the user can utilize the navigation route planning service included in the electronic map application to obtain the required navigation route by querying the departure place and the destination, or plan the travel route by himself / herself by viewing the road network topology displayed by the electronic map application.

[0030] Generally speaking, the intersections in the road network topology may be associated with various types of traffic restriction information, and the traffic restriction information is used to restrict the traffic on relevant road sections. For example, it may be various prohibitive regulations formulated by the traffic management department according to laws and regulations for the passage of vehicles and pedestrians on the road and other traffic-related activities, such as prohibiting left turns, prohibiting U-turns, prohibiting motor vehicle passage, etc. For another example, it may also be traffic restrictions caused by objective reasons such as road construction and road damage.

[0031] When the electronic map application program performs navigation route planning, or when the user independently plans a travel route by viewing the electronic map, it is necessary to refer to the traffic restriction information associated with each intersection to ensure smooth passage. In the real scenario, the traffic restrictions at intersections often change, and the electronic map may not be updated in time. In this case, the accuracy of the traffic restriction information at intersections can directly affect the accuracy of navigation route planning and also affect the experience of the user directly viewing the road network topology and independently planning a travel route. Therefore, it is necessary to timely identify the invalid traffic restriction information at the intersections in the electronic map and update the road network topology based on this to improve the accuracy of the road network topology.

[0032] In the related art, it is usually relied on manual work to discover the invalid traffic restriction information and update the information of the road network topology in time. This method requires a high cost and low efficiency. Or, image recognition technology can also be used to respectively identify and judge the traffic restriction information at the intersections in the historical image and the current image of a certain area, and determine the invalid traffic restriction information by comparing the recognition results corresponding to the historical image and the current image of this area. However, this method needs to rely on the real images corresponding to each intersection, and the acquisition cost of the images is high.

[0033] Based on this, the present disclosure provides a method for mining invalid traffic restriction information at intersections, which utilizes the vehicle travel trajectory data associated with the target intersection and determines whether the traffic restriction information at the target intersection is invalid by using the trajectory form type indicating the vehicle travel direction, and can improve the efficiency and accuracy of mining invalid traffic restriction information.

[0034] The embodiments of the present disclosure will be described in detail below with reference to the drawings.

[0035] Figure 1 FIG. shows a schematic diagram of an exemplary system 100 in which the various methods and apparatuses described herein can be implemented according to an embodiment of the present disclosure. Refer to Figure 1, the system 100 includes one or more client devices 101, 102, 103, 104, 105, and 106, a server 120, and one or more communication networks 110 that couple the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105, and 106 can be configured to execute one or more applications.

[0036] In an embodiment of the present disclosure, the server 120 can run one or more services or software applications that enable a mining method for failure passing restriction information at intersections to be executed.

[0037] In certain embodiments, the server 120 can also provide other services or software applications, which can include non-virtual environments and virtual environments. In certain embodiments, these services can be provided as web-based services or cloud services, such as provided to users of the client devices 101, 102, 103, 104, 105, and / or 106 under a software as a service (SaaS) model.

[0038] In Figure 1 In the configuration shown, the server 120 can include one or more components that implement the functions performed by the server 120. These components can include software components, hardware components, or a combination thereof that can be executed by one or more processors. Users operating the client devices 101, 102, 103, 104, 105, and / or 106 can in turn utilize one or more client applications to interact with the server 120 to utilize the services provided by these components. It should be understood that various different system configurations are possible, which can be different from the system 100. Therefore, Figure 1 is an example of a system for implementing the various methods described herein and is not intended to be limiting.

[0039] Users can use the client devices 101, 102, 103, 104, 105, and / or 106 to send road network topologies. The client device can provide an interface that enables a user of the client device to interact with the client device. The client device can also output information to the user via the interface. Although Figure 1 only six client devices are depicted, those skilled in the art will be able to understand that the present disclosure can support any number of client devices.

[0040] Client devices 101, 102, 103, 104, 105, and / or 106 may include various types of computing devices such as portable handheld devices, general-purpose computers (such as personal computers and laptop computers), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, gaming systems, thin clients, various messaging devices, sensors, or other sensing devices, etc. These computing devices may run various types and versions of software applications and operating systems such as MICROSOFT Windows, APPLE iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as GOOGLE Chrome OS); or include various mobile operating systems such as MICROSOFT WindowsMobile OS, iOS, Windows Phone, Android. Portable handheld devices may include cellular phones, smartphones, tablets, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Gaming systems may include various handheld gaming devices, Internet-enabled gaming devices, etc. The client devices are capable of executing various different applications such as various Internet-related applications, communication applications (such as email applications), short message service (SMS) applications, and may use various communication protocols.

[0041] Network 110 can be any type of network known to those skilled in the art, which can support data communication using any of a variety of available protocols (including but not limited to TCP / IP, SNA, IPX, etc.). By way of example only, one or more networks 110 can be a local area network (LAN), Ethernet-based network, token ring, wide area network (WAN), the Internet, virtual network, virtual private network (VPN), intranet, extranet, blockchain network, public switched telephone network (PSTN), infrared network, wireless network (such as Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0042] Server 120 may include one or more general-purpose computers, dedicated server computers (such as PC (personal computer) servers, UNIX servers, midrange servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running a virtual operating system, or other computing architectures involving virtualization (such as one or more flexible pools of logical storage devices that can be virtualized to maintain virtual storage devices for the server). In various embodiments, server 120 may run one or more services or software applications that provide the functions described below.

[0043] The computing unit in server 120 can run one or more operating systems including any of the above-mentioned operating systems and any commercially available server operating systems. Server 120 can also run any one of a variety of additional server applications and / or middleware applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0044] In some embodiments, server 120 can include one or more applications to analyze and combine data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 can also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0045] In some embodiments, server 120 can be a server of a distributed system, or a server combined with a blockchain. Server 120 can also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in the cloud computing service system to solve the defects of high management difficulty and weak business scalability existing in traditional physical hosts and virtual private server (VPS) services.

[0046] System 100 can also include one or more databases 130. In certain embodiments, these databases can be used to store data and other information. For example, one or more of databases 130 can be used to store information such as audio files and video files. Databases 130 can reside in various locations. For example, the databases used by server 120 can be local to server 120, or can be remote from server 120 and can communicate with server 120 via a network-based or dedicated connection. Databases 130 can be of different types. In certain embodiments, the databases used by server 120 can be, for example, relational databases. One or more of these databases can store, update, and retrieve data to and from the databases in response to commands.

[0047] In certain embodiments, one or more of databases 130 can also be used by applications to store application data. The databases used by applications can be different types of databases, such as key-value repositories, object repositories, or conventional repositories supported by a file system.

[0048] Figure 1System 100 can be configured and operated in various ways to enable the application of the various methods and apparatuses described in this disclosure.

[0049] Figure 2 The flowchart of a method 200 for mining invalid traffic restriction information at an intersection according to an exemplary embodiment of the present disclosure is shown. As Figure 2 shown, method 200 includes:

[0050] Step S210: Obtain a target intersection from the road network topology, where the target intersection is associated with traffic restriction information for restricting the traffic of a plurality of target road segments associated with the target intersection;

[0051] Step S220: Obtain a plurality of vehicle travel trajectory data within a preset duration before the current moment associated with the target intersection, where the travel trajectory data includes a plurality of road segments and a plurality of intersections in the road network topology;

[0052] Step S230: For each vehicle travel trajectory data among the plurality of vehicle travel trajectory data, determine the trajectory form type of the vehicle travel trajectory data, where the trajectory form type can indicate the travel direction of the vehicle at each intersection among the corresponding plurality of intersections; and

[0053] Step S240: Based on the trajectory form types of the plurality of vehicle travel trajectory data, determine whether the traffic restriction information of the target intersection has expired.

[0054] By obtaining the vehicle travel trajectory data associated with the target intersection, it is possible to use the trajectory form type indicating the vehicle travel direction to determine whether the traffic restriction information of the target intersection has expired. For example, when the traffic restriction information associated with the target intersection is used to restrict the left-turn traffic of vehicles at the target intersection, the trajectory form types of multiple vehicles passing through the target intersection can be identified. When there are a large number of vehicles with a left-turn trajectory form type when passing through the target intersection, it can be determined that the traffic restriction information of the target intersection has expired. The method can use real vehicle travel trajectory data to indicate the traffic state of the intersection, thereby improving the efficiency and accuracy of mining invalid traffic restriction information.

[0055] Exemplarily, the preset duration can be set manually according to actual needs, so as to more accurately obtain the vehicle travel trajectory data that may indicate the expiration of the traffic restriction information at the intersection.

[0056] According to some embodiments, the trajectory form type includes at least one of the following: left turn, right turn, straight ahead, and U-turn. Thus, it is possible to simply and clearly indicate the travel direction of the vehicle at the intersection, facilitating the determination of the traffic state of the intersection.

[0057] Exemplarily, the trajectory form type may also include other types, such as driving forward to the left front, driving forward to the right front, driving in a roundabout, etc., so as to be able to more comprehensively and accurately indicate the driving direction of the vehicle at different positions.

[0058] It should be understood that the multiple target road segments associated with the target intersection are not necessarily directly connected to the target intersection, but may be associated through other attribute information. For example, when the target intersection is an intersection included in one direction of a two-way lane, the road segments included in the other direction of the lane may also be associated with the target intersection. The implementation manner of determining the traffic restriction information will be further described below.

[0059] In some embodiments, the traffic restriction information may be explicitly provided. For example, it may be included in the attribute information of each intersection. In this case, the target intersection can be directly obtained from the road network topology by filtering the attribute information of the intersection. For example, the traffic restriction information may be stored in the attribute information of each intersection in the form of traffic restriction labels. The traffic restriction labels may include prohibited straight, prohibited left turn, prohibited right turn, etc. Furthermore, the target intersection can be filtered based on this and the corresponding multiple target road segments can be determined.

[0060] In other embodiments, the traffic restriction information may not be explicitly provided. In one example, when there is no road segment that can connect two road segments, namely segment A and segment B, associated with the same intersection, it is equivalent that the intersection is associated with traffic restriction information, and the traffic restriction information is used to restrict the traffic from segment A to segment B.

[0061] In this case, according to some embodiments, obtaining the target intersection from the road network topology in step S210 includes: obtaining the associated road segment information of multiple candidate intersections from the road network topology, where the associated road segment information includes multiple road segments associated with the candidate intersection and the included angle information between the multiple road segments; and based on the associated road segment information of the multiple candidate intersections, determining the target intersection and the traffic restriction information associated with the target intersection from the multiple candidate intersections. Thus, by mining the associated road segment information of each intersection in the road network topology, the target intersection associated with the traffic restriction information can be determined therefrom, so as to be able to more comprehensively and accurately obtain the target intersection in the road network topology, avoid missing the invalid traffic restriction information of the intersection, and improve the accuracy of the road network topology.

[0062] Exemplarily, the associated road section information may further include the attribute information of multiple road sections associated with the candidate intersection, and the attribute information of the road section can indicate the road type of the corresponding road section, such as sidewalk, internal road in a community, urban road, highway, etc. On this basis, the target intersection can be filtered based on the attribute information of the multiple road sections. For example, the road types that need to be filtered can be defined manually, and the intersections related to road sections such as sidewalks and internal roads in a community can be filtered out, so that the mining of invalid traffic restriction information can be carried out only for relatively important traffic intersections, which can save hardware resources.

[0063] Exemplarily, according to a preset rule defined manually, the target intersection and the traffic restriction information associated with the target intersection can be determined based on the associated road section information of the multiple candidate intersections. For example, in a real scenario, there may be the following situation: among the associated road sections of intersection A, there are two road sections, road section B and road section C. Then it can be determined that intersection A is associated with traffic restriction information, and the traffic restriction information is used to restrict the passage from road section B and road section C. Further, the included angle information between road section B and road section C can be used to determine the specific content of the traffic restriction information. For example, when the included angle is 180 degrees, it is determined that the traffic restriction information is used to restrict the straight-through passage from road section B and road section C.

[0064] According to some embodiments, when the target intersection is associated with multiple road sections, in step S220, obtaining multiple vehicle travel trajectory data associated with the target intersection includes: obtaining multiple candidate vehicle travel trajectory data within a preset time period before the current moment from the vehicle travel trajectory database; and for each candidate vehicle travel trajectory data among the multiple candidate vehicle travel trajectory data, in response to the fact that the multiple target road sections are included in the candidate vehicle travel trajectory data, determining that the candidate vehicle travel trajectory data is the vehicle travel trajectory data associated with the target intersection. As described above, the traffic restriction information is used to restrict the passage of multiple target road sections. On this basis, by using the target road sections to screen the vehicle travel trajectory data, the travel trajectory data that may indicate the invalidation of the traffic restriction information at the intersection can be obtained more accurately, the screening efficiency can be improved, and further the efficiency of mining invalid traffic restriction information can be improved.

[0065] Exemplarily, the vehicle travel trajectory database can be pre-constructed, which stores the travel trajectory data of multiple vehicles, and each vehicle travel trajectory data includes the corresponding time information, so that the required vehicle travel trajectory data can be obtained from the database through query.

[0066] Generally speaking, during the driving process of a vehicle, a driving trajectory sequence of the vehicle can be collected by a positioning module in the vehicle (for example, it can be a GPS positioning module or a cellular positioning module), and the driving trajectory sequence includes a plurality of trajectory points arranged in chronological order. In some examples, the driving trajectory sequence collected by the positioning module of the vehicle can be matched with the road network topology to obtain vehicle driving trajectory data corresponding to the driving trajectory sequence. The vehicle driving trajectory data includes a plurality of road segments and intersections in the road network topology, and each of the road segments and intersections can respectively correspond to one or more trajectory points included in the driving trajectory sequence.

[0067] For example, a Hidden Markov Model (HMM) can be used to determine the vehicle driving trajectory data corresponding to the driving trajectory sequence of the vehicle. Specifically, the driving trajectory sequence of the vehicle is the observation sequence in the HMM, and the driving trajectory data is the hidden sequence in the HMM. The Viterbi algorithm can be used to solve the HMM to obtain the hidden sequence corresponding to the observation sequence, that is, to determine the vehicle driving trajectory data corresponding to the driving trajectory sequence.

[0068] In some embodiments, it can be to directly determine the trajectory form type of the vehicle driving trajectory data by using the information of the plurality of road segments and intersections included in the vehicle driving trajectory data. For example, when the vehicle driving trajectory data includes road segment A, intersection B, and road segment C, and the included angle between road segment A and road segment C is 180 degrees, the corresponding trajectory form type can be determined based on this as a straight line.

[0069] However, due to reasons such as positioning errors, coordinate system conversion errors, and electronic map accuracy errors, the trajectory points collected by the positioning module may deviate from the position where the road is located. For example, the vehicle is driving in the auxiliary road segment A, but the coordinates of the trajectory points collected by the positioning module are not located in the auxiliary road segment A, but in the main road segment B next to the auxiliary road segment A, resulting in errors in the vehicle driving trajectory data. In this case, the trajectory form type determined by using the information of the plurality of road segments and intersections included in the vehicle driving trajectory data may be inaccurate.

[0070] Based on this, the inventors propose a method of determining the trajectory form type by using the driving steering angles corresponding to each trajectory point in the driving trajectory sequence corresponding to the vehicle driving trajectory data, which can avoid the deviation of the vehicle driving trajectory data from affecting the accuracy of the trajectory form type.

[0071] Figure 3 Shows a flowchart of some example processes in the method for mining invalid traffic restriction information of intersections according to an exemplary embodiment of the present disclosure. As Figure 3As shown, in some embodiments, for each of the multiple vehicle travel trajectory data in step S230, determining the trajectory form type of the vehicle travel trajectory data includes:

[0072] Step S231, obtain the travel trajectory sequence corresponding to the vehicle travel trajectory data, where the travel trajectory sequence includes the position information of multiple trajectory points;

[0073] Step S232, based on the position information of the multiple trajectory points, determine the travel steering angle corresponding to each of the multiple trajectory points;

[0074] Step S233, based on the multiple travel steering angles respectively corresponding to the multiple trajectory points, determine at least one travel inflection point from the multiple trajectory points; and

[0075] Step S234, based on the position information of the at least one travel inflection point and the travel steering angle corresponding to the at least one travel inflection point, determine the multiple intersections and the trajectory form type included in the vehicle travel trajectory data.

[0076] Thus, it is possible to determine multiple inflection points by obtaining the travel steering angles corresponding to each trajectory point in the travel trajectory sequence corresponding to the vehicle travel trajectory data, and use the multiple inflection points to simply and accurately indicate the corresponding trajectory form type.

[0077] According to some embodiments, in step S232, based on the position information of the multiple trajectory points, determining the travel steering angle corresponding to each of the multiple trajectory points includes: sequentially extracting multiple window subsequences from the travel trajectory sequence by using a sliding window, each window subsequence includes multiple trajectory points, and the multiple trajectory points included in each window subsequence include a central trajectory point; and based on the position information of the multiple travel trajectory points included in each window subsequence, calculate the travel steering angle corresponding to the central trajectory point included in the window subsequence.

[0078] Exemplarily, the size of the sliding window can be set manually according to actual needs. By using the position information of the multiple travel trajectory points included in the window subsequence, it is possible to more conveniently calculate and determine the travel steering angle corresponding to the corresponding central trajectory point.

[0079] Exemplarily, calculating the driving steering angle corresponding to the central trajectory point included in the window subsequence based on the position information of the multiple driving trajectory points included in each window subsequence may include: calculating the included angle between the line connecting the starting trajectory point and the central trajectory point and the line connecting the central trajectory point and the ending trajectory point based on the position information of the starting trajectory point, the central trajectory point, and the ending trajectory point included in the window subsequence, and taking the included angle as the driving steering angle corresponding to the central trajectory point.

[0080] Exemplarily, it may also be possible to determine the driving steering angle corresponding to the central trajectory point by other means. For example, the lines connecting the multiple driving trajectory points included in the window subsequence may be fitted into an arc, and the driving steering angle corresponding to the central trajectory point may be determined based on the radian of the arc.

[0081] Further, according to some embodiments, the step of sequentially extracting multiple window subsequences from the driving trajectory sequence by using a sliding window includes: sequentially extracting multiple first window subsequences from the driving trajectory sequence by using a first sliding window; and sequentially extracting multiple second window subsequences from the driving trajectory sequence by using a second sliding window having a different size from the first sliding window; and simultaneously, calculating the driving steering angle corresponding to the central trajectory point included in the window subsequence based on the position information of the multiple driving trajectory points included in each window subsequence includes: calculating the first driving steering angle corresponding to the central trajectory point included in the first window subsequence based on the position information of the multiple driving trajectory points included in each first window subsequence; calculating the second driving steering angle corresponding to the central trajectory point included in the second window subsequence based on the position information of the multiple driving trajectory points included in each second window subsequence; and determining the maximum value of the first driving steering angle and the second driving steering angle corresponding to each trajectory point as the driving steering angle corresponding to the trajectory point.

[0082] It should be understood that since the position distribution of the multiple trajectory points included in the driving trajectory sequence may be uneven, the size of the sliding window can directly affect the accuracy of the driving steering angle corresponding to the central trajectory point of the window subsequence. By using sliding windows of different sizes to obtain multiple steering angles corresponding to each trajectory point and determining the maximum value among them as the driving steering angle corresponding to the trajectory point, the accuracy of the determined driving steering angle can be improved.

[0083] Exemplarily, based on the above implementation, it is also possible to extract the corresponding window subsequences by using a greater number of sliding windows of different sizes to further improve the accuracy of the determined driving steering angle.

[0084] According to some embodiments, determining at least one driving inflection point from the plurality of trajectory points based on the plurality of driving steering angles respectively corresponding to the plurality of trajectory points in step S233 includes: for each of the plurality of trajectory points, in response to the driving steering angle corresponding to this trajectory point satisfying a first preset condition, determining this trajectory point as a candidate inflection point to obtain at least one candidate inflection point; and based on the position information of the at least one candidate inflection point, determining at least one driving inflection point from the at least one candidate inflection point. Exemplarily, the first preset condition can be set manually according to actual requirements, so that candidate inflection points can be determined from a plurality of trajectory points simply and quickly, improving efficiency.

[0085] Exemplarily, the determining this trajectory point as a candidate inflection point in response to the driving steering angle corresponding to this trajectory point satisfying a first preset condition may include: in response to the driving steering angle corresponding to this trajectory point being not less than a preset minimum threshold and not greater than a preset maximum threshold, determining this trajectory point as a candidate inflection point. The preset minimum threshold and maximum threshold can be set manually according to actual requirements. The first preset condition may also include other contents. For example, it may be that in response to the change rate of the driving steering angle corresponding to this trajectory point compared to the driving steering angle corresponding to the previous trajectory point of this trajectory point being greater than a preset threshold, determining this trajectory point as a candidate inflection point.

[0086] Further, according to some embodiments, the determining at least one driving inflection point from the at least one candidate inflection point based on the position information of the at least one candidate inflection point includes: for each of the plurality of candidate inflection points, in response to the distance between this candidate inflection point and an adjacent candidate inflection point satisfying a second preset condition, determining this candidate inflection point as a driving inflection point. Exemplarily, the second preset condition can be set manually according to actual requirements, so that driving inflection points can be determined from a plurality of candidate inflection points simply and quickly, improving efficiency.

[0087] Exemplarily, the determining this candidate inflection point as a driving inflection point in response to the distance between this candidate inflection point and an adjacent candidate inflection point satisfying a second preset condition may include: in response to the distance between this candidate inflection point and an adjacent candidate inflection point being greater than a preset threshold, determining this candidate inflection point as a driving inflection point. The preset threshold can be set manually according to actual requirements. By manually setting the corresponding threshold, the driving inflection point can be determined more accurately, avoiding the influence of outlier trajectory points on the determined result.

[0088] Exemplarily, it may also be to determine at least one driving inflection point from the at least one candidate inflection point based on the position information of the at least one candidate inflection point in other ways. For example, it may be to utilize the matching result of the driving trajectory sequence and the vehicle driving trajectory data, and in response to an intersection existing within a preset range around the candidate inflection point, determining this trajectory point as a candidate inflection point.

[0089] According to some embodiments, for each of the multiple vehicle travel trajectory data in step S230, determining the trajectory form type of the vehicle travel trajectory data further includes: determining whether the travel trajectory sequence corresponding to the vehicle travel trajectory data is an abnormal trajectory sequence based on the position information of multiple trajectory points included in the travel trajectory sequence; and in response to the travel trajectory sequence being an abnormal trajectory sequence, removing the travel trajectory sequence. Thereby, the influence of the abnormal trajectory sequence on the mining of the ineffective traffic restriction information at the intersection can be avoided.

[0090] Exemplarily, determining whether the travel trajectory sequence is an abnormal trajectory sequence based on the position information of multiple trajectory points included in the travel trajectory sequence corresponding to the vehicle travel trajectory data includes: determining that the travel trajectory sequence is an abnormal trajectory sequence in response to the number of abnormal trajectory points among the multiple trajectory points exceeding a preset threshold. Specifically, it may be determining that a trajectory point is an abnormal trajectory point in response to the distance between the trajectory point and an adjacent trajectory point exceeding a preset threshold.

[0091] It should be understood that other rules for determining an abnormal trajectory sequence can also be set according to actual needs, as long as the unconventional travel trajectory sequences can be removed, and no limitation is made thereto.

[0092] According to some embodiments, for each of the multiple vehicle travel trajectory data in step S230, determining the trajectory form type of the vehicle travel trajectory data further includes: determining whether the travel trajectory sequence corresponding to the vehicle travel trajectory data is a sparse trajectory sequence based on the position information of multiple trajectory points included in the travel trajectory sequence; and in response to the travel trajectory sequence being a sparse trajectory sequence, performing interpolation on the travel trajectory sequence. It should be understood that there may be a large deviation in the trajectory form type determined based on the sparse trajectory sequence. By performing interpolation on the sparse trajectory sequence, the above deviation and its influence on the mining of the ineffective traffic restriction information at the intersection can be avoided.

[0093] Exemplarily, determining whether the travel trajectory sequence is a sparse trajectory sequence based on the position information of multiple trajectory points included in the travel trajectory sequence corresponding to the vehicle travel trajectory data includes: determining that the travel trajectory sequence is a sparse trajectory sequence in response to the distance between any two adjacent trajectory points among the multiple trajectory points exceeding a preset threshold. It should be understood that other rules for determining a sparse trajectory sequence can also be set according to actual needs, and no limitation is made thereto.

[0094] Exemplarily, the interpolation of the sparse trajectory sequence may include linear interpolation, high-order polynomial interpolation, etc., and no limitation is made thereto.

[0095] According to some embodiments, determining whether the traffic restriction information of the target intersection is invalid based on the trajectory form type of the multiple vehicle travel trajectory data in step S240 includes: determining a target trajectory form type that can characterize the invalidation of the traffic restriction information of the intersection based on the included angle information between the multiple target road segments; and determining that the traffic restriction information of the target intersection is invalid in response to the number of vehicle travel trajectory data including the target trajectory form type being greater than a preset threshold. Thus, it is possible to simply and quickly determine whether the traffic restriction information of the target intersection is invalid by counting the number of vehicle travel trajectory data including the target trajectory form type, improving efficiency.

[0096] In one example, the traffic restriction information associated with target intersection A is used to restrict traffic from road segments B and C. Furthermore, the included angle information between road segments B and C can be used to determine the target trajectory form type that can characterize the invalidation of the traffic restriction information of the intersection. For example, when the included angle is 180 degrees, the target trajectory form type is determined to be going straight.

[0097] Embodiments of the present disclosure will be further described below with reference to examples.

[0098] Figures 4 - 5 Shows a topological schematic diagram of a target intersection and associated road segments according to an exemplary embodiment of the present disclosure.

[0099] As Figure 4 shown, road segments 2 and 3 form one direction of the lanes in a two-way lane, and road segments 4 and 5 form the lanes in the other direction. This two-way lane is connected to road segment 1 through intersection 1. It can be seen that road segment 1 can only communicate with road segments 2 and 3, and cannot communicate with road segments 4 and 5, that is, it constitutes a one-way traffic intersection scenario, and the corresponding traffic restriction information is not explicitly provided.

[0100] For Figure 4 the one-way traffic intersection scenario shown, the method described above can be used. First, the target intersection 1 is determined from the road network topology using the associated road segment information of the intersection. For example, it may be to mine all intersections that include three connected road segments and the included angles between the three connected road segments meet a preset condition, so as to extract the target intersection 1 from the road network topology. Furthermore, based on the information of road segments 1-5 associated with target intersection 1, it is determined that the traffic restriction information associated with target intersection 1 is used to restrict right-turn traffic from road segment 1 to road segment 5.

[0101] After determining that the target road segments are Road Segment 1 and Road Segment 5, the method described above can be used to obtain multiple vehicle travel trajectory data associated with the target intersection and determine the trajectory form type of each vehicle travel trajectory data. In this example, it can be seen that the target trajectory form type that can characterize the invalidation of the traffic restriction information at the intersection is a left turn. Therefore, by counting the number of vehicle travel trajectories including the right turn type, when the number is greater than a preset threshold, it can be determined that the traffic restriction information at Target Intersection 1 has become invalid.

[0102] Based on this, the road network topology can be updated to avoid the invalid traffic restriction information affecting the accuracy of the road network topology. For example, Road Segment 1 can be extended to obtain the road network topology as shown in Figure 5 so that Road Segment 1 can be connected to Road Segment 5 to enable traffic between the two.

[0103] According to another aspect of the present disclosure, there is also provided a method for displaying an electronic map. Figure 6 The flowchart of the method 600 for displaying an electronic map according to an exemplary embodiment of the present disclosure is shown. As Figure 6 shown, the method 600 includes:

[0104] Step S601, determining at least one invalid traffic restriction information from the traffic restriction information associated with the at least one intersection by using the method 200 as described above;

[0105] Step S602, updating the road network topology based on the at least one invalid traffic restriction information; and

[0106] Step S603, displaying the updated road network topology in response to receiving a user's opening request.

[0107] According to another aspect of the present disclosure, there is also provided a device for mining invalid traffic restriction information at an intersection. Figure 7 The structural block diagram of the device 700 for mining invalid traffic restriction information at an intersection according to an exemplary embodiment of the present disclosure is shown. As Figure 7 shown, the device 700 includes:

[0108] A first acquisition unit 701, configured to acquire a target intersection from a road network topology, where the target intersection is associated with traffic restriction information for restricting traffic on multiple target road segments associated with the target intersection;

[0109] A second acquisition unit 702, configured to acquire multiple vehicle travel trajectory data within a preset time period before the current moment associated with the target intersection, where the travel trajectory data includes multiple road segments and multiple intersections in the road network topology;

[0110] A first determination unit 703, configured to determine, for each of the plurality of vehicle travel trajectory data, a trajectory form type of the travel trajectory data, where the trajectory form type can indicate the travel direction of the vehicle at each of the corresponding plurality of intersections; and

[0111] A second determination unit 704, configured to determine whether the traffic restriction information of the target intersection is invalid based on the trajectory form types of the plurality of vehicle travel trajectory data.

[0112] The operations of units 701 - 704 of the mining device 700 for invalid traffic restriction information of intersections are similar to the operations of steps S210 - S240 described above, and will not be elaborated here.

[0113] According to another aspect of the present disclosure, there is also provided a display device for an electronic map. Figure 8 The block diagram of a display device 800 for an electronic map according to an exemplary embodiment of the present disclosure is shown. As Figure 8 shown, the device 800 includes:

[0114] The mining device 700 for invalid traffic restriction information of intersections as described above, configured to determine at least one invalid traffic restriction information from the traffic restriction information associated with the at least one intersection;

[0115] An update unit 801, configured to update the road network topology based on the at least one invalid traffic restriction information; and

[0116] A display unit 802, configured to display the updated road network topology in response to receiving a user's opening request.

[0117] The operations of units 700, 801 - 802 of the display device 800 for an electronic map are similar to the operations of steps S601 - S603 described above, and will not be elaborated here.

[0118] According to another aspect of the present disclosure, there is also provided a vehicle including the display device 800 for an electronic map as described above.

[0119] According to another aspect of the present disclosure, there is also provided an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the above-described method for mining invalid traffic restriction information of intersections or the method for displaying an electronic map.

[0120] According to another aspect of the present disclosure, there is also provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the above-mentioned method for mining invalid traffic restriction information of intersections or the method for displaying electronic maps.

[0121] According to another aspect of the present disclosure, there is also provided a computer program product including a computer program, wherein the computer program, when executed by a processor, implements the above-mentioned method for mining invalid traffic restriction information of intersections or the method for displaying electronic maps.

[0122] Reference Figure 9 , the structural block diagram of an electronic device 900 that can be used as a server or a client of the present disclosure will now be described. It is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0123] As Figure 9 shown, the device 900 includes a computing unit 901, which can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 902 or the computer program loaded from the storage unit 908 into the random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. The input / output (I / O) interface 905 is also connected to the bus 904.

[0124] Multiple components in device 900 are connected to I / O interface 905, including: input unit 906, output unit 907, storage unit 908, and communication unit 909. The input unit 906 can be any type of device capable of inputting information into device 900. The input unit 906 can receive input digital or character information, and generate key signal inputs related to user settings and / or function controls of the electronic device, and can include but are not limited to a mouse, keyboard, touch screen, trackpad, trackball, joystick, microphone, and / or remote control. The output unit 907 can be any type of device capable of presenting information, and can include but are not limited to a display, speaker, video / audio output terminal, vibrator, and / or printer. The storage unit 908 can include but are not limited to magnetic disks and optical discs. The communication unit 909 allows device 900 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks, and can include but are not limited to a modem, network card, infrared communication device, wireless communication transceiver, and / or chipset, such as Bluetooth™ devices, 802.11 devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0125] The computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 executes the various methods and processes described above, such as the method for mining invalid traffic restriction information at intersections or the method for displaying an electronic map. For example, in some embodiments, the method for mining invalid traffic restriction information at intersections or the method for displaying an electronic map can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the method for mining invalid traffic restriction information at intersections or the method for displaying an electronic map described above can be executed. Alternatively, in other embodiments, the computing unit 901 can be configured to execute the method for mining invalid traffic restriction information at intersections or the method for displaying an electronic map in any other suitable manner (e.g., by means of firmware).

[0126] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0127] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing device, such that the program codes, when executed by the processor or controller, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0128] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0129] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball), by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0130] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), the Internet, and blockchain network.

[0131] A computer system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, or a server of a distributed system, or a server incorporating blockchain.

[0132] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitation is imposed herein.

[0133] Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above methods, systems, and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but is only defined by the authorized claims and their equivalent scope. Various elements in the embodiments or examples may be omitted or replaced by their equivalent elements. In addition, the steps may be executed in an order different from that described in the present disclosure. Further, the various elements in the embodiments or examples may be combined in various ways. Importantly, with the evolution of technology, many of the elements described herein may be replaced by equivalent elements that emerge after the present disclosure.

Claims

1. A method for mining invalid traffic restriction information at an intersection, comprising: Obtaining a target intersection from a road network topology, where the target intersection is associated with traffic restriction information for restricting traffic on a plurality of target road segments associated with the target intersection; Obtaining a plurality of vehicle travel trajectory data within a preset time period before the current moment and associated with the target intersection, where the vehicle travel trajectory data includes a plurality of road segments and a plurality of intersections in the road network topology; For each vehicle travel trajectory data among the plurality of vehicle travel trajectory data, determining the trajectory form type of the vehicle travel trajectory data, where the trajectory form type can indicate the driving directions of the vehicle at each intersection among the corresponding plurality of intersections; And Based on the trajectory form types of the plurality of vehicle travel trajectory data, determining whether the traffic restriction information of the target intersection is invalid, where determining the trajectory form type of each vehicle travel trajectory data among the plurality of vehicle travel trajectory data includes: Obtaining a travel trajectory sequence corresponding to the vehicle travel trajectory data, where the travel trajectory sequence includes position information of a plurality of trajectory points; Based on the position information of the plurality of trajectory points, determining the driving steering angle corresponding to each trajectory point among the plurality of trajectory points; Based on the plurality of driving steering angles respectively corresponding to the plurality of trajectory points, determining at least one driving inflection point from the plurality of trajectory points; and Based on the position information of the at least one driving inflection point and the driving steering angle corresponding to the at least one driving inflection point, determining the plurality of intersections and the trajectory form type included in the vehicle travel trajectory data.

2. The method according to claim 1, wherein The trajectory form type includes at least one of the following: Left turn, right turn, straight ahead, and U-turn.

3. The method according to claim 1, wherein, The determining the driving steering angle corresponding to each trajectory point among the plurality of trajectory points based on the position information of the plurality of trajectory points includes: Using a sliding window to sequentially extract a plurality of window subsequences from the travel trajectory sequence, each window subsequence includes a plurality of trajectory points, and among the plurality of trajectory points included in each window subsequence, there is a central trajectory point; and Based on the position information of the plurality of travel trajectory points included in each window subsequence, calculating the driving steering angle corresponding to the central trajectory point included in the window subsequence.

4. The method according to claim 3, wherein, The using a sliding window to sequentially extract a plurality of window subsequences from the travel trajectory sequence includes: Using a first sliding window to sequentially extract a plurality of first window subsequences from the travel trajectory sequence; and Using a second sliding window with a different size from the first sliding window to sequentially extract a plurality of second window subsequences from the travel trajectory sequence, and where the calculating the driving steering angle corresponding to the central trajectory point included in the window subsequence based on the position information of the plurality of travel trajectory points included in each window subsequence includes: Based on the position information of the plurality of travel trajectory points included in each first window subsequence, calculating the first driving steering angle corresponding to the central trajectory point included in the first window subsequence; Calculating a second driving steering angle corresponding to a central trajectory point included in the second window subsequence based on position information of a plurality of driving trajectory points included in each second window subsequence; and Determining a maximum value between the first driving steering angle and the second driving steering angle corresponding to each trajectory point as the driving steering angle corresponding to the trajectory point.

5. The method according to claim 1, wherein, The determining of at least one driving inflection point from the plurality of trajectory points based on a plurality of driving steering angles respectively corresponding to the plurality of trajectory points includes: For each trajectory point among the plurality of trajectory points, in response to the driving steering angle corresponding to the trajectory point satisfying a first preset condition, determining the trajectory point as a candidate inflection point to obtain at least one candidate inflection point; and Determining at least one driving inflection point from the at least one candidate inflection point based on position information of the at least one candidate inflection point.

6. The method according to claim 5, wherein, The determining of at least one driving inflection point from the at least one candidate inflection point based on position information of the at least one candidate inflection point includes: For each candidate inflection point among the at least one candidate inflection point, in response to a distance between the candidate inflection point and an adjacent candidate inflection point satisfying a second preset condition, determining the candidate inflection point as a driving inflection point.

7. The method according to claim 1, wherein The determining of the trajectory form type of each vehicle driving trajectory data among the plurality of vehicle driving trajectory data further includes: Determining whether the driving trajectory sequence corresponding to the vehicle driving trajectory data is an abnormal trajectory sequence based on position information of a plurality of trajectory points included in the driving trajectory sequence corresponding to the vehicle driving trajectory data; and In response to the driving trajectory sequence being an abnormal trajectory sequence, removing the driving trajectory sequence.

8. The method according to claim 1, wherein, The determining of the trajectory form type of each vehicle driving trajectory data among the plurality of vehicle driving trajectory data further includes: Determining whether the driving trajectory sequence corresponding to the vehicle driving trajectory data is a sparse trajectory sequence based on position information of a plurality of trajectory points included in the driving trajectory sequence corresponding to the vehicle driving trajectory data; and In response to the driving trajectory sequence being a sparse trajectory sequence, performing interpolation on the driving trajectory sequence.

9. The method according to any one of claims 1-8, wherein The obtaining of the target intersection from the road network topology includes: Obtaining associated road segment information of a plurality of candidate intersections from the road network topology, where the associated road segment information includes a plurality of road segments associated with the candidate intersections and included angle information between the plurality of road segments; and Determining a target intersection and passing restriction information associated with the target intersection from the plurality of candidate intersections based on the associated road segment information of the plurality of candidate intersections.

10. The method according to any one of claims 1-8, when a plurality of road segments are associated with the target intersection, wherein, The obtaining of a plurality of vehicle driving trajectory data associated with the target intersection includes: Obtaining a plurality of candidate vehicle driving trajectory data within a preset time period before the current moment from a vehicle driving trajectory database; and For each candidate vehicle driving trajectory data among the plurality of candidate vehicle driving trajectory data, in response to the plurality of target road segments being included in the candidate vehicle driving trajectory data, determining the candidate vehicle driving trajectory data as vehicle driving trajectory data associated with the target intersection.

11. The method according to any one of claims 1-8, wherein, The determining of whether the passing restriction information of the target intersection is invalid based on the trajectory form types of the plurality of vehicle driving trajectory data includes: Determine a target trajectory form type that can characterize the invalidation of the traffic restriction information of the intersection based on the included angle information between the multiple target road segments; and Determine that the traffic restriction information of the target intersection is invalid in response to the number of vehicle driving trajectory data including the target trajectory form type being greater than a preset threshold.

12. A method for displaying an electronic map, the electronic map includes a road network topology, and at least one intersection included in the road network topology is associated with traffic restriction information. The method includes: Determine at least one invalid traffic restriction information from the traffic restriction information associated with the at least one intersection by using the method according to any one of claims 1-11; Update the road network topology based on the at least one invalid traffic restriction information; and Display the updated road network topology in response to receiving a user's opening request.

13. A device for mining invalid traffic restriction information of an intersection, including: A first acquisition unit configured to acquire a target intersection from a road network topology, the target intersection being associated with traffic restriction information for restricting the traffic of multiple target road segments associated with the target intersection; A second acquisition unit configured to acquire a plurality of vehicle driving trajectory data within a preset time period before the current moment associated with the target intersection, the driving trajectory data including multiple road segments and multiple intersections in the road network topology; A first determination unit configured to determine, for each vehicle driving trajectory data among the plurality of vehicle driving trajectory data, a trajectory form type of the driving trajectory data, the trajectory form type being capable of indicating the driving direction of the vehicle at each intersection among the corresponding multiple intersections; And A second determination unit configured to determine whether the traffic restriction information of the target intersection is invalid based on the trajectory form types of the plurality of vehicle driving trajectory data, wherein the first determination unit is configured to: Acquire a driving trajectory sequence corresponding to the vehicle driving trajectory data, the driving trajectory sequence including position information of a plurality of trajectory points; Determine a driving turning angle corresponding to each trajectory point among the plurality of trajectory points based on the position information of the plurality of trajectory points; Determine at least one driving inflection point from the plurality of trajectory points based on the plurality of driving turning angles respectively corresponding to the plurality of trajectory points; and Determine the plurality of intersections and the trajectory form type included in the vehicle driving trajectory data based on the position information of the at least one driving inflection point and the driving turning angle corresponding to the at least one driving inflection point.

14. A device for displaying an electronic map, the electronic map includes a road network topology, and at least one intersection included in the road network topology is associated with traffic restriction information. The device includes: The device for mining invalid traffic restriction information of an intersection according to claim 13, configured to determine at least one invalid traffic restriction information from the traffic restriction information associated with the at least one intersection; An update unit configured to update the road network topology based on the at least one invalid traffic restriction information; And A display unit, configured to display the updated road network topology in response to receiving an open request from a user.

15. A vehicle, comprising the display device of the electronic map according to claim 14.

16. An electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-12.

17. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are for causing a computer to execute the method according to any one of claims 1-12.

18. A computer program product comprising a computer program, wherein, The computer program, when executed by a processor, implements the method according to any one of claims 1-12.

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