Road connection status identification method and device, electronic device and medium

Abstract

The present disclosure provides a method and device for identifying road connection status, an electronic device, and a medium, and relates to the fields of computer technology, in particular to the fields of intelligent transportation and computer vision technology. The implementation scheme is as follows: obtaining driving trajectory data of multiple vehicles passing through a test intersection, wherein the multiple vehicles have the same navigation planning path at the test intersection, and the navigation planning path includes an entry section and an exit section of the test intersection; based on the driving trajectory data, determining whether the traffic status of the test intersection is abnormal; in response to determining that the traffic status of the test intersection is abnormal, performing obstacle recognition on the image of the entry section; and based on the result of the obstacle recognition, determining whether the connection between the entry section and the exit section is disconnected.

Description

Technical Field

[0001] The present disclosure relates to the fields of computer technology, in particular to the fields of intelligent transportation and computer vision technology, and specifically to a method and device for identifying road connection status, an electronic device, a computer-readable storage medium, and a computer program product. Background Art

[0002] An electronic map, also known as a digital map, is a map that is stored and accessed digitally using computer technology. It features various map elements, such as roads, shopping malls, schools, hospitals, and landmark buildings.

[0003] Driving is a primary mode of transportation. During a self-driving trip, users can use devices equipped with electronic map applications (such as mobile phones, tablets, and in-car navigation devices) for route navigation. Based on the user's specified departure and destination points, the electronic map application will generate a navigation route for the user. The user can then drive along the route to successfully reach their destination.

[0004] The approaches described in this section are not necessarily approaches that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any approach described in this section is prior art simply by virtue of its inclusion in this section. Similarly, unless otherwise indicated, the issues raised in this section should not be considered as having been recognized in any prior art. Summary of the Invention

[0005] The present disclosure provides a method and apparatus for identifying a road connection status, an electronic device, a computer-readable storage medium, and a computer program product.

[0006] According to one aspect of the present disclosure, a method for identifying a road connection status is provided, comprising: obtaining driving trajectory data of a plurality of vehicles passing through an intersection to be tested, wherein the plurality of vehicles have the same navigation planning path at the intersection to be tested, and the navigation planning path includes an entry section and an exit section of the intersection to be tested; based on the driving trajectory data, determining whether the traffic status of the intersection to be tested is abnormal; in response to determining that the traffic status of the intersection to be tested is abnormal, performing obstacle recognition on an image of the entry section; and based on a result of the obstacle recognition, determining whether the connection between the entry section and the exit section is disconnected.

[0007] According to one aspect of the present disclosure, a device for identifying road connection status is provided, comprising: a trajectory acquisition module configured to acquire driving trajectory data of multiple vehicles passing through a to-be-tested intersection, wherein the multiple vehicles have the same navigation planning path at the to-be-tested intersection, and the navigation planning path includes an entry section and an exit section of the to-be-tested intersection; a first judgment module configured to judge whether the traffic status of the to-be-tested intersection is abnormal based on the driving trajectory data; an image recognition module configured to perform obstacle recognition on an image of the entry section in response to determining that the traffic status of the to-be-tested intersection is abnormal; and a second judgment module configured to judge whether the connection between the entry section and the exit section is disconnected based on a result of the obstacle recognition.

[0008] According to one aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor, the memory storing instructions executable by the at least one processor, the instructions being executed by the at least one processor so that the at least one processor can execute the method.

[0009] According to one aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute the above method.

[0010] According to one aspect of the present disclosure, a computer program product is provided, comprising a computer program, which implements the above method when executed by a processor.

[0011] According to one or more embodiments of the present disclosure, the road connection status at an intersection can be automatically, efficiently and accurately identified, thereby improving the accuracy of navigation planning paths and enhancing the user's navigation experience.

[0012] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings illustrate exemplary embodiments and constitute a part of the specification. Together with the description of the specification, they serve to explain exemplary implementation of the embodiments. The illustrated embodiments are for illustrative purposes only and do not limit the scope of the claims. Throughout the drawings, the same reference numerals designate similar, but not necessarily identical, elements.

[0014] Figure 1 A schematic diagram illustrating an exemplary system in which the various methods described herein may be implemented according to an embodiment of the present disclosure;

[0015] Figure 2 A flowchart illustrating a method for identifying a road connection state according to an embodiment of the present disclosure is shown;

[0016] Figure 3 A structural block diagram of a device for identifying a road connection state according to an embodiment of the present disclosure is shown; and

[0017] Figure 4 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0018] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0019] In this disclosure, unless otherwise specified, the use of terms such as "first" and "second" to describe various elements is 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, while in some cases, based on the context of the description, they may also refer to different instances.

[0020] The terms used in the descriptions of the various examples described in this disclosure are for the purpose of describing specific examples only 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 this disclosure encompasses any one and all possible combinations of the listed items.

[0021] In this disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0022] Driving is a primary mode of transportation. During a self-driving trip, users can use devices equipped with electronic map applications (such as mobile phones, tablets, and in-car navigation devices) for route navigation. Based on the user's input of starting and ending locations, the electronic map application will generate a navigation route for the user. The user can then drive along the route to their destination.

[0023] An intersection is a place where multiple roads meet. It can be of various types (e.g., bifurcations, merging intersections, T-junctions, crossroads, roundabouts, etc.) and varying degrees of complexity. Each intersection has at least one entry and at least one exit. Users can enter the intersection from the entry and exit from the exit.

[0024] In reality, road connectivity changes rapidly, and the connectivity between the entrance and exit sections of an intersection may change. For example, at intersection A, entrance section B and exit section C were originally connected. Users could enter intersection A from entrance section B and continue from intersection A to exit section C (i.e., exit intersection A from exit section C). However, at some point in time, obstacles such as prohibitory markings or medians may be added between entrance section B and exit section C, causing the connection between entrance section B and exit section C to become disconnected. After entering intersection A from entrance section B, users are unable to continue to exit section C, i.e., they are unable to exit from exit section C.

[0025] Accurately describing the connectivity between entry and exit sections at an intersection is a prerequisite for accurate navigation route planning. Therefore, it is necessary to promptly identify changes in road connectivity at intersections and update these changes to the electronic map. If changes in road connectivity at intersections are not promptly identified and updated to the electronic map, the user's navigation route may be incorrect, making it impossible to navigate. For example, in the above example, if the disconnection between entry section B and exit section C is not promptly identified and updated to the electronic map, route navigation based on the original electronic map may still plan a navigation route from section B to section C. However, in reality, sections B and C are no longer connected. If the user follows this navigation route and, after entering section B, finds that they cannot continue to section C, they will be forced to take a detour or re-navigate, severely impacting the user's navigation experience.

[0026] In related technologies, manual methods such as road test data collection and user feedback are often used to identify the road connection status at intersections. This method is labor-intensive, time-consuming, and inefficient. In other related technologies, a collection vehicle can also be used to capture images of intersections. The collected images are then matched to an intersection in the road network topology based on the vehicle's GPS positioning information, and image recognition technology is used to determine the road connection status of the intersection. In this method, due to equipment errors, GPS positioning errors, and other factors, it is often impossible to correctly match the image with the intersection in the road network, resulting in low accuracy in identifying the road connection status of the intersection.

[0027] To this end, an embodiment of the present disclosure provides a method for identifying a road connection status, which can automatically, efficiently and accurately identify the road connection status at an intersection.

[0028] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0029] Figure 1 FIG2 is a schematic diagram of an exemplary system 100 in which the various methods and apparatuses described herein may be implemented according to an embodiment of the present disclosure. 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 coupling 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.

[0030] In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable the method of identifying the road connection status to be performed.

[0031] In some embodiments, server 120 may also provide other services or software applications that may include non-virtualized environments and virtualized environments. In some embodiments, these services may be provided as web-based services or cloud services, such as provided to users of client devices 101, 102, 103, 104, 105, and / or 106 under a software as a service (SaaS) model.

[0032] exist Figure 1 In the configuration shown, the server 120 may include one or more components that implement the functions performed by the server 120. These components may include software components, hardware components, or a combination thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 may, 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 a variety of different system configurations are possible, which may differ from the system 100. Therefore, Figure 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

[0033] The user can use client devices 101, 102, 103, 104, 105 and / or 106 to navigate. The client device can provide an interface that enables the user of the client device to interact with the client device. The client device can also output information to the user via the interface. Figure 1Only six client devices are depicted, but one skilled in the art will appreciate that the present disclosure can support any number of client devices.

[0034] Client devices 101, 102, 103, 104, 105, and / or 106 may include various types of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptops), 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 computer 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 Windows Mobile OS, iOS, Windows Phone, and Android. Portable handheld devices may include cellular phones, smartphones, tablet computers, 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. Client devices are capable of executing a variety of different applications, such as various internet-related applications, communication applications (such as email applications), and short message service (SMS) applications, and may use various communication protocols.

[0035] The network 110 may be any type of network known to those skilled in the art that can support data communications using any of a variety of available protocols, including but not limited to TCP / IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a local area network (LAN), an Ethernet-based network, a token ring, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, Wi-Fi), and / or any combination of these and / or other networks.

[0036] Server 120 may include one or more general-purpose computers, specialized server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range 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 virtual operating systems, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain a server's virtual storage device). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0037] The computing units in the server 120 may run one or more operating systems including any of the operating systems described above as well as any commercially available server operating systems. The server 120 may also run any of a variety of additional server applications and / or middle-tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, and the like.

[0038] In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display the data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0039] In some embodiments, server 120 may be a distributed system server or a server integrated with blockchain. Server 120 may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host equipped with artificial intelligence technology. A cloud server is a host product within the cloud computing service system that addresses the management difficulties and poor scalability of traditional physical hosts and virtual private servers (VPS) services.

[0040] The system 100 may also include one or more databases 130. In some embodiments, these databases may be used to store data and other information. For example, one or more of the databases 130 may be used to store information such as music files. The databases 130 may reside in a variety of locations. For example, the database used by the server 120 may be local to the server 120, or may be remote from the server 120 and communicate with the server 120 via a network-based or dedicated connection. The databases 130 may be of different types. In some embodiments, the databases used by the server 120 may be, for example, relational databases. One or more of these databases may store, update, and retrieve data to and from the databases in response to commands.

[0041] In some embodiments, one or more of the databases 130 may also be used by applications to store application data. The databases used by the applications may be different types of databases, such as a key-value store, an object store, or a conventional store backed by a file system.

[0042] Figure 1 The system 100 may be configured and operated in various ways to enable application of the various methods and apparatuses described in accordance with the present disclosure.

[0043] For the purpose of the embodiments of this disclosure, Figure 1 In the example, client devices 101, 102, 103, 104, 105, and 106 may include an electronic map application that can provide various electronic map-based functions, such as online navigation, offline route planning, and location search. Accordingly, server 120 may be the server corresponding to the electronic map application. Server 120 may include a service program that can provide map services to the electronic map application running on the client device based on the electronic map data stored in database 130. Alternatively, server 120 may provide the electronic map data to the client device, and the electronic map application running on the client device may provide map services based on the locally stored electronic map data.

[0044] Specifically, the server 120 or the client devices 101, 102, 103, 104, 105 and 106 can execute the road connection status identification method of the embodiment of the present disclosure, update the road connection status of each intersection in the electronic map data, make the electronic map data more accurate, thereby improving the accuracy of the navigation planning path and enhancing the user's navigation experience.

[0045] Figure 2 A flow chart of a method 200 for identifying a road connection state according to an embodiment of the present disclosure is shown. The method 200 may be executed on a server (e.g. Figure 1 120 ) and may also be executed on a client device (e.g. Figure 1 The execution of each step of the method 200 may be performed at the client devices 101, 102, 103, 104, 105 and 106 shown in FIG. Figure 1 The server 120 shown in FIG. 1 may also be Figure 1 Client devices 101, 102, 103, 104, 105 and 106 are shown in FIG.

[0046] like Figure 2 As shown, the method 200 includes:

[0047] Step 210: Acquire driving trajectory data of multiple vehicles passing through the intersection to be tested, wherein the multiple vehicles have the same navigation planned path at the intersection to be tested, and the navigation planned path includes an entry section and an exit section of the intersection to be tested;

[0048] Step 220: Based on the driving trajectory data, determine whether the traffic state of the intersection to be tested is abnormal;

[0049] Step 230: In response to determining that the traffic state of the intersection to be tested is abnormal, performing obstacle recognition on the image of the incoming road section; and

[0050] Step 240: Based on the result of obstacle recognition, determine whether the connection between the entry section and the exit section is disconnected.

[0051] According to the embodiments of the present disclosure, it is possible to obtain the driving trajectory data of the intersection to be tested, and based on the driving trajectory data, determine whether the traffic status of the intersection to be tested is abnormal. The connection between the entrance section and the exit section of the intersection to be tested with an abnormal traffic status is likely to be in a disconnected state. After determining that the traffic status of the intersection to be tested is abnormal, the image of the entrance section is used to further verify the road connection status of the intersection to be tested, thereby determining whether the road connection of the intersection to be tested is indeed in a disconnected state. The embodiments of the present disclosure can accurately and efficiently determine whether the connection between the entrance section and the exit section of the intersection is disconnected, and realize timely and automatic identification of the road connection status of the intersection, so that the electronic map is consistent with the actual road conditions and is more accurate, thereby improving the accuracy of the navigation planning path and enhancing the user's navigation experience.

[0052] The various steps of method 200 are described in detail below.

[0053] In step 210, the driving trajectory data of multiple vehicles passing through the intersection to be tested are obtained, and the navigation planning paths of the multiple vehicles at the intersection to be tested are the same, and the navigation planning paths include an entry section and an exit section of the intersection to be tested.

[0054] According to some embodiments, the intersection to be tested may be any intersection in the road network topology.

[0055] In a road network topology, each road consists of a series of ordered nodes, with any two adjacent nodes forming a link. Connectivity between two links can be determined by determining whether the end nodes of one link are identical to those of the other. For example, the two end nodes of link 1 are nodes A and B, while the two end nodes of link 2 are nodes C and D. If any of the end nodes of link 1 and link 2 are identical, for example, nodes B and C, link 1 and link 2 are connected. Conversely, if any of the end nodes of link 1 and link 2 are different, link 1 and link 2 are disconnected.

[0056] In addition, road sections have directionality (i.e., the direction of vehicles traveling on the section). By determining the direction of the same end nodes of two adjacent road sections, it is possible to determine whether the two sections are entry sections or exit sections. For example, in the example above, Node B and Node C are the same, and the direction of Section 1 is from Node A to Node B (i.e., on Section 1, the vehicle is traveling in the direction close to Node B), and the direction of Section 2 is from Node C to Node D (i.e., on Section 2, the vehicle is traveling in the direction away from Node C). In this case, Section 1 is an entry section, and Section 2 is an exit section. For another example, in the example above, Node B and Node C are the same, and the direction of Section 1 is from Node A to Node B (i.e., on Section 1, the vehicle is traveling in the direction close to Node B), and the direction of Section 2 is from Node D to Node C (i.e., on Section 2, the vehicle is traveling in the direction close to Node C). In this case, Section 1 and Section 2 are both entry sections.

[0057] In a road network topology, an intersection is the point where multiple road sections meet. Each intersection connects at least one entry section and at least one exit section. In an electronic map, each intersection is labeled as an intersection object, has a unique identifier, and corresponds to an area. It should be noted that each intersection object in an electronic map can be pre-identified using any intersection recognition algorithm, and this disclosure is not limited to the specific algorithm used to identify intersections in an electronic map.

[0058] According to the above embodiment, by using any intersection in the road network topology as the intersection to be tested in step 210 and identifying the road connection status at the intersection to be tested, the road connection status of all intersections in the road network topology can be updated.

[0059] According to other embodiments, the intersections included in the road network topology can be screened to remove those that do not require road status identification. The remaining intersections are then used as test intersections to identify their road connection status. This can avoid unnecessary calculations, thereby reducing the amount of calculation and improving calculation efficiency.

[0060] Specifically, according to some embodiments, road network topology and road network temporary blockage data can be obtained, wherein the road network topology includes multiple intersections, the road network temporary blockage data includes at least one temporary blockage area, and the temporary blockage area includes a road construction area and a roadblock isolation area; and multiple candidate intersections are determined from the above-mentioned multiple intersections, wherein the position of each candidate intersection does not overlap with the above-mentioned at least one temporary blockage area, and the intersection to be tested is any candidate intersection among the above-mentioned multiple candidate intersections.

[0061] Road construction and temporary roadblocks only temporarily change the road's accessibility (traffic will resume once construction is complete or the roadblock is removed), but do not alter the road's connectivity. According to the above embodiment, intersections located within temporarily blocked areas (including road construction areas and roadblock isolation areas) (referred to as "invalid intersections") can be filtered out, and only intersections outside of these areas (i.e., candidate intersections) are identified for road connectivity. This avoids unnecessary and meaningless calculations, reduces computational effort, and improves computational efficiency.

[0062] According to some embodiments, in addition to filtering invalid intersections in the road network topology, road sections in the road network topology can also be filtered to further reduce the amount of calculation and improve calculation efficiency. For example, the road network topology stores the attribute characteristics of each road section, such as road grade, road shape, the number of lanes in the road section, the location information of the road section, etc. Among them, the road grades from high to low include: expressways, national roads, provincial roads, county roads, township and village roads, ferry roads, pedestrian roads, etc. Road shapes include: main roads, overpasses, auxiliary roads, roundabouts, regional roads, ramps, bus lanes, etc. The embodiments of the present disclosure can filter the entry and exit sections of each intersection based on road grade and road shape, for example, filtering out sections with attributes such as ferry roads, pedestrian roads, regional roads, parking lots, gas stations, etc.

[0063] In step 210, the planned navigation path refers to the navigation path planned by the electronic map application based on the departure and destination specified by the user. It will be understood that the planned navigation path is a theoretically preferred driving path derived by the electronic map application according to a certain algorithm. The driving trajectory data represents the actual driving path of the vehicle. Due to differences in actual road conditions (e.g., changes in road connections, temporary traffic jams, changes in weather conditions, changes in traffic regulations, etc.), the vehicle may not strictly follow the planned navigation path; that is, the vehicle's driving trajectory data may differ from the planned navigation path.

[0064] It is understood that a planned navigation path typically includes multiple road sections and passes through multiple intersections. In step 210, "the navigation planned paths of multiple vehicles at the intersection to be tested are the same" does not mean that the navigation planned paths of the multiple vehicles are exactly the same, but rather that the navigation planned paths of the multiple vehicles are partially identical, and the identical portion is located at the intersection to be tested.

[0065] For example, vehicle 1's planned navigation path 1 is: Section A → Section B → Section C, while vehicle 2's planned navigation path 2 is: Section B → Section C → Section D. The intersection connecting Sections B and C is Intersection 1. For Intersection 1, Section B is the entry section, and Section C is the exit section. Although vehicle 1's planned navigation path 1 and vehicle 2's planned navigation path 2 are different, their planned navigation paths at Intersection 1 are the same: Section B → Section C.

[0066] The vehicle's driving trajectory data is collected by the vehicle's positioning module (e.g., GPS module). Driving trajectory data consists of multiple trajectory points arranged in chronological order. Due to positioning errors, coordinate system conversion errors, electronic map accuracy errors, and other factors, the trajectory points collected by the positioning module may deviate from the road location. For example, the vehicle may be traveling on Road Section 1, but the coordinates of the trajectory point collected by the positioning module are not located on Road Section 1, but rather in the green belt next to Road Section 1.

[0067] According to some embodiments, the trajectory points collected by the vehicle's positioning module can be matched with the road network topology, thereby correcting the trajectory points to the area where the road is located. Specifically, according to some embodiments, a trajectory point observation sequence can be obtained for each vehicle, the trajectory point observation sequence including the trajectory points of the vehicle at various time points; and the trajectory point observation sequence can be matched with the road network topology to determine the driving trajectory data corresponding to the trajectory point observation sequence, wherein the driving trajectory data includes multiple road points in the road network topology, and these multiple road points correspond to each trajectory point included in the trajectory point observation sequence. In this way, the accuracy of the driving trajectory data can be improved, thereby improving the accuracy of road connection status recognition.

[0068] According to some embodiments, a Hidden Markov Model (HMM) can be used to determine the driving trajectory data corresponding to a trajectory point observation sequence. Specifically, the trajectory point observation sequence 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 driving trajectory data corresponding to the trajectory point observation sequence.

[0069] In step 220 , based on the driving trajectory data, it is determined whether the traffic status of the intersection to be tested is abnormal.

[0070] According to some embodiments, step 220 further includes: extracting vehicle traffic characteristics of the intersection to be tested based on the driving trajectory data obtained in step 210; and determining that the traffic state of the intersection to be tested is abnormal in response to determining that the vehicle traffic characteristics meet preset abnormality judgment conditions.

[0071] If the entrance and exit sections of a test intersection are disconnected, the traffic conditions at the test intersection may be abnormal (e.g., a group of vehicles may deviate from their driving trajectories). Based on the above embodiment, by extracting vehicle traffic characteristics and comparing them with the abnormality judgment conditions, intersections suspected of having road disconnections can be quickly screened.

[0072] According to some embodiments, the vehicle traffic characteristics include at least one of the following: the number of trajectories entering from the entry section and exiting from the exit section (i.e., "traffic volume"), the number of trajectories entering from the entry section and directly exiting from the exit section, the number of trajectories entering from the entry section and then detouring to other sections and exiting from the exit section (i.e., "detour volume"), the number of trajectories entering from the entry section and not exiting from the exit section (i.e., "yaw volume"), the ratio of the number of trajectories entering from the entry section and exiting from the exit section to the number of trajectories entering from the entry section (i.e., "traffic entry ratio"), and the ratio of the number of trajectories entering from the entry section and exiting from the exit section to the number of trajectories exiting from the exit section (i.e., "traffic exit ratio").

[0073] Furthermore, the vehicle traffic characteristics may also include items obtained by calculating or combining the above items. For example, the vehicle traffic characteristics may also include the ratio of traffic volume to detour volume (i.e., "traffic detour ratio"), the average traffic volume, average detour volume, and average traffic detour ratio within a preset time period (e.g., the last three days, the last week, etc.), the ratio of the average traffic volume within the current time period (e.g., three days, a week, etc.) to the average traffic volume within the previous time period, the ratio of the average detour volume within the current time period (e.g., three days, a week, etc.) to the average detour volume within the previous time period, etc.

[0074] By extracting a variety of vehicle traffic features, the traffic status of the intersection can be fully and realistically expressed, thereby improving the accuracy of road connection status recognition.

[0075] According to some embodiments, the abnormality judgment condition may be a condition for judging whether the vehicle traffic characteristic is greater than or less than a preset threshold. Specifically, the abnormality judgment condition may be set by those skilled in the art in combination with actual application scenarios.

[0076] For example, at an intersection where the entry and exit sections are disconnected, the traffic volume typically decreases and the number of detours increases dramatically. Therefore, according to some embodiments, whether the traffic state of the intersection is abnormal, that is, whether the entry and exit sections of the intersection are suspected to be disconnected, can be determined by determining whether the traffic volume is less than a threshold and whether the number of detours is greater than a threshold.

[0077] For example, abnormality judgment conditions may include:

[0078] The average traffic volume in the current time period is less than the first threshold

[0079] The average detour amount in the current time period > the second threshold

[0080] Average detour volume in the current time period / Average detour volume in the same period > the third threshold

[0081] Average traffic volume in the current time period / average traffic volume in the same period < the fourth threshold

[0082] The average detour ratio in the current time period is less than the fifth threshold

[0083] The length of the current time period and the values ​​of the first threshold to the fifth threshold can be set by comprehensively considering various factors (such as the update frequency of the electronic map, holidays, city / road closure conditions, etc.).

[0084] When all the above five abnormality judgment conditions are met, it can be determined that the traffic state of the intersection to be tested is abnormal, that is, the connection between the entrance section and the exit section of the intersection to be tested may have been disconnected.

[0085] For another example, at an intersection where the entry and exit sections are disconnected, the traffic volume typically decreases and the yaw rate increases sharply. Therefore, according to some embodiments, whether the traffic state at the intersection is abnormal, i.e., whether there is a suspected disconnection between the entry and exit sections of the intersection, can be determined by determining whether the traffic volume is less than a threshold and whether the yaw rate is greater than a threshold.

[0086] In step 230 , in response to determining that the traffic state of the intersection to be tested is abnormal, obstacle recognition is performed on the image of the incoming road section.

[0087] In the embodiments of the present disclosure, an obstacle refers to any object that can cause a road connection to be disconnected, including but not limited to a separation strip (such as a guardrail), a separation column, a dividing line (solid line) drawn on the road surface to prohibit crossing the opposite lane, etc.

[0088] According to some embodiments, computer vision technology can be used to identify obstacles in images. For example, object detection models such as Faster R-CNN, YOLO V3, and SSD can be used to identify obstacles in images.

[0089] According to some embodiments, performing obstacle recognition on an image of an incoming road section includes: determining the area within which the incoming road section is located; acquiring multiple trajectory points within the area taken by an image acquisition vehicle within a preset time range, as well as multiple environmental images captured by the image acquisition vehicle at the multiple trajectory points; and performing obstacle recognition on the multiple environmental images. By performing obstacle recognition on environmental images corresponding to trajectory points within the area of ​​the incoming road section, the matching degree between the image and the incoming road section can be improved, thereby improving the accuracy of road connection status recognition.

[0090] Each trajectory point includes information such as location coordinates, travel direction, and acquisition time. According to some embodiments, step 230 may further include: determining at least one valid trajectory point from the plurality of trajectory points based on at least one of the trajectory point's travel direction, location within the aforementioned area, and acquisition time. Accordingly, obstacle recognition is performed on the environmental image corresponding to each of the at least one valid trajectory point to determine whether the connection between the entry and exit sections is disconnected. By screening valid trajectory points from the plurality of trajectory points and only performing obstacle recognition on the environmental images corresponding to the valid trajectory points, unnecessary calculations can be avoided, the amount of computation can be reduced, and recognition efficiency and accuracy can be improved.

[0091] According to some embodiments, the angular deviation between the trajectory point's travel direction angle1 and the vehicle's travel direction angle2 entering the road segment (i.e., |angle1-angle2|) can be calculated. Trajectory points with angular deviations less than a sixth threshold (i.e., |angle1-angle2| < sixth threshold) are considered valid trajectory points. This allows trajectory points with large errors to be removed, thereby improving the efficiency and accuracy of obstacle recognition.

[0092] According to some embodiments, the distance 'distance1' between a trajectory point and the first endpoint of an incoming road segment, as well as the distance 'distance2' between the trajectory point and the second endpoint of the incoming road segment, can be calculated. Trajectory points where 'distance1' exceeds the seventh threshold and 'distance2' exceeds the eighth threshold are considered valid trajectory points. Due to positioning errors and other factors, trajectory points closer to the endpoint of an incoming road segment may actually belong to other road segments. Based on this embodiment, trajectory points with large positioning errors can be removed, thereby improving the efficiency and accuracy of obstacle recognition.

[0093] According to some embodiments, the weight of a trajectory point can be determined based on its acquisition time, with the closer the acquisition time is to the current time, the greater the weight. Trajectory points with weights greater than a ninth threshold are considered valid trajectory points. This allows trajectory points that are far from the current time and therefore not meaningful for reference to be removed, thereby improving the efficiency and accuracy of obstacle recognition.

[0094] In step 240 , based on the result of the obstacle recognition, it is determined whether the connection between the entry section and the exit section is disconnected.

[0095] Specifically, if it is recognized that the image includes an obstacle (such as a median, a separator, a solid dividing line prohibiting crossing the opposite lane, etc.), it is determined that the connection between the entry section and the exit section is disconnected.

[0096] According to an embodiment of the present disclosure, a device for identifying a road connection status is also provided. Figure 3 FIG. 3 shows a structural block diagram of a road connection state recognition device 300 according to an embodiment of the present disclosure. Figure 3 As shown, the apparatus 300 includes:

[0097] The trajectory acquisition module 310 is configured to acquire driving trajectory data of a plurality of vehicles passing through a test intersection, wherein the plurality of vehicles have the same navigation planned path at the test intersection, and the navigation planned path includes an entry section and an exit section of the test intersection;

[0098] A first judgment module 320 is configured to judge whether the traffic state of the intersection to be tested is abnormal based on the driving trajectory data;

[0099] An image recognition module 330 is configured to perform obstacle recognition on the image of the incoming road section in response to determining that the traffic state of the intersection to be tested is abnormal; and

[0100] The second judgment module 340 is configured to judge whether the connection between the entry section and the exit section is disconnected based on the result of the obstacle recognition.

[0101] According to the embodiments of the present disclosure, it is possible to obtain the driving trajectory data of the intersection to be tested, and based on the driving trajectory data, determine whether the traffic status of the intersection to be tested is abnormal. The connection between the entrance section and the exit section of the intersection to be tested with an abnormal traffic status is likely to be in a disconnected state. After determining that the traffic status of the intersection to be tested is abnormal, the image of the entrance section is used to further verify the road connection status of the intersection to be tested, thereby determining whether the road connection of the intersection to be tested is indeed in a disconnected state. The embodiments of the present disclosure can accurately and efficiently determine whether the connection between the entrance section and the exit section of the intersection is disconnected, and realize timely and automatic identification of the road connection status of the intersection, so that the electronic map is consistent with the actual road conditions and is more accurate, thereby improving the accuracy of the navigation planning path and enhancing the user's navigation experience.

[0102] According to some embodiments, the device 300 also includes: a road network acquisition module, configured to acquire road network topology and road network temporary blockage data, wherein the road network topology includes multiple intersections, and the road network temporary blockage data includes at least one temporary blockage area, and the temporary blockage area includes a road construction area and a road barrier isolation area; and an intersection screening module, configured to determine multiple candidate intersections from the multiple intersections, wherein the position of each candidate intersection does not overlap with the at least one temporary blockage area, and the intersection to be tested is any candidate intersection among the multiple candidate intersections.

[0103] According to some embodiments, the trajectory acquisition module 310 includes: a first acquisition unit, configured to acquire a trajectory point observation sequence of each vehicle, the trajectory point observation sequence including the trajectory points of the vehicle at each time point; and a matching unit, configured to match the trajectory point observation sequence with the road network topology to determine the driving trajectory data corresponding to the trajectory point observation sequence, wherein the driving trajectory data includes multiple road points in the road network topology, and the multiple road points correspond to each trajectory point included in the trajectory point observation sequence.

[0104] According to some embodiments, the first judgment module 320 includes: an extraction unit, configured to extract the vehicle traffic characteristics of the intersection to be tested based on the driving trajectory data; a judgment unit, configured to determine that the traffic state of the intersection to be tested is abnormal in response to determining that the vehicle traffic characteristics meet the preset abnormal judgment conditions.

[0105] According to some embodiments, the vehicle traffic characteristics include at least one of the following: the number of trajectories entering from the entry section and exiting from the exit section, the number of trajectories entering from the entry section and directly exiting from the exit section, the number of trajectories entering from the entry section and then detouring to other sections and exiting from the exit section, the number of trajectories entering from the entry section and not exiting from the exit section, the ratio of the number of trajectories entering from the entry section and exiting from the exit section to the number of trajectories entering from the entry section, and the ratio of the number of trajectories entering from the entry section and exiting from the exit section to the number of trajectories exiting from the exit section.

[0106] According to some embodiments, the image recognition module 330 includes: a determination unit, configured to determine the area where the entry road section is located; a second acquisition unit, configured to acquire multiple trajectory points of the image acquisition vehicle located in the area within a preset time range, and multiple environmental images collected by the image acquisition vehicle at the multiple trajectory points; and an identification unit, configured to perform obstacle identification on the multiple environmental images.

[0107] According to some embodiments, the image recognition module 330 further includes: a screening unit configured to determine at least one valid trajectory point from the multiple trajectory points based on at least one of the trajectory point's direction of travel, its position in the area, and its acquisition time, and the recognition unit is further configured to perform obstacle recognition on the environmental image corresponding to each of the at least one valid trajectory point.

[0108] It should be understood that Figure 3 The modules or units of the apparatus 300 shown in FIG. 3 can be used in conjunction with the reference Figure 2 The steps in the method 200 described above correspond to each other. Therefore, the operations, features and advantages described above for the method 200 are also applicable to the apparatus 300 and the modules and units included therein. For the sake of brevity, some operations, features and advantages are not repeated here.

[0109] While specific functions are discussed above with reference to specific modules, it should be noted that the functions of the various modules discussed herein may be separated into multiple modules, and / or at least some functions of multiple modules may be combined into a single module. For example, the trajectory acquisition module 310 and the first determination module 320 described above may be combined into a single module in some embodiments.

[0110] It should also be understood that various techniques may be described herein in the general context of software hardware elements or program modules. Figure 3 The various modules described can be implemented in hardware or in hardware in combination with software and / or firmware. For example, these modules can be implemented as computer program code / instructions, which are configured to be executed in one or more processors and stored in a computer-readable storage medium. Alternatively, these modules can be implemented as hardware logic / circuits. For example, in some embodiments, one or more of modules 310-340 can be implemented together in a system on chip (SoC). SoC can include an integrated circuit chip (which includes a processor (e.g., a central processing unit (CPU), a microcontroller, a microprocessor, a digital signal processor (DSP), etc.), a memory, one or more communication interfaces, and / or one or more components in other circuits), and can optionally execute the received program code and / or include embedded firmware to perform functions.

[0111] According to an embodiment of the present disclosure, an electronic device, a readable storage medium, and a computer program product are also provided.

[0112] refer to Figure 4, a block diagram of an electronic device 400 that can serve as a server or client of the present disclosure will now be described, which 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 processing, 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 required herein.

[0113] like Figure 4 As shown, electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. Various programs and data required for the operation of device 400 can also be stored in RAM 403. Computing unit 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0114] Multiple components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, an output unit 407, a storage unit 408, and a communication unit 409. The input unit 406 can be any type of device that can input information to the device 400. The input unit 406 can receive input digital or character information, and generate key signal input related to user settings and / or function control of the electronic device, and can include but is not limited to a mouse, a keyboard, a touch screen, a trackpad, a trackball, a joystick, a microphone and / or a remote control. The output unit 407 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator and / or a printer. The storage unit 408 can include but is not limited to a magnetic disk, an optical disk. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver and / or a chipset, such as Bluetooth TM devices, 802.11 devices, Wi-Fi devices, WiMAX devices, cellular communication devices, and / or the like.

[0115] The computing unit 401 can be a variety of general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of the computing unit 401 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 that run machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as method 200. For example, in some embodiments, the method 200 can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method 200 described above can be performed. Alternatively, in other embodiments, the computing unit 401 can be configured to perform the method 200 in any other appropriate manner (e.g., by means of firmware).

[0116] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (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 interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] The program code for implementing the method 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, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0118] 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 conjunction with an instruction execution system, device or equipment. 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, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types 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, voice input, or tactile input).

[0120] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0121] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0122] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed 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. This is not limited herein.

[0123] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned 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 limited by the claims after authorization and their equivalents. Various elements in the embodiments or examples may be omitted or replaced by their equivalents. In addition, the steps may be performed in an order different from that described in this disclosure. Further, the various elements in the embodiments or examples may be combined in various ways. It is important that as technology evolves, many of the elements described herein may be replaced by equivalent elements that appear after this disclosure.

Claims

1. A method for identifying a road connection state at an intersection, comprising: Acquire a road network topology and road network temporary blockage data, wherein the road network topology includes multiple intersections, and the road network temporary blockage data includes at least one temporary blockage area, and the temporary blockage area includes a road construction area and a roadblock isolation area; Determining a plurality of candidate intersections from the plurality of intersections, wherein a location of each candidate intersection does not overlap with the at least one temporarily blocked area; Based on the road grade and road morphology, filtering the entry and exit sections of any candidate intersection among the plurality of candidate intersections, wherein the filtering includes removing sections with at least one of the attributes of a ferry road, a pedestrian road, an intra-regional road, a parking lot, and a gas station; Taking any candidate intersection among the multiple candidate intersections as the intersection to be tested; Acquiring driving trajectory data of a plurality of vehicles passing through the intersection to be tested, wherein the plurality of vehicles have the same navigation planned path at the intersection to be tested, and the navigation planned path includes an entry section and an exit section of the intersection to be tested; Based on the driving trajectory data, determining whether the traffic state of the intersection to be tested is abnormal; In response to determining that the traffic state of the intersection to be tested is abnormal, performing obstacle recognition on the image of the incoming road section includes: determining the area where the entry road section is located; Acquiring a plurality of trajectory points of an image acquisition vehicle located within the area within a preset time range, and a plurality of environment images acquired by the image acquisition vehicle at the plurality of trajectory points; Determining at least one valid trajectory point from the plurality of trajectory points based on at least one of a traveling direction of the trajectory point, a position in the area, and a collection time, including: calculating an angular deviation between the traveling direction of the trajectory point and the traveling direction of the vehicle entering the road segment, and selecting a trajectory point whose angular deviation is less than a sixth threshold as a valid trajectory point; calculating a first distance from the trajectory point to a first endpoint of the entering road segment and a second distance from the trajectory point to a second endpoint of the entering road segment, and selecting a trajectory point whose first distance is greater than a seventh threshold and whose second distance is greater than an eighth threshold as a valid trajectory point; or determining a weight of the trajectory point based on the collection time of the trajectory point, and selecting a trajectory point whose weight is greater than a ninth threshold as a valid trajectory point, wherein the weight is negatively correlated with a difference between a current time and the collection time; and Performing obstacle recognition on the environment image corresponding to each of the at least one valid trajectory points; and Based on the result of the obstacle recognition, it is determined whether the connection between the entry section and the exit section is disconnected.

2. The method according to claim 1, wherein The obtaining of the driving trajectory data of a plurality of vehicles passing through the intersection to be tested comprises: Acquire a trajectory point observation sequence for each vehicle, the trajectory point observation sequence including the trajectory points of the vehicle at each time point; and The trajectory point observation sequence is matched with a road network topology to determine driving trajectory data corresponding to the trajectory point observation sequence, wherein the driving trajectory data includes a plurality of road points in the road network topology, and the plurality of road points correspond to each trajectory point included in the trajectory point observation sequence.

3. The method according to claim 1 or 2, wherein: The determining, based on the driving trajectory data, whether the traffic state of the intersection to be tested is abnormal includes: Extracting vehicle traffic characteristics of the intersection to be tested based on the driving trajectory data; In response to determining that the vehicle traffic characteristics meet a preset abnormality judgment condition, it is determined that the traffic state of the intersection to be tested is abnormal.

4. The method according to claim 3, wherein: The vehicle traffic characteristics include at least one of the following: The number of trajectories that enter from the entry section and exit from the exit section, the number of trajectories that enter from the entry section and directly exit from the exit section, the number of trajectories that enter from the entry section and then detour to other sections and exit from the exit section, the number of trajectories that enter from the entry section and do not exit from the exit section, the ratio of the number of trajectories that enter from the entry section and exit from the exit section to the number of trajectories that enter from the entry section, and the ratio of the number of trajectories that enter from the entry section and exit from the exit section to the number of trajectories that exit from the exit section.

5. A device for identifying a road connection status at an intersection, comprising: a road network acquisition module configured to acquire a road network topology and road network temporary blockage data, wherein the road network topology includes a plurality of intersections, and the road network temporary blockage data includes at least one temporary blockage area, wherein the temporary blockage area includes a road construction area and a roadblock isolation area; an intersection screening module, configured to determine a plurality of candidate intersections from the plurality of intersections, wherein a position of each candidate intersection does not overlap with the at least one temporary blocking area; a road segment screening module configured to filter the entry and exit road segments of any candidate intersection among the plurality of candidate intersections based on the road grade and the road morphology, wherein the filtering includes removing road segments having at least one of the attributes of a ferry road, a pedestrian road, an intra-regional road, a parking lot, and a gas station; a determination module configured to select any candidate intersection among the plurality of candidate intersections as an intersection to be tested; a trajectory acquisition module configured to acquire driving trajectory data of a plurality of vehicles passing through the intersection to be tested, wherein the plurality of vehicles have the same navigation planned path at the intersection to be tested, and the navigation planned path includes an entry section and an exit section of the intersection to be tested; A first judgment module is configured to judge whether the traffic state of the intersection to be tested is abnormal based on the driving trajectory data; The image recognition module is configured to perform obstacle recognition on the image of the entrance section in response to determining that the traffic state of the intersection to be tested is abnormal, including: determining the area where the entry road section is located; Acquiring a plurality of trajectory points of an image acquisition vehicle located within the area within a preset time range, and a plurality of environment images acquired by the image acquisition vehicle at the plurality of trajectory points; Determining at least one valid trajectory point from the plurality of trajectory points based on at least one of a traveling direction of the trajectory point, a position in the area, and a collection time, including: calculating an angular deviation between the traveling direction of the trajectory point and the traveling direction of the vehicle entering the road segment, and selecting a trajectory point whose angular deviation is less than a sixth threshold as a valid trajectory point; calculating a first distance from the trajectory point to a first endpoint of the entering road segment and a second distance from the trajectory point to a second endpoint of the entering road segment, and selecting a trajectory point whose first distance is greater than a seventh threshold and whose second distance is greater than an eighth threshold as a valid trajectory point; or determining a weight of the trajectory point based on the collection time of the trajectory point, and selecting a trajectory point whose weight is greater than a ninth threshold as a valid trajectory point, wherein the weight is negatively correlated with a difference between a current time and the collection time; and Performing obstacle recognition on the environment image corresponding to each of the at least one valid trajectory points; and The second judgment module is configured to judge whether the connection between the entry section and the exit section is disconnected based on the result of the obstacle recognition.

6. The device according to claim 5, wherein The trajectory acquisition module includes: A first acquiring unit is configured to acquire a trajectory point observation sequence of each vehicle, wherein the trajectory point observation sequence includes the trajectory points of the vehicle at each time point; and A matching unit is configured to match the trajectory point observation sequence with a road network topology to determine driving trajectory data corresponding to the trajectory point observation sequence, wherein the driving trajectory data includes a plurality of road points in the road network topology, and the plurality of road points correspond to each trajectory point included in the trajectory point observation sequence.

7. The device according to claim 5 or 6, wherein: The first judgment module includes: an extraction unit configured to extract vehicle traffic characteristics of the intersection to be tested based on the driving trajectory data; The judgment unit is configured to determine that the traffic state of the intersection to be tested is abnormal in response to determining that the vehicle traffic characteristics meet a preset abnormality judgment condition.

8. The device according to claim 7, wherein The vehicle traffic characteristics include at least one of the following: The number of trajectories that enter from the entry section and exit from the exit section, the number of trajectories that enter from the entry section and directly exit from the exit section, the number of trajectories that enter from the entry section and then detour to other sections and exit from the exit section, the number of trajectories that enter from the entry section and do not exit from the exit section, the ratio of the number of trajectories that enter from the entry section and exit from the exit section to the number of trajectories that enter from the entry section, and the ratio of the number of trajectories that enter from the entry section and exit from the exit section to the number of trajectories that exit from the exit section.

9. An electronic device comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; in The memory stores instructions that can be executed 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 perform the method according to any one of claims 1 to 4.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 4.

11. A computer program product comprising a computer program, wherein When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

Images