CN114202924B

CN114202924B - Redundant traffic restriction information identification method and device, electronic equipment and medium

Info

Publication number: CN114202924B
Application number: CN202111535069.0A
Authority: CN
Inventors: 刘泳慷; 宗希鹏; 谷艳蕾; 钟智宇; 杨建忠; 夏德国; 卢振; 曹婷婷
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2021-12-15
Filing date: 2021-12-15
Publication date: 2024-01-09
Anticipated expiration: 2041-12-15
Also published as: CN114202924A

Abstract

The disclosure provides a redundant traffic restriction information identification method and device, electronic equipment and medium, relates to the technical field of computers, and particularly relates to the technical field of intelligent traffic and computer vision. The implementation scheme is as follows: acquiring driving track data of a plurality of vehicles passing through an intersection to be detected, wherein the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected; determining a traffic state parameter of the intersection to be detected based on the driving track data; identifying a traffic restriction object in an image of the entering road section in response to determining that the traffic state parameter meets a preset condition; and judging whether the traffic restriction information is redundant or not based on the result of the identification.

Description

Redundant traffic restriction information identification method and device, electronic equipment and medium

Technical Field

The disclosure relates to the technical field of computers, in particular to the technical field of intelligent traffic and computer vision, and specifically relates to a method and a device for identifying redundant traffic restriction information, electronic equipment, a computer readable storage medium and a computer program product.

Background

An electronic map (electronic map), i.e., a digital map, is a map that is stored and referred to digitally using computer technology. Various types of map elements are drawn on an electronic map, such as roads, malls, schools, hospitals, signage buildings, and the like.

Self-driving travel is the main mode of traffic travel. In the self-driving travel process, a user can use terminal equipment (such as a mobile phone, a tablet computer, a vehicle navigation device and the like) provided with an electronic map application to conduct route navigation. The electronic map application can plan a navigation path according to the departure place and the destination designated by the user and provide the navigation path for the user. The user can drive along the navigation path to smoothly reach the destination.

The approaches described in this section are not necessarily approaches that have been previously conceived or pursued. Unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, the problems mentioned in this section should not be considered as having been recognized in any prior art unless otherwise indicated.

Disclosure of Invention

The present disclosure provides a method and apparatus for identifying redundant traffic restriction information, an electronic device, a computer-readable storage medium, and a computer program product.

According to an aspect of the present disclosure, there is provided a method for identifying redundant traffic restriction information, including: acquiring driving track data of a plurality of vehicles passing through an intersection to be detected, wherein the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected; determining a traffic state parameter of the intersection to be detected based on the driving track data; identifying a traffic restriction object in an image of the entering road section in response to determining that the traffic state parameter meets a preset condition; and judging whether the traffic restriction information is redundant or not based on the result of the identification.

According to an aspect of the present disclosure, there is provided an identification apparatus of redundant traffic restriction information, including: the system comprises a track acquisition module, a traffic control module and a control module, wherein the track acquisition module is configured to acquire driving track data of a plurality of vehicles passing through an intersection to be detected, the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected; the determining module is configured to determine a traffic state parameter of the intersection to be detected based on the driving track data; an image recognition module configured to recognize a traffic restriction object in an image of the entering road section in response to determining that the traffic state parameter satisfies a preset condition; and a judging module configured to judge whether the traffic restriction information is redundant based on a result of the recognition.

According to an aspect of the present disclosure, there is provided an electronic apparatus including: at least one processor; and a memory communicatively coupled to the at least one processor, the memory storing instructions executable by the at least one processor to enable the at least one processor to perform the method.

According to an aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the above-described method.

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

According to one or more embodiments of the present disclosure, redundant traffic restriction information at an intersection can be automatically, efficiently and accurately identified, so that accuracy of an electronic map and a navigation planning path can be improved, and navigation experience of a user can be improved.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The accompanying drawings illustrate exemplary embodiments and, together with the description, serve to explain exemplary implementations of the embodiments. The illustrated embodiments are for exemplary purposes only and do not limit the scope of the claims. Throughout the drawings, identical reference numerals designate similar, but not necessarily identical, elements.

FIG. 1 illustrates a schematic diagram of an exemplary system in which various methods described herein may be implemented, in accordance with an embodiment of the present disclosure;

FIG. 2 illustrates a flow chart of a method of identifying redundant traffic restriction information according to an embodiment of the present disclosure;

FIG. 3 illustrates a block diagram of a redundant traffic restriction information identification device according to an embodiment of the present disclosure; and

fig. 4 illustrates a block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In the present disclosure, the use of the terms "first," "second," and the like to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of the elements, unless otherwise indicated, and such terms are merely used to distinguish one element from another. In some examples, a first element and a second element may refer to the same instance of the element, and in some cases, they may also refer to different instances based on the description of the context.

The terminology used in the description of the various illustrated examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise, the elements may be one or more if the number of the elements is not specifically limited. Furthermore, the term "and/or" as used in this disclosure encompasses any and all possible combinations of the listed items.

In the present disclosure, the processes of collecting, storing, using, processing, transmitting, providing, disclosing, etc. related personal information of a user all conform to the regulations of the related laws and regulations and do not violate the public welfare.

Self-driving travel is the main mode of traffic travel. In the self-driving travel process, a user can use terminal equipment (such as a mobile phone, a tablet computer, a vehicle navigation device and the like) provided with an electronic map application to conduct route navigation. The electronic map application can plan a navigation path according to the starting point position and the end point position input by the user and provide the navigation path for the user. The user can drive along the navigation path to smoothly reach the destination.

Traffic restrictions are specific regulations with grooming, prohibiting, limiting or indicating properties, such as prohibiting left-hand turns, prohibiting u-turns, prohibiting motor vehicle traffic, etc., formulated by traffic authorities for vehicles and pedestrians to pass on roads and other traffic related activities according to legal regulations. The traffic restriction may be represented specifically by a traffic restriction sign set up at an intersection, or by a road marking, a lane information indicator, or the like drawn on a road surface. When the electronic map is applied to navigation planning, the traffic restriction information of each intersection stored in the electronic map needs to be referred to so as to ensure that a user cannot pass illegally.

In reality, the road traffic condition changes rapidly, and the traffic limit at the intersection often changes. For example, an entrance section a and an exit section B are connected to the intersection 1. There is originally a traffic restriction (e.g., a warning sign of "no left turn") that prohibits left turn at the entry road segment a of the intersection 1, i.e., the left turn at the entry road segment a to enter the exit road segment B. At a later time, the above-described traffic restriction prohibiting the left turn is released, and thus the left turn is allowed at the entering section a to enter the exiting section B.

The accurate description of traffic restriction at the intersection is a precondition for accurately planning the navigation path. Therefore, it is necessary to identify redundant traffic restriction information at intersections in the electronic map in time and delete the redundant traffic restriction information. The redundant traffic restriction information refers to traffic restriction information that exists in the electronic map but does not exist in the actual road. Redundant traffic restriction information in electronic maps is typically generated due to traffic restriction cancellation at the actual intersection (in some cases, it may also be generated due to information entry errors or other causes). If redundant traffic restriction information is not recognized in time and deleted from the electronic map, the user may be forced to detour, severely affecting the user experience. For example, in the above example, after the traffic restriction at the intersection 1 is released, the user may directly turn left from the link a to enter the link B. However, if redundant traffic restriction information of "prohibited left turn" at the intersection 1 is not recognized and deleted from the electronic map in time, route navigation is performed according to the original electronic map (prohibited from entering the road B from the road a left turn at the intersection 1), a navigation planning path of the road a→the road c→the road d→the road B may be obtained, resulting in unnecessary detours by the user, wasting time and effort of the user, and reducing user experience.

In the related art, redundant traffic restriction information at a road junction is generally identified by manual means such as road test collection and user feedback. The method has the advantages of large workload, long time consumption and low efficiency. In other related art, redundant traffic restriction information is identified solely by track data of a vehicle. Because the traffic of each intersection in reality has larger difference, the low-traffic intersection is difficult to recall, and a large number of users are in illegal traffic, so that the identification accuracy of redundant traffic restriction information of the intersection is lower.

In other related technologies, an acquisition vehicle may be used to acquire an image of an intersection, the acquired image is matched to an intersection in a road network topology according to GPS positioning information of the acquisition vehicle, and an image recognition technology is used to determine whether redundant traffic restriction information exists at the intersection. In the method, due to equipment errors, GPS positioning errors and the like, images cannot be matched with intersections in the road network correctly, so that the identification accuracy of redundant traffic restriction information of the intersections is low.

For this reason, the embodiment of the present disclosure provides a method for identifying redundant traffic restriction information, which can automatically, efficiently and accurately identify redundant traffic restriction information at an intersection.

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

Fig. 1 illustrates a schematic diagram of an exemplary system 100 in which various methods and apparatus described herein may be implemented, in accordance with an embodiment of the present disclosure. Referring to fig. 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. Client devices 101, 102, 103, 104, 105, and 106 may be configured to execute one or more applications.

In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable the identification method of redundant traffic restriction information to be performed.

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

In the configuration shown in fig. 1, server 120 may include one or more components that implement the functions performed by server 120. These components may include software components, hardware components, or a combination thereof that are executable by one or more processors. A user operating client devices 101, 102, 103, 104, 105, and/or 106 may in turn utilize one or more client applications to interact with server 120 to utilize the services provided by these components. It should be appreciated that a variety of different system configurations are possible, which may differ from system 100. Accordingly, FIG. 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

The user may navigate using client devices 101, 102, 103, 104, 105, and/or 106. The client device may provide an interface that enables a user of the client device to interact with the client device. The client device may also output information to the user via the interface. Although fig. 1 depicts only six client devices, those skilled in the art will appreciate that the present disclosure may support any number of client devices.

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 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, and the like. 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 (e.g., GOOGLE Chrome OS); or include various mobile operating systems such as MICROSOFT Windows Mobile OS, iOS, windows Phone, android. Portable handheld devices may include cellular telephones, smart phones, tablet computers, personal Digital Assistants (PDAs), and the like. Wearable devices may include head mounted displays (such as smart glasses) and other devices. The gaming system may include various handheld gaming devices, internet-enabled gaming devices, and the like. The client device is capable of executing a variety of different applications, such as various Internet-related applications, communication applications (e.g., email applications), short Message Service (SMS) applications, and may use a variety of communication protocols.

Network 110 may be any type of network known to those skilled in the art that may support data communications using any of a number 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.

The server 120 may include one or more general purpose computers, special purpose server computers (e.g., PC (personal computer) servers, UNIX servers, mid-end servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and/or combination. The server 120 may include one or more virtual machines running a virtual operating system, or other computing architecture that involves virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain virtual storage devices of the server). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

The computing units in 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. 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, etc.

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 data feeds and/or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

In some implementations, the server 120 may be a server of a distributed system or a server that incorporates a blockchain. The server 120 may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. The cloud server is a host product in a cloud computing service system, so as to solve the defects of large management difficulty and weak service expansibility in the traditional physical host and virtual private server (VPS, virtual Private Server) service.

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. Database 130 may reside in various 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 may communicate with the server 120 via a network-based or dedicated connection. Database 130 may be of different types. In some embodiments, the database used by server 120 may be, for example, a relational database. One or more of these databases may store, update, and retrieve the databases and data from the databases in response to the commands.

In some embodiments, one or more of databases 130 may also be used by applications to store application data. The databases used by the application may be different types of databases, such as key value stores, object stores, or conventional stores supported by the file system.

The system 100 of fig. 1 may be configured and operated in various ways to enable application of the various methods and apparatus described in accordance with the present disclosure.

For purposes of embodiments of the present disclosure, in the example of fig. 1, client devices 101, 102, 103, 104, 105, and 106 may include an electronic map application therein that may provide various electronic map-based functions, such as online navigation, offline route planning, location finding, and the like. Accordingly, the server 120 may be a server corresponding to the electronic map application. The server 120 may include a service program therein that may provide map services to electronic map applications running in the client devices based on electronic map data stored in the database 130. Alternatively, the server 120 may also provide electronic map data to the client device, with the map service provided by an electronic map application running in the client device based on the locally stored electronic map data.

Specifically, the server 120 or the client devices 101, 102, 103, 104, 105 and 106 may execute the method for identifying redundant traffic restriction information according to the embodiments of the present disclosure, and delete the identified redundant traffic restriction information from the electronic map, so that the electronic map data is more accurate, thereby improving the accuracy of the navigation planning path and improving the navigation experience of the user.

Fig. 2 illustrates a flow chart of a method 200 of identifying redundant traffic restriction information in accordance with an embodiment of the present disclosure. The method 200 may be performed at a server (e.g., server 120 shown in fig. 1) or at a client device (e.g., client devices 101, 102, 103, 104, 105, and 106 shown in fig. 1). That is, the subject of execution of the steps of method 200 may be server 120 shown in FIG. 1, or client devices 101, 102, 103, 104, 105, and 106 shown in FIG. 1.

As shown in fig. 2, the method 200 includes:

step 210, acquiring driving track data of a plurality of vehicles passing through an intersection to be detected, wherein the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected;

220, determining traffic state parameters of the intersection to be detected based on the driving track data;

step 230, identifying a traffic limiting object in an image of the entering road section in response to determining that the traffic state parameter meets a preset condition; and

step 240, based on the result of the identification, it is determined whether the traffic restriction information is redundant.

According to the embodiment of the disclosure, the driving track data of the intersection to be detected can be obtained, and the traffic state parameters of the intersection to be detected are determined based on the driving track data. When the traffic state parameter of the intersection to be detected meets the preset condition, the traffic limit information of the intersection to be detected is considered to be possibly redundant. After the fact that the traffic restriction information of the intersection to be detected is possibly redundant is judged, the image of the entering road section is adopted to further verify the traffic restriction state of the intersection to be detected, so that whether the traffic restriction information of the intersection to be detected is truly redundant or not is judged. The method and the device can accurately and efficiently judge whether the redundant traffic restriction information exists at the intersection, and realize timely and automatic identification of the redundant traffic restriction information of the intersection, so that the electronic map is consistent with the actual road condition, the accuracy of the navigation planning path is improved, and the navigation experience of a user is improved.

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

In step 210, driving track data of a plurality of vehicles passing through the intersection to be detected is obtained, and the intersection to be detected is associated with traffic restriction information for restricting the passage from an entering road section to an exiting road section of the intersection to be detected.

According to some embodiments, the intersection to be tested may be any intersection with traffic restriction information in a road network topology.

In the road network topology, each road is composed of a series of ordered nodes, a road section (link) is formed between any two adjacent nodes, and whether two road sections are communicated can be judged by judging whether the end node of one road section is identical to the end node of the other road section. For example, the two end nodes of road segment 1 are: node a and node B; the two end nodes of road segment 2 are: node C and node D; if a certain end node of the road segment 1 and the road segment 2 is the same, for example, the node B and the node C are the same, it means that the road segment 1 and the road segment 2 are connected; conversely, if any one of the end nodes in segment 1 is different from any one of the end nodes in segment 2, it means that segment 1 and segment 2 are not connected.

In addition, the road segment has directivity (i.e., the traveling direction of the vehicle on the road segment). By determining the direction of the same end node of two adjacent road segments, it is possible to determine whether the two road segments are entering road segments or exiting road segments. For example, in the above example, where the node B and the node C are the same, the direction of the segment 1 is the direction from the node a to the node B (i.e., the vehicle travels in the direction approaching the node B on the segment 1), the direction of the segment 2 is the direction from the node C to the node D (i.e., the vehicle travels in the direction away from the node C on the segment 2), the segment 1 is the entering segment, and the segment 2 is the exiting segment. For another example, in the above example, the node B and the node C are the same, the direction of the link 1 is the direction from the node a to the node B (i.e., on the link 1, the vehicle travels in the direction approaching the node B), the direction of the link 2 is the direction from the node D to the node C (i.e., on the link 2, the vehicle travels in the direction approaching the node C), and both the link 1 and the link 2 are the entering links.

In road network topology, an intersection is a junction of multiple road segments. Each intersection is connected with at least one entering road segment and at least one exiting road segment. In the electronic map, each intersection is labeled as an intersection object, has a unique identification, and corresponds to an area range. It should be noted that, each intersection object in the electronic map may be identified in advance by any intersection identification algorithm, and the disclosure is not limited to a specific algorithm adopted to identify an intersection from the electronic map.

According to some embodiments, in the road network topology, each intersection association stores traffic restriction information indicating whether or not the corresponding intersection has traffic restriction, and a traffic direction (hereinafter referred to as "no-traffic direction") restricted by the traffic restriction. For example, traffic restriction information of the intersection 1 is used to prohibit traffic in the direction from the entering section a to the exiting section B.

In step 210, the travel track data is an actual travel path of the vehicle.

The travel track data of the vehicle is collected by a positioning module (e.g., a GPS module) in the vehicle. The travel track data includes a plurality of track points arranged in time series. Due to positioning errors, coordinate system conversion errors, electronic map precision errors and the like, the track points acquired by the positioning module may deviate from the positions of roads. For example, the vehicle travels in the road section a, but the coordinates of the trajectory points acquired by the positioning module are not located in the road section a but in the green belt beside the road section a.

According to some embodiments, the track points collected by the positioning module of the vehicle can be matched with the road network topology, so that the track points are corrected to the area where the road is located. Specifically, according to some embodiments, a track point observation sequence of each vehicle may be obtained, where the track point observation sequence includes track points of the vehicle at each time point; and matching the track point observation sequence with the road network topology to determine driving track data corresponding to the track point observation sequence, wherein the driving track data comprises a plurality of road points in the road network topology, and the plurality of road points respectively correspond to each track point included in the track point observation sequence. Therefore, the accuracy of the driving track data can be improved, and the accuracy of redundant traffic restriction information identification is improved.

According to some embodiments, a hidden Markov model (Hidden Markov Model, HMM) may be employed to determine travel trajectory data corresponding to a sequence of trajectory point observations. Specifically, the track point observation sequence is an observation sequence in the HMM, the driving track data is a hidden sequence in the HMM, and the viterbi algorithm can be adopted to solve the HMM so as to obtain a hidden sequence corresponding to the observation sequence, namely, the driving track data corresponding to the track point observation sequence is determined.

In step 220, traffic state parameters of the intersection to be tested are determined based on the driving trajectory data.

The traffic state parameter is used for indicating the trafficability of the intersection to be tested. According to some embodiments, the traffic state parameters include at least one of: the number of trajectories (i.e., "traffic volume") entering from the entering road section and exiting from the exiting road section, the number of trajectories directly exiting from the exiting road section after entering from the entering road section, the number of trajectories (i.e., "detour volume") detouring to other road sections and exiting from the exiting road section after entering from the entering road section, the ratio of the number of trajectories entering from the entering road section and exiting from the exiting road section to the number of trajectories entering from the entering road section (i.e., "traffic entry ratio"), the ratio of the number of trajectories entering from the entering road section and exiting from the exiting road section to the number of trajectories exiting from the exiting road section (i.e., "traffic exit ratio").

Further, the traffic state parameter may further include an item obtained by calculating or combining the above items. For example, the traffic state parameters may also include a ratio of traffic to detour (i.e., "detour ratio"), an average traffic over a preset time period (e.g., last 3 days, last week, etc.), an average detour amount, an average detour ratio, a ratio of an average traffic over a current time period (e.g., 3 days, a week, etc.) to an average traffic over a last time period, a ratio of an average detour over a current time period (e.g., 3 days, a week, etc.) to an average detour over a last time period, etc.

By extracting various traffic state parameters, the traffic state of the intersection can be comprehensively and truly expressed, so that the accuracy of identifying redundant traffic restriction information is improved.

Redundant traffic restriction information in an electronic map generally corresponds to traffic restriction release at an actual intersection, so that the trafficability of the original traffic-forbidden direction of the intersection is improved. Therefore, the intersection suspected of having redundant traffic restriction information can be rapidly screened out by calculating the traffic state parameters of the intersection to be detected and judging whether the trafficability of the intersection to be detected is improved based on the traffic state parameters.

According to some embodiments, whether the trafficability of the intersection to be tested is improved can be judged by judging whether the traffic state parameter of the intersection to be tested meets the preset condition. That is, the preset condition is used for judging whether the trafficability of the intersection to be tested is improved. Specifically, the preset conditions may be set by those skilled in the art in conjunction with the actual application scenario. The present disclosure is not limited to the number and content of preset conditions.

For example, for intersections where redundant traffic restriction information exists, the traffic volume will generally increase and the detour volume will decrease. Thus, according to some embodiments, whether the intersection has redundant traffic restriction information may be determined by determining the relative magnitudes of traffic state parameters, such as traffic volume, detour volume, and the like, and a threshold value.

For example, the preset conditions may include:

cumulative traffic over current time period > first threshold

Average traffic over current time period > second threshold

Average traffic in current time period/average traffic in cyclic ratio period > average traffic in current time period/historical average traffic in third threshold > fourth threshold

Average transit detour ratio over the current time period > fifth threshold

Average transit detour ratio in current time period > average transit detour ratio in cyclic ratio period

Average traffic detour ratio > history average traffic detour ratio ("> >" indicates much larger than the current time period)

The length of the current time period and the values of the first threshold-fifth threshold may be set by comprehensively considering various factors (e.g., update frequency of electronic map, holidays, city/road closure situation, etc.).

When all the seven preset conditions are met, the traffic restriction information redundancy of the intersection to be detected can be judged.

For another example, the traffic volume and the traffic exit ratio of an intersection where redundant traffic restriction information exists generally increase. Thus, according to other embodiments, whether the intersection has redundant traffic restriction information may be determined by determining the relative magnitudes of traffic state parameters such as traffic volume, traffic exit ratio, and the like, and a threshold value.

In step 230, in response to determining that the traffic state parameter meets a preset condition, i.e., in response to determining that the trafficability of the intersection to be tested is improved, traffic restriction objects in the image of the entering road segment are identified.

In embodiments of the present disclosure, traffic limiting objects refer to any object capable of functioning as traffic limiting, including, but not limited to, traffic limiting signs set up at intersections, road markings drawn on road surfaces (e.g., double solid lines for prohibiting crossing of opposing lanes, etc.), lane information indicators (e.g., right turn arrows, straight arrows, etc.), and the like.

According to some embodiments, computer vision techniques may be employed to identify traffic limiting objects in an image. For example, a target detection model such as Faster R-CNN, yolo V3, SSD, etc. may be employed to identify traffic-limiting objects in the image.

According to some embodiments, identifying traffic limiting objects in an image of an incoming road segment includes: determining the area where the entering road section is located; acquiring a plurality of track points of an image acquisition vehicle in the region within a preset time range, and acquiring a plurality of environment images at the plurality of track points by the image acquisition vehicle; and identifying traffic limiting objects in the plurality of environmental images. By carrying out traffic restriction object recognition on the environment image corresponding to the track point in the entering road section area, the matching degree of the image and the entering road section can be improved, and therefore the accuracy of redundant traffic restriction information recognition is improved.

Each track point comprises information such as position coordinates, running direction, acquisition time and the like. According to some embodiments, step 230 may further comprise: at least one effective track point is determined from the plurality of track points based on at least one of the traveling direction of the track point, the position in the area and the acquisition time. Accordingly, whether the traffic restriction information is redundant or not is judged by identifying the traffic restriction object in the environment image corresponding to each of the at least one effective track point. By screening the effective track points from the plurality of pairs of track points and only identifying the traffic limiting objects on the environment images corresponding to the effective track points, unnecessary calculation can be avoided, the calculated amount is reduced, and the identification efficiency and accuracy are improved.

According to some embodiments, an angular deviation of the traveling direction angle1 of the trajectory point from the vehicle traveling direction angle2 of the entering road section, i.e., |angl1-angl2|, may be calculated, and a trajectory point having an angular deviation smaller than a sixth threshold value (i.e., |angl1-angl2| < sixth threshold value) may be taken as the effective trajectory point. Therefore, the track points with larger errors can be removed, and the efficiency and accuracy of identifying the traffic limiting objects are improved.

According to some embodiments, a distance1 of the track point to a first end point of the incoming road segment and a distance2 of the track point to a second end point of the incoming road segment may be calculated. The locus points of distance1> the seventh threshold value and distance2> the eighth threshold value are taken as effective locus points. The track points closer to the end point of the entering road segment are likely to actually belong to other road segments due to positioning errors and the like. Based on the embodiment, the track points with larger positioning errors can be removed, so that the efficiency and accuracy of identifying the traffic limiting objects are improved.

According to some embodiments, the weights of the trajectory points may be determined based on the acquisition times of the trajectory points, the closer the acquisition time is to the current time, the greater the weights. And taking the track point with the weight greater than the ninth threshold value as an effective track point. Therefore, the track points which are far away from the current time and have no reference meaning can be removed, so that the efficiency and accuracy of identifying the traffic limiting objects are improved.

In step 240, it is determined whether the traffic restriction information of the intersection to be detected is redundant based on the result of the traffic restriction object identification.

Specifically, if it is recognized that no traffic restriction object consistent with the traffic restriction information in step 210 is included in the image, or that a traffic restriction object opposite to the traffic restriction information in step 210 is included in the image, it is determined that the traffic restriction information is redundant.

For example, the traffic restriction information in step 210 indicates that right turn on the entry road segment a is prohibited to enter the exit road segment B. Then, if a right turn prohibition flag (the right turn prohibition flag coincides with the meaning expressed by the traffic restriction information) is not recognized in the image of the entering road section a, or a right turn arrow (the meaning expressed by the right turn arrow is right turn permission, opposite to the meaning of right turn prohibition expressed by the traffic restriction information) within the lane is recognized in the image of the entering road section a, it is determined that the traffic restriction information is redundant, that is, the corresponding traffic restriction has been released.

According to an embodiment of the present disclosure, there is also provided an identification apparatus of redundant traffic restriction information. Fig. 3 shows a block diagram of a redundant traffic restriction information identification apparatus 300 according to an embodiment of the present disclosure. As shown in fig. 3, the apparatus 300 includes:

the track acquisition module 310 is configured to acquire driving track data of a plurality of vehicles passing through an intersection to be detected, wherein the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected;

a determining module 320, configured to determine, based on the driving track data, whether the traffic state of the intersection to be detected is abnormal;

An image recognition module 330 configured to recognize a traffic restriction object in an image of the entering road section in response to determining that the traffic state parameter satisfies a preset condition; and

a judging module 340 is configured to judge whether the traffic restriction information is redundant based on the result of the identification.

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

According to some embodiments, the traffic state parameter is used for indicating the trafficability of the intersection to be tested, and the preset condition is used for judging whether the trafficability of the intersection to be tested is improved.

According to some embodiments, the traffic state parameters include at least one of: the number of trajectories entering from the entering road section and exiting from the exiting road section, the number of trajectories exiting from the exiting road section directly after entering from the entering road section, the number of trajectories detouring to other road sections after entering from the entering road section and exiting from the exiting road section, the ratio of the number of trajectories entering from the entering road section and exiting from the exiting road section to the number of trajectories entering from the entering road section, the ratio of the number of trajectories entering from the entering road section and exiting from the exiting road section to the number of trajectories exiting from the exiting road section.

According to some embodiments, the image recognition module 330 includes: a determining unit configured to determine an area in which the entering road section is located; a second acquisition unit configured to acquire a plurality of track points of an image acquisition vehicle within the region within a preset time range, and a plurality of environmental images acquired by the image acquisition vehicle at the plurality of track points; and an identification unit configured to identify a traffic restriction object in the plurality of environment images.

According to some embodiments, the image recognition module 330 further comprises: and a screening unit configured to determine at least one effective track point from the plurality of track points based on at least one of the traveling direction of the track point, the position in the area and the acquisition time, and the identifying unit is further configured to identify traffic restriction objects in the environment images corresponding to the at least one effective track point.

It should be appreciated that the various modules or units of the apparatus 300 shown in fig. 3 may correspond to the various steps in the method 200 described with reference to fig. 2. Thus, the operations, features and advantages described above with respect to method 200 apply equally to apparatus 300 and the modules and units comprised thereof. For brevity, certain operations, features and advantages are not described in detail herein.

Although 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 divided into multiple modules and/or at least some of the functions of the multiple modules may be combined into a single module. For example, the trajectory acquisition module 310 and the determination module 320 described above may be combined into a single module in some embodiments.

It should also be appreciated that various techniques may be described herein in the general context of software hardware elements or program modules. The various modules described above with respect to fig. 3 may be implemented in hardware or in hardware in combination with software and/or firmware. For example, the modules may be implemented as computer program code/instructions configured to be executed in one or more processors and stored in a computer-readable storage medium. Alternatively, these modules may be implemented as hardware logic/circuitry. For example, in some embodiments, one or more of the modules 310-340 may be implemented together in a System on Chip (SoC). The SoC may include an integrated circuit chip including one or more components of a processor (e.g., a central processing unit (Central Processing Unit, CPU), microcontroller, microprocessor, digital signal processor (Digital Signal Processor, DSP), etc.), memory, one or more communication interfaces, and/or other circuitry, and may optionally execute received program code and/or include embedded firmware to perform functions.

According to embodiments of the present disclosure, there is also provided an electronic device, a readable storage medium and a computer program product.

Referring to fig. 4, a block diagram of an electronic device 400 that may be a server or a client of the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 4, the electronic device 400 includes a computing unit 401 that can perform various suitable 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. In RAM403, various programs and data required for the operation of device 400 may also be stored. The computing unit 401, ROM402, and RAM403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

Various components in electronic device 400 are connected to 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 may be any type of device capable of inputting information to the device 400, the input unit 406 may receive input numeric or character information and generate key signal inputs related to user settings and/or function control of the electronic device, and may 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 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. Storage unit 408 may include, but is not limited to, magnetic disks, optical disks. The communication unit 409 allows the device 400 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth ^TM Equipment, 802.11 equipment,Wi-Fi devices, wiMAX devices, cellular communication devices, and/or the like.

The computing unit 401 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 401 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized 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 401 performs the various methods and processes described above, such as method 200. For example, in some embodiments, the method 200 may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 400 via the ROM 402 and/or the communication unit 409. One or more of the steps of the method 200 described above may be performed when a computer program is loaded into RAM 403 and executed by computing unit 401. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the method 200 by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may 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 may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute 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.

In the context of this disclosure, a machine-readable medium may 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. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, 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.

To provide for interaction with a user, the systems and techniques described here 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 a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, 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: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.

Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it is to be understood that the foregoing methods, systems, and apparatus are merely exemplary embodiments or examples, and that the scope of the present invention is not limited by these embodiments or examples but only by the claims following the grant and their equivalents. Various elements of the embodiments or examples may be omitted or replaced with equivalent elements thereof. Furthermore, the steps may be performed in a different order than described in the present disclosure. Further, various elements of 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 the disclosure.

Claims

1. A method of identifying redundant traffic restriction information, comprising:

Acquiring driving track data of a plurality of vehicles passing through an intersection to be detected, wherein the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected;

determining a traffic state parameter of the intersection to be detected based on the driving track data;

identifying a traffic restriction object in the image of the entering road section in response to determining that the traffic state parameter meets a preset condition, wherein the traffic restriction object is an object playing a role in traffic restriction in the entering road section, and the identifying the traffic restriction object in the image of the entering road section comprises:

determining the area where the entering road section is located;

acquiring a plurality of track points of an image acquisition vehicle in a preset time range and a plurality of environment images acquired by the image acquisition vehicle at the track points; and

identifying traffic limiting objects in the plurality of environmental images; and

judging whether the traffic restriction information is redundant or not based on the identification result, wherein the judging whether the traffic restriction information is redundant or not based on the identification result comprises:

And determining that the traffic restriction information is redundant in response to either the plurality of environmental images not including traffic restriction objects consistent with the traffic restriction information or the plurality of environmental images not including traffic restriction objects opposite to the traffic restriction information.

2. The method of claim 1, wherein the acquiring travel track data for a plurality of vehicles passing through the intersection under test comprises:

acquiring a track point observation sequence of each vehicle, wherein the track point observation sequence comprises track points of the vehicle at each time point; and

and matching the track point observation sequence with a road network topology to determine driving track data corresponding to the track point observation sequence, wherein the driving track data comprises a plurality of road points in the road network topology, and the plurality of road points respectively correspond to each track point included in the track point observation sequence.

3. The method of claim 1, wherein the traffic state parameter is used to indicate the trafficability of the intersection to be tested, and the preset condition is used to determine whether the trafficability of the intersection to be tested is improved.

4. The method of claim 1, wherein the traffic state parameters include at least one of:

The number of trajectories entering from the entering road section and exiting from the exiting road section, the number of trajectories exiting from the exiting road section directly after entering from the entering road section, the number of trajectories detouring to other road sections after entering from the entering road section and exiting from the exiting road section, the ratio of the number of trajectories entering from the entering road section and exiting from the exiting road section to the number of trajectories entering from the entering road section, the ratio of the number of trajectories entering from the entering road section and exiting from the exiting road section to the number of trajectories exiting from the exiting road section.

5. The method of claim 1, further comprising:

determining at least one effective track point from the plurality of track points based on at least one of the traveling direction of the track points, the position in the area and the acquisition time,

wherein the identifying traffic limiting objects in the plurality of environmental images comprises: and identifying the traffic limiting objects in the environment images corresponding to the at least one effective track point respectively.

6. An identification device of redundant traffic restriction information, comprising:

the system comprises a track acquisition module, a traffic control module and a control module, wherein the track acquisition module is configured to acquire driving track data of a plurality of vehicles passing through an intersection to be detected, wherein the intersection to be detected is associated with traffic restriction information, and the traffic restriction information is used for restricting the traffic from an entering road section to an exiting road section of the intersection to be detected;

The determining module is configured to determine a traffic state parameter of the intersection to be detected based on the driving track data;

an image recognition module configured to recognize a traffic restriction object in an image of the entering road section in response to determining that the traffic state parameter satisfies a preset condition, wherein the traffic restriction object is an object that plays a role in traffic restriction in the entering road section, the image recognition module comprising:

a determining unit configured to determine an area in which the entering road section is located;

a second acquisition unit configured to acquire a plurality of track points of an image acquisition vehicle within the region within a preset time range, and a plurality of environmental images acquired by the image acquisition vehicle at the plurality of track points; and

an identification unit configured to identify a traffic restriction object in the plurality of environment images; and

a judging module configured to judge whether the traffic restriction information is redundant based on a result of the recognition, wherein the judging module is configured to:

7. The apparatus of claim 6, wherein the trajectory acquisition module comprises:

a first acquisition unit configured to acquire a track point observation sequence of each vehicle, the track point observation sequence including track points of the vehicle at each time point; and

the matching unit is configured to match the track point observation sequence with a road network topology so as to determine driving track data corresponding to the track point observation sequence, wherein the driving track data comprises a plurality of road points in the road network topology, and the plurality of road points respectively correspond to each track point included in the track point observation sequence.

8. The device of claim 6, wherein the traffic state parameter is used to indicate the trafficability of the intersection to be tested, and the preset condition is used to determine whether the trafficability of the intersection to be tested is improved.

9. The apparatus of claim 6, wherein the traffic state parameters comprise at least one of:

10. The apparatus of claim 6, wherein the image recognition module further comprises:

a screening unit configured to determine at least one effective track point from the plurality of track points based on at least one of a traveling direction of the track point, a position in the area, and an acquisition time,

the identification unit is further configured to identify traffic limitation objects in the environment image to which the at least one valid track point corresponds respectively.

11. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the method comprises the steps of

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

12. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1-5.