CN114615241A - Dynamic road network display method based on high-precision map and related equipment - Google Patents
Dynamic road network display method based on high-precision map and related equipment Download PDFInfo
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Abstract
The application relates to a dynamic road network display method based on a high-precision map and related equipment. The method comprises the following steps: receiving video stream data which are shot and uploaded by a plurality of road side devices in a road network, and receiving a data request uploaded by a web end; obtaining dynamic road network data of the road network according to a plurality of images in the video stream data; and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional manner by adopting a set algorithm. The scheme provided by the application can intuitively display the dynamic road network data of the road network on the high-precision map in real time.
Description
Technical Field
The application relates to the technical field of high-precision maps, in particular to a dynamic road network display method based on a high-precision map and related equipment.
Background
The dynamic road network can directly reflect urban/regional traffic conditions, is more vivid compared with a static road network, gives more accurate real-time traffic data to people, reflects traffic direction and speed intensity according to the real-time traffic data. However, the dynamic road network display of the related art is displayed in a two-dimensional manner on a map, and thus dynamic road network data cannot be updated in time, and changes of the dynamic road network cannot be intuitively displayed in real time.
Disclosure of Invention
In order to solve or partially solve the problems in the related art, the application provides a dynamic road network display method and related equipment based on a high-precision map, which can intuitively display dynamic road network data of a road network on the high-precision map in real time.
The application provides a dynamic road network display method based on a high-precision map in a first aspect, and the method comprises the following steps:
receiving video stream data which are shot and uploaded by a plurality of road side devices in a road network, and receiving a data request uploaded by a web end;
obtaining dynamic road network data of the road network according to a plurality of images in the video stream data;
and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional manner by adopting a set algorithm.
Preferably, the obtaining dynamic road network data of the road network according to a plurality of images in the video stream data includes:
extracting images in the video stream data according to a set time interval to obtain the plurality of images shot by each of the plurality of road side devices at the same time;
and carrying out YOLO algorithm recognition on the images by adopting a neural network model to obtain dynamic road network data of the road network, wherein the dynamic road network data of the road network comprises dynamic road network types, and the dynamic road network types comprise road construction points and traffic accident points.
Preferably, the dynamic road network data of the road network further includes location information, time information, and screenshot of the dynamic road network type;
the step of performing YOLO algorithm recognition on the plurality of images by using a neural network model to obtain dynamic road network data of the road network comprises the following steps:
carrying out YOLO algorithm identification on the multiple images by adopting a neural network model to obtain a dynamic road network type of the road network;
giving the dynamic road network type position information and the time information according to the position information of road side equipment for shooting images and the time information of the shot images;
taking the image of the identified dynamic road network type as a screenshot of the dynamic road network type;
and acquiring dynamic road network data of the road network, wherein the dynamic road network data comprises the dynamic road network type, position information of the dynamic road network type, time information and screenshot.
Preferably, the sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on a high-precision map, includes: issuing the dynamic road network data of the road network as HTTP service of WFS protocol;
and sending the dynamic road network data of the road network, which are issued as HTTP service of WFS protocol, to the web end according to the data request uploaded by the web end according to the set time interval, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional manner by adopting a set algorithm.
The second aspect of the present application provides a cloud server, comprising:
the receiving unit is used for receiving video stream data which are shot and uploaded by a plurality of road side devices in a road network and receiving data requests uploaded by a web end;
the processing unit is used for obtaining dynamic road network data of the road network according to a plurality of images in the video stream data received by the receiving unit;
and the sending unit is used for sending the dynamic road network data of the road network obtained by the processing unit to the web end according to the data request uploaded by the web end and received by the receiving unit, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional mode by adopting a set algorithm.
Preferably, the processing unit includes:
an extracting subunit, configured to extract, according to a set time interval, images in the video stream data received by the receiving unit, and obtain the multiple images captured by each of the multiple pieces of road side equipment at the same time;
and the identification subunit is used for performing the YOLO algorithm identification on the plurality of images obtained by the extraction subunit by adopting a neural network model to obtain dynamic road network data of the road network, wherein the dynamic road network data of the road network comprises dynamic road network types, and the dynamic road network types comprise road construction points and traffic accident points.
Preferably, the processing unit further comprises a publishing subunit;
the issuing subunit is configured to issue the obtained dynamic road network data of the road network as an HTTP service of a WFS protocol;
the receiving unit is further configured to receive a data request uploaded by the web end at a set time interval;
the sending unit is further configured to send the dynamic road network data of the road network of the HTTP service of the WFS protocol, which is obtained by the processing unit, to the web end according to the data request uploaded by the web end at the set time interval, which is received by the receiving unit, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map.
The third aspect of the application provides a dynamic road network display system based on a high-precision map, wherein the system comprises a plurality of road side devices, a cloud server and a web end;
the road side devices are used for being installed at the road sides of the roads in the road network, and shooting and uploading video stream data of the roads in the road network to the cloud server;
the cloud server is used for receiving video stream data which are shot and uploaded by each of the multiple road side devices, obtaining dynamic road network data of the road network according to multiple images in the video stream data, receiving a data request uploaded by the web end, and sending the dynamic road network data of the road network to the web end according to the received data request uploaded by the web end;
the web end is used for uploading a data request to the cloud server, receiving the dynamic road network data of the road network sent by the cloud server according to the data request, and displaying the dynamic road network data of the road network in a three-dimensional manner on a high-precision map by adopting a set algorithm.
Preferably, the web end is further configured to:
and if the dynamic road network type does not exist in the position corresponding to the position information of the dynamic road network type of the dynamic road network data of the web end and the high-precision map, taking the dynamic road network type as a point element, adopting a webgl rendering technology, calling a GPU, rendering the dynamic road network type to the high-precision map in a GLB model mode, and displaying the dynamic road network data of the road network in a three-dimensional mode.
A fourth aspect of the present application provides an electronic device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method as described above.
A fifth aspect of the present application provides a computer-readable storage medium having stored thereon executable code, which, when executed by a processor of an electronic device, causes the processor to perform a method as described above.
The technical scheme provided by the application can comprise the following beneficial effects:
according to the technical scheme, dynamic road network data of the road network can be automatically obtained according to the video stream data of the road network; and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map, and the dynamic road network data of the road network can be visually displayed on the high-precision map in real time.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
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The foregoing and other objects, features and advantages of the application will be apparent from the following more particular descriptions of exemplary embodiments of the application as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the application.
Fig. 1 is a schematic flow chart of a dynamic road network display method based on a high-precision map according to an embodiment of the present application;
fig. 2 is another schematic flow chart of a dynamic road network display method based on high-precision maps according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a cloud server according to an embodiment of the present application;
fig. 4 is another schematic structural diagram of the cloud server according to the embodiment of the present application;
fig. 5 is a schematic structural diagram of a high-precision map-based dynamic road network display system according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device shown in an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While embodiments of the present application are illustrated in the accompanying drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," "third," etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
The embodiment of the application provides a dynamic road network display method based on a high-precision map, which can intuitively display dynamic road network data of a road network on the high-precision map in real time.
The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.
The first embodiment is as follows:
fig. 1 is a schematic flow chart of a dynamic road network display method based on a high-precision map according to an embodiment of the present application.
Referring to fig. 1, a dynamic road network display method based on a high-precision map includes the steps of:
in step S101, video stream data captured and uploaded by a plurality of road side devices in a road network is received.
In one embodiment, a plurality of road side devices are installed on the road sides of the roads in the road network, each road side device comprises a camera, the cameras face the roads and shoot the roads in real time to obtain video stream data of the roads in the road network, and each road side device uploads the video stream data shot by the cameras to a cloud server. The cloud server receives video stream data uploaded by a plurality of road side devices in a road network.
In step S102, dynamic road network data of the road network is obtained from a plurality of images in the video stream data.
In one implementation mode, the cloud server extracts images in video stream data to obtain a plurality of images of each of the plurality of road side devices at the current moment, wherein the images are shot by each of the plurality of road side devices at the same time; carrying out YOLO algorithm identification on the extracted multiple images at the current moment by adopting a neural network model to obtain a dynamic road network type of a road network, wherein the dynamic road network type comprises road construction points and traffic accident points; and obtaining dynamic road network data of the road network according to the dynamic road network type of the road network, wherein the obtained dynamic road network data of the road network comprises time information, position information and screenshots of road construction points.
In step S103, a data request uploaded by the web end is received.
In one embodiment, a web-side uploads a data request to obtain dynamic road network data for a road network. And the cloud server receives a data request uploaded by the web terminal.
In step S104, according to the received data request uploaded by the web end, the dynamic road network data of the road network is sent to the web end, so that the web end can display the dynamic road network data of the road network in three dimensions on the high-precision map by using a set algorithm.
In one embodiment, the cloud server stores the obtained dynamic road network data of the road network in a set form; and the cloud server sends the dynamic road network data of the road network at the current moment to the web end according to the received data request uploaded by the web end. And the web end receives the dynamic road network data at the current moment sent by the cloud server, and three-dimensionally renders and three-dimensionally displays the dynamic road network data at the current moment of the road network on the high-precision map by adopting a set algorithm.
The dynamic road network display method based on the high-precision map can automatically obtain dynamic road network data of a road network according to video stream data of the road network; and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map, and the dynamic road network data of the road network can be visually displayed on the high-precision map in real time.
Example two:
fig. 2 is another schematic flow chart of a dynamic road network display method based on a high-precision map according to an embodiment of the present application. Fig. 2 describes the solution of the present application in more detail with respect to fig. 1.
Referring to fig. 2, a dynamic road network display method based on a high-precision map includes:
in step S201, video stream data captured and uploaded by a plurality of road side devices in a road network is received.
In one embodiment, a plurality of roadside devices are installed in a set manner on all roadsides in a road network, each roadside device including a camera, the camera facing the road. The method comprises the steps that a plurality of road side devices in a road network continuously shoot traffic of all roads in the road network in real time to obtain video stream data of the roads in the road network, and each road side device uploads the video stream data shot by a camera to a cloud server according to a set uploading frequency. The cloud server receives video stream data uploaded by a plurality of road side devices in a road network.
In step S202, images in the video stream data are extracted at set time intervals to obtain a plurality of images captured by each of the plurality of roadside devices at the same time.
In one embodiment, the cloud server performs image extraction on the video stream data uploaded by each of the multiple road side devices at set time intervals, for example, every 5 minutes, to obtain multiple images of the current time captured by each of the multiple road side devices at the same time.
In step S203, the multiple images are subjected to YOLO algorithm recognition using a neural network model, and a dynamic road network type of the road network is obtained.
In one embodiment, the cloud server performs YOLO algorithm recognition on the obtained multiple images at the current time by respectively using a neural network model to obtain a dynamic road network type at the current time in a road network, where the dynamic road network type includes a road construction point and a traffic accident point. The neural network model comprises a construction recognition algorithm model and a traffic accident recognition algorithm model, and the cloud server can perform YOLO algorithm recognition on the obtained multiple images at the current moment by adopting the construction recognition algorithm model to obtain road construction points in the road network at the current moment; the YOLO algorithm recognition can be carried out on the obtained multiple images at the current moment by adopting a traffic accident recognition algorithm model, and the traffic accident point at the current moment in the road network is obtained.
In step S204, the dynamic road network type position information and the time information are given based on the position information of the roadside device that captured the image and the time information of the captured image.
In one implementation mode, the cloud server calibrates the position information of each road side device on a high-precision map based on the longitude and latitude of each road side device in a plurality of road side devices in a road network; according to the position information of the road side equipment which shoots the image, the position information is correspondingly endowed to the road construction point and/or the traffic accident point which are identified according to the image shot by the road side equipment. And the cloud server gives time information of the road construction point and/or the traffic accident point according to the time information of the shot image and the time information of the identified image of the road construction point and/or the traffic accident point. And the cloud server identifies the shooting time of the images of the road construction points and/or the traffic accident points as the occurrence time of the road construction points and/or the traffic accident points.
In step S205, the image identifying the dynamic road network type is taken as a screenshot of the dynamic road network type.
In one embodiment, the cloud server takes the image of the identified road construction point and/or traffic accident point as a screenshot corresponding to the identified road construction point and/or traffic accident point.
In step S206, dynamic road network data of the road network including the dynamic road network type, the position information of the dynamic road network type, the time information, and the screen shot is obtained.
In one embodiment, the dynamic road network data of the road network obtained by the cloud server includes road construction points, position information of the road construction points, time information of the road construction points, screenshots of the road construction points, and traffic accident points, position information of the traffic accident points, time information of the traffic accident points, and screenshots of the traffic accident points.
In step S207, dynamic road network data of the road network is distributed as an HTTP service of the WFS protocol.
In one embodiment, the cloud server stores the dynamic road network data of the road network at the current time in a Postgis (an extension of the object-relational database system PostgreSQL) database, and issues the dynamic road network data of the road network at the current time as HTTP (Hyper Text Transfer Protocol) Service of WFS (Web Feature Service) Protocol by using a GeoServer map server for being called by a Web end.
In one embodiment, when the cloud server stores the dynamic road network data of the road network at the current time in the Postgis database, the cloud server performs state identification on the road construction points and/or traffic accident points which have occurred, performs state update on the road construction points and/or traffic accident points which have been stored in the Postgis database, and can update the time information of the road construction points and/or traffic accident points which have occurred, record the duration of the road construction points and/or traffic accident points which have occurred, and capture images corresponding to the road construction points and/or traffic accident points.
In an embodiment, the GeoServer map server may publish the map layer as a WFS service, which is implemented by a Java 2Platform Enterprise Edition (Java 2Platform Enterprise Edition) specified by an OpenGIS (Open Geodata interworking Specification) Web server, and may conveniently publish the map data by using the GeoServer map server, allowing the user to perform operations of updating, deleting and inserting the feature data, and quickly share the spatial geographic information among the users through the GeoServer map server. The WFS conforms to the WFS implementation specification set by the OGC (Open geographic information Consortium). The WFS transmits geospatial data through GML (geographic Markup Language), supports operations such as INSERT (INSERT), UPDATE (UPDATE), DELETE (DELETE) and Discover (DISCOVERY) on a distributed computing platform based on HTTP protocol, and ensures consistency of geographic data change in the process of the operations.
In step S208, a data request uploaded by the web end at a set time interval is received.
In one embodiment, the dynamic road network display engine on the web side sends HTTP service requests to the cloud server at set time intervals, for example, every 5 minutes. The cloud server receives HTTP service requests sent by the web end according to set time intervals.
In step S209, according to the data request uploaded by the web end at the set time interval, the dynamic road network data of the road network issued as the HTTP service of the WFS protocol is transmitted to the web end, so that the web end can three-dimensionally display the dynamic road network data of the road network on the high-precision map by using the set algorithm.
In one embodiment, the cloud server sends dynamic road network data of a road network at the current time, which is issued as an HTTP service of a WFS protocol, to the web side according to the received HTTP service request. The method comprises the steps that a web side obtains dynamic road network data of a road network at the current moment, which are sent by a cloud server; the Web-side dynamic road network display engine calls a Graphic Processing Unit (GPU) by using a webGL (Web Graphics Library, a 3-dimensional drawing protocol) technology, performs three-dimensional rendering on the dynamic road network data of the current road network on the high-precision map, and three-dimensionally displays the dynamic road network data of the current road network on the high-precision map.
In one embodiment, the dynamic road network display engine at the web end uses a dynamic road network type as a point element, and uses a webgl rendering technology to invoke a GPU to render the dynamic road network type to a high-precision map in a GLB (Graphics road Binary, a 3D model format) model form, so as to three-dimensionally display the dynamic road network data of the road network at the current time. A dynamic road network display engine at a web end searches a GLB model of the dynamic road network type according to the name of the dynamic road network type to obtain a GLB model of a point element of the dynamic road network type; and rendering the GLB model of the dynamic road network type to a high-precision map by taking the position information of the dynamic road network type at the corresponding position of the high-precision map as the position for placing the GLB model, wherein the azimuth angle is due north, and three-dimensionally displaying the dynamic road network data of the road network at the current moment on the high-precision map.
In one embodiment, the web-side dynamic road network display engine may close a road segment with a set length where a dynamic road network type is located, that is, display the road segment with the dynamic road network type in red, display a menu bar on the right side of a web-side page, display a dynamic road network type list of the dynamic road network in the menu bar, and position a map to a position where the dynamic road network type occurs in each piece of data when the data is selected by clicking with a mouse.
In one embodiment, if a high-precision map of the dynamic road network type in the dynamic road network data of the road network at the current time does not exist at the current time, which is acquired by the dynamic road network display engine at the web end, the dynamic road network type in the dynamic road network data of the road network at the current time is rendered to the high-precision map, the dynamic road network data of the road network at the current time is three-dimensionally displayed on the high-precision map, and a road section with a set length where the dynamic road network type is located is closed. If the dynamic road network type in the dynamic road network data of the road network at the current moment acquired by the dynamic road network display engine at the web end exists in the high-precision map of the current moment, it is determined that the dynamic road network type in the dynamic road network data of the road network at the current moment is not processed, the dynamic road network display engine at the web end can update the screenshot of the dynamic road network type on the high-precision map, update the duration of the dynamic road network type, and continue to close the road section with the set length where the dynamic road network type is located. And if the dynamic road network data of the high-precision map does not exist in the dynamic road network data of the road network at the current moment, determining that the occurred dynamic road network type is completely disposed at the current moment, removing the GLB model of the corresponding dynamic road network type from the high-precision map, unsealing the corresponding closed road section, namely changing the color of the corresponding closed road section into the color of the normal road.
In one embodiment, taking a dynamic road network type as a road construction point as an example, if a dynamic road network display engine at a web end judges that the road construction point is not displayed at a position on a high-precision map corresponding to position information of the road construction point according to dynamic road network data of a road network at the current moment and dynamic road network data of the road network displayed on the high-precision map, a GLB model of the road construction point is searched for by using the road construction point, and a GLB model of a point element of the road construction point is obtained; placing a GLB model at a position corresponding to the position information of the road construction point on the high-precision map, rendering the GLB model of the road construction point to the high-precision map with the azimuth angle being due north, and displaying the road construction point on the high-precision map in a three-dimensional manner; and closing the road section with the set length where the road construction point is located, and displaying the closed road section in red.
According to the dynamic road network data of the road network at the current moment and the dynamic road network data of the road network displayed on the high-precision map, if the dynamic road network display engine at the web end judges that the road construction point is displayed at the position corresponding to the position information of the road construction point on the high-precision map, the road construction point is determined not to be processed, the dynamic road network display engine at the web end can update the screenshot of the road construction point on the high-precision map, update the duration of the road construction point and continue to close the road section with the set length where the road construction point is located.
According to the dynamic road network data of the road network at the current moment and the dynamic road network data of the road network displayed on the high-precision map, if the dynamic road network display engine at the web end judges that the road construction point on the high-precision map does not exist in the dynamic road network data acquired at the current moment, the fact that the construction of the occurred road construction point is completed at the current moment is determined, namely the fact that the construction of the road construction point on the high-precision map is completed is determined, the GLB model of the corresponding road construction point is removed from the high-precision map, the corresponding closed road section is unsealed, and the color of the corresponding closed road section is changed into the color of a normal road.
The following two road side devices of one road in a road network: the technical scheme of the application is explained by taking the road side equipment A and the road side equipment B as examples.
The road side equipment A continuously obtains video stream data a 'of a road section a in real time and uploads the video stream data a' to a cloud server; the road side device B continuously obtains video stream data B 'of the road section B in real time and uploads the video stream data B' to the cloud server.
The cloud server continuously receives video stream data a 'uploaded by the roadside device A and video stream data B' uploaded by the roadside device B in real time, image extraction is respectively carried out on the video stream data a 'and the video stream data B', an image X in the video stream data a 'and an image Y in the video stream data B' are respectively obtained, and the shooting time of the image X and the shooting time of the image Y are the same time; and respectively using a construction recognition algorithm neural network model and a traffic accident algorithm neural network model to perform YOLO algorithm recognition on the image X and the image Y to obtain the dynamic road network type of the road network, wherein the dynamic road network type comprises a road construction point and a traffic accident point. Suppose that image X is identified to obtain road construction points of a road network, and image Y is identified to obtain traffic accident points of the road network.
The cloud server can calibrate the position information of the road side equipment A and the road side equipment B on the high-precision map according to the longitude and latitude of the road side equipment A and the road side equipment B; the identified road construction site is correspondingly given position information based on the position information of the roadside apparatus a, and the identified traffic accident site is correspondingly given position information based on the position information of the roadside apparatus B, and the position information can be expressed by latitude and longitude.
The cloud server can give time information to the road construction point according to the time for shooting the image X, the time for shooting the image X is used as the occurrence time of the road construction point, the time information can be given to the traffic accident point according to the time for shooting the image Y, and the time for shooting the image Y is used as the occurrence time of the traffic accident point.
The cloud server can take the image X as a screenshot of a road construction point and can take the image Y as a screenshot of a traffic accident point.
The dynamic road network data of the road network obtained by the cloud server comprises road construction points, position information of the road construction points, time information of the road construction points, screenshots of the road construction points, position information of traffic accident points, time information of the traffic accident points and screenshots of the traffic accident points.
The cloud server stores the dynamic road network data of the road network in a Postgis database, and the dynamic road network data of the road network is issued to HTTP service of WFS protocol by using a GeoServer map server for being called by a web end.
And uploading an HTTP service request to a cloud server by a dynamic road network display engine of the web end to acquire dynamic road network data of the road network.
And if no road construction point exists in the position corresponding to the position information of the high-precision map and the road construction point at the web end, the dynamic road network display engine at the web end takes the road construction point as a point element, adopts a webgl rendering technology, calls a GPU, renders the road construction point to the high-precision map in a GLB model mode, and displays the road construction point in a three-dimensional mode. Searching a GLB model of the road construction point by using the road construction point to obtain a GLB model of a point element of the road construction point; and placing a GLB model at a position corresponding to the position information of the road construction point on the high-precision map, rendering the GLB model of the road construction point to a high-precision map with the azimuth angle of due north, and displaying the road construction point on the high-precision map in a three-dimensional manner.
If the road construction point exists at the position corresponding to the position information of the high-precision map at the web end and the road construction point, the dynamic road network display engine at the web end can update the screenshot of the road construction point on the high-precision map, update the duration of the road construction point and continue to close the road section with the set length where the road construction point is located.
And if no traffic accident point exists in the position corresponding to the position information of the high-precision map and the traffic accident point at the web end, the dynamic road network display engine at the web end takes the traffic accident point as a point element, adopts a webgl rendering technology, calls a GPU, renders the traffic accident point to a high-precision map in a GLB model mode, and three-dimensionally displays the road construction point. Searching a GLB model of a traffic accident point by using the traffic accident point to obtain a GLB model of a point element of the traffic accident point; and placing a GLB model at a position corresponding to the position information of the traffic accident point on the high-precision map, rendering the GLB model of the traffic accident point to the high-precision map with the azimuth angle being due north, and displaying the traffic accident point on the high-precision map in a three-dimensional manner.
If the traffic accident point exists at the position corresponding to the position information of the high-precision map at the web end and the traffic accident point, the dynamic road network display engine at the web end can update the screenshot of the traffic accident point on the high-precision map, update the duration of the traffic accident point and continuously close the road section with the set length where the traffic accident point is located.
And the web end closes the road sections with the road construction points and the traffic accident points, namely, the color of the road sections corresponding to the road construction points and the traffic accident points is changed from the color of the normal road to red.
After 5 minutes, the cloud server respectively extracts images of the video stream data a 'and the video stream data b' received in real time, and respectively obtains an image X 'in the video stream data a' and an image Y 'in the video stream data b', wherein the shooting time of the image X 'and the shooting time of the image Y' are the same; and respectively using a construction recognition algorithm neural network model and a traffic accident algorithm neural network model to carry out YOLO algorithm recognition on the image X 'and the image Y' so as to obtain road construction points and traffic accident points of the road network. Assume that the road construction point is obtained by identifying the image X ', and the traffic accident point is not obtained by identifying the image Y'.
The cloud server may correspondingly assign location information to the identified road construction site based on the location information of the roadside apparatus a.
The cloud server can give time information to the road construction point according to the time for shooting the image X ', and the time for shooting the image X' is used as the time information of the road construction point.
The cloud server may take the image X' as a screenshot of the road construction point.
The dynamic road network data of the road network obtained by the cloud server comprises road construction points, position information of the road construction points, time information of the road construction points and screenshots of the road construction points.
The cloud server stores the dynamic road network data of the road network in a Postgis database, and the dynamic road network data of the road network is issued to HTTP service of WFS protocol by using a GeoServer map server for being called by a web end.
And the dynamic road network display engine of the web end uploads an HTTP service request to the cloud server after every 5 minutes to acquire dynamic road network data of the road network at the current moment.
And the dynamic road network display engine at the web end judges that the road construction point exists at the position corresponding to the high-precision map at the current moment and the position information of the road construction point at the current moment, determines that the occurred road construction point is not completely processed at the current moment, can update the screenshot of the road construction point on the high-precision map, update the duration of the road construction point and continuously close the road section with the set length where the road construction point is located.
And the dynamic road network display engine at the web end judges that no traffic accident point corresponding to the position information of the traffic accident point displayed on the high-precision map exists in the dynamic road network data at the current moment, the traffic accident point which has already occurred is determined to be completely disposed at the current moment, the GLB model corresponding to the traffic accident point is removed from the high-precision map, and the corresponding closed road section is unpacked, namely the red color of the corresponding closed road section is changed into the color of a normal road.
The dynamic road network display method based on the high-precision map can automatically obtain dynamic road network data of a road network according to video stream data of the road network; and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map, and the dynamic road network data of the road network can be visually displayed on the high-precision map in real time.
Further, according to the dynamic road network display method based on the high-precision map, images in video stream data which are shot and uploaded by multiple road side devices in the road network are extracted according to set time intervals, and the images are identified by a YOLO algorithm through a neural network model, so that dynamic road network data of the road network including road construction points and traffic accident points can be automatically identified. The web end acquires dynamic road network data of a road network according to a set time interval, adopts a webGL rendering technology, calls a GPU, and renders the dynamic road network type to a high-precision map in a GLB model mode, so that the acceleration capability of the GPU can be fully utilized, the rendering performance and speed of the web end are improved, and the number of elements borne by the high-precision map is increased; the dynamic road network data of the road network are displayed in a three-dimensional mode on the high-precision map, and can be fused with the high-precision map, so that the dynamic road network data of the road network are displayed with lane-level precision; the dynamic road network display engine at the web end can add dynamic road network data of a road network to the high-precision map, update the dynamic road network data of the road network and delete the dynamic road network data of the road network, and can intuitively display the change of road construction points and traffic accident points of the road network on the high-precision map in real time.
Example three:
corresponding to the embodiment of the application function implementation method, the application further provides a cloud server, a high-precision map-based dynamic road network display system, an electronic device and a corresponding embodiment.
Fig. 3 is a schematic structural diagram of a cloud server according to an embodiment of the present application.
Referring to fig. 3, a cloud server 30 includes a receiving unit 301, a processing unit 302, and a sending unit 303.
The receiving unit 301 is configured to receive video stream data that is shot and uploaded by multiple road side devices in a road network, and receive a data request uploaded by a web end.
A processing unit 302, configured to obtain dynamic road network data of a road network according to multiple images in the video stream data received by the receiving unit 301.
The sending unit 303 is configured to send the dynamic road network data of the road network obtained by the processing unit 302 to the web end according to the data request uploaded by the web end and received by the receiving unit, so that the web end can display the dynamic road network data of the road network in a three-dimensional manner on the high-precision map by using a setting algorithm.
According to the technical scheme shown in the embodiment of the application, the dynamic road network data of the road network can be automatically obtained according to the video stream data of the road network; and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map, and the dynamic road network data of the road network can be visually displayed on the high-precision map in real time.
Example four:
fig. 4 is another schematic structural diagram of the cloud server according to the embodiment of the present application.
Referring to fig. 4, a cloud server 30 includes a receiving unit 301, a processing unit 302, and a sending unit 303.
The receiving unit 301 is configured to receive video stream data that is shot and uploaded by multiple road side devices in a road network, and receive a data request that is uploaded by a web end at a set time interval.
The processing unit 302 comprises a decimation subunit 3021, an identification subunit 3022, and a distribution subunit 3023.
An extracting sub-unit 3021, configured to extract, at set time intervals, images in the video stream data received by the receiving unit 301, and obtain multiple images captured at the same time by each of the multiple roadside devices.
The identifying subunit 3022 is configured to perform YOLO algorithm identification on the multiple images obtained by the extracting subunit 3021 by using a neural network model to obtain dynamic road network data of a road network, where the dynamic road network data of the road network includes a dynamic road network type, and the dynamic road network type includes a road construction point and a traffic accident point.
In one embodiment, the identifying subunit 3022 performs a YOLO algorithm identification on the multiple images by using a neural network model to obtain a dynamic road network type of the road network; giving position information and time information of the dynamic road network type according to the position information of road side equipment for shooting the image and the time information of the shot image; taking the image for identifying the dynamic road network type as a screenshot of the dynamic road network type; and acquiring dynamic road network data of the road network, wherein the dynamic road network data comprises dynamic road network types, position information of the dynamic road network types, time information and screenshots.
A distribution subunit 3023, configured to distribute the obtained dynamic road network data of the road network as an HTTP service in the WFS protocol.
The sending unit 3023 is further configured to send the dynamic road network data of the road network of the HTTP service in the WFS protocol, which is obtained by the processing unit 302, to the web end according to the data request uploaded by the web end at the set time interval, which is received by the receiving unit 301, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map.
Example five:
fig. 5 is a schematic structural diagram of a dynamic road network display system based on a high-precision map according to an embodiment of the present application.
Referring to fig. 5, a dynamic road network display system based on a high-precision map includes the plurality of road side devices 50, the cloud server 30, and the web server 40.
And the multiple roadside devices 50 are used for being installed at the roadside of the road in the road network, and shooting and uploading the video stream data of the road in the road network to the cloud server 30.
The cloud server 30 is configured to receive video stream data that is shot and uploaded by each of the multiple roadside devices 50, obtain dynamic road network data of a road network according to multiple images in the video stream data, receive a data request uploaded by the web end 40, and send the dynamic road network data of the road network to the web end 40 according to the received data request uploaded by the web end 40.
And the web terminal 40 is used for uploading a data request to the cloud server 30, receiving the dynamic road network data of the road network sent by the cloud server 30 according to the data request, and displaying the dynamic road network data of the road network in a three-dimensional manner on the high-precision map by adopting a set algorithm.
In one embodiment, the web end 40 determines, based on the received dynamic road network data of the road network at the current time and the dynamic road network data of the road network displayed on the high-precision map at the web end 40, whether or not a position corresponding to the position information of the dynamic road network type of the high-precision map at the web end and the dynamic road network data of the road network at the current time exists; and if the dynamic road network type does not exist in the position corresponding to the position information of the dynamic road network type of the high-precision map at the web end and the dynamic road network data of the road network, taking the dynamic road network type as a point element, adopting a webgl rendering technology, calling a GPU, rendering the dynamic road network type to a high-precision map in a GLB model mode, and three-dimensionally displaying the dynamic road network data of the road network.
With regard to the related devices in the above embodiments, the specific manner of performing the operations thereof has been described in detail in the embodiments related to the method, and will not be elaborated upon here.
Fig. 6 is a schematic structural diagram of an electronic device shown in an embodiment of the present application.
Referring to fig. 6, an electronic device 600 includes a memory 610 and a processor 620.
The Processor 620 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 610 may include various types of storage units such as system memory, Read Only Memory (ROM), and permanent storage. Wherein the ROM may store static data or instructions that are required by the processor 620 or other modules of the computer. The persistent storage device may be a read-write storage device. The persistent storage may be a non-volatile storage device that does not lose stored instructions and data even after the computer is powered off. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the permanent storage may be a removable storage device (e.g., floppy disk, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as a dynamic random access memory. The system memory may store instructions and data that some or all of the processors require at runtime. In addition, the memory 610 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic and/or optical disks, as well. In some embodiments, memory 610 may include a removable storage device that is readable and/or writable, such as a Compact Disc (CD), a digital versatile disc read only (e.g., DVD-ROM, dual layer DVD-ROM), a Blu-ray disc read only, an ultra-dense disc, a flash memory card (e.g., SD card, min SD card, Micro-SD card, etc.), a magnetic floppy disk, or the like. Computer-readable storage media do not contain carrier waves or transitory electronic signals transmitted by wireless or wired means.
The memory 610 has stored thereon executable code that, when processed by the processor 620, causes the processor 620 to perform some or all of the methods described above.
Furthermore, the method according to the present application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing some or all of the steps of the above-described method of the present application.
Alternatively, the present application may also be embodied as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) having executable code (or a computer program or computer instruction code) stored thereon, which, when executed by a processor of an electronic device (or server, etc.), causes the processor to perform part or all of the various steps of the above-described method according to the present application.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A dynamic road network display method based on high-precision maps is characterized by comprising the following steps:
receiving video stream data shot and uploaded by a plurality of road side devices in a road network, and receiving a data request uploaded by a web end;
obtaining dynamic road network data of the road network according to a plurality of images in the video stream data;
and sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional manner by adopting a set algorithm.
2. The method according to claim 1, wherein said obtaining dynamic road network data of said road network from a plurality of images in said video stream data comprises:
extracting images in the video stream data according to a set time interval to obtain the plurality of images shot by each of the plurality of road side devices at the same time;
and carrying out YOLO algorithm identification on the plurality of images by adopting a neural network model to obtain dynamic road network data of the road network, wherein the dynamic road network data of the road network comprises dynamic road network types, and the dynamic road network types comprise road construction points and traffic accident points.
3. The method of claim 2, wherein said dynamic road network data of said road network further comprises location information, time information, screenshots of said dynamic road network type;
the step of performing YOLO algorithm recognition on the plurality of images by using a neural network model to obtain dynamic road network data of the road network comprises the following steps:
carrying out YOLO algorithm identification on the multiple images by adopting a neural network model to obtain a dynamic road network type of the road network;
giving the dynamic road network type position information and the time information according to the position information of road side equipment for shooting images and the time information of the shot images;
taking the image of the identified dynamic road network type as a screenshot of the dynamic road network type;
and acquiring dynamic road network data of the road network, wherein the dynamic road network data comprises the dynamic road network type, position information of the dynamic road network type, time information and screenshot.
4. The method according to claim 1, wherein the sending the dynamic road network data of the road network to the web end according to the data request uploaded by the web end, so that the web end can display the dynamic road network data of the road network in three dimensions on a high-precision map by using a set algorithm, comprises: issuing the dynamic road network data of the road network as HTTP service of WFS protocol;
and sending the dynamic road network data of the road network, which are issued as HTTP service of WFS protocol, to the web end according to the data request uploaded by the web end according to the set time interval, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional manner by adopting a set algorithm.
5. A cloud server, comprising:
the receiving unit is used for receiving video stream data which are shot and uploaded by a plurality of road side devices in a road network and receiving data requests uploaded by a web end;
the processing unit is used for obtaining dynamic road network data of the road network according to a plurality of images in the video stream data received by the receiving unit;
and the sending unit is used for sending the dynamic road network data of the road network obtained by the processing unit to the web end according to the data request uploaded by the web end and received by the receiving unit, so that the web end can display the dynamic road network data of the road network in a high-precision map three-dimensional mode by adopting a set algorithm.
6. Cloud server according to claim 5, wherein the processing unit comprises:
an extracting subunit, configured to extract, according to a set time interval, images in the video stream data received by the receiving unit, and obtain the multiple images captured by each of the multiple pieces of road side equipment at the same time;
and the identification subunit is used for performing the YOLO algorithm identification on the plurality of images obtained by the extraction subunit by adopting a neural network model to obtain dynamic road network data of the road network, wherein the dynamic road network data of the road network comprises dynamic road network types, and the dynamic road network types comprise road construction points and traffic accident points.
7. Cloud server according to claim 5, wherein: the processing unit further comprises a publishing subunit;
the issuing subunit is configured to issue the obtained dynamic road network data of the road network as an HTTP service of a WFS protocol;
the receiving unit is further configured to receive a data request uploaded by the web end at a set time interval;
the sending unit is further configured to send the dynamic road network data of the road network of the HTTP service of the WFS protocol, which is obtained by the processing unit, to the web end according to the data request uploaded by the web end at the set time interval, which is received by the receiving unit, so that the web end adopts a set algorithm to three-dimensionally display the dynamic road network data of the road network on the high-precision map.
8. A dynamic road network display system based on high-precision maps is characterized in that: comprising a plurality of roadside devices, cloud servers, web sites as claimed in any one of claims 5 to 7;
the road side devices are used for being installed at the road sides of the roads in the road network, and shooting and uploading video stream data of the roads in the road network to the cloud server;
the cloud server is used for receiving video stream data which are shot and uploaded by each of the multiple road side devices, obtaining dynamic road network data of the road network according to multiple images in the video stream data, receiving a data request uploaded by the web end, and sending the dynamic road network data of the road network to the web end according to the received data request uploaded by the web end;
the web end is used for uploading a data request to the cloud server, receiving the dynamic road network data of the road network sent by the cloud server according to the data request, and displaying the dynamic road network data of the road network in a three-dimensional manner on a high-precision map by adopting a set algorithm.
9. The system of claim 8, wherein the web-side is further configured to:
and if the dynamic road network type does not exist in the position corresponding to the position information of the dynamic road network type of the dynamic road network data of the web end and the high-precision map, taking the dynamic road network type as a point element, adopting a webgl rendering technology, calling a GPU, rendering the dynamic road network type to the high-precision map in a GLB model mode, and displaying the dynamic road network data of the road network in a three-dimensional mode.
10. A computer-readable storage medium characterized by: stored with executable code which, when executed by a processor of an electronic device, causes the processor to perform the method of any of claims 1-4.
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