CN114863285B - Method, device, equipment and storage medium for identifying target road - Google Patents
Method, device, equipment and storage medium for identifying target road Download PDFInfo
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Abstract
The disclosure provides a method, a device, equipment and a storage medium for identifying a target road, relates to the technical field of computers, and particularly relates to the technical field of maps. The specific implementation scheme is as follows: determining a plurality of first candidate roads in the target area according to the road network data and the area data of the target area; determining a second candidate road in the first candidate roads according to the driving track information corresponding to the first candidate roads; determining road width and road side facility information of each second candidate road according to the road image corresponding to each second candidate road; and determining a target road in the second candidate road according to the road width and the road side facility information.
Description
Technical Field
The present disclosure relates to the field of computer technology, and in particular, to the field of map technology.
Background
Electronic maps, i.e., digital maps, are maps that are stored and referred to digitally using computer technology. The electronic map user can find various places or various locations through the electronic map. In addition, the user can search the travel route through the electronic map.
The electronic map manufacturer can collect the form data of the road through the collection vehicle, and then the form data is presented in the electronic map for users to use.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, storage medium, and program product for identifying a target link.
According to an aspect of the present disclosure, there is provided a method of identifying a target road, including: determining a plurality of first candidate roads in a target area according to road network data and area data of the target area; determining a second candidate road in the first candidate roads according to the driving track information corresponding to the first candidate roads; determining the road width and road side facility information of each second candidate road according to the road image corresponding to each second candidate road; and determining a target road in the second candidate road according to the road width and the road side facility information.
According to another aspect of the present disclosure, there is provided an apparatus for identifying a target road, including: the first determining module is used for determining a plurality of first candidate roads in the target area according to road network data and area data of the target area; a second determining module, configured to determine a second candidate road among the plurality of first candidate roads according to travel track information corresponding to the plurality of first candidate roads; a third determining module, configured to determine a road width and road side facility information of each second candidate road according to a road image corresponding to each second candidate road; and a fourth determining module configured to determine a target road in the second candidate road according to the road width and the road side facility information.
Another aspect of the present disclosure provides an electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods shown in the embodiments of the present disclosure.
According to another aspect of the disclosed embodiments, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the methods shown in the disclosed embodiments.
According to another aspect of the disclosed embodiments, there is provided a computer program product comprising a computer program/instruction, characterized in that the computer program/instruction, when executed by a processor, implements the steps of the method shown in the disclosed embodiments.
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 drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 schematically illustrates an application scenario in which a target road recognition method and apparatus may be applied according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a method of identifying a target link according to an embodiment of the disclosure;
FIG. 3 schematically illustrates a flow chart of a method of determining a second candidate road in accordance with an embodiment of the disclosure;
FIG. 4 schematically illustrates a flow chart of a method of determining road width and roadside facility information for each second candidate road in accordance with an embodiment of the disclosure;
FIG. 5 schematically illustrates a schematic diagram of identifying a target link according to another embodiment of the present disclosure;
FIG. 6 schematically illustrates a block diagram of an apparatus for identifying a target link according to an embodiment of the present disclosure; and
FIG. 7 schematically illustrates a block diagram of an example electronic device that may 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 and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
An application scenario in which the method and apparatus for identifying a target road can be applied provided in the present disclosure will be described below with reference to fig. 1.
Fig. 1 schematically illustrates an application scenario in which a target road recognition method and apparatus may be applied according to an embodiment of the present disclosure.
It should be noted that fig. 1 is only an example of an application scenario where the method and apparatus for identifying a target road of the embodiments of the present disclosure may be applied, so as to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments, or scenarios.
As shown in fig. 1, an application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and/or wireless communication links, and the like.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications may be installed on the terminal devices 101, 102, 103, such as an electronic map application, a knowledge reading class application, a web browser application, a search class application, an instant messaging tool, a mailbox client and/or social platform software, to name a few.
The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for content browsed by the user using the terminal devices 101, 102, 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the method for identifying the target road provided in the embodiment of the disclosure may also be performed by the server 105. Accordingly, the apparatus for identifying a target road provided by the embodiments of the present disclosure may be generally provided in the server 105. The method of identifying a target link provided by the embodiments of the present disclosure may also be performed by a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the apparatus for identifying a target road provided by the embodiments of the present disclosure may also be provided in a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
Alternatively, the method of identifying a target road provided by the embodiment of the present disclosure may also be performed by the terminal device 101, 102 or 103. Accordingly, the apparatus for identifying a target road provided by the embodiments of the present disclosure may also be provided in the terminal device 101, 102 or 103.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
In the technical scheme of the disclosure, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing, applying and the like of the personal information of the user all conform to the regulations of related laws and regulations, necessary security measures are adopted, and the public order harmony is not violated.
In the technical scheme of the disclosure, the authorization or consent of the user is obtained before the personal information of the user is obtained or acquired.
Since the mountain road is relatively easy to be accident-prone, there is a high risk when the vehicle is traveling on the mountain road. In the process of planning the path for the user according to the electronic map, if the mountain road is not avoided or the user is not reminded of the mountain road, the traveling danger of the user is increased. Based on the above, it is necessary to identify a mountain road having a high risk.
The method of identifying a target road provided by the present disclosure will be described below with reference to fig. 2. The target road may include a mountain road with a high risk.
Fig. 2 schematically illustrates a flowchart of a method of identifying a target link according to an embodiment of the present disclosure.
As shown in fig. 2, the method 200 of identifying a target link includes determining a plurality of first candidate links located within a target area according to road network data and area data of the target area in operation S210.
According to embodiments of the present disclosure, a road network refers to a road network in the traffic domain. The road network data may include information about the road network, such as location information, start and end points, etc. of each road in the road network. The location information may include, for example, longitude and latitude.
According to embodiments of the present disclosure, the target area may be a geographic area to be identified. For example, a mountain area is highly dangerous on roads, and thus can be selected as a target area. The region data may include, for example, geographic information of the target region, such as elevation, longitude and latitude, and the like.
According to an embodiment of the present disclosure, the location information of a plurality of original roads may be determined, for example, from road network data. And determining the geographic range of the target area according to the area data of the target area. And then determining an original road which is in a geographic range from the plurality of original roads as a first candidate road according to the position information.
According to another embodiment of the present disclosure, the safety of the closed road is high due to the expressway, and the like. Based on this, it is possible to exclude a closed road such as an expressway and an expressway when determining the first candidate road, thereby reducing the amount of data to be processed later.
Then, in operation S220, a second candidate road among the plurality of first candidate roads is determined according to the travel track information corresponding to the plurality of first candidate roads.
According to an embodiment of the present disclosure, the driving trajectory information may include trajectory information of a vehicle driving in a corresponding road, for example, information including an elevation, a speed, and coordinates of a plurality of trajectory points. For example, a road having a high altitude, a low speed, and a large steering angle among the plurality of first candidate roads may be determined as the second candidate road based on the travel track information.
According to another embodiment of the present disclosure, for example, a plurality of original travel track information may be collected, and then travel track information matching each first candidate road among the plurality of original travel track information is determined. For example, in the present embodiment, the matching model may be trained in advance based on the sample travel track information and the sample road, and the original travel track information and the first candidate road may be input into the matching model to determine whether the original travel track information and the first candidate road match. The matching model may include, for example, a Hidden Markov model (Hidden MarkovModel, HMM).
In operation S230, the road width and the road side facility information of each second candidate road are determined according to the road image corresponding to each second candidate road.
According to embodiments of the present disclosure, the road image may include environmental information in the road and around the road. For example, in the present embodiment, the road image may be acquired by a vehicle running in a road. For example, road images may be acquired by an acquisition vehicle traveling in a road. Alternatively, it may be acquired by an image acquisition facility provided in the road. The road image may be acquired, for example, by a monitoring camera provided in the road. Or may also be acquired by an aerial image acquisition device. For example, the road image may be acquired by a drone, a satellite, or the like.
In operation S240, a target link in the second candidate link is determined according to the link width and the road side facility information.
According to an embodiment of the present disclosure, the roadside facility information may be used to indicate whether facilities are provided on both sides of the road, and in the case where facilities are provided, the type of each facility. For example, a second candidate road in which the road width is smaller than the width threshold value and the road side facility information satisfies the predetermined condition may be determined as the target road. Wherein the predetermined condition may include, for example, roadside facility information indicating that the road is not provided with a safety facility. The safety facilities may include, for example, railings, cones, posts, cue signs, traffic wide angle lenses, and the like.
For road driving safety, no guardrails, excessively narrow road width and the like are important reasons for accidents, so that dangerous roads in a target area can be identified in advance by determining that the road width is smaller than a width threshold value and road side facility information indicates a target road where no safety facility is arranged on the road, and driving safety can be improved.
According to the embodiment of the disclosure, when the navigation path planning is performed according to the departure place and the destination of the user, the recommended path for avoiding the target road can be generated according to the identified target road, so that the target road can be avoided when the user navigates, and the driving safety is improved.
According to another embodiment of the disclosure, in the case that the recommended route cannot avoid passing through the target road, a prompt message for the target road may be generated and displayed to the user, so that the user may perform early warning according to the prompt message.
The method of determining the second candidate road provided in the present disclosure will be described below with reference to fig. 3.
Fig. 3 schematically illustrates a flow chart of a method of determining a second candidate road according to an embodiment of the disclosure.
As shown in fig. 3, the method 320 of determining the second candidate road includes determining elevation features, speed features, and steering angle features of each first candidate road according to travel track information corresponding to each first candidate road in operation S321.
In operation S322, a second candidate road among the plurality of first candidate roads is determined according to the elevation feature, the speed feature, and the steering angle feature.
According to an embodiment of the present disclosure, an elevation refers to a distance from a point to an absolute base surface along a plumb line direction, called an absolute elevation, for short.
According to an embodiment of the present disclosure, at least one of a maximum elevation difference, an average elevation, and an n-th percentile among a plurality of elevations, where n is a positive integer and is less than or equal to the total number of elevations in the travel track information, may be calculated as an elevation feature of the first candidate road, for example, according to the plurality of elevations in the travel track information corresponding to the first candidate road. Where percentile is a statistical term, if a set of data is ordered from small to large and a corresponding cumulative percentile is calculated, the value of the data corresponding to a certain percentile is referred to as the percentile of that percentile.
For example, the difference between the largest elevation and the smallest elevation among the plurality of elevations may be calculated as the largest elevation difference.
Illustratively, in this embodiment, the maximum elevation difference, the average elevation, the 95 th percentile, the 5 th percentile, and the median of the plurality of elevations may be calculated as the elevation features.
According to the embodiment of the present disclosure, for example, at least one of an average speed and an mth percentile among a plurality of speeds may be calculated as a speed feature of a first candidate road according to a plurality of speeds in travel track information corresponding to the first candidate road, where m is a positive integer and is less than or equal to the total number of speeds in the travel track information. Illustratively, in the present embodiment, an average speed, 95 th percentile, 5 th percentile, and median of a plurality of speeds may be calculated as the speed characteristics.
According to the embodiments of the present disclosure, for example, the maximum steering angle may be calculated as the steering angle characteristic of the first candidate road from a plurality of coordinates, such as latitude and longitude coordinates, in the travel locus information corresponding to the first candidate road.
According to other embodiments of the present disclosure, the predetermined length may be set, for example. If the trajectory is greater than or equal to the predetermined length, a maximum steering angle within the trajectory is calculated as a steering angle feature. If the track is smaller than the preset length, the track is extended to the preset length in a front-back equidistant mode, and then the maximum steering angle of the extended track is calculated and is used as a steering angle characteristic. Therefore, errors caused by too short track can be reduced, and the recognition accuracy can be improved. The predetermined length can be set according to actual needs. Illustratively, in this embodiment, the predetermined length may be 100 meters.
According to the embodiments of the present disclosure, for example, a first candidate road whose elevation feature, speed feature, and steering angle feature satisfy predetermined requirements may be determined as a second candidate road. Wherein the predetermined requirement may include a steering angle greater than an angle threshold, an elevation greater than an elevation threshold, and a speed less than a speed threshold. Wherein the angle threshold, elevation threshold, and speed threshold may be set according to the altitude of the target area. For example, the angle threshold, elevation threshold, and speed threshold for plain and mountain areas may be different. Compared with plain, the mountain area has smaller angle threshold value, larger elevation threshold value and smaller speed threshold value.
The method of determining the road width and the road side facility information of each second candidate road provided in the present disclosure will be described below with reference to fig. 4.
Fig. 4 schematically illustrates a flowchart of a method of determining road width and roadside facility information for each second candidate road according to an embodiment of the disclosure.
As shown in fig. 4, the method 430 of identifying a target link includes performing operations S431 to S434 for each second candidate link.
In operation S431, a lane line and a road side facility in the road image corresponding to the second candidate road are identified.
In operation S432, a facility type of the road side facility is determined as road side facility information of the second candidate road.
In operation S433, the number of lanes of the second candidate road is determined according to the lane lines.
In operation S434, the road width of the second candidate road is determined according to the road class, the facility type, and the number of lanes of the second candidate road.
According to an embodiment of the present disclosure, each road image may include at least one object. The objects may include, for example, lane lines and roadside facilities. The lane lines may include, for example, white solid single lines, white double solid lines, white double dashed lines, yellow solid single dashed lines, yellow double solid lines, yellow double dashed lines, white solid dashed lines, yellow solid dashed lines, and the like. Roadside facilities may include, for example, types of railings, cones, posts, cue signs, traffic wide angle lenses, and the like.
According to the embodiment of the disclosure, for example, the road image of the road to be identified may be subjected to semantic segmentation to obtain at least one image segmentation result. Wherein the image segmentation result may be used to characterize objects contained in the road image. In the case where it is recognized that the road image contains a road test facility, the type of the road side device indicated by the image division result may be determined as the road side facility information.
In this embodiment, the semantic segmentation model may be trained by using the sample road image, and then the road image may be semantically segmented by using the trained semantic segmentation model, so as to obtain a corresponding image segmentation result. The semantic segmentation model may include, for example, a residual network ResNet50 model.
According to an embodiment of the present disclosure, based on the number of lane lines obtained by the division, the corresponding number of lanes may be determined. For example, the number of lanes may be reduced by 1 from the number of lane lines to obtain the corresponding number of lanes. For example, if the number of lane lines is 3, it is possible to determine that the number of lanes is 2.
According to the embodiments of the present disclosure, for example, the road surface level of a road may be determined, and then the average road surface width corresponding to the road surface level may be obtained. The product of the number of lanes and the average road surface width is calculated as the road width. The road surface level of the road may include, for example, expressways, urban expressways, national roads, provincial roads, county roads, village roads, other roads, and the like. Illustratively, in the present embodiment, the road surface level of the road may be an attribute of the road at the time of producing the road network data. Based on this, the road surface level of the road can be obtained from the road network data.
According to another embodiment of the present disclosure, for example, the product of the number of lanes and the average road surface width may be added to the adjustment value as the road width. Thereby, the accuracy of the road width can be further improved. The adjustment value may be adjusted by factors such as the type of lane line in the center of the road, whether there is a non-motor vehicle lane in the road, and the like.
According to another embodiment of the present disclosure, lane lines of a mountain road may include a white single solid line, a yellow double dashed line, a yellow single solid line, and a yellow single dashed line, which are generally applied to other types of lane lines on roads having good traffic or high grade. Based on this, when determining the target road in the mountain area, a road whose lane line type includes any one of a white single solid line, a yellow double dashed line, a yellow single solid line, and a yellow single dashed line may be screened out from the second candidate road as the target road. For roads with lane lines of other types, the road is not a target road.
The method of identifying a target link shown above is further described with reference to fig. 5 in conjunction with an exemplary embodiment. Those skilled in the art will appreciate that the following example embodiments are merely for the understanding of the present disclosure, and the present disclosure is not limited thereto.
Fig. 5 schematically illustrates a schematic diagram of identifying a target road according to another embodiment of the present disclosure.
In fig. 5, it is shown that a first candidate road is determined and a second candidate road is determined from the first candidate roads in operation S501.
According to an embodiment of the present disclosure, the location information of a plurality of original roads may be determined, for example, from road network data. And determining the geographic range of the target area according to the area data of the target area. And then determining an original road which is in the geographic range from the plurality of original roads as a first candidate road according to the position information. Illustratively, in the present embodiment, the target area may be a mountain area.
Next, according to an embodiment of the present disclosure, travel track information corresponding to each first candidate road may be acquired. For each first candidate road, the maximum elevation difference, the average elevation, the 95 th percentile, the 5 th percentile, and the median of the plurality of elevations may be calculated as elevation features from the plurality of elevations in the travel track information corresponding to the first candidate road.
According to the embodiment of the present disclosure, the 95 th percentile, the 5 th percentile, and the median of the average speed and the plurality of speeds may be calculated as the speed characteristics of the first candidate road from the plurality of speeds in the travel locus information corresponding to the first candidate road.
According to the embodiments of the present disclosure, the maximum steering angle may be calculated as the steering angle characteristic of the first candidate road from a plurality of coordinates in the travel locus information corresponding to the first candidate road.
Then, according to the embodiment of the present disclosure, a first candidate road whose elevation feature, speed feature, and steering angle feature satisfy predetermined requirements may be determined as a second candidate road.
In operation S502, for each second candidate road, a semantic segmentation is performed on a road image corresponding to the second candidate road.
According to an embodiment of the present disclosure, for each second candidate road, a lane line and a roadside facility in a road image corresponding to the second candidate road are identified. And determining the facility type of the road side facility as road side facility information of the second candidate road. And determining the number of lanes of the second candidate road according to the lane lines. And determining the road width of the second candidate road according to the road grade, the facility type and the number of lanes of the second candidate road.
In operation S503, it is determined whether a lane line and a roadside apparatus are recognized in the road image. If a lane line or roadside apparatus is identified, operation S504 is performed, otherwise operation S506 is performed.
In operation S504, it is determined whether the road width is less than a width threshold and the road side facility information includes a safety facility type. If the road width is less than the width threshold and the road side facility information contains a safety facility type, operation S505 is performed, otherwise operation S506 is performed. The safety facilities may include, for example, railings, cones, posts, cue signs, traffic wide angle lenses, and the like.
In operation S505, the second candidate road is determined as the target road.
According to an embodiment of the present disclosure, the target road is a road with a small road surface width and a road side lacking safety facilities. The width of the road surface is smaller, and running is dangerous under the condition that the road side lacks safety facilities. By identifying the target road, the running safety can be improved.
In operation S506, it is determined that the recognition result of the second candidate road is indeterminate.
According to other embodiments of the present disclosure, operations S502 to S506 may be performed a plurality of times for the second candidate road whose recognition result is indeterminate. And if the number of times that the second candidate road is determined to be the second candidate road and the identification result is that the undetermined number of times is larger than the threshold number of times, determining the suspected second candidate road as the target road. The frequency threshold can be set according to actual needs.
According to the method for identifying the target road, dangerous mountain roads in a mountain area can be identified in advance, so that driving safety can be improved.
The apparatus for identifying a target road provided by the present disclosure will be described below with reference to fig. 6.
Fig. 6 schematically illustrates a block diagram of an apparatus for identifying a target link according to an embodiment of the present disclosure.
As shown in fig. 6, the apparatus 600 for identifying a target link includes a first determination module 610, a second determination module 620, a third determination module 630, and a fourth determination module 640.
The first determining module 610 is configured to determine a plurality of first candidate roads located in the target area according to the road network data and the area data of the target area.
The second determining module 620 is configured to determine a second candidate road among the plurality of first candidate roads according to the driving track information corresponding to the plurality of first candidate roads.
The third determining module 630 is configured to determine a road width and road side facility information of each second candidate road according to the road image corresponding to each second candidate road.
And a fourth determining module 640, configured to determine a target road in the second candidate road according to the road width and the road side facility information.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
Fig. 7 schematically illustrates a block diagram of an example electronic device 700 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate 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. 7, the apparatus 700 includes a computing unit 701 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 may also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in device 700 are connected to I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, etc.; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, an optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 701 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 701 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 calculation unit 701 performs the respective methods and processes described above, for example, a method of identifying a target road. For example, in some embodiments, the method of identifying a target link may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 700 via ROM 702 and/or communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the above-described method of identifying a target link may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the method of identifying the target road by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments 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 can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service ("Virtual Private Server" or simply "VPS") are overcome. The server may also be a server of a distributed system or a server that incorporates 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 or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (8)
1. A method of identifying a target link, comprising:
determining a plurality of first candidate roads in a target area according to road network data and area data of the target area, wherein position information of a plurality of original roads is determined according to the road network data; determining the geographic range of the target area according to the area data of the target area; determining an original road which is in the geographic range from a plurality of original roads as the first candidate road according to the position information;
determining a second candidate road in the first candidate roads according to the driving track information corresponding to the first candidate roads;
determining the road width and road side facility information of each second candidate road according to the road image corresponding to each second candidate road; and
and determining a target road in the second candidate road according to the road width and the road side facility information.
2. The method of claim 1, wherein the determining a second candidate link of the plurality of first candidate links from the travel track information corresponding to the plurality of first candidate links comprises:
determining elevation features, speed features and steering angle features of each first candidate road according to the driving track information corresponding to each first candidate road; and
and determining a second candidate road in the first candidate roads according to the elevation characteristic, the speed characteristic and the steering angle characteristic.
3. The method of claim 2, wherein the travel trajectory information includes elevation, speed, and coordinates of a plurality of trajectory points; the determining the elevation feature, the speed feature and the steering angle feature of each first candidate road according to the driving track information corresponding to each first candidate road comprises the following steps:
for each of said first candidate roads,
calculating at least one of a maximum elevation difference, an average elevation and an n-th percentile of the elevations according to a plurality of elevations in the travel track information corresponding to the first candidate road, wherein n is a positive integer and is less than or equal to the total number of elevations in the travel track information;
calculating at least one of an average speed and an mth percentile of a plurality of speeds according to a plurality of speeds in the driving track information corresponding to the first candidate road as a speed characteristic of the first candidate road, wherein m is a positive integer and is less than or equal to the total number of speeds in the driving track information; and
and calculating a maximum steering angle as a steering angle characteristic of the first candidate road according to a plurality of coordinates in the driving track information corresponding to the first candidate road.
4. The method of claim 1, wherein the determining the road width and the road side facility information of each of the second candidate roads from the road image corresponding to each of the second candidate roads comprises:
for each of said second candidate roads,
identifying a lane line and a road side facility in a road image corresponding to the second candidate road;
determining a facility type of the road side facility as road side facility information of the second candidate road;
determining the number of lanes of the second candidate road according to the lane lines; and
and determining the road width of the second candidate road according to the road grade of the second candidate road, the facility type and the number of lanes.
5. The method of claim 4, wherein the determining a target link in the second candidate link according to the link width and the roadside utility information comprises:
and determining a second candidate road, of which the road width is smaller than a width threshold value and the road side facility information satisfies a predetermined condition, as the target road.
6. An apparatus for identifying a target link, comprising:
the first determining module is used for determining a plurality of first candidate roads in the target area according to road network data and area data of the target area, wherein the position information of a plurality of original roads is determined according to the road network data; determining the geographic range of the target area according to the area data of the target area; determining an original road which is in the geographic range from a plurality of original roads as the first candidate road according to the position information;
a second determining module, configured to determine a second candidate road among the plurality of first candidate roads according to travel track information corresponding to the plurality of first candidate roads;
a third determining module, configured to determine a road width and road side facility information of each second candidate road according to a road image corresponding to each second candidate road; and
and a fourth determining module, configured to determine a target road in the second candidate road according to the road width and the road side facility information.
7. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
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.
8. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-5.
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