CN112541464A - Method and device for determining associated road object, road side equipment and cloud control platform - Google Patents
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Abstract
The invention discloses a determination method and device of an associated road object, roadside equipment and a cloud control platform, relates to the technical field of computers, and particularly relates to the field of intelligent transportation and the field of data fusion. The specific implementation scheme is as follows: the method comprises the steps of obtaining structured road information of different sources, wherein the structured road information comprises a target object and at least one candidate object, calculating the whisker similarity between the whisker of the target object and the whisker of each candidate object based on the structured road information and the whisker algorithm of each source, and finally determining an object to be associated of the target object from the at least one candidate object based on the whisker similarity.
Description
Technical Field
The present disclosure relates to the field of computer technology, and more particularly, to the field of intelligent transportation and the field of data fusion.
Background
With the rapid development of social economy, the number and types of motor vehicles are also increasing rapidly, and when vehicles are monitored, road object association and information fusion are required to be carried out on the acquired vehicle information from different sources.
When the road object association is performed on vehicles from different sources, the transverse and longitudinal euclidean distances or mahalanobis distances between the target object and the object to be associated are usually calculated, and when the transverse and longitudinal euclidean distances or mahalanobis distances between the target object and the object to be associated satisfy preset conditions, the target object and the object to be associated are associated.
Disclosure of Invention
The disclosure provides a determination method and device of a related road object, electronic equipment, roadside equipment, a cloud control platform and a storage medium.
According to an aspect of the present disclosure, there is provided a determination method of an associated road object, the method including: acquiring structured road information of different sources, wherein the structured road information comprises a target object and at least one candidate object; calculating the whisker similarity between the whisker of the target object and the whisker of each candidate object based on the structured road information of each source and a whisker algorithm; and determining an object to be associated of the target object from at least one candidate object based on the whisker similarity.
According to another aspect of the present disclosure, there is provided a determination apparatus of an associated road object, the apparatus including: an acquisition module configured to acquire structured road information of different sources, wherein the structured road information includes a target object and at least one candidate object; a computing module configured to compute whisker similarity between the tentacles of the target object and the tentacles of each candidate object based on the structured road information and the whisker algorithm of each source; and the determining module is configured to determine an object to be associated of the target object from the at least one candidate object based on the whisker similarity.
According to another aspect of the present disclosure, there is provided 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 determining an associated road object.
According to another aspect of the present disclosure, a computer-readable medium is provided, on which computer instructions are stored, the computer instructions being used for enabling a computer to execute the above-mentioned method for determining an associated road object.
According to another aspect of the present disclosure, the present application provides a roadside apparatus, which includes the electronic apparatus.
According to another aspect of the present disclosure, an embodiment of the present application provides a cloud control platform, which includes the above electronic device.
According to another aspect of the present disclosure, a computer program product is provided, which includes a computer program, and the computer program, when executed by a processor, implements the method for determining an associated road object described above.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary system architecture diagram in which the present disclosure may be applied;
FIG. 2 is a flow diagram of one embodiment of a method of determining an associated road object according to the present disclosure;
FIG. 3 is a schematic diagram of an application scenario of a method of determining an associated road object according to the present disclosure;
FIG. 4 is a flow diagram for one embodiment of calculating whisker similarity according to the present disclosure;
FIG. 5 is a flow diagram of yet another embodiment of a method of determining an associated road object according to the present disclosure;
FIG. 6 is a schematic diagram of one embodiment of an associated road object determination device, according to the present disclosure;
fig. 7 is a block diagram of an electronic device for implementing a method of determining an associated road object according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those 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.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 illustrates an exemplary system architecture 100 to which embodiments of the disclosed associated road object determination methods may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 104, 105, a network 106, and servers 101, 102, 103. The network 106 serves as a medium for providing communication links between the terminal devices 104, 105 and the servers 101, 102, 103. Network 106 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The terminal devices 104, 105 may interact with the servers 101, 102, 103 via the network 106 to receive or transmit information or the like. The end devices 104, 105 may have installed thereon various applications such as data collection applications, data processing applications, instant messaging tools, social platform software, search-type applications, shopping-type applications, and the like.
The terminal device 104 may be hardware or software. When the terminal device is hardware, it may be various electronic devices having an information acquisition device and supporting communication with a server, including but not limited to a road side system, a vehicle side system, an intelligent camera device, and the like. When the terminal device is software, the terminal device can be installed in the electronic devices listed above. It may be implemented as multiple pieces of software or software modules, or as a single piece of software or software module. And is not particularly limited herein.
The terminal device 104 may be a roadside system having an information collection function, each roadside system may correspond to a different collection range, each roadside system may collect structured road information within the corresponding collection range, and the structured road information may be state information used for representing each object in the road, and may include state information of a target object and state information of other objects in the road, such as state information of an obstacle, and the like. Each road side system can be connected with the servers 101, 102 and 103 through the network 106, can also be connected with the terminal device 105 through the network 106, and sends the acquired structured road information to the servers 101, 102 and 103 or the terminal device 105 through the network 106.
The terminal device 105 may be hardware or software. When the terminal device is hardware, it may be various electronic devices having an information fusion function and supporting communication with the server. When the terminal device is software, the terminal device can be installed in the electronic devices listed above. It may be implemented as multiple pieces of software or software modules, or as a single piece of software or software module. And is not particularly limited herein.
The terminal device 105 may obtain the structured road information of multiple different sources from the terminal device 104 through the network 106, that is, may obtain the structured road information from multiple terminal devices, where the structured road information of each source may include a collected object, and may use the collected object in one of the sources as a target object and then use the collected objects in the remaining other sources as candidate objects. Then, the terminal device 105 calculates the whisker similarity between the whisker of the target object and the whisker of each candidate object according to the structured road information and the whisker algorithm of each source, and determines the object to be associated of the target object from at least one candidate object according to the whisker similarity.
The servers 101, 102, 103 may be servers that provide various services, such as background servers that receive requests sent by terminal devices with which communication connections are established. The background server can receive and analyze the request sent by the terminal device, and generate a processing result.
The servers 101, 102, and 103 may be cloud servers that provide services for the terminal devices 104 and 105, and the cloud servers may receive the structured road information sent by different terminal devices 104 (different road side systems), and use a collection object in one of the terminal devices as a target object, and then use collection objects in the remaining other terminal devices as candidate objects. Then, the servers 101, 102, and 103 respectively calculate the whisker similarity between the whisker of the target object and the whisker of each candidate object according to the structured road information and the whisker algorithm of each terminal device, and determine an object to be associated of the target object from at least one candidate object according to the whisker similarity.
The server may be hardware or software. When the server is hardware, it may be various electronic devices that provide various services to the terminal device. When the server is software, it may be implemented as a plurality of software or software modules for providing various services to the terminal device, or may be implemented as a single software or software module for providing various services to the terminal device. And is not particularly limited herein.
It should be noted that the determination method of the related road object provided by the embodiment of the present disclosure may be executed by the terminal device 105, and may also be executed by the servers 101, 102, and 103. Accordingly, the determination device of the related road object may be provided in the terminal device 105, or may be provided in the servers 101, 102, 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.
Referring to fig. 2, fig. 2 shows a flowchart 200 of an embodiment of a determination method of an associated road object that can be applied to the present disclosure. The method for determining the associated road object comprises the following steps:
In this embodiment, a plurality of intelligent roadside systems may be continuously provided on the road at intervals of a preset distance in advance, and each roadside system is provided with a unique device number and corresponds to an acquisition range. The collection range between the roadside systems can have an overlapping region according to the actual condition of the road, and the collection range between two adjacent roadside systems can also have no overlapping region. And each roadside system respectively collects the structured road information in the corresponding collection range in real time, wherein the structured road information may include each object in the road collected by the roadside systems, and the object may represent any object running in the road, such as a running vehicle, a pedestrian, and the like; road information in the acquisition range can be further included, and the road information in the acquisition range, such as green plant information, building information, traffic cone information and the like, can be determined by combining a network map.
An executing body (for example, the terminal device 105 or the servers 101, 102, 103 in fig. 1) of the determination method of the associated road object may acquire the structured road information collected by each roadside system from a plurality of roadside systems through a network to obtain structured road information of different sources. Then, the execution subject may use the acquisition object in one of the sources as a target object, and use the acquisition objects in the remaining other sources as candidate objects.
As an example, the executing body may obtain structured road information acquired by 3 roadside systems, and take an acquisition object a in the structured road information of the first roadside system as a target object, and take an acquisition object B in the second roadside system and an acquisition object C in the third roadside system as candidate objects.
In this embodiment, after the execution subject determines the target object and the candidate object, based on the source to which the target object belongs, the haptic of the target object is determined by using the structured road information of the source and the haptic algorithm. And determining the tentacles of the candidate objects by using the structured road information and the tentacle algorithm of the source based on the source to which the candidate objects belong. Then the execution main body compares and calculates the tentacles of the target object and the tentacles of each candidate object to respectively obtain the tentacle similarity between the tentacles of the target object and the tentacles of each candidate object.
The tentacle algorithm generates a group of preset tentacles according to the vehicle running speed in each control period, each tentacle takes the current position as a starting point, a running track predicted under a certain front wheel deflection angle is used for constructing the tentacle, 16 speed values can be set in a certain speed range, 81 tentacles (namely predicted running paths of target objects) are correspondingly arranged in each pair of adjacent speed intervals, and one tentacle is selected as a running path according to the actual road condition like the tentacles of insects.
As an example, the executing body takes the acquisition object a in the structured road information of the first roadside system as a target object, takes the acquisition object B in the second roadside system and the acquisition object C in the third roadside system as candidate objects, then generates the tentacles of the acquisition object a based on the tentacle algorithm and the structured road information of the first roadside system, generates the tentacles of the acquisition object B based on the tentacle algorithm and the structured road information of the second roadside system, and generates the tentacles of the acquisition object C based on the tentacle algorithm and the structured road information of the third roadside system. Then the execution main body compares and calculates the tentacles of the acquisition object A and the tentacles of the acquisition object B to obtain a first tentacle similarity, and compares and calculates the tentacles of the acquisition object A and the tentacles of the acquisition object C to obtain a second tentacle similarity.
And step 230, determining an object to be associated of the target object from the at least one candidate object based on the whisker similarity.
In this embodiment, the execution body obtains, through calculation, the whisker similarity between the whisker of the target object and the whisker of each candidate object, may sort the whisker similarities according to the magnitude of the values, and determine the corresponding candidate object with the largest whisker similarity as the object to be associated with the target object. The object to be associated may be the same object collected for different roadside systems as the target object.
As an example, the executing body takes the acquisition object a as a target object, the acquisition object B and the acquisition object C as candidate objects, compares and calculates the tentacles of the acquisition object a and the tentacles of the acquisition object B to obtain a first tentacle similarity, and compares and calculates the tentacles of the acquisition object a and the tentacles of the acquisition object C to obtain a second tentacle similarity. And then, sequencing the first tentacle similarity and the second tentacle similarity according to the numerical value, determining the candidate object corresponding to the tentacle similarity with the maximum numerical value as the associated object of the acquisition object A, and determining the acquisition object B as the object to be associated of the acquisition object A by comparing that the first tentacle similarity is greater than the second tentacle similarity.
With continued reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the determination method of an associated road object according to the present disclosure.
In the application scenario of fig. 3, three roadside systems R1, R2 and R3 are disposed in the road, and R1, R2 and R3 can collect vehicles in the road in real time and send the collected road information to the terminal 301. The terminal 301 receives road information collected by R1, road information collected by R2, and road information collected by R3, wherein the road information collected by R1 includes vehicle a and road conditions, the road information collected by R2 includes vehicle B and road conditions, the road information collected by R3 includes vehicle C and road conditions, the terminal 301 takes the vehicle a collected by R1 as a target object, and the vehicle B collected by R2 and the vehicle C collected by R3 as candidate objects. Then, the terminal 301 calculates the whisker similarity of the antenna of the vehicle a and the antenna of the vehicle B, and the whisker similarity of the antenna of the vehicle a and the antenna of the vehicle C, based on the road information acquired by R1, the road information acquired by R2, the road information acquired by R3, and the whisker algorithm. And finally, the terminal 301 takes the vehicle with the largest whisker similarity as the object to be associated of the vehicle A according to the whisker similarity of the antenna of the vehicle A and the antenna of the vehicle B and the antenna similarity of the antenna of the vehicle A and the antenna of the vehicle C.
The method for determining the associated road object provided by the embodiment of the disclosure includes obtaining structured road information of different sources, where the structured road information includes a target object and at least one candidate object, then calculating the whisker similarity between the whisker of the target object and the whisker of each candidate object based on the structured road information and the whisker algorithm of each source, finally determining an object to be associated of the target object from the at least one candidate object based on the whisker similarity, introducing the whisker in a path plan based on the structured road, where the structured road can give a specific position of an obstacle, the whisker can give a spatial relative relationship between the obstacle and the whisker in combination with the structured road, and can determine the probability of the same obstacle by using the whisker similarity of each acquired object, so as to determine the similarity between each acquired object, the object to be associated of the target object is determined, so that the accuracy of the object to be associated is improved, the problem of object miscorrelation is solved, and the accuracy of object association is improved.
With further reference to FIG. 4, which illustrates step 220 of FIG. 2 of the present disclosure, calculating the whisker similarity between the tentacles of the target object and the tentacles of each candidate object based on the structured road information and the whisker algorithm of each source, may include the steps of:
in step 410, tentacles of the target object and tentacles of each candidate object are determined based on the tentacle algorithm.
In this step, after the execution subject determines the target object and the candidate objects, the tentacles of the target object and the tentacles of each candidate object are obtained according to the tentacle algorithm. The whisker algorithm can set 16 speed values in a certain speed range, 81 whiskers are correspondingly arranged in each pair of adjacent speed intervals, and one whisker is selected as a running path according to the actual road condition like the whisker of an insect.
As an example, the execution subject takes the acquisition object a in the structured road information of the first roadside system as a target object, and takes the acquisition object B in the second roadside system and the acquisition object C in the third roadside system as candidate objects. The whisker algorithm comprises the following steps:
l＝8+33.5q1.2
q＝j/15
the execution main body can obtain 81 complete tentacles corresponding to a certain speed of the acquisition object A at the current time, 81 complete tentacles corresponding to a certain speed of the acquisition object B at the current time and 81 complete tentacles corresponding to a certain speed of the acquisition object C at the current time through the calculation of the steps.
In step 420, based on the structured road information of each source, the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object are determined.
In this step, after the executive body acquires the tentacles of the target object and the tentacles of each candidate object, the executive body analyzes the structured road information of the source to which the target object belongs to obtain the information of the obstacles in the road, wherein the obstacles may be objects which obstruct the target object from passing in the road except the target object, for example, the target object is a running vehicle, and the obstacles may be other vehicles, green plants and the like, and then the executive body may determine the travelable area of the target object and the partial tentacles including the target object in the travelable area according to the complete tentacles of the target object and the information of the obstacles in the road. And the executing body analyzes the structured road information of the source of the candidate object to obtain the information of the obstacles in the road, wherein the obstacles can be objects which obstruct the target object from passing in the road except the candidate object, for example, the candidate object is a running vehicle, the obstacles can be other vehicles, green plants and the like, and then the executing body can determine the travelable area of the candidate object and the partial tentacles including the candidate object in the travelable area according to the complete tentacles of the candidate object and the information of the obstacles in the road.
And step 430, respectively calculating the whisker similarity of the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object.
In this step, after the travelable region of the target object and the travelable region of each candidate object are determined by the execution subject, the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object are respectively compared and calculated, and the tentacle similarity of the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object is obtained.
As an example, the execution subject acquires the travelable region of the acquisition object a, the travelable region of the acquisition object B, and the travelable region of the acquisition object C using the acquisition object a in the structured road information of the first roadside system as the target object, the acquisition object B in the second roadside system, and the acquisition object C in the third roadside system as the candidate objects. Then, the executing body compares and calculates the partial tentacles included in the travelable region of the acquisition object a and the partial tentacles included in the travelable region of the acquisition object B to obtain a first tentacle similarity, and compares and calculates the partial tentacles included in the travelable region of the acquisition object a and the partial tentacles included in the travelable region of the acquisition object C to obtain a second tentacle similarity.
In the embodiment, the accuracy of the whisker similarity is further improved by acquiring the travelable areas of the target object and the candidate object and obtaining the whisker similarity based on the partial whiskers included in the travelable areas, so that the object to be associated determined based on the whisker similarity is more accurate.
As an alternative implementation, the whisker similarity is implemented based on the following steps:
firstly, equally dividing part of tentacles in the travelable area of the target object to obtain at least one equally divided target tentacle.
Specifically, after the executive body acquires the travelable region of the target object, the executive body performs an equal division operation on part of tentacles in the travelable region of the target object to obtain at least one equally divided target tentacle. Optionally, the execution body may equally divide part of the tentacles of the target object by the number, and each equally divided target tentacle includes the same number of tentacles, so as to obtain at least one equally divided target tentacle with the same number of tentacles.
And secondly, equally dividing part of tentacles in the drivable area of the candidate object to obtain at least one equally divided candidate tentacle.
Specifically, after the executive body acquires the travelable region of the candidate object, the executive body performs an equal division operation on part of tentacles in the travelable region of the candidate object to obtain at least one equally divided candidate tentacle. Optionally, the execution body may equally divide part of tentacles of the candidate object by the number, where each equally divided candidate tentacle includes the same number of tentacles, and obtain at least one equally divided candidate tentacle with the same number of tentacles.
And thirdly, calculating each equally divided target tentacle and equally divided candidate tentacles respectively to obtain at least one equally divided tentacle similarity, and obtaining the tentacle similarity based on the at least one equally divided tentacle similarity.
Specifically, after obtaining at least one equally divided target tentacle and at least one equally divided candidate tentacle, the execution subject respectively performs corresponding comparison and calculation on each equally divided target tentacle and each equally divided candidate tentacle to obtain at least one equally divided tentacle similarity. The execution body may number at least one of the equally divided target tentacles and at least one of the equally divided candidate tentacles, respectively, for example, at least one of the equally divided target tentacles may be numbered as target tentacle 1 and target tentacle 2, and at least one of the equally divided candidate tentacles may be numbered as candidate tentacle 1 and candidate tentacle 2, and then compare the target tentacle 1 and candidate tentacle 1, respectively, to obtain a first equally divided tentacle similarity, and compare the target tentacle 2 and candidate tentacle 2, to obtain a second equally divided tentacle similarity. Optionally, the executing body may compare lengths of each of the tentacles to obtain a length difference, and use a mean value of the length differences as the whisker similarity.
After obtaining at least one aliquot tentacle similarity between the target tentacle and the candidate tentacle of each candidate object, the executing body may use the sum of the at least one aliquot tentacle similarity as the tentacle similarity; the average of at least one of the aliquot tentacle similarities may also be taken as the tentacle similarity.
As an example, the executing body takes the acquisition object a in the structured road information of the first roadside system as a target object, takes the acquisition object B in the second roadside system and the acquisition object C in the third roadside system as candidate objects, acquires partial tentacles of the travelable region of the acquisition object a, and performs an equal division operation on the partial tentacles of the acquisition object a to obtain 2 equal divided target tentacles, which are respectively the target tentacles 1 and the target tentacles 2. The execution main body acquires partial tentacles of the travelable area of the acquisition object B, and performs equal division operation on the partial tentacles of the acquisition object B to obtain 2 equally divided candidate tentacles which are respectively a candidate tentacle 1 and a candidate tentacle 2. The execution main body acquires partial tentacles of the travelable area of the acquisition object C, and equally divides the partial tentacles of the acquisition object C to obtain 2 equally divided candidate tentacles which are respectively a candidate tentacle 3 and a candidate tentacle 4. Then the execution main body compares and calculates the target tentacle 1 and the candidate tentacle 1 to obtain a first equal tentacle similarity, compares and calculates the target tentacle 2 and the candidate tentacle 2 to obtain a second equal tentacle similarity, and takes the sum of the first equal tentacle similarity and the second equal tentacle similarity as the tentacle similarity between the acquisition object A and the acquisition object B. And the execution main body compares and calculates the target tentacle 1 and the candidate tentacle 3 to obtain a first equal tentacle similarity, compares and calculates the target tentacle 2 and the candidate tentacle 4 to obtain a second equal tentacle similarity, and takes the sum of the first equal tentacle similarity and the second equal tentacle similarity as the tentacle similarity between the acquisition object A and the acquisition object C.
In the implementation mode, the tentacle similarity is calculated after the partial tentacles are equally divided, so that the accuracy of the tentacle similarity is improved, and the object to be associated determined based on the tentacle similarity is more accurate.
With further reference to fig. 5, a flowchart 500 of another embodiment of the disclosed method of determining an associated road object is shown. The method for determining the associated road object comprises the following steps:
In this step, step 510 is the same as step 210 in the embodiment shown in fig. 2, and is not described herein again.
At step 520, tentacle similarity between the tentacles of the target object and the tentacles of each candidate object is calculated based on the structured road information and the tentacle algorithm of each source.
In this step, step 520 is the same as step 220 in the embodiment shown in fig. 2, and is not described herein again.
In this step, step 530 is the same as step 230 in the embodiment shown in fig. 2, and is not described herein again.
And step 540, in response to determining the object to be associated of the target object, associating the target object and the object to be associated.
In this step, after the execution subject determines the object to be associated of the target object, the target object and the object to be associated are associated. Wherein, the object to be associated can be the same object of the target object in another source.
As an example, the execution main body receives structured road information acquired by three roadside systems, an acquisition object a in the structured road information of the first roadside system is taken as a target object, an acquisition object B in the second roadside system and an acquisition object C in the third roadside system are taken as candidate objects, and the acquisition object B is determined to be an object to be associated with the acquisition object a through the above steps, so that it can be determined that the acquisition object B and the acquisition object a are the same object but are objects acquired by different roadside systems.
And 550, performing information fusion on the perception information corresponding to the target object and the perception information corresponding to the object to be associated to obtain fusion information of the target object.
In this step, after the executing body associates the target object with the object to be associated, the sensing information corresponding to the target object and the sensing information corresponding to the object to be associated may be subjected to information fusion to obtain fusion information of the target object. The sensing information can be characteristic attribute information and traffic state information acquired by a road side system for a target object, or characteristic attribute information and traffic state information acquired by the road side system for a candidate object, and the execution main body performs information fusion on the sensing information corresponding to the target object and the sensing information corresponding to an object to be associated to obtain complete information of the target object.
In the embodiment, the accuracy and the integrity of the information of each acquisition object are improved by associating the target object with the object to be associated and performing information fusion, so that the accuracy of the fusion information of each acquisition object is improved.
With further reference to fig. 6, as an implementation of the methods shown in the above figures, the present application provides an embodiment of an apparatus for determining an associated road object, which corresponds to the embodiment of the method shown in fig. 2, and which is particularly applicable to various electronic devices.
As shown in fig. 6, the determination device 600 of the related road object of the present embodiment includes: an acquisition module 610, a calculation module 620, and a determination module 630.
The obtaining module 610 is configured to obtain structured road information of different sources, where the structured road information includes a target object and at least one candidate object;
a calculation module 620 configured to calculate whisker similarity between the tentacles of the target object and the tentacles of each candidate object based on the structured road information and the whisker algorithm of each source;
the determining module 630 is configured to determine an object to be associated with the target object from the at least one candidate object based on the whisker similarity.
In some optional aspects of this embodiment, the calculating module 620 is further configured to: determining tentacles of the target object and tentacles of each candidate object based on an tentacle algorithm; determining partial tentacles included in the travelable region of the target object and partial tentacles included in the travelable region of each candidate object based on the structured road information of each source; and respectively calculating the whisker similarity of the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object.
In some optional ways of this embodiment, the whisker similarity is implemented based on the following steps: equally dividing part of tentacles in the travelable area of the target object to obtain at least one equally divided target tentacle; equally dividing part of tentacles in the drivable area of the candidate object to obtain at least one equally divided candidate tentacle; and calculating each equally divided target tentacle and equally divided candidate tentacle respectively to obtain at least one equally divided tentacle similarity, and obtaining the tentacle similarity based on the at least one equally divided tentacle similarity.
In some optional manners of this embodiment, the apparatus further includes: the association module is configured to associate the target object and the object to be associated in response to determining the object to be associated of the target object; and the fusion module is configured to perform information fusion on the perception information corresponding to the target object and the perception information corresponding to the object to be associated to obtain fusion information of the target object.
The device for determining the associated road object provided by the embodiment of the disclosure obtains the structured road information of different sources, the structured road information includes a target object and at least one candidate object, then calculates the whisker similarity between the whisker of the target object and the whisker of each candidate object based on the structured road information and the whisker algorithm of each source, finally determines the object to be associated of the target object from at least one candidate object based on the whisker similarity, introduces the whisker in the path planning based on the structured road, the structured road can give the specific position of the obstacle, the whisker can give the spatial relative relationship between the obstacle and the whisker by combining the structured road, can determine the probability of the same obstacle by using the whisker similarity of each acquired object, thereby determining the similarity between each acquired object, the object to be associated of the target object is determined, so that the accuracy of the object to be associated is improved, the problem of object miscorrelation is solved, and the accuracy of object association is improved.
According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, a roadside device, a cloud control platform, and a computer program product.
FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can 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 phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the electronic device 700 includes a computing unit 701, which may 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 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, 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.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes 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 codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. 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. A 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 a pointing device (e.g., a mouse or a 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 can 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, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end 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 back-end, 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 clients and servers. A client and server are generally 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 roadside apparatus may include the electronic apparatus described above for executing the method of determining the associated road object described above. Besides, the roadside apparatus may include an electronic apparatus, a communication unit, and the like, and the electronic apparatus may be integrated with the communication unit or may be provided separately. The electronic device may acquire data, such as pictures and videos, from a sensing device (e.g., a roadside camera) for video processing and data computation.
The cloud control platform may include the electronic device, and is configured to execute the method for determining the associated road object. The cloud control platform can execute processing at a cloud end, and electronic equipment included in the cloud control platform can acquire data of sensing equipment (such as a roadside camera), such as pictures, videos and the like, so as to perform video processing and data calculation; the cloud control platform can also be called a vehicle-road cooperative management platform, an edge computing platform, a cloud computing platform, a central system, a cloud server and the like.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (13)
1. A method of determining an associated road object, comprising:
acquiring structured road information of different sources, wherein the structured road information comprises a target object and at least one candidate object;
calculating whisker similarity between the whisker of the target object and the whisker of each candidate object based on the structured road information of each source and a whisker algorithm;
and determining an object to be associated of the target object from at least one candidate object based on the whisker similarity.
2. The method of claim 1, wherein said calculating the whisker similarity between the tentacles of the target object and the tentacles of each candidate object based on the structured road information and the whisker algorithm of each source comprises:
determining an tentacle of the target object and an tentacle of each candidate object based on an tentacle algorithm;
determining partial tentacles included in the travelable region of the target object and partial tentacles included in the travelable region of each candidate object based on the structured road information of each source;
and respectively calculating the whisker similarity of the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object.
3. The method of claim 2, wherein the whisker similarity is achieved based on:
equally dividing part of tentacles in the travelable area of the target object to obtain at least one equally divided target tentacle;
equally dividing part of tentacles in the drivable area of the candidate object to obtain at least one equally divided candidate tentacle;
and calculating each equally divided target tentacle and equally divided candidate tentacle respectively to obtain at least one equally divided tentacle similarity, and obtaining the tentacle similarity based on the at least one equally divided tentacle similarity.
4. The method of any of claims 1-3, wherein the method further comprises:
in response to determining an object to be associated of the target object, associating the target object and the object to be associated;
and performing information fusion on the perception information corresponding to the target object and the perception information corresponding to the object to be associated to obtain fusion information of the target object.
5. A determination apparatus of an associated road object, comprising:
an acquisition module configured to acquire structured road information of different sources, wherein the structured road information includes a target object and at least one candidate object;
a computing module configured to compute whisker similarity between the tentacles of the target object and the tentacles of each candidate object based on the structured road information and the whisker algorithm of each source;
the determining module is configured to determine an object to be associated with the target object from at least one candidate object based on the whisker similarity.
6. The apparatus of claim 5, wherein the computing module is further configured to:
determining an tentacle of the target object and an tentacle of each candidate object based on an tentacle algorithm;
determining partial tentacles included in the travelable region of the target object and partial tentacles included in the travelable region of each candidate object based on the structured road information of each source;
and respectively calculating the whisker similarity of the partial tentacles included in the travelable region of the target object and the partial tentacles included in the travelable region of each candidate object.
7. The apparatus of claim 6, wherein the whisker similarity is achieved based on:
equally dividing part of tentacles in the travelable area of the target object to obtain at least one equally divided target tentacle;
equally dividing part of tentacles in the drivable area of the candidate object to obtain at least one equally divided candidate tentacle;
and calculating each equally divided target tentacle and equally divided candidate tentacle respectively to obtain at least one equally divided tentacle similarity, and obtaining the tentacle similarity based on the at least one equally divided tentacle similarity.
8. The apparatus of any of claims 5-7, wherein the apparatus further comprises:
the association module is configured to associate the target object and an object to be associated in response to determining the object to be associated of the target object;
and the fusion module is configured to perform information fusion on the perception information corresponding to the target object and the perception information corresponding to the object to be associated to obtain fusion information of the target object.
9. 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 1-4.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-4.
11. A roadside apparatus comprising the electronic apparatus of claim 9.
12. A cloud controlled platform comprising the electronic device of claim 9.
13. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-4.
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