CN117935595A - Vehicle-road cloud cooperation method, device, equipment and readable storage medium - Google Patents
Vehicle-road cloud cooperation method, device, equipment and readable storage medium Download PDFInfo
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Abstract
The invention discloses a vehicle-road cloud cooperation method, a device, equipment and a readable storage medium, wherein the scheme can comprise the following steps: at a first moment and a moment next to the first moment, the target edge cloud equipment acquires vehicle end sensing information sensed by each vehicle terminal and road side end sensing information sensed by each road side terminal in a monitored area to acquire a vehicle end sensing information set and a first road side end sensing information set; the method comprises the steps that an edge cloud device receives an information acquisition request sent by a target vehicle in a coverage area, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises driving auxiliary information, driving decision information or driving control information; the target edge cloud device responds to the information acquisition request based at least on track information of the different vehicles.
Description
Technical Field
The invention relates to the technical field of intelligent transportation, in particular to a vehicle-road cloud cooperation method, a device, equipment and a readable storage medium.
Background
Along with the rapid development of vehicle automation and interconnection technology, a vehicle-road cooperative device has become a key component for realizing an intelligent traffic system. Vehicle-road collaboration aims to improve traffic mobility, safety and efficiency through real-time communication and collaboration between vehicles and road infrastructure. Conventional vehicular collaborative systems typically rely on remote communication with a central server, and such architecture presents problems such as communication latency, security, scalability, and privacy protection.
Therefore, it is necessary to provide a new vehicle-road cloud cooperation method.
Disclosure of Invention
The invention provides a vehicle-road cloud cooperation method, device, equipment and readable storage medium, which are used for overcoming at least one technical problem in the prior art.
According to a first aspect of an embodiment of the present invention, there is provided a vehicle-road cloud cooperation method applied to an edge cloud device disposed in a target area, including:
At a first moment, the target edge cloud equipment acquires vehicle end sensing information sensed by each vehicle terminal and road side end sensing information sensed by each road side terminal in a monitored area of the target edge cloud equipment to obtain a first vehicle end sensing information set and a first road side end sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas;
The target edge cloud device correlates the first vehicle end perception information set and the first road side perception information set to obtain a first driving information set of different vehicles based on a vehicle end angle, wherein the first driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in a monitoring range of the target edge cloud device at the first moment;
At the next moment relative to the first moment, the target edge cloud device acquires vehicle end sensing information sensed by each vehicle terminal and road side sensing information sensed by each road side terminal in a monitored area of the target edge cloud device to obtain a second vehicle end sensing information set and a second road side sensing information set, and associates the second vehicle end sensing information set with the second road side sensing information set to obtain a second driving information set of different vehicles based on vehicle end angles; the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment;
acquiring track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set;
The edge cloud equipment receives an information acquisition request sent by a target vehicle in the coverage area, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises driving auxiliary information, driving decision information or driving control information;
the target edge cloud device responds to the information acquisition request based at least on track information of the different vehicles.
Before obtaining track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set, the method comprises the following steps:
Marking any two adjacent road side terminals at the installation position as a first road side terminal and a second road side terminal respectively, and for the first moment or the next moment relative to the first moment, associating the first road side terminal perceived information with the perceived information about the same vehicle terminal in the second road side terminal perceived information perceived by the first road side terminal, wherein the method specifically comprises the following steps:
Determining a first road side range of the first road side terminal, determining a second road side range of the second road side terminal, and determining a coverage overlapping area of road side coverage in the first road side range and the second road side range;
Determining third road side perception information of the first road side terminal in the coverage overlapping area, wherein the third road side perception information comprises first track information, first position information and first speed information of each vehicle in the coverage overlapping area perceived by the first road side terminal, and determining fourth road side perception information of the second road side terminal in the coverage overlapping area, and the fourth road side perception information comprises second track information, second position information and second speed information of each vehicle in the coverage overlapping area perceived by the second road side terminal;
And based on a Hungary algorithm, correlating the first track information, the first position information and the first speed information of each vehicle with the second track information, the second position information and the second speed information of each vehicle to obtain track information, position information and speed information of the same vehicle.
Preferably, before the target edge cloud device correlates the first vehicle-end sensing information set and the first road-side sensing information set, the target edge cloud device includes:
And aligning the vehicle end sensing information in the first vehicle end sensing information set with the road side sensing information in the first road side sensing information set in a time layer.
Preferably, for any one of the vehicle terminals, the first vehicle end sensing information set includes real-time position information, vehicle identification information, and vehicle end sensing information of the vehicle corresponding to the any one vehicle terminal; for any one of the road side terminals, the first road side sensing information set includes road side range information of the any one road side terminal and road side sensing information of the any one road side terminal;
the target edge cloud device associating the first vehicle-end sensing information set and the first road-side sensing information set specifically includes:
And taking the vehicle identification information as an index to obtain real-time position information of the vehicle corresponding to any vehicle identification information at the first moment, vehicle end perception information of the vehicle corresponding to any vehicle identification information and road side end perception information around the vehicle corresponding to any vehicle identification information.
Preferably, the obtaining track information of different vehicles in the time ranges of the first time and the second time based on the second driving information set and the first driving information set specifically includes:
and determining road side perception information around each vehicle at the first moment based on the first driving information set, determining road side perception information around each vehicle at the second moment based on the second driving information set, and determining track information of any one vehicle in the time range of the first moment and the second moment for the road side perception information around the first moment of any one vehicle based on the road side perception information around the first moment of any one vehicle and the road side perception information around the second moment of any one vehicle.
Preferably, a data caching module is arranged in the target edge cloud device, the data caching module is used for caching real-time data, and the target edge cloud device communicates with each vehicle terminal and each road side terminal based on a 5GUPF server.
According to a second aspect of the embodiment of the present invention, there is provided a vehicle-road cloud cooperation device, including:
The sensing information acquisition module is used for acquiring vehicle end sensing information sensed by each vehicle terminal and road side sensing information sensed by each road side terminal in a monitored area of the target edge cloud equipment at a first moment to obtain a first vehicle end sensing information set and a first road side sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas;
The first perception information association module is used for associating the first vehicle end perception information set and the first road side perception information set by the target edge cloud equipment to obtain a first driving information set of different vehicles based on a vehicle end angle, wherein the first driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in a monitoring range of the target edge cloud equipment at the first moment;
The second perception information association module is used for acquiring vehicle end perception information perceived by each vehicle terminal and road side perception information perceived by each road side terminal in a monitored area of the target edge cloud equipment at the next moment relative to the first moment to obtain a second vehicle end perception information set and a second road side perception information set, and associating the second vehicle end perception information set with the second road side perception information set to obtain a second driving information set of different vehicles based on vehicle end angles; the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment;
The track information analysis module is used for obtaining track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set;
The information acquisition request receiving module is used for receiving an information acquisition request sent by a target vehicle in the coverage area by the edge cloud equipment, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises one of driving auxiliary information, driving decision information or driving control information;
And the information acquisition request response module is used for responding to the information acquisition request by the target edge cloud equipment at least based on track information of different vehicles.
Preferably, the device further includes an information alignment module, where the information alignment module is configured to perform time-plane alignment on the vehicle-end sensing information in the first vehicle-end sensing information set and the road-side sensing information in the first road-side sensing information set before the target edge cloud device correlates the first vehicle-end sensing information set and the first road-side sensing information set.
According to a third aspect of the embodiment of the present invention, there is provided a vehicle-road cloud cooperative apparatus, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the vehicle-road cooperative method set forth above when executing the program.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable storage medium having stored thereon a computer program, characterized in that the program when executed by a processor implements the steps of the vehicle road coordination method set forth above.
One embodiment of the present disclosure can achieve at least the following advantages: according to the vehicle-road cloud cooperative scheme provided by the technical scheme of the invention, the existing vehicle and road infrastructure are adopted, and an additional special communication network is not required to be built. The method is based on the utilization of the existing network infrastructure, reduces the cost of network construction and operation, and simultaneously, because the target edge cloud equipment is arranged at the edge position, compared with the traditional centralized deployment mode, the method reduces the cost of communication and transmission due to the fact that the deployment position is closer to the communication distance between the vehicle and the road, and can avoid the high delay and high bandwidth cost required by long-distance communication and transmission.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a vehicle-road cloud collaboration method according to an embodiment of the present disclosure;
Fig. 2 is a schematic structural diagram of a vehicle-road cloud cooperative device corresponding to fig. 1 according to an embodiment of the present disclosure;
Fig. 3 is a schematic structural diagram of a vehicle-road cloud cooperative device corresponding to fig. 1 according to an embodiment of the present disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of one or more embodiments of the present specification more clear, the technical solutions of one or more embodiments of the present specification will be clearly and completely described below in connection with specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present specification. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without undue burden, are intended to be within the scope of one or more embodiments herein.
It should be understood that although the terms first, second, third, etc. may be used in this document to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another.
In order to solve the drawbacks of the prior art, the present solution provides the following embodiments:
fig. 1 is a schematic flow chart of a vehicle-road cloud collaboration method applied to an edge cloud device disposed in a target area according to an embodiment of the present disclosure. From the program perspective, the execution subject of the flow may be a program of a server mounted on the edge cloud device.
As shown in fig. 1, the process may include the following steps.
Step 102: at a first moment, the target edge cloud equipment acquires vehicle end sensing information sensed by each vehicle terminal and road side end sensing information sensed by each road side terminal in a monitored area of the target edge cloud equipment to obtain a first vehicle end sensing information set and a first road side end sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas.
In the embodiment of the specification, the target edge cloud device can be deployed at the edge positions of vehicles and road infrastructures and is used for receiving the perception information reported by each vehicle terminal and each road side terminal in a local range, and because the target edge cloud device is arranged at the edge positions, compared with a traditional centralized deployment mode, the cost of communication and transmission is reduced because the deployment position is closer to the communication distance between the vehicles and the roads, and the high delay and high bandwidth cost required by long-distance communication and transmission can be avoided. Various vehicle terminals such as vehicle-mounted sensors for sensing driving environment information around the vehicle can be mounted on the vehicle, and the sensed driving environment information can be reported to the target edge cloud device through the vehicle terminals. Similarly, the road side terminals can monitor traffic conditions in real time through equipment such as cameras, sensors and the like, including traffic flow, speed, congestion and the like, and each road side terminal in the monitoring range of the target edge cloud equipment can report perceived road side perception information to the target edge cloud equipment, so that the target edge cloud equipment can perform unified storage and processing. Because each of the road side terminals is used for sensing the road traffic environment information within a range of a path, the road side coverage areas of two adjacent road side terminals can have a certain overlap so as to fully and completely sense the traffic environment information of different paths. In an alternative embodiment, the target edge cloud device may communicate with the road infrastructure in order to obtain data and information of the road infrastructure. In the communication process, a communication module (such as an LTE module, a Wi-Fi module, etc.) on the target edge cloud device and a communication device (such as a traffic light, a roadside base station, etc.) of the road infrastructure need to perform data interaction and communication according to related communication protocols (such as LTE, DSRC, 5G, etc.). The target edge cloud device also needs to communicate with the vehicle to acquire the state and position information of the vehicle, and can establish communication connection with the vehicle by using a vehicle Wi-Fi module or a vehicle Bluetooth module, acquire real-time data of the vehicle by means of wireless technology (such as Wi-Fi, bluetooth, vehicle ad hoc network and the like), and realize data transmission and reception based on communication protocols (such as IEEE 802.11p and Bluetooth V2X).
Step 104: the target edge cloud device correlates the first vehicle end perception information set and the first road side perception information set to obtain a first driving information set of different vehicles based on a vehicle end angle, wherein the first driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in a monitoring range of the target edge cloud device at the first moment.
In this embodiment of the present disclosure, for any one of the vehicle terminals, the first set of vehicle-end sensing information may include real-time location information, vehicle identification information, and vehicle-end sensing information of a vehicle corresponding to the any one vehicle terminal; for any one of the road side terminals, the first road side sensing information set includes road side range information of the any one road side terminal and road side sensing information of the any one road side terminal.
Based on the foregoing, the associating, by the target edge cloud device, the first vehicle-end perceived information set and the first road-side perceived information set may specifically include: and taking the vehicle identification information as an index to obtain real-time position information of the vehicle corresponding to any vehicle identification information at the first moment, vehicle end perception information of the vehicle corresponding to any vehicle identification information and road side end perception information around the vehicle corresponding to any vehicle identification information.
Step 106: at the next moment relative to the first moment, the target edge cloud device acquires vehicle end sensing information sensed by each vehicle terminal and road side sensing information sensed by each road side terminal in a monitored area of the target edge cloud device to obtain a second vehicle end sensing information set and a second road side sensing information set, and associates the second vehicle end sensing information set with the second road side sensing information set to obtain a second driving information set of different vehicles based on vehicle end angles; and the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment.
In this step, the method in step 102 may be referred to, and various data required for the next time relative to the first time are collected, which will not be described herein.
Step 108: and obtaining track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set.
In this embodiment of the present disclosure, the road side sensing information around each vehicle at the first time may be determined based on the first driving information set, the road side sensing information around each vehicle at the second time may be determined based on the second driving information set, and for any one of the vehicles, the track information of the any one vehicle in the time ranges of the first time and the second time may be determined based on the road side sensing information around the any one vehicle at the first time and the road side sensing information around the any one vehicle at the second time, so that the track information of different vehicles in the time ranges of the first time and the second time may be obtained.
Step 110: the edge cloud device receives an information acquisition request sent by a target vehicle in the coverage area, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises driving auxiliary information, driving decision information or driving control information.
In the embodiment of the present disclosure, the difference in the perception capability of different vehicles to the external driving environment or the difference in the calculation power of different vehicles in the actual scene is considered, and a part of vehicles cannot autonomously perform the driving decision or the driving control work, so that in this step, from the perspective of the cloud control platform, the information acquisition requests received by the cloud control platform may be various, in other words, the information acquisition requests sent by the vehicles may be various. Accordingly, the driving demand information included in the information acquisition request may be various, and in the present embodiment, it may be any one of driving assistance information, driving decision information, or driving control information.
Step 112: the target edge cloud device responds to the information acquisition request based at least on track information of the different vehicles.
The method of fig. 1, employing existing vehicle and road infrastructure, does not require the construction of additional private communication networks. The method is based on the utilization of the existing network infrastructure, reduces the cost of network construction and operation, and simultaneously, because the target edge cloud equipment is arranged at the edge position, compared with the traditional centralized deployment mode, the method reduces the cost of communication and transmission due to the fact that the deployment position is closer to the communication distance between the vehicle and the road, and can avoid the high delay and high bandwidth cost required by long-distance communication and transmission.
The examples of the present specification also provide some specific embodiments of the method based on the method of fig. 1, which is described below.
In an optional embodiment, before the target edge cloud device associates the first vehicle-end sensing information set and the first road side sensing information set, the method may include:
And aligning the vehicle end sensing information in the first vehicle end sensing information set with the road side sensing information in the first road side sensing information set in a time layer.
In an optional embodiment, a data caching module is arranged in the target edge cloud device, the data caching module is used for caching real-time data, and the target edge cloud device communicates with each vehicle terminal and each road side terminal based on a 5GUPF server. The target edge cloud equipment and the road side terminal perform data interaction through UPF, the UPF equipment can support two access modes of 5G wireless access and wired access, and network transmission delay is low. And the target edge cloud equipment receives the sensing data uploaded by each road side computing unit in the area range, performs data fusion, and provides real-time suggestion data for the network-connected vehicles in the coverage area of the target edge cloud equipment.
In an alternative embodiment, the target edge cloud device may perform local data processing by using computing resources on the edge device set on the device, and design a data receiving and analyzing module according to needs, so as to receive and analyze data sent by vehicles and road infrastructures, and may also use data preprocessing technologies, such as filtering, interpolation and correction, to improve data quality, perform data format conversion and standardization by using appropriate data formats and protocols, and apply data mining, machine learning and artificial intelligence technologies to analyze the data and extract useful information.
Then, the target edge cloud device needs to temporarily store and cache data on the edge device so as to improve the processing efficiency and response speed of real-time data, and a proper storage medium such as a solid state disk can be selected for storing a certain amount of data on the edge device. A buffer mechanism, such as a buffer, is established for temporarily storing and managing real-time data. Data management, including data writing, updating, and flushing policies, is performed using a caching algorithm. And then the target edge cloud equipment needs to take corresponding security measures to protect the security and privacy of the data. The method comprises the steps of using a data encryption algorithm, establishing an identity authentication and access control mechanism, applying a secure communication protocol and the like, guaranteeing data privacy and information security of vehicles and drivers, and finally realizing cooperative processing and decision between the vehicles and road infrastructure by the target edge cloud equipment. According to the data sent by the vehicles and the road infrastructure, the edge equipment can conduct data analysis and model reasoning so as to make real-time traffic control and management decisions, such as adjustment of traffic light states, road condition optimization and the like.
The foregoing illustrates that the coverage areas of the adjacent two road side terminals have overlapping areas, and the following illustrates that the adjacent two road side terminals fuse the information of the same network-connected vehicle by taking a practical example as an example.
In an optional embodiment, before the obtaining track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set, the method may include:
Marking any two adjacent road side terminals at the installation position as a first road side terminal and a second road side terminal respectively, and for the first moment or the next moment relative to the first moment, associating the first road side perception information perceived by the first road side terminal with the perception information about the same vehicle terminal in the second road side perception information perceived by the second road side terminal, wherein the method specifically may include:
Determining a first road side range of the first road side terminal, determining a second road side range of the second road side terminal, and determining a coverage overlapping area of road side coverage in the first road side range and the second road side range;
Determining third road side perception information of the first road side terminal in the coverage overlapping area, wherein the third road side perception information comprises first track information, first position information and first speed information of each vehicle in the coverage overlapping area perceived by the first road side terminal, and determining fourth road side perception information of the second road side terminal in the coverage overlapping area, and the fourth road side perception information comprises second track information, second position information and second speed information of each vehicle in the coverage overlapping area perceived by the second road side terminal;
And based on a Hungary algorithm, correlating the first track information, the first position information and the first speed information of each vehicle with the second track information, the second position information and the second speed information of each vehicle to obtain track information, position information and speed information of the same vehicle.
Taking a 300m long road segment as an example, there are two road side terminals, and each device perceives an object within 150m (the actual perceived range is 180 m). The target edge cloud equipment is responsible for carrying out data fusion on targets in the overlapping area perceived by the two edge equipment, and ensuring that the information of the targets in the overlapping area is unique. Specifically, how to determine that the target is in the overlapping area can be determined by a fusion rule, if the position of the target meets the condition of data fusion, the target can be subjected to data fusion, the determination of the fusion rule (whether the position of the target is in the fusion area or not) is an important precondition for the fusion algorithm, and the calculation mode of the fusion rule is performed according to the following mode:
Assuming that 100 vehicles pass through a sensing area of a road side terminal, the distance between each device and the road side terminal is Dn (n=1-100), and a least square method is adopted to estimate the normal distribution of the distances: f (D; μ, σ) = (1/(σ×sqrt (2pi))) exp (- (D- μ)/(2/(2σ+2)), where μ represents the mean value, σ represents the standard deviation, and from this normal distribution, the minimum and maximum distances that the target can perceive in the sensing region of an edge device can be derived (minimum, i.e. left threshold (at 95% confidence level): minimum = μ -1.96 x σ), maximum, i.e. right threshold (at 95% confidence level): maximum = μ+1.96 x σ). Because the overlapping area is arranged between the road side terminals, the target with the minimum (or relatively smaller) distance perceived by a certain perception device is necessarily the target with the maximum (or relatively larger) distance perceived by a certain road side terminal, so that the target in the overlapping area is in certain connection with the corresponding two (or more) road side terminals, and the target connected with the plurality of perception devices can be sent into a fusion algorithm for data fusion. With the continuous increase of the number of samples, the statistics and calculation of the target edge cloud equipment on the fusion rule are increasingly accurate, the accuracy judgment on the target to be fused is more accurate, the fusion effect is better, and the forward driving function is achieved on the follow-up tracking and collaborative decision algorithm.
Based on the same thought, the embodiment of the specification also provides a device corresponding to the method. Fig. 2 is a schematic structural diagram of a vehicle-road cloud cooperative device corresponding to fig. 1 according to an embodiment of the present disclosure. As shown in fig. 2, the apparatus may include:
The sensing information obtaining module 202 is configured to obtain, at a first moment, vehicle end sensing information sensed by each vehicle terminal and road side end sensing information sensed by each road side terminal in a monitored area of the target edge cloud device, to obtain a first vehicle end sensing information set and a first road side end sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas.
The first perceived information association module 204 is configured to associate the first vehicle-end perceived information set with the first road-side perceived information set by using the target edge cloud device, so as to obtain a first driving information set of different vehicles based on a vehicle-end angle, where the first driving information set at least includes speed information, position information and driving environment information of each vehicle in different vehicles within a monitoring range of the target edge cloud device at the first moment.
A second perceived information association module 206, configured to, at a time next to the first time, obtain, by the target edge cloud device, vehicle end perceived information perceived by each vehicle terminal and road side perceived information perceived by each road side terminal in a monitored area of the target edge cloud device, obtain a second vehicle end perceived information set and a second road side perceived information set, associate the second vehicle end perceived information set with the second road side perceived information set, and obtain a second driving information set of different vehicles based on a vehicle end angle; and the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment.
The track information analysis module 208 is configured to obtain track information of different vehicles within the time ranges of the first time and the second time based on the second driving information set and the first driving information set.
The information acquisition request receiving module 210 is configured to receive an information acquisition request sent by a target vehicle in the coverage area by using the edge cloud device, where the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information includes one of driving assistance information, driving decision information, and driving control information.
An information acquisition request response module 212, configured to respond to the information acquisition request by the target edge cloud device based at least on track information of the different vehicles.
In an alternative embodiment, the apparatus may further include an information alignment module, where the information alignment module is configured to perform time-plane alignment on the vehicle end sensing information in the first vehicle end sensing information set and the road side sensing information in the first road side sensing information set before the target edge cloud device correlates the first vehicle end sensing information set and the first road side sensing information set.
It will be appreciated that each of the modules described above refers to a computer program or program segment for performing one or more particular functions. Furthermore, the distinction of the above-described modules does not represent that the actual program code must also be separate.
Based on the same thought, the embodiment of the specification also provides equipment corresponding to the method.
Fig. 3 is a schematic structural diagram of a vehicle-road cloud cooperative device provided in an embodiment of the present disclosure. As shown in fig. 3, this hardware device may include:
At least one processor 310; and
A memory 330 communicatively coupled to the at least one processor; wherein,
The memory 330 stores instructions 320 executable by the at least one processor 310 to enable the hardware device to:
At a first moment, the target edge cloud equipment acquires vehicle end sensing information sensed by each vehicle terminal and road side end sensing information sensed by each road side terminal in a monitored area of the target edge cloud equipment to obtain a first vehicle end sensing information set and a first road side end sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas;
The target edge cloud device correlates the first vehicle end perception information set and the first road side perception information set to obtain a first driving information set of different vehicles based on a vehicle end angle, wherein the first driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in a monitoring range of the target edge cloud device at the first moment;
At the next moment relative to the first moment, the target edge cloud device acquires vehicle end sensing information sensed by each vehicle terminal and road side sensing information sensed by each road side terminal in a monitored area of the target edge cloud device to obtain a second vehicle end sensing information set and a second road side sensing information set, and associates the second vehicle end sensing information set with the second road side sensing information set to obtain a second driving information set of different vehicles based on vehicle end angles; the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment;
acquiring track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set;
The edge cloud equipment receives an information acquisition request sent by a target vehicle in the coverage area, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises driving auxiliary information, driving decision information or driving control information;
the target edge cloud device responds to the information acquisition request based at least on track information of the different vehicles.
The embodiment of the invention also provides a computer readable storage medium, which stores computer readable instructions, wherein the computer readable instructions can be executed by a processor to realize a vehicle road cloud cooperation method.
Those of ordinary skill in the art will appreciate that: the drawing is a schematic diagram of one embodiment and the modules or flows in the drawing are not necessarily required to practice the invention.
Those of ordinary skill in the art will appreciate that: the modules in the apparatus of the embodiments may be distributed in the apparatus of the embodiments according to the description of the embodiments, or may be located in one or more apparatuses different from the present embodiments with corresponding changes. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. The vehicle-road cloud cooperation method is applied to edge cloud equipment arranged in a target area, and is characterized by comprising the following steps of:
At a first moment, the target edge cloud equipment acquires vehicle end sensing information sensed by each vehicle terminal and road side end sensing information sensed by each road side terminal in a monitored area of the target edge cloud equipment to obtain a first vehicle end sensing information set and a first road side end sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas;
The target edge cloud device correlates the first vehicle end perception information set and the first road side perception information set to obtain a first driving information set of different vehicles based on a vehicle end angle, wherein the first driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in a monitoring range of the target edge cloud device at the first moment;
At the next moment relative to the first moment, the target edge cloud device acquires vehicle end sensing information sensed by each vehicle terminal and road side sensing information sensed by each road side terminal in a monitored area of the target edge cloud device to obtain a second vehicle end sensing information set and a second road side sensing information set, and associates the second vehicle end sensing information set with the second road side sensing information set to obtain a second driving information set of different vehicles based on vehicle end angles; the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment;
acquiring track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set;
The edge cloud equipment receives an information acquisition request sent by a target vehicle in the coverage area, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises driving auxiliary information, driving decision information or driving control information;
the target edge cloud device responds to the information acquisition request based at least on track information of the different vehicles.
2. The vehicle-road cloud cooperation method according to claim 1, wherein before obtaining track information of different vehicles in the first time and the second time ranges based on the second driving information set and the first driving information set, the method comprises:
Marking any two adjacent road side terminals at the installation position as a first road side terminal and a second road side terminal respectively, and for the first moment or the next moment relative to the first moment, associating the first road side terminal perceived information with the perceived information about the same vehicle terminal in the second road side terminal perceived information perceived by the first road side terminal, wherein the method specifically comprises the following steps:
Determining a first road side range of the first road side terminal, determining a second road side range of the second road side terminal, and determining a coverage overlapping area of road side coverage in the first road side range and the second road side range;
Determining third road side perception information of the first road side terminal in the coverage overlapping area, wherein the third road side perception information comprises first track information, first position information and first speed information of each vehicle in the coverage overlapping area perceived by the first road side terminal, and determining fourth road side perception information of the second road side terminal in the coverage overlapping area, and the fourth road side perception information comprises second track information, second position information and second speed information of each vehicle in the coverage overlapping area perceived by the second road side terminal;
And based on a Hungary algorithm, correlating the first track information, the first position information and the first speed information of each vehicle with the second track information, the second position information and the second speed information of each vehicle to obtain track information, position information and speed information of the same vehicle.
3. The vehicle-road cloud coordination method according to claim 1, wherein before the target edge cloud device correlates the first vehicle-end perceived information set and the first road-side perceived information set, the method comprises:
And aligning the vehicle end sensing information in the first vehicle end sensing information set with the road side sensing information in the first road side sensing information set in a time layer.
4. The vehicle-road cloud cooperation method according to claim 1, wherein, for any one of the vehicle terminals, the first vehicle-end sensing information set includes real-time position information, vehicle identification information, and vehicle-end sensing information of a vehicle corresponding to the any one vehicle terminal; for any one of the road side terminals, the first road side sensing information set includes road side range information of the any one road side terminal and road side sensing information of the any one road side terminal;
the target edge cloud device associating the first vehicle-end sensing information set and the first road-side sensing information set specifically includes:
And taking the vehicle identification information as an index to obtain real-time position information of the vehicle corresponding to any vehicle identification information at the first moment, vehicle end perception information of the vehicle corresponding to any vehicle identification information and road side end perception information around the vehicle corresponding to any vehicle identification information.
5. The vehicle-road cloud cooperation method according to claim 4, wherein the obtaining track information of different vehicles in the first time and the second time ranges based on the second driving information set and the first driving information set specifically includes:
and determining road side perception information around each vehicle at the first moment based on the first driving information set, determining road side perception information around each vehicle at the second moment based on the second driving information set, and determining track information of any one vehicle in the time range of the first moment and the second moment for the road side perception information around the first moment of any one vehicle based on the road side perception information around the first moment of any one vehicle and the road side perception information around the second moment of any one vehicle.
6. The vehicle-road cloud cooperation method according to claim 1, wherein a data caching module is arranged in the target edge cloud device, the data caching module is used for caching real-time data, and the target edge cloud device communicates with each vehicle terminal and each road side terminal based on a 5GUPF server.
7. A vehicle road cloud cooperative apparatus, characterized in that the apparatus comprises:
The sensing information acquisition module is used for acquiring vehicle end sensing information sensed by each vehicle terminal and road side sensing information sensed by each road side terminal in a monitored area of the target edge cloud equipment at a first moment to obtain a first vehicle end sensing information set and a first road side sensing information set; the target edge cloud equipment stores the vehicle end perception information and the road side perception information in a data storage module of the target edge cloud equipment; different road side terminals in the road side terminals have different road side coverage areas, and the road side coverage areas of any two adjacent road side terminals in the installation positions of the road side terminals have overlapping areas;
The first perception information association module is used for associating the first vehicle end perception information set and the first road side perception information set by the target edge cloud equipment to obtain a first driving information set of different vehicles based on a vehicle end angle, wherein the first driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in a monitoring range of the target edge cloud equipment at the first moment;
The second perception information association module is used for acquiring vehicle end perception information perceived by each vehicle terminal and road side perception information perceived by each road side terminal in a monitored area of the target edge cloud equipment at the next moment relative to the first moment to obtain a second vehicle end perception information set and a second road side perception information set, and associating the second vehicle end perception information set with the second road side perception information set to obtain a second driving information set of different vehicles based on vehicle end angles; the second driving information set at least comprises speed information, position information and driving environment information of each vehicle in different vehicles in the monitoring range of the target edge cloud equipment at the second moment;
The track information analysis module is used for obtaining track information of different vehicles in the time ranges of the first moment and the second moment based on the second driving information set and the first driving information set;
The information acquisition request receiving module is used for receiving an information acquisition request sent by a target vehicle in the coverage area by the edge cloud equipment, wherein the information acquisition request at least carries driving requirement information of the target vehicle, and the driving requirement information comprises one of driving auxiliary information, driving decision information or driving control information;
And the information acquisition request response module is used for responding to the information acquisition request by the target edge cloud equipment at least based on track information of different vehicles.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method steps of any of claims 1 to 6 when the program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method steps of any of claims 1-6.
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