CN115100852A - High-availability roadside fusion sensing system and method for serving intelligent networked automobile - Google Patents
High-availability roadside fusion sensing system and method for serving intelligent networked automobile Download PDFInfo
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Abstract
The application provides a high available roadside fusion perception system for intelligent networked automobiles, which adopts a plurality of all-in-one machine for thunderbolt perception to acquire perception fusion data of intersections. A wireless ad hoc network is formed by the wireless transmission module and the data collection module. Based on the wireless ad hoc network, the data collection module acquires multi-channel perception fusion data. Based on 5G mobile communication, the data collection module sends the multi-channel perception fusion data to the background end. By means of the global coverage and unicast communication capacity of the 5G network, the background end provides different real-time data (roadside full-view perception data) for each vehicle end, and vehicle-road cooperative fusion perception and fusion regulation data closed loop serving for a single vehicle is achieved. The sensing fusion data of the intersection are backed up to the background end through the data collection module of the adjacent intersection, so that high reliability of data transmission is realized. The integrated machine for the radar vision sensing + the wireless ad hoc network +5G achieves low road side transformation cost, reliable data transmission and low time delay, and can realize the driving and the driving of vehicles.
Description
Technical Field
The application relates to the field of intelligent traffic, in particular to a high-availability road side fusion perception system and method for serving intelligent networked automobiles.
Background
Automatic driving has become a current trend in line with the development of intelligent automobiles in China, for example, automatic driving based on vehicle-road coordination. Based on the cooperative automatic driving of the vehicle and the road, road data is sent to the vehicle end for the road side infrastructure through broadcasting, and the vehicle end adjusts the driving state based on the received road data. The core idea of intelligent road service vehicle is realized through road side infrastructure, and the rapid digital road modification of the intelligent road becomes urgent.
Therefore, it is necessary to provide a high-availability roadside reconstruction overall solution based on full wireless, reduce reconstruction cost and improve roadside service capability; and, based on 5G base station laying of operator and 5G as the direction that national strategy vigorously advances, realize 5G universe coverage basically, still necessarily combine 5G to provide the whole solution of high available road side transformation.
Disclosure of Invention
The application aims to provide a high-availability road side fusion perception system and method for serving an intelligent networked automobile, and the system and method are used for solving the problems.
The first aspect of the embodiment of the application provides a high available road side fusion perception system for serving an intelligent networked automobile, the system comprises:
a plurality of perceptual computation modules: the system comprises a monitoring unit, a fusion unit and a data processing unit, wherein the monitoring unit is used for monitoring different positions of a first intersection to acquire perception fusion data of each position;
a plurality of wireless transmission modules: each wireless transmission module is connected with a perception calculation module;
a data collection module: it and said plurality of wireless transmission modules form a wireless ad hoc network; the data collection module is a central node of the wireless ad hoc network, and each wireless transmission module is a non-central node of the wireless ad hoc network; based on the wireless ad hoc network, the data collection module collects multi-path perception fusion data of the first intersection;
a back desk end: based on 5G mobile communication, receiving the multi-path perception fusion data of the first intersection forwarded by the data collection module; processing the received multi-channel perception fusion data to obtain a perception result; when communicating with a vehicle end, the background end sends a perception result of a corresponding position to the vehicle end based on the position of the vehicle end.
Optionally, the data collection module is located at the first intersection; the system further comprises:
a plurality of standby wireless transmission modules: each standby wireless transmission module is connected with a perception calculation module;
the standby wireless transmission modules and the standby data collection module form a standby wireless ad hoc network, and the standby data collection module is a data collection module of a second intersection; the standby data collection module is a central node of a standby wireless ad hoc network, and each standby wireless transmission module is a non-central node of the standby wireless ad hoc network;
based on the standby wireless ad hoc network, the standby data collection module collects the multi-channel perception fusion data of the first intersection, and then forwards the multi-channel perception fusion data of the first intersection based on 5G mobile communication.
Optionally: and the wireless transmission module and the standby wireless transmission module which are connected with the same perception calculation module are positioned in the same circuit board.
Optionally, the second intersection is an intersection within a preset range of the first intersection, and the preset range is determined according to a signal coverage range of the standby wireless ad hoc network.
Optionally: the perception calculation module comprises a thunder and vision perception all-in-one machine.
Optionally: the data aggregation module is further configured to: and performing space-time alignment on the multi-channel perception fusion data of the first intersection, generating a data packet according to the multi-channel perception fusion data after the space-time alignment, and forwarding the data packet to the background end based on 5G mobile communication.
Optionally, the back end is further configured to: and sending the perception result of the corresponding position to the vehicle end based on the position of the vehicle end through 5G mobile communication.
The first aspect of the embodiment of the application provides a high-availability roadside fusion perception method for serving intelligent networked automobiles, and the method comprises the following steps:
monitoring a plurality of positions of a first intersection through a plurality of perception calculation modules to obtain multi-path perception fusion data corresponding to the positions;
transmitting the multi-channel perception fusion data to a data collection module through a wireless ad hoc network; the wireless ad hoc network comprises a plurality of wireless transmission modules and a data collection module, and the wireless transmission modules are connected with corresponding perception calculation modules;
based on 5G mobile communication, the multi-channel perception fusion data are sent to a background end through the data collection module;
processing the multi-channel perception fusion data through the background end to obtain a perception result;
when communicating with a vehicle end, sending a perception result of a corresponding position to the vehicle end through the background end based on the position of the vehicle end.
Optionally, the data collection module is located at the first intersection; the method further comprises the following steps:
transmitting the multi-channel perception fusion data to a standby data collection module through a standby wireless ad hoc network; the standby wireless ad hoc network comprises a plurality of standby wireless transmission modules and a standby data collection module, the standby wireless transmission modules are connected with the corresponding perception calculation modules, and the standby data collection module is a data collection module of a second intersection;
and based on 5G mobile communication, the multi-channel perception fusion data is sent to a background end through the standby data collection module.
Optionally, the method further comprises:
and based on 5G mobile communication, sending a perception result of the corresponding position to the vehicle end through the background end based on the position of the vehicle end.
The high available road side fusion perception system and method for the high available road side system based on the wireless network to serve the intelligent networked automobile, provided by the embodiment of the application, have the following advantages:
1. by adopting the all-in-one machine for sensing the thunder, the problems of overlong time delay of video coding and decoding and time-space synchronization of a radar and a camera facing a single intersection are solved.
2. The problem that optical fiber transmission needs to be laid is solved through a wireless ad hoc network between equipment, and the roadside construction cost is reduced to a great extent.
3. Based on 5G base station laying of operators and the direction of 5G as national strategy vigorous promotion, 5G global coverage is basically realized.
4. Compared with PC5 broadcasting, the vehicle-side data customization service system is based on the 5G characteristic and has the single-point communication capability, so that the data pushing capability facing to a single vehicle can be realized, the customized vehicle-side data service can be established, and the road-side service capability can be improved.
5. Compared with PC5 broadcasting, the wide-area coverage broadcasting and processing method is based on the 5G characteristic, wide-area coverage broadcasting and processing stability can be achieved, and roadside service capability is improved.
It is to be understood that: in this application, through the whole solution of high available roadside transformation that adopts full wireless (wireless ad hoc network +5G private network), a plurality of equipment pass through wireless ad hoc network and wireless transmission technologies such as 5G, carry out the communication interaction with the full traffic element that the roadside perception was arrived to very big improvement the wisdom road and transformed required time, accomplished really that move less, highly available theory, realized hanging along with the core theory of usefulness.
Drawings
Fig. 1 schematically shows a component configuration diagram of a roadside system in the related art;
fig. 2 schematically illustrates a high-availability roadside fusion perception system serving an intelligent networked automobile according to a first embodiment of the application;
FIG. 3 is a diagram schematically illustrating component configuration in a high-availability roadside fusion perception system serving an intelligent networked automobile according to a first embodiment of the application;
FIG. 4 is a flowchart of the operation of the system according to the first embodiment;
FIG. 5 is a diagram schematically illustrating component configuration in a high-availability roadside fusion perception system serving an intelligent networked automobile according to the second embodiment of the application;
fig. 6 schematically shows a flowchart of a high-availability roadside fusion perception method for serving an intelligent networked automobile according to a third embodiment of the present application;
fig. 7 schematically shows a hardware architecture diagram of a computer device corresponding to the torpedo all-in-one machine, the wireless transmission module, the background end, the data collection module or the vehicle end.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the descriptions relating to "first", "second", "third", etc. in this application are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicit to the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
In the description of the present application, it should be understood that the numerical references before the steps do not identify the order of performing the steps, but merely serve to facilitate the description of the present application and to distinguish each step, and therefore should not be construed as limiting the present application.
The following are explanations of terms of the present application:
wireless Ad-Hoc Network (Wireless Ad-Hoc Network): the network is a multi-hop mobility peer-to-peer network which is composed of several to dozens of nodes, adopts a wireless communication mode and is dynamically networked. The aim is to transport voice streams with quality of service requirements by means of dynamic routing and mobility management techniques. Usually, the nodes have continuous energy supply without fixed equipment support, and each node is self-organized. During communication, other user nodes forward data.
All-in-one machine is known to thunder vision: a set of cameras and millimeter wave radars/laser radars and the like meeting the detection requirements are integrated, and the space-time synchronization of the orientation of a single intersection and the output of the result of fusion perception are realized through a high-integration-level radar vision perception all-in-one machine.
A wireless transmission module: the method comprises the steps of obtaining relevant data of the all-in-one machine through communication with the all-in-one machine for the thunderbolt vision sensing, and sending the data to a central node through a wireless ad hoc network. It should be noted that the wireless transmission module may be built in or externally connected.
A data collection module: the central node of the wireless ad hoc network has 5G communication transmission capacity, performs space-time alignment and packaging on multi-interface-oriented perception fusion data collected by the ad hoc network, and transmits the data to the computing unit through 5G.
The RSU (Road Side Unit) is installed at the roadside and can communicate with the On Board Unit (OBU) by using dsrc (dedicated Short Range communication) technology.
The MEC (Mobile Edge Computing) unit can effectively identify targets such as vehicle ends, non-motor vehicles, pedestrians and the like in a road and provide key information such as the position, direction, speed and the like of the targets by using original data such as videos, point clouds and the like collected by a camera, a radar and the like and by means of a built-in high-performance GPU and AI algorithm.
And the MEC unit is divided into an edge cloud and a roadside hardware unit arranged at the intersection. Based on the capital construction cost, the method adopts edge cloud.
In order to facilitate those skilled in the art to understand the technical solutions provided in the embodiments of the present application, the following description is provided for the related technologies:
as shown in fig. 1, the intelligent road modification with vehicle-road cooperation can perform communication interaction of road side information by using RSU + optical fiber networking.
The method comprises the following specific steps:
traffic light data (e.g., traffic light status) is read by roadside signal readers.
Secondly, reading road side traffic element data through a split camera and a radar respectively, for example: video, point cloud data.
And thirdly, the signal lamp data and the road test traffic element data are transmitted to the MEC unit arranged at the intersection through the optical fiber by the switchboard arranged in the comprehensive cabinet for data interaction.
And fourthly, the MEC unit arranged at the intersection processes, identifies and fuses various multi-channel sensor data based on high computational power, and outputs a final reliable traffic element sensing result.
The exchanger sends the result obtained by the MEC unit arranged at the intersection to the RSU according to the networking address.
Sixthly, the RSU broadcasts the packaged data to a vehicle end with PC5 capability within the coverage range (about 200 meters) through a specific frequency band of 5.9 Ghz.
The inventor thinks that the intelligent road reconstruction scheme based on the vehicle-road cooperation has the following defects:
1. the split radar and the camera have the problems of overlong video coding and decoding time delay and air-to-air alignment.
2. Data of the camera and the radar need to be transmitted through optical fibers, and for the reconstruction of a newly added intersection, the optical fibers need to be additionally laid.
3. The RSU is arranged at the intersection and is used as the attribute of a base station, so that RSU transmission has a certain range and cannot be spread in wide-area coverage.
The RSU PC5 protocol is a broadcasting type, has uniform data content and does not have a single-vehicle subscription or a single-vehicle push-oriented service.
In view of the above-mentioned drawbacks of the related art, the present application will provide a high-availability roadside reconstruction overall solution based on full wireless, specifically as follows:
1. by adopting the all-in-one machine for sensing the thunder, the problems of overlong time delay of video coding and decoding and time-space synchronization of a radar and a camera facing a single intersection are solved.
2. The problem that optical fiber transmission needs to be laid is solved through the ad hoc network among the devices, and the roadside construction cost is reduced to a great extent.
3. Based on 5G base station laying of operators and the direction of 5G as national strategy vigorous promotion, 5G global coverage is basically realized.
4. Based on the 5G characteristic, the system has the capability of single-point communication, can realize the data pushing capability facing to a single vehicle, and further establishes the service of customizing the data at the vehicle end.
5. Based on the 5G characteristics, the capability of wide-area coverage propagation (unlimited distance) can be achieved.
In the following, the present application will specifically introduce a whole solution for high-availability roadside reconstruction based on full wireless through several embodiments.
Example one
The embodiment can be applied to application scenes such as automatic driving and intelligent transportation in computer technology.
As shown in fig. 2, a high availability roadside system based on full wireless is schematically shown according to an embodiment of the present application. The system comprises: the system comprises a plurality of perception calculation modules, a plurality of wireless transmission modules, a data collection module and a background end. The perception calculation modules, the wireless transmission modules and the data collection module are located at the first intersection.
The various components of the system are described in detail below.
(1) A plurality of perception computation modules: the system is used for monitoring different positions of the first intersection to acquire perception fusion data of all the positions.
As shown in fig. 2, it shows four perceptual computation modules at the first intersection, respectively:
the perception calculation module A: the perception fusion data is used for acquiring perception fusion data of intersection traffic elements in a first orientation;
the perception calculation module B: the perception fusion data is used for acquiring the perception fusion data of the intersection traffic elements in the second orientation;
a perception calculation module C: the perception fusion data is used for acquiring perception fusion data of intersection traffic elements in the third direction;
perception calculation module D: the perception fusion data is used for acquiring the perception fusion data of the intersection traffic elements in the fourth direction;
it should be noted that the number and direction of the perceptual computing modules in fig. 1 are only schematic and are not intended to limit the present application. According to actual needs, any number of perception calculation modules can be arranged, and perception fusion data in any direction can be obtained. Additionally, the perceptually fused data may include video and point cloud data, as well as other types of data.
In an alternative embodiment, each perceptual-computation module may be a rayprecision all-in-one machine. The all-in-one machine for the radar vision sensing can solve the problems of overlong time delay and time-space synchronization of video coding and decoding of a single radar and a single camera. Through the high-integration radar vision all-in-one machine, the cost of the roadside equipment end can be directly reduced. According to actual research and investigation, the price of a single product of the radar-vision all-in-one machine is lower than the price of the same type of camera, the millimeter wave radar and related components.
In specific application, the all-in-one machine for the radar vision sensing can acquire information of vehicles, pedestrians, obstacles and the like, establish an environment three-dimensional model, realize a high-precision positioning function, sense target distance, speed information and the like under all-weather and any environmental conditions, and realize the high-precision positioning function. The all-in-one machine for the radar vision sensing can further integrate various capabilities, such as laser radar and the like, and can acquire the multi-dimensional data and generate sensing fusion data through the existing or further integrated capability of the all-in-one machine.
(2) A plurality of wireless transmission modules: each wireless transmission module is connected with one perception calculation module.
With continued reference to fig. 2, each wireless transmission module is internally provided with or externally connected with a sensing calculation module through a network cable, such as:
the wireless transmission module A is used for providing a wireless transmission function for the perception calculation module A;
the wireless transmission module B is used for providing a wireless transmission function for the perception calculation module B;
the wireless transmission module C is used for providing a wireless transmission function for the perception calculation module C;
and the wireless transmission module D is used for providing a wireless transmission function for the perception calculation module D.
It should be noted that the number of the wireless transmission modules in fig. 1 is only illustrative and is not intended to limit the present application.
(3) A data collection module: the wireless self-organizing network is formed by the wireless self-organizing network and a plurality of wireless transmission modules; the data collection module is a central node of the wireless ad hoc network, and each wireless transmission module is a non-central node of the wireless ad hoc network; based on the wireless ad hoc network, the data collection module collects the multi-channel perception fusion data of the first intersection through the plurality of wireless transmission modules.
With continued reference to fig. 2, the data collection module X is disposed at one of the sub-intersections of the first intersection, for example, at the right side of the first intersection.
The data collection module X and each wireless transmission module at the first intersection may form a wireless ad hoc network, such as an LTE (long Term Evolution) ad hoc network. Of course, other forms of wireless ad hoc networks may be formed as desired.
The wireless ad hoc network is a star networking or Mesh networking and the like. When the wireless ad hoc network is a star type network, the data collection module X is a central node in the wireless ad hoc network, and each wireless transmission module is a non-central node in the wireless ad hoc network.
Based on a wireless ad hoc network formed by the data collection module X and the plurality of wireless transmission modules, each perception calculation module at the first intersection can send the obtained perception fusion data to the data collection module X through the corresponding wireless transmission module.
Due to the fact that the wireless ad hoc network is adopted to replace an optical fiber scheme in the related technology, the construction cost of the road side is greatly reduced. Specifically, the method comprises the following steps: through the mode of wireless ad hoc network, can reduce the construction cost of broken earth worker by a large scale, rely on the power supply unit of current member to supply power to the equipment (data collection module etc.) that this embodiment relates to, can follow the use of hanging. The method has important economic benefits for rapidly paving intelligent road reconstruction in the whole area.
(4) A back desk end: based on 5G mobile communication, receiving multi-path perception fusion data of a first intersection forwarded by a data collection module X; processing the received multi-channel perception fusion data to obtain a perception result; when communicating with the vehicle end, the background end sends the sensing result of the corresponding position to the vehicle end based on the position of the vehicle end.
Specifically, the multi-channel perception fusion data of the first intersection are subjected to space-time alignment through the data collection module X, a data packet is generated according to the multi-channel perception fusion data after space-time alignment, and the data packet is forwarded to the background end based on 5G mobile communication.
In the embodiment, the perception data can be processed and fused by relying on the high computational power of the background end, so that a perception result is obtained. The backend may be composed of one or more computing devices, such as a rack server, a blade server, a tower server, or a cabinet server (including an independent server or a server cluster composed of multiple servers). The one or more computer devices may include virtualized compute instances. The computer device may load the virtual machine based on a virtual image and/or other data that defines the particular software (e.g., operating system, dedicated application, server) used for emulation. As the demand for different types of processing services changes, different virtual machines may be loaded and/or terminated on the one or more computer devices. The background end can be a multi-stage cloud platform, for example, a background architecture of an edge cloud + a center cloud is adopted. The edge cloud can process fusion calculation with high time delay requirement and issue the fusion calculation, and the center cloud can process traffic light information with low time delay requirement.
And the background end sends a sensing result of the corresponding position to the vehicle end based on the position of the vehicle end through 5G mobile communication. Specifically, the method comprises the following steps: the background end can issue the sensing result to the vehicle end through the 5G base station of the 5G network and the universe layout. The vehicle end and the background end can be long links, the background end can send sensing results of corresponding intersections according to the positions of the vehicle ends, and customized service of sensing data of thousands of vehicles and thousands of faces is achieved based on the characteristics of 5G single-point communication and long links.
Compared with the prior art that the sensing result of the sensing fusion data is calculated by the MEC unit arranged at the intersection and is broadcast to the nearby vehicle end in the form of PC5 through the RSU, the embodiment has the following advantages by utilizing the background end:
the method has the advantages that: there is no need to set MEC units at each crossing and to run optical fibers for MEC unit interaction.
The advantages are two: relative to the range limitations, instability and poor targeting caused by RSU and PC5 broadcasts, in this embodiment: the data collection module X provides the perception fusion data to the background end, and the background end calculates and issues perception results. First, the coverage is wide: through 5G mobile communication, the 5G base station that the backstage end can be based on the universe overall arrangement issues the perception result to the vehicle end, and coverage is almost unrestricted, and the place that has the 5G base station all can issue the perception result. Secondly, the data stability is high: compared with the frequency band used by PC5, 5G mobile communication, the frequency band is more stable. Finally, the pertinence is good: based on the characteristics of 5G single-point communication and long link, the background end sends the sensing result of the specific intersection to the vehicle end according to the position of the vehicle end, and the interference of excessive data to the vehicle end is prevented.
In order to make the present embodiment easier to understand, a workflow based on the above system is provided below.
Fig. 3 shows a structure of a traffic light pole on the right side of a first intersection, which includes: the system comprises a perception calculation module B (a thunder and vision perception all-in-one machine), a wireless transmission module B, a data collection module X, a router, a roadside signal lamp reader, a signal control machine and a power supply. The perception calculation module B, the wireless transmission module B and the data collection module X can be hung at any time depending on the existing power supply on the lamp post, so that the construction cost of the road side system is greatly reduced.
The other side of the first intersection has a traffic light pole of substantially the same construction as the light pole shown in fig. 3, but without the data collection module.
The working flow of the roadside system in the present embodiment is described below with reference to fig. 2 to 4.
S400: and each perception calculation module acquires perception fusion data of the intersection traffic elements at the preset positions.
S402: based on the LTE ad hoc network, each perception calculation module transmits perception fusion data to the data collection module X through each wireless transmission module.
S404: and the data collection module X carries out space-time synchronization and data packing on the multi-channel fusion sensing data.
S406: and the data collection module X transmits the processed fusion sensing data to a background terminal through 5G mobile communication.
S408: and the background end processes the received perception fusion data to obtain a perception result (final reliable traffic element data).
The back end and the vehicle end are established with a long link.
And the vehicle end can be provided with or connected with an On-board unit (OBU), a vehicle data recorder, a smart phone and the like.
S410: the vehicle end provides real-time position data to the background end through 5G mobile communication.
S412: and the background end sends the sensing result of the corresponding position to the vehicle end through the real-time position of the vehicle end and 5G mobile communication.
S414: the vehicle end can execute corresponding operations such as line adjustment, speed adjustment and the like according to the received sensing result.
The working flow of the roadside system of the embodiment and the interaction flow with the vehicle end are described above.
It should be noted that 5G mobile communication is a future network communication direction for future popularization as a national strategy, and the current traffic package charging mode based on a single C-end user is not enough to support the forward input-output ratio of an operator. And the 5G to B mode is actively explored to expand the 5G profit mode and meet the national strategy.
Through driving the upgrade of the upstream and downstream and related industrial chains of the cooperative automatic driving intelligent automobile of the vehicle and the road, the intelligent road reconstruction scheme which can meet the real requirement of the vehicle end and lay quickly can be expanded. The verification of scheme with fall to the ground will accelerate the digital transformation of wisdom road, along with more and more vehicle end closed loop application, must drive the upgrading of whole industrial chain.
Example two
In this embodiment, on the basis of the first embodiment, a primary/standby active policy is provided, so that data reliability is improved.
With continuing reference to fig. 2 and with reference to fig. 5, in this embodiment, the fully wireless based high availability roadside system may include:
(1) a plurality of perception computation modules located at the first intersection.
(2) And the wireless transmission modules are positioned at the first intersection.
(3) And the standby wireless transmission modules are positioned at the first intersection.
Each standby wireless transmission module is connected with one perception calculation module. For example, in the first intersection, four standby wireless transmission modules may be provided, which are respectively embedded in or externally connected to the perception calculation module A, B, C, D in a one-to-one correspondence.
And the wireless transmission module and the standby wireless transmission module which are connected with the same perception calculation module are positioned in the same circuit board.
(4) And the data collection module X is positioned at the first intersection.
(5) And the data collection module Y is positioned at the second intersection.
(6) A back desk end.
The wireless transmission modules and the data collection module X positioned at the first intersection form a wireless ad hoc network.
The standby wireless transmission modules positioned at the first intersection and the data collection module (hereinafter referred to as standby data collection module) Y positioned at the second intersection form another wireless ad hoc network (hereinafter referred to as standby wireless ad hoc network).
Referring to the wireless ad hoc network, in the standby wireless ad hoc network, the standby data collection module is a central node of the standby wireless ad hoc network, and each standby wireless transmission module is a non-central node of the standby wireless ad hoc network. Based on the standby wireless ad hoc network, the standby data collection module Y collects the multi-channel perception fusion data of the first intersection through the plurality of standby wireless transmission modules, and then forwards the multi-channel perception fusion data of the first intersection based on 5G mobile communication.
In this embodiment, the perception fusion data obtained by each perception calculation module A, B, C, D of the first intersection is provided to the data collection module X of the intersection (the first intersection) through the wireless ad hoc network, and is provided to the data collection module Y of the nearby intersection (the second intersection) through the standby wireless ad hoc module. Based on the potential instability of 5G mobile communication, the stability of data transmission is guaranteed by connecting with two adjacent data aggregation modules at the same time. Namely, the perception fusion data is simultaneously sent to the data collection modules of the two intersections, and double-channel data transmission from the ad hoc network to the 5G link is realized. And the data is ensured not to be lost through double connection, and high reliability of the data is realized.
It should be noted that:
the standby wireless transmission modules and the standby data collection module Y are respectively positioned at different intersections, in order to ensure the stability of the standby wireless ad hoc network formed by the standby wireless transmission modules and the standby data collection module, the second intersection is an intersection within a preset range of the first intersection, and the preset range is determined according to the signal coverage range of the standby wireless ad hoc network.
EXAMPLE III
The embodiment provides a high-availability road side fusion sensing method for the intelligent networked automobile, and specific details can refer to the first embodiment and the second embodiment.
As shown in fig. 2, the method for high-availability roadside fusion perception for serving an intelligent networked automobile may include steps S200 to S208, wherein:
step S200, monitoring a plurality of positions of a first intersection through a plurality of perception calculation modules to obtain multi-channel perception fusion data corresponding to the positions;
step S202, the multi-channel perception fusion data are transmitted to a data collection module through a wireless ad hoc network; the wireless ad hoc network comprises a plurality of wireless transmission modules and a data collection module, and the wireless transmission modules are connected with corresponding perception calculation modules;
step S204, based on 5G mobile communication, the multi-channel perception fusion data is sent to a background end through the data collection module;
step S206, processing the multi-channel perception fusion data through the background end to obtain a perception result;
and step S208, when the vehicle terminal is communicated, the perception result of the corresponding position is sent to the vehicle terminal through the background terminal based on the position of the vehicle terminal.
Optionally, the data collection module is located at the first intersection; the method further comprises the following steps:
transmitting the multi-channel perception fusion data to a standby data collection module through a standby wireless ad hoc network; the standby wireless ad hoc network comprises a plurality of standby wireless transmission modules and a standby data collection module, the standby wireless transmission modules are connected with the corresponding perception calculation modules, and the standby data collection module is a data collection module of a second intersection;
and based on 5G mobile communication, the multi-channel perception fusion data is sent to a background end through the standby data collection module.
Optionally, the method further includes:
and based on 5G mobile communication, sending a perception result of the corresponding position to the vehicle end through the background end based on the position of the vehicle end.
Optionally, the wireless transmission module and the standby wireless transmission module connected to the same sensing and computing module are located in the same circuit board.
Optionally, the second intersection is an intersection within a preset range of the first intersection, and the preset range is determined according to a signal coverage range of the standby wireless ad hoc network.
Optionally, the sensing and calculating module comprises a radar sensing and integrating machine.
Optionally, step S204 further includes: and performing space-time alignment on the multi-channel perception fusion data of the first intersection, generating a data packet according to the multi-channel perception fusion data after the space-time alignment, and forwarding the data packet to the background end based on 5G mobile communication.
The hardware architecture of the radar-vision all-in-one machine, the wireless transmission module, the data collection module, the vehicle end and the background end is provided below.
As shown in fig. 7, the computer device 10000 may be a back-end or vehicle-end or data collection module, which may include: the memory 10010, the processor 10020, and the network interface 10030 may be communicatively linked to each other through a system bus. Wherein:
the memory 10010 includes at least one type of computer-readable storage medium including a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage 10010 may be an internal storage module of the computer device 10000, such as a hard disk or a memory of the computer device 10000. In other embodiments, the memory 10010 may also be an external storage device of the computer device 10000, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the computer device 10000. Of course, the memory 10010 may also include both internal and external memory modules of the computer device 10000. In the embodiment of the present application, the memory 10010 is generally configured to store an operating system and various application software installed on the computer device 10000. In addition, the memory 10010 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 10020, in some embodiments, can be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip. The processor 10020 is generally configured to control overall operations of the computer device 10000, such as performing control and processing related to data interaction or communication with the computer device 10000. In this embodiment, the processor 10020 is configured to execute the program codes stored in the memory 10010 or process data, for example, process the received perceptually fused data.
Network interface 10030 may comprise a wireless network interface or a wired network interface, and network interface 10030 is generally used to establish a communication link between computer device 10000 and other computer devices. For example, the network interface 10030 is used to connect the computer device 10000 to an external terminal through a network, establish a data transmission channel and a communication link between the computer device 10000 and the external terminal, and the like. The network may be based on 5G mobile communication or next generation mobile communication.
It should be noted that fig. 7 only illustrates a computer device having the components 10010-10030, but it is to be understood that not all illustrated components need be implemented and that more or fewer components may be implemented instead.
It should be apparent to those skilled in the art that the modules or steps of the embodiments of the present application described above can be implemented by a general-purpose computing device, they can be integrated on a single computing device or distributed on a network formed by a plurality of computing devices, and alternatively, they can be implemented by program codes executable by the computing devices, so that they can be stored in a storage device and executed by the computing devices, and in some cases, the steps shown or described can be executed in a different order from that of the above, or they can be separately manufactured into various integrated circuit modules, or a plurality of modules or steps among them can be manufactured into a single integrated circuit module. Thus, embodiments of the present application are not limited to any specific combination of hardware and software.
It should be noted that the above is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all the equivalent structures or equivalent flow transformations made by the contents of the specification and the drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A high-availability roadside fusion perception system serving an intelligent networked automobile, the system comprising:
a plurality of perceptual computation modules: the system comprises a monitoring system, a first intersection and a second intersection, wherein the monitoring system is used for monitoring different positions of the first intersection to acquire perception fusion data of all the positions;
a plurality of wireless transmission modules: each wireless transmission module is connected with a perception calculation module;
a data collection module: the wireless transmission module and the plurality of wireless transmission modules form a wireless ad hoc network; the data collection module is a central node of the wireless ad hoc network, and each wireless transmission module is a non-central node of the wireless ad hoc network; based on the wireless ad hoc network, the data collection module collects multi-path perception fusion data of the first intersection;
a back desk end: receiving multi-channel perception fusion data of the first intersection forwarded by the data collection module based on 5G mobile communication; processing the received multi-channel perception fusion data to obtain a perception result; when communicating with a vehicle end, the background end sends a perception result of a corresponding position to the vehicle end based on the position of the vehicle end.
2. The system of claim 1, wherein the data aggregation module is located at the first intersection; the system further comprises:
a plurality of standby wireless transmission modules: each standby wireless transmission module is connected with a perception calculation module;
the standby wireless transmission modules and the standby data collection module form a standby wireless ad hoc network, and the standby data collection module is a data collection module of a second intersection; the standby data collection module is a central node of a standby wireless ad hoc network, and each standby wireless transmission module is a non-central node of the standby wireless ad hoc network;
based on the standby wireless ad hoc network, the standby data collection module collects the multi-channel perception fusion data of the first intersection, and then forwards the multi-channel perception fusion data of the first intersection based on 5G mobile communication.
3. The system of claim 2, wherein:
and the wireless transmission module and the standby wireless transmission module which are connected with the same perception calculation module are positioned in the same circuit board.
4. The system of claim 2,
the second intersection is an intersection within a preset range of the first intersection, and the preset range is determined according to the signal coverage range of the standby wireless ad hoc network.
5. The system of any one of claims 1 to 4, wherein:
the perception calculation module comprises a thunder and vision perception all-in-one machine.
6. The system of any one of claims 1 to 4, wherein:
the data aggregation module is further configured to: and performing space-time alignment on the multi-channel perception fusion data of the first intersection, generating a data packet according to the multi-channel perception fusion data after the space-time alignment, and forwarding the data packet to the background terminal based on 5G mobile communication.
7. The system according to any one of claims 1 to 4, wherein:
the back end is further configured to: and sending the perception result of the corresponding position to the vehicle end based on the position of the vehicle end through 5G mobile communication.
8. A high-availability roadside fusion perception method serving an intelligent networked automobile is characterized by comprising the following steps:
monitoring a plurality of positions of a first intersection through a plurality of perception calculation modules to obtain multi-channel perception fusion data corresponding to the positions;
transmitting the multi-channel perception fusion data to a data collection module through a wireless ad hoc network; the wireless ad hoc network comprises a plurality of wireless transmission modules and the data collection module, and the wireless transmission modules are connected with the corresponding perception calculation modules;
based on 5G mobile communication, the multi-channel perception fusion data are sent to a background end through the data collection module;
processing the multi-channel perception fusion data through the background end to obtain a perception result;
when communicating with a vehicle end, sending a perception result of a corresponding position to the vehicle end through the background end based on the position of the vehicle end.
9. The method of claim 8, wherein a data aggregation module is located at the first intersection; the method further comprises the following steps:
transmitting the multi-channel perception fusion data to a standby data collection module through a standby wireless ad hoc network; the standby wireless ad hoc network comprises a plurality of standby wireless transmission modules and a standby data collection module, the standby wireless transmission modules are connected with the corresponding perception calculation modules, and the standby data collection module is a data collection module of a second intersection;
and based on 5G mobile communication, the multi-channel perception fusion data is sent to a background end through the standby data collection module.
10. The method of any one of claims 8 to 9, further comprising:
and based on 5G mobile communication, sending a perception result of the corresponding position to the vehicle end through the background end based on the position of the vehicle end.
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Citations (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007287016A (en) * | 2006-04-19 | 2007-11-01 | Nec Engineering Ltd | Vehicle driving support system |
| KR20090053013A (en) * | 2007-11-22 | 2009-05-27 | 한국전자통신연구원 | Method and system for accident detection using sensor attached to the median strip |
| KR20120126739A (en) * | 2011-05-12 | 2012-11-21 | 정철호 | Sensor node having radar and method for detecting vehicle using sensor node |
| US20140244145A1 (en) * | 2013-02-28 | 2014-08-28 | Naztec, Inc. | Wireless vehicle detection system and associated methods having enhanced response time |
| CN104778840A (en) * | 2015-04-30 | 2015-07-15 | 南京中大东博信息科技有限公司 | Vehicle information sensing system and method |
| WO2017012468A1 (en) * | 2015-07-17 | 2017-01-26 | 袁丽 | Wireless communication system and method for smart traffic monitoring |
| CN108833833A (en) * | 2018-06-20 | 2018-11-16 | 长安大学 | Towards intelligent network connection automobile scene image data perception and coprocessing system |
| US20190156668A1 (en) * | 2016-08-11 | 2019-05-23 | Jiangsu University | Driving service active sensing system and method in internet of vehicles environment |
| CN109816996A (en) * | 2017-11-21 | 2019-05-28 | 重庆瑞升康博电气有限公司 | Intelligent traffic light control system based on wireless sensor network |
| JP2019175201A (en) * | 2018-03-29 | 2019-10-10 | 住友電気工業株式会社 | Sensor sharing system, sensor sharing server, method for operating sensor sharing server, sensor equipment device, and computer program for sharing sensor |
| CN111477001A (en) * | 2020-03-04 | 2020-07-31 | 中国联合网络通信有限公司广州市分公司 | Traffic signal acquisition and management system based on 5G and MEC |
| CN111880174A (en) * | 2020-07-03 | 2020-11-03 | 芜湖雄狮汽车科技有限公司 | Roadside service system for supporting automatic driving control decision and control method thereof |
| CN111932937A (en) * | 2020-08-17 | 2020-11-13 | 苏州健雄职业技术学院 | Urban parking space reservation scheduling system based on Internet of things technology and working method thereof |
| CN112562409A (en) * | 2020-12-04 | 2021-03-26 | 上海淞泓智能汽车科技有限公司 | Autonomous parking system and method based on multi-access edge calculation |
| CN112863187A (en) * | 2021-01-18 | 2021-05-28 | 北京百度网讯科技有限公司 | Detection method of perception model, electronic equipment, road side equipment and cloud control platform |
| CN213817845U (en) * | 2021-01-20 | 2021-07-27 | 亚哲科技股份有限公司 | Roadside convergence equipment based on artificial intelligence and used for vehicle-road cooperative system |
| WO2021184841A1 (en) * | 2020-03-19 | 2021-09-23 | 中移(上海)信息通信科技有限公司 | Internet of vehicles method and apparatus, device, storage medium, and system |
| CN113485319A (en) * | 2021-06-08 | 2021-10-08 | 中兴智能汽车有限公司 | Automatic driving system based on 5G vehicle-road cooperation |
| CN113506454A (en) * | 2021-05-18 | 2021-10-15 | 江西方兴科技有限公司 | Expressway induction lamp system and method based on audio event detection |
| CN113581211A (en) * | 2021-08-30 | 2021-11-02 | 深圳清航智行科技有限公司 | Vehicle driving control method, system and device and readable storage medium |
| US20210409917A1 (en) * | 2019-08-05 | 2021-12-30 | Tencent Technology (Shenzhen) Company Limited | Vehicle-road collaboration apparatus and method, electronic device, and storage medium |
| CN114067556A (en) * | 2020-08-05 | 2022-02-18 | 北京万集科技股份有限公司 | Environment sensing method, device, server and readable storage medium |
| CN114170803A (en) * | 2021-12-15 | 2022-03-11 | 阿波罗智联(北京)科技有限公司 | Roadside sensing system and traffic control method |
| CN114245340A (en) * | 2021-11-23 | 2022-03-25 | 浙江嘉兴数字城市实验室有限公司 | C-V2X-based urban road and vehicle cooperative cloud control vehicle guiding system |
| US20220110003A1 (en) * | 2020-10-01 | 2022-04-07 | Nokia Technologies Oy | Configuring wireless sensor network paths |
| CN114429711A (en) * | 2021-12-23 | 2022-05-03 | 联通智网科技股份有限公司 | Message distribution method, device, storage medium and server |
-
2022
- 2022-06-09 CN CN202210653515.6A patent/CN115100852A/en active Pending
Patent Citations (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007287016A (en) * | 2006-04-19 | 2007-11-01 | Nec Engineering Ltd | Vehicle driving support system |
| KR20090053013A (en) * | 2007-11-22 | 2009-05-27 | 한국전자통신연구원 | Method and system for accident detection using sensor attached to the median strip |
| KR20120126739A (en) * | 2011-05-12 | 2012-11-21 | 정철호 | Sensor node having radar and method for detecting vehicle using sensor node |
| US20140244145A1 (en) * | 2013-02-28 | 2014-08-28 | Naztec, Inc. | Wireless vehicle detection system and associated methods having enhanced response time |
| CN104778840A (en) * | 2015-04-30 | 2015-07-15 | 南京中大东博信息科技有限公司 | Vehicle information sensing system and method |
| WO2017012468A1 (en) * | 2015-07-17 | 2017-01-26 | 袁丽 | Wireless communication system and method for smart traffic monitoring |
| US20190156668A1 (en) * | 2016-08-11 | 2019-05-23 | Jiangsu University | Driving service active sensing system and method in internet of vehicles environment |
| CN109816996A (en) * | 2017-11-21 | 2019-05-28 | 重庆瑞升康博电气有限公司 | Intelligent traffic light control system based on wireless sensor network |
| JP2019175201A (en) * | 2018-03-29 | 2019-10-10 | 住友電気工業株式会社 | Sensor sharing system, sensor sharing server, method for operating sensor sharing server, sensor equipment device, and computer program for sharing sensor |
| US20190394427A1 (en) * | 2018-06-20 | 2019-12-26 | Chang'an University | System for perceiving and co-processing intelligent connected vehicle-oriented scene image data |
| CN108833833A (en) * | 2018-06-20 | 2018-11-16 | 长安大学 | Towards intelligent network connection automobile scene image data perception and coprocessing system |
| US20210409917A1 (en) * | 2019-08-05 | 2021-12-30 | Tencent Technology (Shenzhen) Company Limited | Vehicle-road collaboration apparatus and method, electronic device, and storage medium |
| CN111477001A (en) * | 2020-03-04 | 2020-07-31 | 中国联合网络通信有限公司广州市分公司 | Traffic signal acquisition and management system based on 5G and MEC |
| WO2021184841A1 (en) * | 2020-03-19 | 2021-09-23 | 中移(上海)信息通信科技有限公司 | Internet of vehicles method and apparatus, device, storage medium, and system |
| CN111880174A (en) * | 2020-07-03 | 2020-11-03 | 芜湖雄狮汽车科技有限公司 | Roadside service system for supporting automatic driving control decision and control method thereof |
| CN114067556A (en) * | 2020-08-05 | 2022-02-18 | 北京万集科技股份有限公司 | Environment sensing method, device, server and readable storage medium |
| CN111932937A (en) * | 2020-08-17 | 2020-11-13 | 苏州健雄职业技术学院 | Urban parking space reservation scheduling system based on Internet of things technology and working method thereof |
| US20220110003A1 (en) * | 2020-10-01 | 2022-04-07 | Nokia Technologies Oy | Configuring wireless sensor network paths |
| CN112562409A (en) * | 2020-12-04 | 2021-03-26 | 上海淞泓智能汽车科技有限公司 | Autonomous parking system and method based on multi-access edge calculation |
| CN112863187A (en) * | 2021-01-18 | 2021-05-28 | 北京百度网讯科技有限公司 | Detection method of perception model, electronic equipment, road side equipment and cloud control platform |
| CN213817845U (en) * | 2021-01-20 | 2021-07-27 | 亚哲科技股份有限公司 | Roadside convergence equipment based on artificial intelligence and used for vehicle-road cooperative system |
| CN113506454A (en) * | 2021-05-18 | 2021-10-15 | 江西方兴科技有限公司 | Expressway induction lamp system and method based on audio event detection |
| CN113485319A (en) * | 2021-06-08 | 2021-10-08 | 中兴智能汽车有限公司 | Automatic driving system based on 5G vehicle-road cooperation |
| CN113581211A (en) * | 2021-08-30 | 2021-11-02 | 深圳清航智行科技有限公司 | Vehicle driving control method, system and device and readable storage medium |
| CN114245340A (en) * | 2021-11-23 | 2022-03-25 | 浙江嘉兴数字城市实验室有限公司 | C-V2X-based urban road and vehicle cooperative cloud control vehicle guiding system |
| CN114170803A (en) * | 2021-12-15 | 2022-03-11 | 阿波罗智联(北京)科技有限公司 | Roadside sensing system and traffic control method |
| CN114429711A (en) * | 2021-12-23 | 2022-05-03 | 联通智网科技股份有限公司 | Message distribution method, device, storage medium and server |
Non-Patent Citations (1)
| Title |
|---|
| 李泽军 等: "城市轨道交通列车运行控制", 31 August 2017, 中国建材工业出版社, pages: 39 - 45 * |
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