Cross-edge cloud vehicle tracking method, device and system and storage medium

Abstract

The invention discloses a cross-edge cloud vehicle tracking method, device and system and a storage medium, which are used for realizing continuous tracking of a vehicle. The method comprises the following steps: in a process of continuously tracking a first target vehicle, according to preset data of the first target vehicle, judging whether the first target vehicle has a possibility of running across edge cloud; when the first target vehicle has the possibility of running across the edge cloud, predicting a first target edge cloud into which the first target vehicle enters after running across the edge cloud; transmitting the track information of the first target vehicle to the first target edge cloud in real time; and when it is detected that the first target vehicle is taken over by the first target edge cloud, stopping transmitting the track information of the first target vehicle to the first target edge cloud, and disconnecting the connection with the first target edge cloud. According to the scheme, the vehicle can be continuously tracked in real time when the vehicle runs across the edge cloud.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a vehicle tracking method, device, system and storage medium across edge clouds. Background Art

[0002] The vehicle-road-cloud integrated cloud control basic platform usually divides the system into a three-layer cloud architecture of central cloud, regional cloud, and edge cloud, of which the edge cloud serves autonomous driving. The networked autonomous driving vehicles and roadside equipment report data to the edge cloud, which integrates the data to generate a digital twin that corresponds to the real-world vehicle and generates a unique ID for the vehicle.

[0003] Edge cloud usually provides real-time services for vehicles, such as emergency braking warning of vehicles ahead and pedestrian crossing warning, which have high real-time requirements and are sensitive to latency. To ensure the reliability of services, the edge cloud needs to correctly identify the vehicle throughout its life cycle (i.e., driving on roads continuously covered by sensing devices) and assign the correct vehicle ID to the vehicle, that is, the edge cloud can continuously track the vehicle.

[0004] Because of its sensitivity to latency, edge clouds are usually deployed in computer rooms close to the roadside through technologies such as UPF sinking to shorten the network path and provide vehicles with low-latency and high-reliability services. As a result, multiple edge clouds are deployed in a large area to collaboratively provide services for connected autonomous vehicles. As vehicles move, it is possible to travel from the coverage area of ​​one edge cloud to the coverage area of ​​another edge cloud, so a solution is needed to ensure that the vehicle can still be tracked when it travels across edge clouds to ensure that the vehicle ID remains unchanged.

[0005] Therefore, how to provide a cross-edge cloud vehicle tracking method to achieve real-time and continuous tracking of the vehicle when the vehicle travels across the edge cloud is an existing technology that needs to be solved urgently. Summary of the invention

[0006] The present application provides a vehicle tracking method, device, system and storage medium across edge clouds, which are used to achieve real-time and continuous tracking of vehicles when the vehicles travel across edge clouds.

[0007] The present application provides a vehicle tracking method across edge clouds, including:

[0008] In the process of continuously tracking the first target vehicle, judging whether the first target vehicle has the possibility of traveling across the edge cloud according to preset data of the first target vehicle;

[0009] When the first target vehicle has the possibility of traveling across the edge cloud, predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud;

[0010] Transmitting the track information of the first target vehicle to the first target edge cloud in real time, wherein the track information includes a unique ID assigned to the target vehicle, the vehicle position, speed, heading, and the original target object constituting the track;

[0011] When it is detected that the first target vehicle is taken over by the first target edge cloud, the transmission of the track information of the first target vehicle to the first target edge cloud is stopped, and the connection with the first target edge cloud is disconnected.

[0012] The beneficial effects of the present application are: by continuously tracking the first target vehicle, judging whether the first target vehicle has the possibility of traveling across the edge cloud according to the preset data of the first target vehicle, and when the first target vehicle has the possibility of traveling across the edge cloud, predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud, and then transmitting the track information of the first target vehicle to the first target edge cloud in real time, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle position, speed, heading and the original target object constituting the track, and when it is detected that the first target vehicle is taken over by the first target edge cloud, stopping the transmission of the track information of the first target vehicle to the first target edge cloud, and disconnecting the connection with the first target edge cloud. Because when the device judges that the vehicle has the possibility of traveling across the edge cloud, the first target edge cloud that the vehicle may enter after traveling across the edge cloud is predicted in advance, and the track information of the first target vehicle is transmitted to the first target edge cloud in real time, so as to realize the takeover of the first target edge cloud by the first target vehicle, thereby ensuring the real-time and continuous tracking of the vehicle when traveling across the edge cloud.

[0013] In one embodiment, judging whether the first target vehicle has the possibility of traveling across the edge cloud according to the preset data of the first target vehicle includes:

[0014] When the first target vehicle enters the electronic fence at the edge cloud boundary, it is determined that the first target vehicle has the possibility of traveling across the edge cloud.

[0015] In one embodiment, predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud includes:

[0016] Determining a predicted driving trajectory of a first target vehicle based on the position of the vehicle, the historical trajectory of the vehicle, and the heading of the vehicle;

[0017] It is determined that the edge cloud entered by the predicted driving trajectory when traveling across the edge cloud is the first target edge cloud.

[0018] In one embodiment, the method further comprises:

[0019] Extracting a vehicle position from the track information of the first target vehicle;

[0020] When the vehicle position enters the coverage of the first target edge cloud, it is determined that the first target vehicle is taken over by the first target edge cloud.

[0021] In one embodiment, before transmitting the track information of the first target vehicle to the first target edge cloud in real time, the method further includes:

[0022] Sending a connection request to the first target edge cloud;

[0023] When the first target edge cloud responds to the connection request and successfully connects with the target edge cloud, the connection with the target edge cloud is maintained, wherein the connection with the target edge cloud ends when the first target vehicle is taken over by the first target edge cloud.

[0024] In one embodiment, the method further comprises:

[0025] When the track information of the second target vehicle sent by the second target edge cloud is received, the track information of the second target vehicle is managed by the remote track management module, and the track information of the managed second target vehicle is corrected according to the new track information of the second target vehicle continuously sent by the second target edge cloud.

[0026] In one embodiment, the method further comprises:

[0027] When a vehicle is detected entering the coverage area of ​​the local edge cloud, the real vehicle data of the vehicle is obtained;

[0028] Comparing the real vehicle data with the track information of the second target vehicle managed by the remote track management module;

[0029] When the comparison is consistent, the entering vehicle is determined to be the second target vehicle;

[0030] The vehicle is associated with the track information of the second target vehicle, and the second target vehicle is continuously tracked.

[0031] The present application also provides a cross-edge cloud vehicle tracking device, comprising:

[0032] The edge cloud fusion module is used to fuse the data reported by the roadside across poles, assign a unique ID to the vehicle, and continuously track the vehicle based on the unique ID;

[0033] The cross-edge cloud prediction module is used to determine whether the vehicle will travel across the edge cloud based on the vehicle's position, the vehicle's historical trajectory, and the vehicle's heading; the cross-edge cloud track transmission module is used to transmit the vehicle's track information to the edge cloud that the vehicle enters after traveling across the edge cloud when there is a possibility that the vehicle will travel across the edge cloud, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle's position, speed, heading, and the original target object that constitutes the track.

[0034] In one embodiment, the apparatus further comprises:

[0035] The remote track management module is used to manage the remote track information sent by other edge clouds and to modify the managed remote track information according to the new remote track information continuously sent by other edge clouds;

[0036] The remote track association module is used to obtain the real vehicle data of the vehicle when a vehicle is detected entering the coverage area of ​​the local edge cloud, and compare the real vehicle data with the remote track information managed by the remote track management module. When the comparison is consistent, the vehicle is associated with the corresponding remote track information.

[0037] The present application also provides a cross-edge cloud vehicle tracking system, including:

[0038] at least one processor; and,

[0039] a memory communicatively connected to the at least one processor; wherein,

[0040] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the cross-edge cloud vehicle tracking method recorded in any of the above embodiments.

[0041] The present application also provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor corresponding to the cross-edge cloud vehicle tracking system, the cross-edge cloud vehicle tracking system can implement the cross-edge cloud vehicle tracking method recorded in any of the above embodiments.

[0042] Other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings.

[0043] The technical solution of the present application is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings:

[0045] Figure 1 This is a flow chart of a vehicle tracking method across edge clouds in one embodiment of the present application;

[0046] Figure 2 This is a schematic diagram of a cross-edge cloud vehicle tracking device in one embodiment of the present application;

[0047] Figure 3 This is a schematic diagram of the hardware structure of a cross-edge cloud vehicle tracking system in one embodiment of the present application. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application.

[0049] Figure 1 Flow chart of a vehicle tracking method across edge clouds in one embodiment of the present application, such as Figure 1 As shown, the method can be implemented as the following steps S101-S104:

[0050] In step S101, during the continuous tracking of the first target vehicle, it is determined whether the first target vehicle has the possibility of traveling across the edge cloud according to the preset data of the first target vehicle;

[0051] In step S102, when there is a possibility that the first target vehicle travels across the edge cloud, predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud;

[0052] In step S103, the track information of the first target vehicle is transmitted to the first target edge cloud in real time, wherein the track information includes a unique ID assigned to the target vehicle, the vehicle position, speed, heading, and the original target object constituting the track;

[0053] In step S104, when it is detected that the first target vehicle is taken over by the first target edge cloud, the transmission of the track information of the first target vehicle to the first target edge cloud is stopped, and the connection with the first target edge cloud is disconnected.

[0054] The method provided in this application can be applied to Figure 2 The vehicle tracking device across the edge cloud is shown. Figure 2As shown, the cross-edge cloud vehicle tracking device can be set inside the edge cloud. When the vehicle moves across edge cloud A to edge cloud B, the cross-edge cloud vehicle tracking device can realize real-time continuous tracking of the vehicle. Figure 2 As shown in the edge cloud A in the figure, the cross-edge cloud vehicle tracking device includes at least: an edge cloud fusion module, a cross-edge cloud prediction module and a cross-edge cloud track transmission module. Among them, the edge cloud fusion module is used to perform cross-pole fusion on the data reported by the roadside, assign a unique ID to the vehicle, and continuously track the vehicle based on the unique ID; the cross-edge cloud prediction module is used to determine whether the vehicle will travel across the edge cloud based on information such as the vehicle's location, heading and historical trajectory; the cross-edge cloud track transmission module is used to transmit the vehicle's track information to the edge cloud that the vehicle enters after traveling across the edge cloud when there is a possibility that the vehicle will travel across the edge cloud, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle's location, speed, heading and the original target object that constitutes the track. As shown Figure 2 In the edge cloud B shown, the vehicle tracking device may also include a remote track management module and a remote track association module. Among them, the remote track management module is used to manage the remote track information sent by other edge clouds, and to modify the managed remote track information according to the new remote track information continuously sent by other edge clouds; the remote track association module is used to obtain the real vehicle data of the entering vehicle when it is detected that the vehicle enters the coverage area of ​​the local edge cloud, and compare the real vehicle data with the remote track information managed by the remote track management module. When the comparison is consistent, the vehicle is associated with the corresponding remote track information. It can be understood that the modules in edge cloud A and edge cloud B are essentially the same, that is, edge cloud A also includes the remote track management module and remote track association module in edge cloud B. Similarly, edge cloud B also includes a cross-edge cloud prediction module and a cross-edge cloud track transmission module. In order to simplify the view, Figure 2 Not shown.

[0055] In the process of continuously tracking the first target vehicle, it is determined whether the first target vehicle has the possibility of traveling across the edge cloud based on the preset data of the first target vehicle. Among them, the preset data includes information such as the vehicle's location, heading, and historical trajectory. There are many judgment methods, such as determining the predicted driving trajectory of the first target vehicle based on the vehicle's location, the vehicle's historical trajectory, and the vehicle's heading; then, judging that the edge cloud entered by the predicted driving trajectory when traveling across the edge cloud is the first target edge cloud, for example, combining the road topology relationship of the high-precision map to predict whether the vehicle will enter other edge cloud areas. Of course, it is also possible to draw an electronic fence at the edge cloud boundary without relying on the high-precision map. When the first target vehicle enters the electronic fence at the edge cloud boundary, it is determined that the first target vehicle has the possibility of traveling across the edge cloud.

[0056] When the first target vehicle has the possibility of traveling across an edge cloud, the first target edge cloud that the first target vehicle enters after traveling across the edge cloud is predicted. The predicted driving trajectory of the first target vehicle is determined according to the vehicle's position, the vehicle's historical trajectory, and the vehicle's heading; the edge cloud that the predicted driving trajectory enters when traveling across the edge cloud is determined to be the first target edge cloud, wherein the first target edge cloud may be one or more.

[0057] The track information of the first target vehicle is transmitted to the first target edge cloud in real time, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle position, speed, heading and the original target object constituting the track. In other words, when it is predicted that a vehicle may cross an edge cloud, the cross-edge cloud track transmission module is responsible for transmitting the track information of the vehicle to the edge cloud that it may enter. When there are multiple first target edge clouds, the track information of the first target vehicle is transmitted to multiple first target edge clouds in real time at the same time.

[0058] It is understandable that in order to ensure the real-time transmission of the track, the edge clouds need to establish connections in advance and maintain the correspondence between the edge clouds and the connections. When it is determined that the vehicle will enter the remote edge cloud, the connection corresponding to the edge cloud is found, and the data is sent to the corresponding edge cloud in real time through the connection. In one embodiment of the present application, before the track information of the first target vehicle is transmitted to the first target edge cloud in real time, a connection request is sent to the first target edge cloud; when the first target edge cloud responds to the connection request and successfully connects to the target edge cloud, the connection with the target edge cloud is maintained, wherein the connection with the target edge cloud ends when the first target vehicle is taken over by the first target edge cloud.

[0059] When it is detected that the first target vehicle is taken over by the first target edge cloud, the transmission of the track information of the first target vehicle to the first target edge cloud is stopped, and the connection with the first target edge cloud is disconnected. In one embodiment of the present application, the vehicle position is extracted from the track information of the first target vehicle; when the vehicle position enters the coverage range of the first target edge cloud, it is determined that the first target vehicle is taken over by the first target edge cloud. When there are multiple first target edge clouds, when it is detected that the first target vehicle is taken over by one of the first target edge clouds, the transmission of the track information of the first target vehicle to all first target edge clouds is stopped, and the first target edge cloud that has not taken over the vehicle stops managing the track information of the first target vehicle; of course, when there are multiple first target edge clouds, when it is detected that the first target vehicle is taken over by one of the first target edge clouds, an instruction to stop managing the track information of the first target vehicle may also be sent to the first target edge cloud that has not taken over the first target vehicle.

[0060] Since the edge cloud also receives the remote vehicle track information transmitted to it in real time by other remote edge clouds, when receiving the track information of the second target vehicle sent by the second target edge cloud, the remote track management module manages the track information of the second target vehicle and corrects the track information of the managed second target vehicle according to the new track information of the second target vehicle continuously sent by the second target edge cloud. Figure 2 As shown in the figure, when the track information of the second target vehicle sent by the second target edge cloud is received, the remote vehicle track information will be handed over to the remote track management module for management. Since the remote track is pre-transmitted, the remote edge cloud will continue to transmit information to the local edge cloud before the vehicle enters the local edge cloud. Therefore, the remote track management module needs to correct the managed vehicle track according to the latest track information to ensure that the local vehicle track is the latest data when the vehicle enters the local edge cloud.

[0061] In addition, in order to achieve real-time continuous tracking of vehicle trajectories, when a vehicle is detected entering the coverage of the local edge cloud, the real vehicle data of the incoming vehicle is obtained; the real vehicle data is compared with the track information of the second target vehicle managed by the remote track management module; when the comparison is consistent, the incoming vehicle is determined to be the second target vehicle; the vehicle is associated with the track information of the second target vehicle, and the second target vehicle is continuously tracked. In other words, when a vehicle enters a new edge cloud, the real vehicle data of the incoming vehicle is obtained, and the vehicle data is matched with the remote track managed by the remote track management module. If a match is found, the vehicle is associated with this track, thereby achieving ID consistency and completing continuous tracking.

[0062] The beneficial effects of the present application are: by continuously tracking the first target vehicle, judging whether the first target vehicle has the possibility of traveling across the edge cloud according to the preset data of the first target vehicle, and when the first target vehicle has the possibility of traveling across the edge cloud, predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud, and then transmitting the track information of the first target vehicle to the first target edge cloud in real time, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle position, speed, heading and the original target object constituting the track, and when it is detected that the first target vehicle is taken over by the first target edge cloud, stopping the transmission of the track information of the first target vehicle to the first target edge cloud, and disconnecting the connection with the first target edge cloud. Because when the device judges that the vehicle has the possibility of traveling across the edge cloud, the first target edge cloud that the vehicle may enter after traveling across the edge cloud is predicted in advance, and the track information of the first target vehicle is transmitted to the first target edge cloud in real time, so as to realize the takeover of the first target edge cloud by the first target vehicle, thereby ensuring the real-time and continuous tracking of the vehicle when traveling across the edge cloud.

[0063] In one embodiment, the above step S101 can also be implemented as the following steps:

[0064] When the first target vehicle enters the electronic fence at the edge cloud boundary, it is determined that the first target vehicle has the possibility of traveling across the edge cloud.

[0065] In one embodiment, the above step S101 can also be implemented as the following steps A1-A2:

[0066] In step A1, a predicted driving trajectory of a first target vehicle is determined based on the position of the vehicle, the historical trajectory of the vehicle, and the heading of the vehicle;

[0067] In step A2, it is determined that the edge cloud entered by the predicted driving trajectory when traveling across the edge cloud is the first target edge cloud.

[0068] In this embodiment, the cross-edge cloud prediction module determines whether the vehicle will travel across the edge cloud based on information such as the vehicle's location, heading, and historical trajectory. There are many prediction methods, such as predicting whether the vehicle will enter other edge cloud coverage areas based on the vehicle's location and heading, combined with the road topology of the high-precision map. Specifically, when the vehicle is located close to the boundary of the edge cloud coverage area, and the general trend of the historical trajectory also points to the outside of the local edge cloud coverage area, there is a possibility of traveling across the edge cloud. If the heading also points to the outside of the local edge cloud coverage area, this possibility is even greater. If it is found that the road on which the vehicle is traveling is a one-way road in combination with the road topology of the high-precision map, and even if the vehicle changes lanes, it can only travel to the outside of the edge cloud coverage area, it can be determined that this possibility is more than 90%.

[0069] Then, it is determined that the edge cloud entered by the predicted driving trajectory when traveling across the edge cloud is the first target edge cloud. The first target edge cloud may be one or more.

[0070] In one embodiment, the above step S102 may also be implemented as the following steps B1-B2:

[0071] In step B1, extracting the vehicle position from the track information of the first target vehicle;

[0072] In step B2, when the vehicle position enters the coverage of the first target edge cloud, it is determined that the first target vehicle is taken over by the first target edge cloud.

[0073] In one embodiment, before the above step S103, the method may also be implemented as the following steps C1-C2:

[0074] In step C1, a connection request is sent to the first target edge cloud;

[0075] In step C2, when the first target edge cloud responds to the connection request and successfully connects with the target edge cloud, the connection with the target edge cloud is maintained, wherein the connection with the target edge cloud ends when the first target vehicle is taken over by the first target edge cloud.

[0076] In one embodiment, the method can also be implemented as follows:

[0077] When the track information of the second target vehicle sent by the second target edge cloud is received, the track information of the second target vehicle is managed by the remote track management module, and the track information of the managed second target vehicle is corrected according to the new track information of the second target vehicle continuously sent by the second target edge cloud.

[0078] In one embodiment, the method can also be implemented as the following steps D1-D2:

[0079] In step D1, when a vehicle is detected entering the coverage area of ​​the local edge cloud, the real vehicle data of the entering vehicle is obtained;

[0080] In step D2, the real vehicle data is compared with the track information of the second target vehicle managed by the remote track management module;

[0081] In step D3, when the comparison is consistent, the entering vehicle is determined to be the second target vehicle;

[0082] In step D4, the vehicle is associated with the track information of the second target vehicle, and the second target vehicle is continuously tracked.

[0083] Figure 2 A vehicle tracking device across edge clouds in an embodiment of the present application, such as Figure 2 As shown, including:

[0084] The edge cloud fusion module is used to fuse the data reported by the roadside across poles, assign a unique ID to the vehicle, and continuously track the vehicle based on the unique ID;

[0085] The cross-edge cloud prediction module is used to determine whether the vehicle will travel across the edge cloud based on the vehicle's position, the vehicle's historical trajectory, and the vehicle's heading; the cross-edge cloud track transmission module is used to transmit the vehicle's track information to the edge cloud that the vehicle enters after traveling across the edge cloud when there is a possibility that the vehicle will travel across the edge cloud, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle's position, speed, heading, and the original target object that constitutes the track.

[0086] In one embodiment, the apparatus further comprises:

[0087] The remote track management module is used to manage the remote track information sent by other edge clouds and to modify the managed remote track information according to the new remote track information continuously sent by other edge clouds;

[0088] The remote track association module is used to obtain the real vehicle data of the vehicle when a vehicle is detected entering the coverage area of ​​the local edge cloud, and compare the real vehicle data with the remote track information managed by the remote track management module. When the comparison is consistent, the vehicle is associated with the corresponding remote track information.

[0089] It can be understood that the remote track information in this embodiment is the track information of the first target vehicle or the track information of the second target vehicle in the aforementioned embodiment.

[0090] Figure 3 FIG. 1 is a schematic diagram of the hardware structure of a vehicle tracking system across edge clouds in an embodiment of the present application. Figure 3 As shown, the cross-edge cloud vehicle tracking system includes:

[0091] at least one processor 320; and,

[0092] A memory 304 in communication with the at least one processor 320; wherein,

[0093] The memory 304 stores instructions that can be executed by the at least one processor 320, and the instructions are executed by the at least one processor 320 to implement the cross-edge cloud vehicle tracking method recorded in any of the above embodiments.

[0094] Reference Figure 3 The cross-edge cloud vehicle tracking system 300 may include one or more of the following components: a processing component 302, a memory 304, a power component 306, a multimedia component 308, an audio component 310, an input / output (I / O) interface 312, a sensor component 314, and a communication component 316.

[0095] The processing component 302 generally controls the overall operation of the vehicle tracking system 300 across the edge cloud. The processing component 302 may include one or more processors 320 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 302 may include one or more modules to facilitate the interaction between the processing component 302 and other components. For example, the processing component 302 may include a multimedia module to facilitate the interaction between the multimedia component 308 and the processing component 302.

[0096] The memory 304 is configured to store various types of data to support the operation of the vehicle tracking system 300 across the edge cloud. Examples of such data include instructions for any application or method operating on the vehicle tracking system 300 across the edge cloud, such as text, pictures, videos, etc. The memory 304 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0097] The power supply component 306 provides power to various components of the vehicle tracking system across edge clouds 300. The power supply component 306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the vehicle tracking system across edge clouds 300.

[0098] The multimedia component 308 includes a screen that provides an output interface between the vehicle tracking system 300 across the edge cloud and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 308 may also include a front camera and / or a rear camera. When the vehicle tracking system 300 across the edge cloud is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0099] The audio component 310 is configured to output and / or input audio signals. For example, the audio component 310 includes a microphone (MIC), and when the cross-edge cloud vehicle tracking system 300 is in an operating mode, such as an alarm mode, a recording mode, a voice recognition mode, and a voice output mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 304 or sent via the communication component 316. In some embodiments, the audio component 310 also includes a speaker for outputting an audio signal.

[0100] I / O interface 312 provides an interface between processing component 302 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0101] The sensor component 314 includes one or more sensors for providing various aspects of status assessment for the vehicle tracking system 300 across the edge cloud. For example, the sensor component 314 may include a sound sensor. In addition, the sensor component 314 can detect the open / closed state of the vehicle tracking system 300 across the edge cloud, the relative positioning of the components, such as the display and keypad of the vehicle tracking system 300 across the edge cloud, and the sensor component 314 can also detect the operating state of the vehicle tracking system 300 across the edge cloud or a component of the vehicle tracking system 300 across the edge cloud, the orientation or acceleration / deceleration of the vehicle tracking system 300 across the edge cloud, and the temperature change of the vehicle tracking system 300 across the edge cloud. The sensor component 314 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor component 314 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor component 314 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, or a temperature sensor.

[0102] The communication component 316 is configured to enable the cross-edge cloud vehicle tracking system 300 to provide the ability to communicate with other devices and cloud platforms in a wired or wireless manner. The cross-edge cloud vehicle tracking system 300 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 316 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0103] In an exemplary embodiment, the cross-edge cloud vehicle tracking system 300 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the cross-edge cloud vehicle tracking method described in any of the above embodiments.

[0104] The present application also provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor corresponding to the cross-edge cloud vehicle tracking system, the cross-edge cloud vehicle tracking system can implement the cross-edge cloud vehicle tracking method recorded in any of the above embodiments.

[0105] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0106] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A vehicle tracking method across edge clouds, characterized in that: include: In the process of continuously tracking the first target vehicle, judging whether the first target vehicle has the possibility of traveling across the edge cloud according to preset data of the first target vehicle; When the first target vehicle has the possibility of traveling across the edge cloud, predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud; Transmitting the track information of the first target vehicle to the first target edge cloud in real time, wherein the track information includes a unique ID assigned to the target vehicle, the vehicle position, speed, heading, and the original target object constituting the track; When it is detected that the first target vehicle is taken over by the first target edge cloud, the transmission of the track information of the first target vehicle to the first target edge cloud is stopped, and the connection with the first target edge cloud is disconnected.

2. The method according to claim 1, characterized in that The determining, based on preset data of the first target vehicle, whether the first target vehicle has the possibility of traveling across the edge cloud includes: When the first target vehicle enters the electronic fence at the edge cloud boundary, it is determined that the first target vehicle has the possibility of traveling across the edge cloud.

3. The method according to claim 1, characterized in that The predicting the first target edge cloud that the first target vehicle enters after traveling across the edge cloud includes: Determining a predicted driving trajectory of a first target vehicle based on the position of the vehicle, the historical trajectory of the vehicle, and the heading of the vehicle; It is determined that the edge cloud entered by the predicted driving trajectory when traveling across the edge cloud is the first target edge cloud.

4. The method according to claim 1, characterized in that The method further comprises: Extracting a vehicle position from the track information of the first target vehicle; When the vehicle position enters the coverage of the first target edge cloud, it is determined that the first target vehicle is taken over by the first target edge cloud.

5. The method according to claim 1, characterized in that Before transmitting the track information of the first target vehicle to the first target edge cloud in real time, the method further includes: Sending a connection request to the first target edge cloud; When the first target edge cloud responds to the connection request and successfully connects with the target edge cloud, the connection with the target edge cloud is maintained, wherein the connection with the target edge cloud ends when the first target vehicle is taken over by the first target edge cloud.

6. The method according to claim 1, characterized in that The method further comprises: When the track information of the second target vehicle sent by the second target edge cloud is received, the track information of the second target vehicle is managed by the remote track management module, and the track information of the managed second target vehicle is corrected according to the new track information of the second target vehicle continuously sent by the second target edge cloud.

7. The method according to claim 6, characterized in that The method further comprises: When a vehicle is detected entering the coverage area of ​​the local edge cloud, the real vehicle data of the vehicle is obtained; Comparing the real vehicle data with the track information of the second target vehicle managed by the remote track management module; When the comparison is consistent, determining that the vehicle entering is the second target vehicle; The vehicle is associated with the track information of the second target vehicle, and the second target vehicle is continuously tracked.

8. A vehicle tracking device across edge cloud, characterized in that: include: The edge cloud fusion module is used to fuse the data reported by the roadside across poles, assign a unique ID to the vehicle, and continuously track the vehicle based on the unique ID; A cross-edge cloud prediction module is used to determine whether the vehicle will travel across the edge cloud based on the vehicle's location, the vehicle's historical trajectory, and the vehicle's heading; The cross-edge cloud track transmission module is used to transmit the track information of the vehicle to the edge cloud entered by the vehicle after crossing the edge cloud when there is a possibility that the vehicle may travel across the edge cloud, wherein the track information includes the unique ID assigned to the target vehicle, the vehicle position, speed, heading and the original target object constituting the track.

9. The cross-edge cloud vehicle tracking device according to claim 8, characterized in that: The device also includes: The remote track management module is used to manage the remote track information sent by other edge clouds and to modify the managed remote track information according to the new remote track information continuously sent by other edge clouds; The remote track association module is used to obtain the real vehicle data of the vehicle when a vehicle is detected entering the coverage area of ​​the local edge cloud, and compare the real vehicle data with the remote track information managed by the remote track management module. When the comparison is consistent, the vehicle is associated with the corresponding remote track information.

10. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor corresponding to the cross-edge cloud vehicle tracking system, the cross-edge cloud vehicle tracking system can implement the cross-edge cloud vehicle tracking method as described in any one of claims 1-7.

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