Traffic participant identification method and electronic device for connected vehicles
By calculating the road side points to be screened for the connected vehicle association and screening traffic participants, the blind spots and blind spots of the connected vehicle when sensing environmental vehicles are solved, and cloud-based perception services for environmental traffic participants for connected vehicles are realized.
Patent Information
- Application Number
- CN202411919163.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-24
- Publication Date
- 2025-04-08
AI Technical Summary
The existing technology of connected vehicles has blind spots and blind spots when perceiving environmental vehicles, which affects the effect of autonomous driving.
By obtaining the real-time status data reported by the connected car, the roadside points to be screened associated with the connected car are calculated, and traffic participants are screened out from the perceived data reported by the connected car as environmental traffic participants of the connected car.
The information of traffic participants supplemented by roadside points solves the blind spots and blind spots in vehicle sense knowledge. In high real-time scenarios, cloud-based perception services for environmental traffic participants are provided for connected vehicles.
Smart Images
Figure CN119773805A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of vehicle-related technologies, and in particular to a method for identifying traffic participants of a networked vehicle, an electronic device, a storage medium, and a computer program product. Background Art
[0002] A connected car is an autonomous driving vehicle connected to a network server. When driving on a road, a connected car uses sensors to sense road conditions and detect traffic participants on the road, such as environmental vehicles on the road. The connected car then plans the driving path based on the status data of the detected traffic participants and the connected car's own data, or the server plans the driving path based on the status data of the traffic participants and the connected car's own data, thereby achieving autonomous driving.
[0003] However, due to the influence of factors such as the sensor perception range and occlusion in the road environment, the connected vehicles in the existing technology have problems such as blind spots and dead angles in their perception and identification of surrounding vehicles, which affects autonomous driving. Summary of the invention
[0004] Based on this, it is necessary to provide a method for identifying traffic participants in a connected vehicle, an electronic device, a storage medium and a computer program product to address the technical problems in the existing connected vehicle perception and recognition technologies, which have blind spots and dead angles and affect autonomous driving.
[0005] The present invention provides a method for identifying traffic participants of a connected vehicle, comprising:
[0006] Acquire real-time status data reported by the connected vehicle, and calculate the roadside points to be screened associated with the connected vehicle according to the real-time status data;
[0007] The environmental traffic participants of the connected vehicle are determined based on the traffic participants identified at the roadside points to be screened.
[0008] Further, the calculating, according to the real-time status data, the roadside points to be screened associated with the connected vehicle includes:
[0009] Generate a connected vehicle perception area based on the real-time status data;
[0010] The roadside point perception areas of all roadside points are obtained, collision calculation is performed using the connected vehicle perception area and all the roadside point perception areas, and the roadside points corresponding to the roadside point perception areas that collide with the connected vehicle perception area are used as the roadside points to be screened.
[0011] Furthermore, the connected vehicle perception area is a circle or polygon generated based on the connected vehicle perception range, with the longitude and latitude of the connected vehicle as the center.
[0012] Furthermore, the roadside point sensing area is a circle or polygon generated based on the roadside point sensing range with the longitude and latitude of the roadside point as the center.
[0013] Furthermore, the step of determining the environmental traffic participants of the connected vehicle based on the traffic participants identified at the roadside points to be screened includes:
[0014] From a database storing the perception data reported by the roadside points, the traffic participants reported by the roadside points to be screened are screened out as the environmental traffic participants of the connected vehicle.
[0015] Furthermore, it also includes:
[0016] Acquire sensing data reported by a roadside point, wherein the sensing data includes a roadside point identifier and information of identified traffic participants;
[0017] The perception data is saved in a database using the roadside point identifier as a key value.
[0018] Furthermore, the step of filtering out the traffic participants reported by the roadside points to be filtered from the database storing the perception data reported by the roadside points as the environmental traffic participants of the connected vehicle includes:
[0019] Calculating the road where the connected vehicle is located;
[0020] From a database storing perception data reported by roadside points, traffic participants reported by the roadside points to be screened and located on the road where the connected vehicle is located are screened out as environmental traffic participants of the connected vehicle.
[0021] The present invention provides an electronic device, comprising:
[0022] at least one processor; and,
[0023] a memory communicatively connected to at least one of the processors; wherein,
[0024] The memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors so that at least one of the processors can execute the traffic participant identification method for a connected vehicle as described above.
[0025] The present invention provides a storage medium, which stores computer instructions. When a computer executes the computer instructions, it is used to execute all steps of the traffic participant identification method for a networked vehicle as described above.
[0026] The present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the traffic participant identification method for a networked vehicle as described above.
[0027] The present invention calculates the roadside points to be screened associated with the connected vehicle through the real-time status data reported by the connected vehicle, and obtains the traffic participants identified by the roadside points to be screened as the environmental traffic participants of the connected vehicle. The information of traffic participants supplemented by the roadside points solves the blind spot problem in vehicle perception and recognition, and provides cloud perception services of environmental traffic participants to the connected vehicle in a high real-time scenario. BRIEF DESCRIPTION OF THE DRAWINGS
[0028] Figure 1 This is a workflow diagram of a method for identifying traffic participants in a networked vehicle according to an embodiment of the present invention;
[0029] Figure 2 This is a workflow diagram of a method for identifying traffic participants in a networked vehicle according to another embodiment of the present invention;
[0030] Figure 3 A flowchart of a method for identifying traffic participants in a networked vehicle according to a preferred embodiment of the present invention;
[0031] Figure 4 The figure is a schematic diagram of the hardware structure of an electronic device of the present invention. DETAILED DESCRIPTION
[0032] The specific embodiments of the present invention are further described below in conjunction with the accompanying drawings. The same components are represented by the same reference numerals. It should be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to directions in the accompanying drawings, and the words "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.
[0033] like Figure 1 The figure shows a workflow diagram of a method for identifying traffic participants of a networked vehicle according to an embodiment of the present invention, comprising:
[0034] Step S101, obtaining real-time status data reported by a connected vehicle, and calculating a roadside point to be screened associated with the connected vehicle according to the real-time status data;
[0035] Step S102: determining the environmental traffic participants of the connected vehicle according to the traffic participants identified at the roadside points to be screened.
[0036] Specifically, the present invention can be applied to electronic devices with processing capabilities, such as cloud servers.
[0037] First, execute step S101 to obtain real-time status data reported by the connected vehicle, and calculate the roadside points to be screened associated with the connected vehicle based on the real-time status data.
[0038] Specifically, the server uses a message queue to receive the real-time status data of the connected vehicle in real time. The real-time status data contains relevant information such as the connected vehicle number, longitude and latitude. Then, the real-time status data of the connected vehicle is consumed (taken out) from the message queue. For the acquired connected vehicle, the roadside points associated with the connected vehicle are calculated according to the longitude and latitude as the roadside points to be screened. Among them, the roadside points are traffic monitoring equipment on the roadside, including but not limited to traffic cameras, roadside sensors, traffic flow meters, etc. The roadside points identify traffic participants and determine the information of traffic participants. Traffic participants include but are not limited to environmental vehicles, pedestrians, etc. The information of traffic participants includes but is not limited to: traffic participant number, longitude and latitude of traffic participants, etc.
[0039] Then, step S102 is executed to determine the environmental traffic participants of the connected vehicle based on the traffic participants identified at the roadside points to be screened.
[0040] Specifically, the traffic participants identified by the roadside points to be screened are obtained, and a merge operation can be performed on the obtained traffic participants. Since the roadside points to be screened are near the connected vehicle, different roadside points to be screened may identify the same traffic participant. Therefore, a merge operation is performed to merge the same traffic participants in different roadside points to be screened to avoid data duplication.
[0041] Then, the environmental traffic participants of the connected vehicle are determined based on the traffic participants identified at the roadside points to be screened.
[0042] The information of the environmental traffic participants of the connected vehicle can be sent to the connected vehicle, and the connected vehicle performs the autonomous driving operation based on the received information of the traffic participants and the real-time status data of the vehicle. The server can also plan the driving trajectory of the connected vehicle based on the information of the environmental traffic participants of the connected vehicle and the real-time status data of the connected vehicle, and send the planned driving trajectory to the connected vehicle, so that the connected vehicle performs the autonomous driving operation.
[0043] The present invention calculates the roadside points to be screened associated with the connected vehicle through the real-time status data reported by the connected vehicle, obtains the traffic participants identified by the roadside points to be screened, and sends the information of the identified traffic participants to the connected vehicle. The traffic participant information supplemented by the roadside points solves the blind spot problem in vehicle perception and recognition, and provides cloud perception services of environmental traffic participants to the connected vehicle in a high real-time scenario.
[0044] like Figure 2 The flowchart of a method for identifying traffic participants of a networked vehicle in another embodiment of the present invention includes:
[0045] Step S201, obtaining real-time status data reported by the connected vehicle.
[0046] Step S202: Generate a connected vehicle perception area based on the real-time status data.
[0047] In one of the embodiments, the connected vehicle perception area is a circle or polygon generated based on the perception range of the connected vehicle with the longitude and latitude of the connected vehicle as the center.
[0048] Step S203, obtaining the roadside point perception areas of all roadside points, using the connected vehicle perception area and all the roadside point perception areas to perform collision calculation, and taking the roadside point corresponding to the roadside point perception area that collides with the connected vehicle perception area as the roadside point to be screened.
[0049] In one of the embodiments, the roadside point sensing area is a circle or polygon generated based on the roadside point sensing range with the longitude and latitude of the roadside point as the center.
[0050] Step S204: Filter out the traffic participants reported by the roadside points to be filtered from the database storing the perception data reported by the roadside points as the environmental traffic participants of the connected vehicle.
[0051] In one embodiment, it also includes:
[0052] Acquire sensing data reported by a roadside point, wherein the sensing data includes a roadside point identifier and information of identified traffic participants;
[0053] The perception data is saved in a database using the roadside point identifier as a key value.
[0054] In one embodiment, the step of selecting, from a database storing the perception data reported by the roadside points, the traffic participants reported by the roadside points to be selected as the environmental traffic participants of the connected vehicle includes:
[0055] Calculating the road where the connected vehicle is located;
[0056] From a database storing perception data reported by roadside points, traffic participants reported by the roadside points to be screened and located on the road where the connected vehicle is located are screened out as environmental traffic participants of the connected vehicle.
[0057] This embodiment is executed in a cloud server.
[0058] Specifically, first execute step S201 to obtain real-time status data reported by the connected vehicle.
[0059] Specifically, the server uses a message queue to receive the real-time status data of the connected vehicle in real time, and the real-time status data includes related information such as the connected vehicle number, longitude and latitude, etc. Then, the real-time status data of the connected vehicle is consumed (retrieved) from the message queue.
[0060] Then, step S202 is executed to generate a connected vehicle perception area based on the real-time status data.
[0061] Specifically, for the acquired connected vehicle A, the environmental vehicle perception area is generated according to the longitude and latitude and the perception range of the preset value (for example, 200 meters). Optionally, the road configuration is performed using the map data and the longitude and latitude of the connected vehicle and other location data to obtain the road number where the connected vehicle is currently located.
[0062] In one of the embodiments, the connected vehicle perception area is a circle or polygon generated based on the perception range of the connected vehicle with the longitude and latitude of the connected vehicle as the center.
[0063] In some embodiments:
[0064] A circle is generated with the longitude and latitude of the connected vehicle as the center and the sensing range of the connected vehicle as the radius as the sensing range of the connected vehicle; or
[0065] Generate a circle with the longitude and latitude of the connected vehicle as the center and the connected vehicle's sensing range as the radius, and draw a polygon inscribed in or circumscribed in the circle as the connected vehicle's sensing range; or
[0066] With the longitude and latitude of the connected vehicle as the center, a rectangle is drawn with twice the perception distance in the length direction of the connected vehicle body as the length, and twice the perception distance in the width direction of the connected vehicle body as the width, as the perception range of the connected vehicle.
[0067] Step S203, obtaining the roadside point perception areas of all roadside points, using the connected vehicle perception area and all the roadside point perception areas to perform collision calculation, and taking the roadside point corresponding to the roadside point perception area that collides with the connected vehicle perception area as the roadside point to be screened.
[0068] Get the list of roadside points from the system. For each road test point data, include the roadside point perception range of the road test point. Use the perception range of the connected vehicle and the perception range of the roadside point to perform collision calculation, and use the roadside points that collide with the perception range of the connected vehicle as the roadside points to be screened. The roadside points to be screened can be saved in the roadside point list.
[0069] In one of the embodiments, the roadside point sensing area is a circle or polygon generated based on the roadside point sensing range with the longitude and latitude of the roadside point as the center.
[0070] In some embodiments:
[0071] A circle is generated with the longitude and latitude of the roadside point as the center and the roadside point sensing range as the radius as the roadside point sensing range; or
[0072] A circle is generated with the longitude and latitude of the roadside point as the center and the roadside point sensing range as the radius, and a polygon inscribed in or circumscribed in the circle is made as the roadside point sensing range; or
[0073] With the longitude and latitude of the roadside point as the center and the side length of twice the roadside point perception distance as the perception range of the roadside point, a square is drawn.
[0074] Specifically, the connected vehicle perception polygon and the roadside point perception polygon are used for collision calculation, and the roadside points that collide with the connected vehicle perception polygon are used as roadside points to be screened.
[0075] Step S204: Filter out the traffic participants reported by the roadside points to be filtered from the database storing the perception data reported by the roadside points as the environmental traffic participants of the connected vehicle.
[0076] Specifically, the roadside points to be screened obtained by the above calculation are used to obtain corresponding perception data from the memory database, and the data are merged to obtain the final calculation result.
[0077] In one embodiment, it also includes:
[0078] Acquire sensing data reported by a roadside point, wherein the sensing data includes a roadside point identifier and information of identified traffic participants;
[0079] The perception data is saved in a database using the roadside point identifier as a key value.
[0080] Specifically, the message queue is used to receive the perception data reported by the roadside point in real time, and the reported perception data includes the roadside point identifier and the information of the identified traffic participant. The roadside point identifier is preferably the roadside point number. The information of the traffic participant includes the traffic participant number, the longitude and latitude of the traffic participant, and other information.
[0081] Then, the perception data in the message queue is consumed (retrieved) in real time, and the perception data is saved in a memory database (such as redis) according to the roadside point identifier as a key value.
[0082] In one embodiment, the step of selecting, from a database storing the perception data reported by the roadside points, the traffic participants reported by the roadside points to be selected as the environmental traffic participants of the connected vehicle includes:
[0083] Calculating the road where the connected vehicle is located;
[0084] From a database storing perception data reported by roadside points, traffic participants reported by the roadside points to be screened and located on the road where the connected vehicle is located are screened out as environmental traffic participants of the connected vehicle.
[0085] Specifically, the road configuration is performed using map data and the location data such as the longitude and latitude of the connected vehicle, and the road number of the connected vehicle can be obtained. The road matching calculation of the traffic participants in the perception data is performed with the map according to the longitude and latitude positions, and the road number of the traffic participants can be calculated, and the data of the traffic participants on the same road as the connected vehicle can be selected as the final calculation result.
[0086] This embodiment can ensure that cloud-based perception services of other traffic participants in the environment are provided to connected vehicles in high real-time scenarios. This embodiment uses a geospatial collision algorithm to calculate the perception area of the connected vehicle and the perception area of the roadside point, so as to quickly screen out one or more roadside points to be screened that collide with the perception area of the connected vehicle. Then, by subscribing to the perception data reported by the road test points to be screened, the information of traffic participants is screened out to solve the blind spot problem in vehicle perception and identification. Furthermore, since the traffic participants on different roads have little impact on the connected vehicle, the map road matching method is used to screen the information of traffic participants to reduce the amount of calculation.
[0087] like Figure 3 The flowchart of a method for identifying traffic participants of a networked vehicle in a preferred embodiment of the present invention is shown, comprising:
[0088] Step S301, generating a connected vehicle perception polygon based on the latitude and longitude and other vehicle running status data reported by the connected vehicle as the main vehicle, and performing collision calculation based on the connected vehicle perception polygon and the road test point perception polygon to obtain a list of road test point numbers where the connected vehicle is located;
[0089] Step S302, according to the road test point number calculated in step S301, filter and calculate the environmental vehicle information from the road test point perception data memory database.
[0090] Specifically, the main process of step S301 is as follows:
[0091] 1) Use the message queue to receive the real-time status data of the connected perception vehicle in real time. The real-time status data includes the connected vehicle number and longitude and latitude information.
[0092] 2) Consume the real-time status data of the connected vehicle from the message queue, and for the acquired connected vehicle A, generate the connected vehicle perception polygon according to the longitude and latitude and the preset perception range (e.g. 200 meters). Optionally, the road configuration is performed using the map data and the longitude and latitude of the connected vehicle and other location data to obtain the road number where the connected vehicle is currently located.
[0093] 3) Obtain a list of roadside points from the system, including the perception range polygon of each roadside point data. Use the connected vehicle perception polygon and each roadside point perception polygon to perform collision calculation, obtain the roadside points to be screened that collide with the connected vehicle perception polygon, and record the roadside point numbers of the roadside points to be screened as a list of roadside point numbers to be screened.
[0094] The process of step S302 is as follows:
[0095] 1) Use the message queue to receive the perception data reported by the roadside point in real time. The reported perception data includes the roadside point number, perception timestamp, number of the environmental vehicle identified by the roadside point, longitude and latitude, and other information.
[0096] 2) Consume the roadside point perception data in the message queue in real time, and save the roadside point perception data into a memory database (such as redis) according to the roadside point number as the key value.
[0097] 3) Using the list of roadside point numbers to be screened calculated in step S301, the corresponding perception data is obtained from the memory database, and the data is merged to obtain the final calculation result.
[0098] Optionally, the environmental vehicle identified by the roadside point to be screened is matched with the map according to the longitude and latitude position, and the road number where the environmental vehicle is located can be calculated, and the environmental vehicle information on the same road as the connected vehicle is screened as the final calculation result. The environmental vehicle information includes but is not limited to the number, longitude and latitude of the environmental vehicle.
[0099] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.
[0100] like Figure 4 The figure shows a hardware structure diagram of an electronic device of the present invention, including:
[0101] at least one processor 401; and,
[0102] A memory 402 is communicatively connected to at least one of the processors 401; wherein,
[0103] The memory 402 stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors so that the at least one processor can execute the traffic participant identification method for the connected vehicle as described above.
[0104] Figure 4 A processor 401 is taken as an example.
[0105] The electronic device may further include: an input device 403 and a display device 404 .
[0106] The processor 401, the memory 402, the input device 403 and the display device 404 may be connected via a bus or other means, and the figure takes the connection via a bus as an example.
[0107] The memory 402 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules corresponding to the method for identifying traffic participants in a connected vehicle in an embodiment of the present application, for example, Figure 1 , Figure 2 The processor 401 executes various functional applications and data processing by running the non-volatile software programs, instructions and modules stored in the memory 402, that is, the method for identifying traffic participants in the networked vehicle in the above embodiment is implemented.
[0108] The memory 402 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function; the data storage area may store data created according to the use of the method for identifying traffic participants in a networked vehicle, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 402 may optionally include a memory remotely arranged relative to the processor 401, and these remote memories may be connected to a device for executing the method for identifying traffic participants in a networked vehicle via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0109] The input device 403 can receive input user clicks and generate signal inputs related to user settings and function control of the traffic participant identification method of the networked vehicle. The display device 404 can include display devices such as a display screen.
[0110] The one or more modules are stored in the memory 402 , and when executed by the one or more processors 401 , the method for identifying traffic participants in a networked vehicle in any of the above method embodiments is executed.
[0111] The present invention calculates the roadside points to be screened associated with the connected vehicle through the real-time status data reported by the connected vehicle, obtains the traffic participants identified by the roadside points to be screened, and sends the information of the identified traffic participants to the connected vehicle. The traffic participant information supplemented by the roadside points solves the blind spot problem in vehicle perception and recognition, and provides cloud perception services of environmental traffic participants to the connected vehicle in a high real-time scenario.
[0112] An embodiment of the present invention provides a storage medium, which stores computer instructions. When a computer executes the computer instructions, it is used to execute all steps of the traffic participant identification method for a connected vehicle as described above.
[0113] In the context of the present disclosure, a storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. The storage medium may be a machine-readable signal medium or a machine-readable storage medium. Alternatively, the storage medium may be a non-temporary computer-readable storage medium, for example, a non-temporary computer-readable storage medium may be a ROM, a random access memory (Random Access Memory, RAM), a compact disc read-only memory (Compact Disc ROM, CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.
[0114] An embodiment of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the above-mentioned method for identifying traffic participants in a connected vehicle.
[0115] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.
Claims
1. A method for identifying traffic participants of a connected vehicle, characterized in that: include: Acquire real-time status data reported by the connected vehicle, and calculate the roadside points to be screened associated with the connected vehicle according to the real-time status data; The environmental traffic participants of the connected vehicle are determined based on the traffic participants identified at the roadside points to be screened.
2. The method for identifying traffic participants in a connected vehicle according to claim 1, characterized in that: The step of calculating the roadside points to be screened associated with the connected vehicle according to the real-time status data includes: Generate a connected vehicle perception area based on the real-time status data; The roadside point perception areas of all roadside points are obtained, collision calculation is performed using the connected vehicle perception area and all the roadside point perception areas, and the roadside points corresponding to the roadside point perception areas that collide with the connected vehicle perception area are used as the roadside points to be screened.
3. The method for identifying traffic participants of a connected vehicle according to claim 2, characterized in that: The connected vehicle perception area is a circle or polygon generated based on the connected vehicle's perception range, with the longitude and latitude of the connected vehicle as the center.
4. The method for identifying traffic participants of a connected vehicle according to claim 2, characterized in that: The roadside point sensing area is a circle or polygon generated based on the roadside point sensing range with the longitude and latitude of the roadside point as the center.
5. The method for identifying traffic participants of a connected vehicle according to claim 1, characterized in that: The step of determining the environmental traffic participants of the connected vehicle according to the traffic participants identified by the roadside points to be screened includes: From a database storing the perception data reported by the roadside points, the traffic participants reported by the roadside points to be screened are screened out as the environmental traffic participants of the connected vehicle.
6. The method for identifying traffic participants of a connected vehicle according to claim 5, characterized in that: Also includes: Acquire sensing data reported by a roadside point, wherein the sensing data includes a roadside point identifier and information of identified traffic participants; The perception data is saved in a database using the roadside point identifier as a key value.
7. The method for identifying traffic participants of a connected vehicle according to claim 5, characterized in that: The step of selecting, from a database storing the perception data reported by the roadside points, the traffic participants reported by the roadside points to be selected as the environmental traffic participants of the connected vehicle includes: Calculating the road where the connected vehicle is located; From a database storing perception data reported by roadside points, traffic participants reported by the roadside points to be screened and located on the road where the connected vehicle is located are screened out as environmental traffic participants of the connected vehicle.
8. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors so that at least one of the processors can execute the traffic participant identification method for a connected vehicle as described in any one of claims 1 to 7.
9. A storage medium, characterized in that: The storage medium stores computer instructions, which, when executed by a computer, are used to execute all steps of the method for identifying traffic participants in a connected vehicle as described in any one of claims 1 to 7.
10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the method for identifying traffic participants in a connected vehicle as described in any one of claims 1 to 7 is implemented.