CN115116044A

CN115116044A - Vehicle identification information processing method, device and equipment and automatic driving vehicle

Info

Publication number: CN115116044A
Application number: CN202210757556.XA
Authority: CN
Inventors: 谭业辉; 刘楠科
Original assignee: Apollo Zhilian Beijing Technology Co Ltd
Current assignee: Apollo Zhilian Beijing Technology Co Ltd
Priority date: 2022-06-29
Filing date: 2022-06-29
Publication date: 2022-09-27

Abstract

The disclosure provides a vehicle identification information processing method, device and equipment and an automatic driving vehicle, and relates to the technical field of artificial intelligence, in particular to the technical fields of Internet of vehicles, intelligent transportation, automatic driving and the like. The specific implementation scheme is as follows: acquiring first perception data of a target vehicle, wherein the first perception data comprise first vehicle characteristic information of the target vehicle; acquiring target vehicle identification information of the target vehicle based on the first vehicle characteristic information, wherein the target vehicle identification information is used for identifying the target vehicle in a network; outputting a first message including the target vehicle identification information. The vehicle identification method and the vehicle identification device can realize the identification of the vehicle in the network through the vehicle identification information so as to improve the capacity of identifying the vehicle.

Description

Vehicle identification information processing method, device and equipment and automatic driving vehicle

Technical Field

The disclosure relates to the technical field of artificial intelligence, such as internet of vehicles, intelligent transportation, automatic driving and the like, in particular to a vehicle identification information processing method, device and equipment and an automatic driving vehicle.

Background

The development of free science and technology and economy, vehicles are more and more at present, and for the identification vehicle at present, a license plate is mainly configured for the vehicle, and is hung on the vehicle, so that the purpose of identifying the vehicle is achieved.

Disclosure of Invention

The disclosure provides a vehicle identification information processing method, a device and equipment and an automatic driving vehicle.

According to an aspect of the present disclosure, there is provided a vehicle identification information processing method including:

acquiring first perception data of a target vehicle, wherein the first perception data comprise first vehicle characteristic information of the target vehicle;

acquiring target vehicle identification information of the target vehicle based on the first vehicle characteristic information, wherein the target vehicle identification information is used for identifying the target vehicle in a network;

outputting a first message including the target vehicle identification information.

According to another aspect of the present disclosure, there is provided a vehicle identification information processing apparatus including:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring first perception data of a target vehicle, and the first perception data comprises first vehicle characteristic information of the target vehicle;

a second obtaining module, configured to obtain target vehicle identification information of the target vehicle based on the first vehicle characteristic information, where the target vehicle identification information is used to identify the target vehicle in a network;

an output module to output a first message, the first message including the target vehicle identification information.

According to another aspect of the present disclosure, there is provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods provided by the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method provided by the present disclosure.

According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method provided by the present disclosure.

According to another aspect of the present disclosure, an autonomous vehicle is provided, including an electronic device provided by the present disclosure.

In the present disclosure, since the target vehicle identification information of the target vehicle is acquired based on the first vehicle characteristic information, the target vehicle identification information is used to identify the target vehicle in the network, and the first message including the target vehicle identification information is output, it is possible to identify the vehicle in the network by the vehicle identification information to improve the ability of identifying the vehicle.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of a vehicle identification information processing method provided by the present disclosure;

FIG. 2 is a schematic illustration of vehicle identification information provided by the present disclosure;

FIG. 3 is a schematic diagram of a vehicle identification information processing method provided by the present disclosure;

FIG. 4 is a schematic illustration of another vehicle identification information processing method provided by the present disclosure;

fig. 5a and 5b are schematic diagrams of a vehicle identification information processing apparatus provided by the present disclosure;

FIG. 6 is a block diagram of an electronic device used to implement embodiments of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

Referring to fig. 1, fig. 1 is a flowchart of a vehicle identification information processing method provided by the present disclosure, as shown in fig. 1, including the following steps:

step S101, first perception data of a target vehicle are obtained, and the first perception data comprise first vehicle characteristic information of the target vehicle.

The obtaining of the first sensing data of the target vehicle may be that the first sensing data is obtained by performing sensing operation or sensing measurement on the target vehicle. For example: and performing sensing operation or sensing measurement on the target vehicle through a radar sensor, a visual sensor or a communication interface to obtain the first sensing data.

The first vehicle characteristic information may be information for characterizing the target vehicle, such as characteristic information of shape, size, speed, position, and the like.

The target vehicle may be a car, a truck, a bus, a motorcycle, etc., and the target vehicle may be a non-networked vehicle, and in some embodiments, the target vehicle may also be a networked vehicle.

In this disclosure, non-networking vehicle means the vehicle that can't network, and non-networking vehicle can't carry out the network interaction with equipment such as other vehicles, roadside equipment, high in the clouds promptly, and networking vehicle means the vehicle that can network, and networking vehicle can carry out the network interaction with equipment such as other vehicles, roadside equipment, high in the clouds promptly.

Step S102, obtaining target vehicle identification information of the target vehicle based on the first vehicle characteristic information, wherein the target vehicle identification information is used for identifying the target vehicle in a network.

The above-mentioned obtaining the target vehicle identification information of the target vehicle based on the first vehicle characteristic information may be generating the target vehicle identification information of the target vehicle based on the first vehicle characteristic information, or may be selecting the target vehicle identification information among a plurality of candidate vehicle identification information based on the first vehicle characteristic information.

The target vehicle identification information may be used to identify the target vehicle in a network, where the uniqueness of the vehicle is identified, that is, the target vehicle identification information corresponds to the target vehicle in the network.

In this disclosure, the above-mentioned network can be vehicle road cooperative network, and this network can support the network interaction between vehicle, roadside equipment, high in the clouds and the user terminal.

In some embodiments, the network is a regional network, and the network is a network of a local region where the target vehicle is located, so that the uniqueness of the target vehicle can be determined in the surrounding environment of the target vehicle, that is, the target vehicle identification information may be local vehicle identification information of the local region.

In some embodiments, the vehicle identification information in the present disclosure may be a vehicle number or an identification.

And step S103, outputting a first message, wherein the first message comprises the target vehicle identification information.

The outputting the first message may be sending the first message to a surrounding environment, so that a vehicle, a roadside device, a user terminal, or the like in the environment may receive the first message to determine target vehicle identification information of the target vehicle. Alternatively, the outputting the first message may be displaying the first message on a display device, that is, displaying the identification information of the target vehicle, for example, displaying the identification information of the target vehicle on a large traffic management screen, so as to facilitate better traffic management of transportation personnel.

In the present disclosure, based on the above steps, the vehicle can be identified in the network through the vehicle identification information, so as to improve the capability of identifying the vehicle.

In addition, the vehicle identification information can be used for uniquely indicating the vehicle in the vehicle-road cooperative network, so that the development of the vehicle-road cooperative service is facilitated, and the problems of repeated perception of the same vehicle and false alarm and false statistics can be avoided.

It should be noted that the above method may be applied to an electronic device, that is, all steps of the above method are performed by the electronic device, and the electronic device may be an electronic device such as a vehicle, a road side device, and the like, for example, an autonomous driving vehicle.

In one embodiment, step S102 in the embodiment shown in fig. 1 includes:

generating first candidate vehicle identification information of the target vehicle based on the first vehicle characteristic information, the first candidate vehicle identification information being associated with a first time;

matching the first vehicle characteristic information with second vehicle characteristic information in the case of receiving a second message, the second message indicating second candidate vehicle identification information, the second vehicle characteristic information and a second time;

determining the target vehicle identification information in the first candidate vehicle identification information and the second candidate identification information if the first vehicle characteristic information matches the second vehicle characteristic information;

wherein the target vehicle identification information is the first candidate vehicle identification information when the first time is earlier than the second time, and the target vehicle identification information is the second candidate vehicle identification information when the first time is later than the second time.

The generating of the first candidate vehicle identification information of the target vehicle based on the first vehicle characteristic information may be generating the first candidate vehicle identification information according to a preset identification information generation rule.

The first candidate vehicle identification information may be associated with a first time, where the first candidate vehicle identification information may have a corresponding relationship with the first time, and the first time may be a first vehicle sensing time for sensing the target vehicle or a generation time for generating the first candidate vehicle identification information.

The second message may be a message sent by the networked vehicle or the roadside device, for example: and the networked vehicle or the roadside device broadcasts the second message to the surroundings.

The matching between the first vehicle characteristic information and the second vehicle characteristic information may be that the first vehicle characteristic information is the same as the second vehicle characteristic information, or the similarity between the first vehicle characteristic information and the second vehicle characteristic information is higher than a preset threshold, or the number of the same characteristics between the first vehicle characteristic information and the second vehicle characteristic information exceeds a preset threshold, or the like.

It should be noted that, in this embodiment, the execution order of the step of generating the first candidate vehicle identification information and the step of receiving the second message is not limited, for example: the first candidate vehicle identification information may be generated and then the second message may be received, or the second message may be received and then the first candidate vehicle identification information may be generated.

In the embodiment, the target vehicle identification information can be determined from the candidate vehicle identification information which is earlier in time, so that the finally determined target vehicle identification information can be ensured to be unique, and the vehicle identification error caused by the existence of a plurality of vehicle identification information in the same vehicle can be avoided.

It should be noted that, in the present disclosure, if the vehicle feature information associated with two candidate vehicle identification information matches and the time is the same, the two candidate vehicle identification information are the same vehicle identification information.

In one embodiment, the first perception data includes a first vehicle perception time for perceiving the target vehicle, the first time is the first vehicle perception time, the second time is a second vehicle perception time, and the second vehicle perception time is a perception time for perceiving a vehicle corresponding to the second candidate vehicle identification information by the device sending the second message; or

The first time is the generation time of the first candidate vehicle identification information, and the second time is the generation time of the second candidate vehicle identification information.

The first vehicle sensing time for sensing the target vehicle may be a vehicle sensing time for sensing the target vehicle for the first time, that is, a starting time for sensing the target vehicle. The sensing the first vehicle sensing time of the target vehicle may also include sensing a start time and an end time of the target vehicle

In this embodiment, the candidate vehicle identification information with the vehicle perception time or the generation time being earlier can be used for determining the target vehicle identification information, so that the finally determined target vehicle identification information can be ensured to be unique, and the vehicle identification error caused by the existence of a plurality of vehicle identification information in the same vehicle can be avoided.

In one embodiment, the second message includes the second candidate vehicle identification information, the second candidate vehicle identification information indicating the second vehicle characteristic information and the second time, and the first candidate vehicle identification information indicating the first vehicle characteristic information and the first time; alternatively, the first and second electrodes may be,

the second message includes the second candidate vehicle identification information, the second vehicle characteristic information, and the second time; the first message includes the target vehicle identification information, the first vehicle characteristic information, and the first time when the target vehicle identification information is the first candidate vehicle identification information, and includes the target vehicle identification information, the first vehicle characteristic information, and the second time when the target vehicle identification information is the second candidate vehicle identification information.

The first candidate vehicle identification information is used for indicating the first vehicle characteristic information and the first time, and it is understood that the vehicle characteristic information and the first time may be embodied in the first candidate vehicle identification information.

For example: taking fig. 2 as an example, 201 shown in fig. 2 is used for indicating the type of the target vehicle, such as a non-internet vehicle, 202 shown in fig. 2 is used for indicating the color of the target vehicle, such as 00 for white, and 203 shown in fig. 3 is used for indicating the first time. It should be noted that the vehicle identification information shown in fig. 2 is only an example, and the disclosure is not limited thereto.

In this embodiment, the vehicle identification information indicates the vehicle characteristic information and time, which can save message overhead.

In addition, in this embodiment, when the target vehicle identification information is the second candidate vehicle identification information, the first message may include the target vehicle identification information, the first vehicle characteristic information, and the second time, so that the time included in the first message may be the earliest time corresponding to the target vehicle identification information, so as to avoid a judgment error of the device vehicle identification information that receives the first message.

In one embodiment, step S102 shown in fig. 1 further includes:

determining the first vehicle characteristic information as the target vehicle characteristic information if the second message is not received;

wherein the target vehicle characteristic information is indicative of the first vehicle characteristic information and the first time; alternatively, the first message includes the target vehicle identification information, the first vehicle characteristic information, and the first time.

In this embodiment, it may be achieved that, under the condition that the second message is not received, the first vehicle feature information is directly determined as the target vehicle feature information, and the first message is sent, so that the target vehicle feature information may be obtained in time by other vehicles, the routing device, and the cloud, and thus the working efficiency is improved.

In one embodiment, the first vehicle characteristic information in the present disclosure includes at least one of:

vehicle static characteristic information and vehicle dynamic characteristic information;

wherein the vehicle static characteristic information comprises at least one of:

color, model, license plate and size;

the vehicle dynamic characteristic information includes at least one of:

the system comprises position, speed, orientation and track information, wherein the track information is a running track of the target vehicle in a target time period.

Similarly, the second vehicle characteristic information in the present disclosure includes at least one of:

color, model, license plate and size;

the vehicle dynamic characteristic information includes at least one of:

position, velocity, orientation, and trajectory information.

The running track of the target vehicle in the target time period may be a running track composed of positions at multiple times, so that whether the vehicle characteristic information in the first message and the second message is the characteristic information of the same vehicle can be more accurately judged through the running track.

In this embodiment, whether the vehicle feature information in the first message and the second message is feature information of the same vehicle can be more accurately determined through the static feature information and the dynamic feature information, so as to improve the accuracy of the target vehicle identification information.

In one embodiment, the target vehicle is a non-networked vehicle, and step S101 in the embodiment shown in fig. 1 includes:

and sensing the target vehicle under the condition that a third message which is sent by the target vehicle and comprises vehicle identification information is not received, so as to obtain the first sensing data of the target vehicle.

The third message including the vehicle identification information, which is not received from the target vehicle, may be understood as detecting that the target vehicle is a non-networked vehicle.

In the embodiment, the target vehicle can be perceived only when the target vehicle is determined to be a non-internet vehicle, so that the vehicle with the vehicle identification information can be prevented from being perceived, and perception overhead is saved.

In one embodiment, the above method is performed by a first networked vehicle, the method further comprising:

detecting the number of networked vehicles in a target area;

determining the distance between the first internet vehicle and a second internet vehicle under the condition that the quantity is smaller than a preset threshold value, wherein the second internet vehicle is the internet vehicle which is closest to the first internet vehicle in the target area;

calculating a perception area of the first networked vehicle within the target area based on the position of the first networked vehicle and a distance between the first networked vehicle and a second networked vehicle;

wherein the target vehicle is a non-networked vehicle within the perception area.

The target area is a local position area where the target vehicle is located or a local position area where the first networked vehicle is located.

The number of networked vehicles in the detection target area may be that a networked vehicle discovery request message is sent in the target area, and when receiving the discovery request message, the networked vehicle returns a confirmation message to the first networked vehicle, thereby determining which vehicles are networked vehicles, and finally determining the number of networked vehicles in the target area. Alternatively, the number of networked vehicles in the target area is determined by vehicle identification information of networked vehicles in the network, since, in some embodiments, the vehicle identification information may indicate the type of vehicle, i.e. which vehicles are networked vehicles may be determined by the vehicle identification information. In some embodiments, the vehicle identification information of the networked vehicle may be distributed by a network, or may be generated by vehicle characteristic information, which is not limited to this.

The preset threshold may be a threshold preset according to actual service requirements, such as 3, 4, or 5.

The determining of the distance between the first internet vehicle and the second internet vehicle may be performed by performing sensing operation on the second internet vehicle to obtain the distance between the first internet vehicle and the second internet vehicle, or may be performed by interacting respective position information between the first internet vehicle and the second internet vehicle to calculate the distance between the first internet vehicle and the second internet vehicle.

The calculating of the sensing area of the first networked vehicle in the target area may be dividing a position area between the first networked vehicle and the second networked vehicle into two sensing areas, which are respectively used as sensing areas of the first networked vehicle and the second networked vehicle, where the two sensing areas are at least partially non-overlapping, and may be allowed to be partially overlapping in some embodiments.

The target vehicle is a non-networked vehicle in the sensing area, and the first networked vehicle only senses the vehicle in the sensing area, so that sensing cost can be saved.

The following description is given by taking the target vehicle as a non-internet vehicle, and as shown in fig. 3, the method includes the following steps:

step S301, vehicle data in the road side equipment or the first vehicle perception range;

step S302, recording vehicle perception data of the non-networked vehicle by the road side equipment or the vehicle, wherein the vehicle perception data comprises: the initial sensing time T1, the dynamic vehicle characteristic information and the static vehicle characteristic information;

step S303, the roadside device or the first vehicle locally defines a non-networked vehicle number (such as FWL00T1) according to vehicle perception data of the non-networked vehicle, namely defines vehicle identification information;

step S304, the road side equipment or the first vehicle sends a non-internet vehicle number, primary sensing time T1, dynamic vehicle characteristic information and static vehicle characteristic information to the surroundings; it should be noted that, in the drawings, S304 is illustrated as being executed multiple times;

step S305, vehicle data in a second vehicle perception range;

step S306, recording vehicle perception data of the non-networked vehicle by the second vehicle, wherein the vehicle perception data comprises: the initial sensing time T2, the dynamic vehicle characteristic information and the static vehicle characteristic information;

step S307, the second vehicle locally defines a non-networked vehicle number (such as FWL00T2) according to vehicle perception data of the non-networked vehicle, namely defines vehicle identification information;

step S308, the second vehicle matches the characteristic information of the non-networked vehicle with the sensed vehicle characteristic information;

step S309, comparing the first sensing time of the successfully matched non-networked vehicles by the second vehicle to determine the number of the non-networked vehicles (FWL00T1 or FWL00T 2);

and S310, the second vehicle sends the non-internet vehicle serial number, the first sensing time, the dynamic vehicle characteristic information and the static vehicle characteristic information to the periphery.

Fig. 3 illustrates interaction among a plurality of devices, and the steps performed by the second vehicle shown in fig. 3 may be performed by a road side device. For example: in one embodiment, when the vehicle or the roadside sensing device detects the non-networked vehicle, a number distinguished from the networked vehicle, such as FWL00T1 (non-networked 1), is given to the non-networked vehicle, when the non-networked vehicle is recognized for the first time, dynamic vehicle characteristic information such as the first sensing time, position, speed, size orientation and the like of the non-networked vehicle, static vehicle characteristic information such as vehicle color, vehicle license plate and the like, and a historical track of the non-networked vehicle are continuously recorded, the number, the dynamic vehicle characteristic, the static vehicle characteristic and the historical track of the non-networked vehicle are sent to the surrounding environment, after the surrounding vehicle or the roadside device receives the data, the data are matched and compared with vehicle data sensed by the surrounding vehicle or the roadside device, if the dynamic vehicle characteristic, the static vehicle characteristic and the historical track are matched successfully, the judgment is carried out successively according to the first sensing time, if the time of the received sensing data is earlier than the self sensing time of the vehicle, the vehicle updates the corresponding number of the non-networked vehicle, such as FWL001 (non-networked No. 1), to determine the non-networked vehicle number.

In the following, the target vehicle is also exemplified as a non-networked vehicle, and as shown in fig. 4, the method includes the following steps:

step S401, acquiring environment perception data through road side equipment, wherein the environment perception data comprise vehicle characteristic information, vehicle numbers and primary perception time;

s402, acquiring environment perception data through a vehicle sensor, wherein the environment perception data comprises vehicle characteristic information, a vehicle number and primary perception time;

s403, comparing the environmental perception data obtained through the road side equipment with the environmental perception data obtained through the vehicle sensor;

s404, determining that the matching is successful, namely that the environment sensing data is obtained through the road side equipment and the environment sensing data is obtained through the vehicle sensor to represent the same vehicle;

step S405, judging the sequence of the primary sensing time;

and S406, selecting the vehicle number with the early primary sensing time.

For example: the vehicle compares the vehicle data sensed by the vehicle with the non-networked vehicle data sent by other vehicles or roadside, after the matching is successful by matching the dynamic and/or static vehicle characteristic information of the non-networked vehicle, the initial sensing time T2 of the vehicle is compared with the initial sensing time T1 of other vehicles or roadside, the number of the non-networked vehicle corresponding to the position before the initial sensing time is selected, if T2 is later than T1, the corresponding number of the non-networked vehicle is FWL00T1, and when the vehicle sends the sensing data to the surrounding environment, the number of the same non-networked vehicle, namely FWL00T2, is updated to FWL00T 1.

Referring to fig. 5a, fig. 5a is a vehicle identification information processing apparatus provided by the present disclosure, and as shown in fig. 5a, the vehicle identification information processing apparatus 500 includes:

a first obtaining module 501, configured to obtain first perception data of a target vehicle, where the first perception data includes first vehicle characteristic information of the target vehicle;

a second obtaining module 502, configured to obtain target vehicle identification information of the target vehicle based on the first vehicle characteristic information, where the target vehicle identification information is used to identify the target vehicle in a network;

an output module 503, configured to output a first message, where the first message includes the target vehicle identification information.

Optionally, the second obtaining module 502 is configured to:

Optionally, the first perception data includes a first vehicle perception time for perceiving the target vehicle, where the first time is the first vehicle perception time, the second time is a second vehicle perception time, and the second vehicle perception time is a perception time for perceiving, by the device sending the second message, the vehicle corresponding to the second candidate vehicle identification information; or alternatively

Optionally, the second message includes the second candidate vehicle identification information, the second candidate vehicle identification information is used to indicate the second vehicle characteristic information and the second time, and the first candidate vehicle identification information is used to indicate the first vehicle characteristic information and the first time; alternatively, the first and second electrodes may be,

Optionally, the second obtaining module 502 is further configured to:

Optionally, the first vehicle characteristic information includes at least one of:

color, model, license plate and size;

the vehicle dynamic characteristic information includes at least one of:

Optionally, the target vehicle is a non-internet vehicle, and the first obtaining module 501 is configured to:

Optionally, the apparatus is an apparatus in a first networked vehicle, as shown in fig. 5b, the apparatus further includes:

a detection module 504, configured to detect the number of networked vehicles in a target area;

a determining module 505, configured to determine, when the number is smaller than a preset threshold, a distance between the first internet vehicle and a second internet vehicle, where the second internet vehicle is an internet vehicle closest to the first internet vehicle in the target area;

a calculating module 506, configured to calculate a perception area of the first networked vehicle within the target area based on a position of the first networked vehicle and a distance between the first networked vehicle and a second networked vehicle;

The vehicle identification information processing device provided by the disclosure can realize each process realized by the vehicle identification information processing method provided by the disclosure, and achieve the same technical effect, and is not repeated here for avoiding repetition.

The present disclosure also provides an electronic device, a readable storage medium, a computer program product, and an autonomous vehicle according to embodiments of the present disclosure.

Wherein, above-mentioned electronic equipment includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the vehicle identification information processing method provided by the present disclosure.

The readable storage medium stores computer instructions for causing the computer to execute the vehicle identification information processing method provided by the present disclosure.

The above-mentioned computer program product includes a computer program which, when executed by a processor, implements the vehicle identification information processing method provided by the present disclosure.

The automatic driving vehicle comprises the electronic equipment provided by the disclosure.

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.

FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 6, the apparatus 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, and the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 601 executes the respective methods and processes described above, such as the vehicle identification information processing method. For example, in some embodiments, the vehicle identification information processing method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the vehicle identification information processing method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the vehicle identification information processing method in any other suitable manner (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A vehicle identification information processing method, comprising:

2. The method of claim 1, wherein the obtaining vehicle identification information of the target vehicle based on the first vehicle characteristic information comprises:

wherein the target vehicle identification information is the first candidate vehicle identification information if the first time is earlier than the second time, and the target vehicle identification information is the second candidate vehicle identification information if the first time is later than the second time.

3. The method of claim 2, wherein the first perception data includes a first vehicle perception time for perceiving the target vehicle, the first time is the first vehicle perception time, the second time is a second vehicle perception time, and the second vehicle perception time is a perception time for a device sending the second message to perceive a vehicle corresponding to the second candidate vehicle identification information; or

4. The method of claim 2, wherein the second message includes the second candidate vehicle identification information, the second candidate vehicle identification information indicating the second vehicle characteristic information and the second time, and the first candidate vehicle identification information indicating the first vehicle characteristic information and the first time; alternatively, the first and second electrodes may be,

5. The method of claim 2, wherein the obtaining vehicle identification information of the target vehicle based on the first vehicle characteristic information further comprises:

6. The method of any of claims 1-5, wherein the first vehicle characteristic information includes at least one of:

color, model, license plate and size;

the vehicle dynamic characteristic information comprises at least one of the following:

7. The method of any one of claims 1 to 5, wherein the target vehicle is a non-networked vehicle, the obtaining first perception data of the target vehicle comprising:

and under the condition that a third message which is sent by the target vehicle and comprises vehicle identification information is not received, the target vehicle is perceived to obtain the first perception data of the target vehicle.

8. The method of claim 7, wherein the method is performed by a first networked vehicle, the method further comprising:

detecting the number of networked vehicles in a target area;

determining the distance between the first internet vehicle and a second internet vehicle under the condition that the number is smaller than a preset threshold value, wherein the second internet vehicle is the internet vehicle which is closest to the first internet vehicle in the target area;

9. A vehicle identification information processing device comprising:

10. The apparatus of claim 9, wherein the second obtaining means is configured to:

11. The apparatus according to claim 10, wherein the first perception data includes a first vehicle perception time for perceiving the target vehicle, the first time is the first vehicle perception time, the second time is a second vehicle perception time, and the second vehicle perception time is a perception time for a device sending the second message to perceive a vehicle corresponding to the second candidate vehicle identification information; or

12. The apparatus of claim 10, wherein the second message includes the second candidate vehicle identification information, the second candidate vehicle identification information to indicate the second vehicle characteristic information and the second time, and the first candidate vehicle identification information to indicate the first vehicle characteristic information and the first time; alternatively, the first and second electrodes may be,

13. The apparatus of claim 10, wherein the second obtaining means is further configured to:

14. The apparatus of any of claims 9 to 13, wherein the first vehicle characteristic information comprises at least one of:

color, model, license plate and size;

the vehicle dynamic characteristic information includes at least one of:

15. The apparatus of any of claims 9-13, wherein the target vehicle is a non-networked vehicle, the first obtaining module to:

16. The apparatus of claim 15, wherein the apparatus is an apparatus in a first networked vehicle, the apparatus further comprising:

the detection module is used for detecting the number of networked vehicles in the target area;

the determining module is used for determining the distance between the first internet vehicle and a second internet vehicle under the condition that the number is smaller than a preset threshold value, wherein the second internet vehicle is the internet vehicle which is closest to the first internet vehicle in the target area;

the calculation module is used for calculating a perception area of the first networked vehicle in the target area based on the position of the first networked vehicle and the distance between the first networked vehicle and a second networked vehicle;

17. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.

19. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-8.

20. An autonomous vehicle comprising the electronic device of claim 17.