Vehicle identification information processing method, device, equipment and autonomous driving vehicle
By acquiring and processing vehicle feature information, generating or selecting vehicle identification information and identifying vehicles in the network, the problems of vehicle identification errors and repeated perception in the prior art are solved, and more accurate and efficient vehicle identification is achieved.
Patent Information
- Application Number
- CN202210757556.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-06-29
- Publication Date
- 2024-12-27
- Estimated Expiration
- 2042-06-29
AI Technical Summary
The prior art is difficult to efficiently identify vehicles, especially non-connected vehicles, in the network, resulting in vehicle identification errors and repeated perception problems.
By acquiring the perceived data of the target vehicle, generating or selecting vehicle identification information based on the vehicle characteristic information, and uniquely identifying it in the network, and outputting messages to identify the vehicle in the vehicle-road collaborative network to avoid repeated perception.
It improves the accuracy and uniqueness of vehicle identification, reduces the problem of false alarms and misstating statistics, and enhances the identification ability of vehicles in the network.
Smart Images
Figure CN115116044B_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the fields of artificial intelligence technologies such as Internet of Vehicles, intelligent transportation, and autonomous driving, and in particular to a vehicle identification information processing method, device, equipment, and autonomous driving vehicle. Background Art
[0002] With the development of science and technology and economy, there are more and more vehicles. Currently, the main way to identify a vehicle is to configure a license plate for the vehicle and hang the license plate on the vehicle to achieve the purpose of identifying the vehicle. Summary of the invention
[0003] The present disclosure provides a vehicle identification information processing method, device, equipment and an autonomous driving vehicle.
[0004] According to one aspect of the present disclosure, a vehicle identification information processing method is provided, comprising:
[0005] Acquire first perception data of a target vehicle, wherein the first perception data includes first vehicle characteristic information of the target vehicle;
[0006] Based on the first vehicle characteristic information, acquiring target vehicle identification information of the target vehicle, wherein the target vehicle identification information is used to identify the target vehicle in a network;
[0007] A first message is output, wherein the first message includes the target vehicle identification information.
[0008] According to another aspect of the present disclosure, there is provided a vehicle identification information processing device, comprising:
[0009] A first acquisition module, used to acquire first perception data of a target vehicle, wherein the first perception data includes first vehicle characteristic information of the target vehicle;
[0010] A second acquisition module, used for 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 the network;
[0011] The output module is used to output a first message, wherein the first message includes the target vehicle identification information.
[0012] According to another aspect of the present disclosure, there is provided an electronic device, comprising:
[0013] at least one processor; and
[0014] a memory communicatively connected to the at least one processor; wherein,
[0015] 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 enable the at least one processor to perform the method provided by the present disclosure.
[0016] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method provided by the present disclosure.
[0017] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein the computer program implements the method provided by the present disclosure when executed by a processor.
[0018] According to another aspect of the present disclosure, an autonomous driving vehicle is provided, comprising the electronic device provided by the present disclosure.
[0019] In the present disclosure, since the target vehicle identification information of the target vehicle is obtained based on the first vehicle characteristic information, the target vehicle identification information is used to identify the target vehicle in the network, and a first message including the target vehicle identification information is output, it is possible to identify the vehicle in the network through the vehicle identification information to improve the ability to identify the vehicle.
[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.
[0022] Figure 1 is a flow chart of a vehicle identification information processing method provided by the present disclosure;
[0023] Figure 2 is a schematic diagram of vehicle identification information provided by the present disclosure;
[0024] Figure 3 is a schematic diagram of a vehicle identification information processing method provided by the present disclosure;
[0025] Figure 4 is a schematic diagram of another vehicle identification information processing method provided by the present disclosure;
[0026] Figure 5a and 5b is a schematic diagram of a vehicle identification information processing device provided by the present disclosure;
[0027] Figure 6 is a block diagram of an electronic device for implementing the embodiments of the present disclosure. DETAILED DESCRIPTION
[0028] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.
[0029] See also Figure 1 , Figure 1 is a flow chart of a vehicle identification information processing method provided by the present disclosure, such as Figure 1 As shown, the following steps are included:
[0030] Step S101: Acquire first perception data of a target vehicle, where the first perception data includes first vehicle characteristic information of the target vehicle.
[0031] The first sensing data of the target vehicle may be obtained by performing sensing operations or sensing measurements on the target vehicle to obtain the first sensing data. For example, the first sensing data may be obtained by performing sensing operations or sensing measurements on the target vehicle through a radar sensor, a visual sensor or a communication interface.
[0032] The first vehicle characteristic information may be information used to characterize the characteristics of the target vehicle, such as shape, size, speed, position and other characteristic information.
[0033] The target vehicle may be a car, a truck, a bus, a motorcycle, etc., and the target vehicle may be a non-networked vehicle. In some embodiments, the target vehicle may also be a networked vehicle.
[0034] In the present disclosure, a non-connected vehicle refers to a vehicle that cannot be connected to the Internet, that is, a non-connected vehicle cannot interact with other vehicles, roadside equipment, cloud and other devices through the network. A connected vehicle refers to a vehicle that can be connected to the Internet, that is, a connected vehicle can interact with other vehicles, roadside equipment, cloud and other devices through the network.
[0035] Step S102: Based on the first vehicle characteristic information, obtain target vehicle identification information of the target vehicle, where the target vehicle identification information is used to identify the target vehicle in a network.
[0036] 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 from a plurality of candidate vehicle identification information based on the first vehicle characteristic information.
[0037] The target vehicle identification information is used to identify the target vehicle in the network and can be unique in identifying the vehicle in the network, that is, the target vehicle identification information has a one-to-one correspondence with the target vehicle in the network.
[0038] In the present disclosure, the above-mentioned network may be a vehicle-road cooperative network, which may support network interaction between vehicles, roadside equipment, the cloud and user terminals.
[0039] In some embodiments, the above-mentioned network is a regional network, such as the above-mentioned network is a network of the local area where the above-mentioned 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 above-mentioned target vehicle identification information can be the local vehicle identification information of the local area.
[0040] In some embodiments, the vehicle identification information in the present disclosure may be a vehicle number or an identity identification.
[0041] Step S103: output a first message, wherein the first message includes the target vehicle identification information.
[0042] The output of the first message may be to send the first message to the surrounding environment, so that vehicles, roadside equipment, user terminals and other equipment in the environment can receive the first message to determine the target vehicle identification information of the target vehicle. Alternatively, the output of the first message may be to display the first message on a display device, that is, to display the target vehicle identification information, such as displaying the target vehicle identification information on a large screen for traffic management, so as to facilitate traffic personnel to better manage traffic.
[0043] In the present disclosure, based on the above steps, it is possible to identify a vehicle in a network through vehicle identification information to improve the ability to identify a vehicle.
[0044] In addition, the above-mentioned vehicle identification information can be used to uniquely indicate the vehicle in the vehicle-road cooperative network to facilitate the development of vehicle-road cooperative services and avoid repeated perception of the same vehicle, resulting in false alarms and false statistics.
[0045] It should be noted that the above method can be applied to electronic devices, that is, all steps of the above method are performed by the electronic device, and the electronic device can be a vehicle, roadside equipment or other electronic device, such as an autonomous driving vehicle.
[0046] In one embodiment, Figure 1 Step S102 in the illustrated embodiment includes:
[0047] Based on the first vehicle characteristic information, generating first candidate vehicle identification information of the target vehicle, the first candidate vehicle identification information being associated with a first time;
[0048] matching the first vehicle characteristic information with the second vehicle characteristic information upon receiving a second message, the second message being used to indicate the second candidate vehicle identification information, the second vehicle characteristic information, and a second time;
[0049] In the case where the first vehicle characteristic information matches the second vehicle characteristic information, determining the target vehicle identification information from the first candidate vehicle identification information and the second candidate identification information;
[0050] Among them, when the first time is earlier than the second time, the target vehicle identification information is the first candidate vehicle identification information, and when the first time is later than the second time, the target vehicle identification information is the second candidate vehicle identification information.
[0051] 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 generating rule.
[0052] The first candidate vehicle identification information being associated with the first time may be that the first candidate vehicle identification information has a corresponding relationship with the first time, and the first time may be the first vehicle perception time of perceiving the target vehicle or the generation time of generating the first candidate vehicle identification information.
[0053] The second message may be a message sent by a connected vehicle or a roadside device, for example, the connected vehicle or the roadside device broadcasts the second message to its surroundings.
[0054] The matching of 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 features between the first vehicle characteristic information and the second vehicle characteristic information exceeds a preset threshold, etc.
[0055] 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, they can be executed simultaneously, or the first candidate vehicle identification information can be generated first and then the second message is received, or the second message can be received first and then the first candidate vehicle identification information is generated.
[0056] In this embodiment, the target vehicle identification information can be determined by using the candidate vehicle identification information with an earlier time, so that the target vehicle identification information finally determined can be guaranteed to be unique, thereby avoiding vehicle identification errors caused by multiple vehicle identification information of the same vehicle.
[0057] It should be noted that, in the present disclosure, if the vehicle characteristic 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.
[0058] In one embodiment, the first perception data includes a first vehicle perception time of perceiving the target vehicle, the first time is the first vehicle perception time, the second time is the second vehicle perception time, and the second vehicle perception time is the perception time when the device sending the second message perceives the vehicle corresponding to the second candidate vehicle identification information; or
[0059] 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.
[0060] The first vehicle sensing time for sensing the target vehicle may be the vehicle sensing time for the first sensing of the target vehicle, that is, the start time of sensing the target vehicle. The first vehicle sensing time for sensing the target vehicle may also include the start time and end time of sensing the target vehicle.
[0061] In this embodiment, the target vehicle identification information can be determined by the candidate vehicle identification information with an earlier vehicle perception time or generation time, so that the final determined target vehicle identification information can be guaranteed to be unique, thereby avoiding vehicle identification errors caused by multiple vehicle identification information of the same vehicle.
[0062] In one embodiment, the second message includes the second candidate vehicle identification information, the second candidate vehicle identification information is used to indicate the second vehicle feature information and the second time, and the first candidate vehicle identification information is used to indicate the first vehicle feature information and the first time; or,
[0063] The second message includes the second candidate vehicle identification information, the second vehicle characteristic information and the second time; when the target vehicle identification information is the first candidate vehicle identification information, 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 second candidate vehicle identification information, the first message includes the target vehicle identification information, the first vehicle characteristic information and the second time.
[0064] The first candidate vehicle identification information is used to indicate the first vehicle characteristic information and the first time, which can be understood as the first candidate vehicle identification information can be reflected in the first candidate vehicle identification information.
[0065] For example: Figure 2 For example, Figure 2 The 201 shown is used to indicate the type of the target vehicle, such as a non-connected vehicle. Figure 2 The 202 shown is used to indicate the color of the target vehicle, such as 00 represents white, Figure 3 The 203 shown is used to indicate the first time. It should be noted that Figure 2 The vehicle identification information shown is only an example and is not limited to this disclosure.
[0066] In this embodiment, indicating the vehicle characteristic information and time through the vehicle identification information can save message overhead.
[0067] In addition, in this embodiment, when the target vehicle identification information is the second candidate vehicle identification information, the first message includes the target vehicle identification information, the first vehicle characteristic information and the second time. In this way, the time included in the first message can be the earliest time corresponding to the target vehicle identification information, so as to avoid the device receiving the first message from making an incorrect judgment on the vehicle identification information.
[0068] In one embodiment, Figure 1 The step S102 shown also includes:
[0069] In the case where the second message is not received, determining the first vehicle characteristic information as the target vehicle characteristic information;
[0070] The target vehicle characteristic information is used to indicate the first vehicle characteristic information and the first time; or the first message includes the target vehicle identification information, the first vehicle characteristic information and the first time.
[0071] In this embodiment, without receiving the second message, the first vehicle characteristic information can be directly determined as the target vehicle characteristic information, and the first message can be sent, so that other vehicles, routing devices, and the cloud can obtain the target vehicle characteristic information in a timely manner to improve work efficiency.
[0072] In one embodiment, the first vehicle characteristic information in the present disclosure includes at least one of the following:
[0073] Vehicle static characteristic information and vehicle dynamic characteristic information;
[0074] The vehicle static feature information includes at least one of the following:
[0075] Color, model, license plate, and size;
[0076] The vehicle dynamic feature information includes at least one of the following:
[0077] Position, speed, direction and trajectory information, wherein the trajectory information is the driving trajectory of the target vehicle within the target time period.
[0078] Similarly, the second vehicle characteristic information in the present disclosure includes at least one of the following:
[0079] Vehicle static characteristic information and vehicle dynamic characteristic information;
[0080] The vehicle static feature information includes at least one of the following:
[0081] Color, model, license plate, and size;
[0082] The vehicle dynamic feature information includes at least one of the following:
[0083] Position, speed, orientation and trajectory information.
[0084] The driving trajectory of the target vehicle within the target time period may be a driving trajectory composed of positions at multiple moments, so that the driving trajectory can be used to more accurately determine whether the vehicle characteristic information in the first message and the second message is characteristic information of the same vehicle.
[0085] In this embodiment, the static feature information and dynamic feature information can be used to more accurately determine whether the vehicle feature information in the first message and the second message is feature information of the same vehicle, thereby improving the accuracy of the target vehicle identification information.
[0086] In one embodiment, the target vehicle is a non-networked vehicle. Figure 1 Step S101 in the illustrated embodiment includes:
[0087] In the case where a third message including vehicle identification information sent by the target vehicle is not received, the target vehicle is sensed to obtain the first sensed data of the target vehicle.
[0088] The above-mentioned failure to receive the third message including the vehicle identification information sent by the target vehicle can be understood as detecting that the above-mentioned target vehicle is a non-networked vehicle.
[0089] In this embodiment, the target vehicle can be sensed only when it is determined that the target vehicle is a non-networked vehicle. This can avoid sensing vehicles with vehicle identification information, thereby saving sensing overhead.
[0090] In one embodiment, the above method is performed by a first connected vehicle, and the method further includes:
[0091] Detect the number of connected vehicles in the target area;
[0092] When the number is less than a preset threshold, determining the distance between the first connected vehicle and a second connected vehicle, the second connected vehicle being the connected vehicle closest to the first connected vehicle in the target area;
[0093] Calculating a perception area of the first connected vehicle within the target area based on a position of the first connected vehicle and a distance between the first connected vehicle and a second connected vehicle;
[0094] Among them, the target vehicle is a non-networked vehicle within the perception area.
[0095] The target area is the local location area where the target vehicle is located, or the local location area where the first networked vehicle is located.
[0096] The number of connected vehicles in the above-mentioned detection target area can be, in the above-mentioned target area, sending a connected vehicle discovery request message, when the connected vehicle receives the discovery request message, it will return a confirmation message to the first connected vehicle, so as to determine which vehicles are connected vehicles, and finally determine the number of connected vehicles in the target area. Alternatively, the number of connected vehicles in the target area is determined by the vehicle identification information of the connected vehicles in the network, because, in some embodiments, the vehicle identification information can indicate the type of vehicle, that is, the vehicle identification information can be used to determine which vehicles are connected vehicles. It should be noted that, in some embodiments, the vehicle identification information of the connected vehicle can be assigned by the network, or it can be generated by vehicle feature information, and there is no limitation on this.
[0097] The above preset threshold can be a threshold pre-set according to actual business needs, such as 3, 4 or 5.
[0098] The above-mentioned determination of the distance between the first connected vehicle and the second connected vehicle may be by performing a sensing operation on the second connected vehicle to obtain the distance between the first connected vehicle and the second connected vehicle, or the first connected vehicle and the second connected vehicle may exchange their respective position information to calculate the distance between the first connected vehicle and the second connected vehicle.
[0099] The above calculation of the perception area of the first connected vehicle within the target area may be that the position area between the first connected vehicle and the second connected vehicle is divided into two perception areas, which are respectively used as the perception areas of the first connected vehicle and the second connected vehicle. The two perception areas are at least partially non-overlapping, and partial overlap may be allowed in some embodiments.
[0100] The above-mentioned target vehicle is a non-networked vehicle within the perception area, which can be understood as the first networked vehicle only senses the vehicles within the perception area, which can save perception overhead.
[0101] The following example takes the target vehicle as a non-connected vehicle. Figure 3 As shown, the following steps are included:
[0102] Step S301: vehicle data within a sensing range of a roadside device or a first vehicle;
[0103] Step S302: The roadside device or the vehicle records the vehicle perception data of the non-networked vehicle, where the vehicle perception data includes: initial perception time T1, dynamic vehicle characteristic information, and static vehicle characteristic information;
[0104] Step S303: The roadside device or the first vehicle locally defines a non-networked vehicle number (such as FWL00T1) according to the vehicle sensing data of the non-networked vehicle, that is, defines vehicle identification information;
[0105] Step S304, the roadside device or the first vehicle sends the non-networked vehicle number, the initial sensing time T1, the dynamic vehicle characteristic information and the static vehicle characteristic information to the surroundings; it should be noted that the accompanying drawings illustrate an example of executing S304 multiple times;
[0106] Step S305, vehicle data within the sensing range of the second vehicle;
[0107] Step S306: The second vehicle records the vehicle perception data of the non-networked vehicle, where the vehicle perception data includes: initial perception time T2, dynamic vehicle characteristic information, and static vehicle characteristic information;
[0108] Step S307: The second vehicle locally defines a non-networked vehicle number (such as FWL00T2) according to the vehicle sensing data of the non-networked vehicle, that is, defines vehicle identification information;
[0109] Step S308: The second vehicle matches the characteristic information of the non-networked vehicle with the perceived characteristic information of the vehicle;
[0110] Step S309: The second vehicle successfully matches the non-networked vehicle, and compares the initial sensing time to determine the non-networked vehicle number (FWL00T1 or FWL00T2);
[0111] Step S310: The second vehicle sends the non-networked vehicle number, initial perception time, dynamic vehicle feature information, and static vehicle feature information to the surrounding areas.
[0112] in, Figure 3 It is an example of interaction between multiple devices. Figure 3The steps performed by the second vehicle shown can also be performed by the roadside device. For example: in one embodiment, when a vehicle or roadside sensing device detects a non-networked vehicle, it assigns a number to the non-networked vehicle that is different from the networked vehicle, such as FWL00T1 (non-networked number 1), and continuously records the dynamic vehicle feature information such as the initial perception time, position, speed, size and orientation of the non-networked vehicle from the time the non-networked vehicle is first identified, as well as the static vehicle feature information such as vehicle color and vehicle license plate, and forms the historical trajectory of the non-networked vehicle, and sends the number, dynamic vehicle features, static vehicle features, and historical trajectory of the non-networked vehicle to the surrounding environment. After receiving the non-networked vehicle or roadside device, it matches and compares the vehicle data perceived by itself. If the dynamic vehicle features, static vehicle features, and historical trajectory match successfully, it is judged according to the first perception time. If the received perception data time is earlier than the vehicle's own perception time, the vehicle updates the number corresponding to the non-networked vehicle, such as FWL001 (non-networked number 1), thereby determining the number of the non-networked vehicle.
[0113] The following example uses a non-connected vehicle as the target vehicle. Figure 4 As shown, the following steps are included:
[0114] Step S401: Acquire environmental perception data through roadside equipment, where the environmental perception data includes vehicle feature information, vehicle number, and initial perception time;
[0115] Step S402: Acquire environmental perception data through the vehicle's own sensor, where the environmental perception data includes vehicle feature information, vehicle number, and initial perception time;
[0116] Step S403, comparing the environmental perception data obtained through the roadside equipment and the environmental perception data obtained through the vehicle's own sensors;
[0117] Step S404: determining that the match is successful, that is, the environmental perception data obtained through the roadside device and the environmental perception data obtained through the vehicle's own sensor represent the same vehicle;
[0118] Step S405, determining the time sequence of initial perception;
[0119] Step S406: Select the vehicle number with the earliest initial sensing time.
[0120] For example: the vehicle compares its own perceived vehicle data with the non-connected vehicle data sent by other vehicles or the roadside, and matches the dynamic and / or static vehicle feature information of the non-connected vehicle. After a successful match, the vehicle's own initial perception time T2 is compared with the initial perception time T1 of other vehicles or the roadside, and the non-connected vehicle number corresponding to the earlier initial perception time is selected. If T2 is later than T1, the corresponding number of the non-connected vehicle is FWL00T1. When the vehicle itself sends perception data to the surrounding environment, the number of the same non-connected vehicle is updated from FWL00T2 to FWL00T1.
[0121] In the present disclosure, since the target vehicle identification information of the target vehicle is obtained based on the first vehicle characteristic information, the target vehicle identification information is used to identify the target vehicle in the network, and a first message including the target vehicle identification information is output, it is possible to identify the vehicle in the network through the vehicle identification information to improve the ability to identify the vehicle.
[0122] See also Figure 5a , Figure 5a The present disclosure provides a vehicle identification information processing device, such as Figure 5a As shown, the vehicle identification information processing device 500 includes:
[0123] A first acquisition module 501 is used to acquire first perception data of a target vehicle, where the first perception data includes first vehicle characteristic information of the target vehicle;
[0124] A second acquisition module 502 is used to acquire target vehicle identification information of the target vehicle based on the first vehicle characteristic information, wherein the target vehicle identification information is used to identify the target vehicle in the network;
[0125] The output module 503 is used to output a first message, where the first message includes the target vehicle identification information.
[0126] Optionally, the second acquisition module 502 is used to:
[0127] Based on the first vehicle characteristic information, generating first candidate vehicle identification information of the target vehicle, the first candidate vehicle identification information being associated with a first time;
[0128] matching the first vehicle characteristic information with the second vehicle characteristic information upon receiving a second message, the second message being used to indicate the second candidate vehicle identification information, the second vehicle characteristic information, and a second time;
[0129] In the case where the first vehicle characteristic information matches the second vehicle characteristic information, determining the target vehicle identification information from the first candidate vehicle identification information and the second candidate identification information;
[0130] Among them, when the first time is earlier than the second time, the target vehicle identification information is the first candidate vehicle identification information, and when the first time is later than the second time, the target vehicle identification information is the second candidate vehicle identification information.
[0131] Optionally, the first perception data includes a first vehicle perception time of 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 the perception time when the device sending the second message perceives the vehicle corresponding to the second candidate vehicle identification information; or
[0132] 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.
[0133] Optionally, the second message includes the second candidate vehicle identification information, the second candidate vehicle identification information is used to indicate the second vehicle feature information and the second time, and the first candidate vehicle identification information is used to indicate the first vehicle feature information and the first time; or,
[0134] The second message includes the second candidate vehicle identification information, the second vehicle characteristic information and the second time; when the target vehicle identification information is the first candidate vehicle identification information, 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 second candidate vehicle identification information, the first message includes the target vehicle identification information, the first vehicle characteristic information and the second time.
[0135] Optionally, the second acquisition module 502 is further used for:
[0136] In the case where the second message is not received, determining the first vehicle characteristic information as the target vehicle characteristic information;
[0137] The target vehicle characteristic information is used to indicate the first vehicle characteristic information and the first time; or the first message includes the target vehicle identification information, the first vehicle characteristic information and the first time.
[0138] Optionally, the first vehicle characteristic information includes at least one of the following:
[0139] Vehicle static characteristic information and vehicle dynamic characteristic information;
[0140] The vehicle static feature information includes at least one of the following:
[0141] Color, model, license plate, and size;
[0142] The vehicle dynamic feature information includes at least one of the following:
[0143] Position, speed, direction and trajectory information, wherein the trajectory information is the driving trajectory of the target vehicle within the target time period.
[0144] Optionally, the target vehicle is a non-networked vehicle, and the first acquisition module 501 is used to:
[0145] In the case where a third message including vehicle identification information sent by the target vehicle is not received, the target vehicle is sensed to obtain the first sensed data of the target vehicle.
[0146] Optionally, the device is a device in the first connected vehicle, such as Figure 5b As shown, the device also includes:
[0147] A detection module 504, used to detect the number of connected vehicles in the target area;
[0148] A determination module 505, configured to determine the distance between the first connected vehicle and a second connected vehicle when the number is less than a preset threshold, the second connected vehicle being the connected vehicle closest to the first connected vehicle in the target area;
[0149] A calculation module 506, configured to calculate a perception area of the first connected vehicle within the target area based on a position of the first connected vehicle and a distance between the first connected vehicle and a second connected vehicle;
[0150] Among them, the target vehicle is a non-networked vehicle within the perception area.
[0151] The vehicle identification information processing device provided in the present disclosure can implement each process implemented by the vehicle identification information processing method provided in the present disclosure and achieve the same technical effect. To avoid repetition, it will not be described here.
[0152] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, a computer program product and an autonomous driving vehicle.
[0153] Among them, the above-mentioned electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein 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 so that the at least one processor can execute the vehicle identification information processing method provided by the present disclosure.
[0154] The above-mentioned readable storage medium stores computer instructions, wherein the computer instructions are used to enable the computer to execute the vehicle identification information processing method provided by the present disclosure.
[0155] The above-mentioned computer program product includes a computer program, and when the computer program is executed by a processor, the vehicle identification information processing method provided by the present disclosure is implemented.
[0156] The above-mentioned autonomous driving vehicle includes the electronic device provided by the present disclosure.
[0157] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.
[0158] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can 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 merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.
[0159] like Figure 6 As shown, the device 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 computing 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 the bus 604.
[0160] 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, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0161] The computing unit 601 may be a variety of general and / or special processing components with 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as a vehicle identification information processing method. For example, in some embodiments, the vehicle identification information processing method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into 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 appropriate manner (e.g., by means of firmware).
[0162] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0163] The program code for implementing the method 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, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0164] In the context of the present disclosure, a machine-readable 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 equipment. A 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, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0165] To provide interaction with a user, the systems and techniques described herein 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 the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the 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 can be received in any form (including acoustic input, voice input, or tactile input).
[0166] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.
[0167] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.
[0168] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.
[0169] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.
Claims
1. A vehicle identification information processing method, comprising: Acquire first perception data of a target vehicle, wherein the first perception data includes first vehicle characteristic information of the target vehicle; Based on the first vehicle characteristic information, acquiring target vehicle identification information of the target vehicle, wherein the target vehicle identification information is used to identify the target vehicle in a network; Outputting a first message, wherein the first message includes the target vehicle identification information; The acquiring the vehicle identification information of the target vehicle based on the first vehicle characteristic information includes: Based on the first vehicle characteristic information, generating first candidate vehicle identification information of the target vehicle, wherein the first candidate vehicle identification information is associated with a first time; matching the first vehicle characteristic information with the second vehicle characteristic information upon receiving a second message, the second message being used to indicate the second candidate vehicle identification information, the second vehicle characteristic information, and a second time; In a case where the first vehicle characteristic information matches the second vehicle characteristic information, determining the target vehicle identification information from the first candidate vehicle identification information and the second candidate vehicle identification information; Among them, when the first time is earlier than the second time, the target vehicle identification information is the first candidate vehicle identification information, and when the first time is later than the second time, the target vehicle identification information is the second candidate vehicle identification information.
2. The method according to claim 1, wherein: The first perception data includes a first vehicle perception time of perceiving the target vehicle, the first time is the first vehicle perception time, the second time is the second vehicle perception time, and the second vehicle perception time is the perception time when the device sending the second message perceives the vehicle corresponding to the second candidate vehicle identification information; 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.
3. The method according to claim 1, wherein: The second message includes the second candidate vehicle identification information, the second candidate vehicle identification information is used to indicate the second vehicle feature information and the second time, and the first candidate vehicle identification information is used to indicate the first vehicle feature information and the first time; or, The second message includes the second candidate vehicle identification information, the second vehicle characteristic information and the second time; when the target vehicle identification information is the first candidate vehicle identification information, 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 second candidate vehicle identification information, the first message includes the target vehicle identification information, the first vehicle characteristic information and the second time.
4. The method according to claim 1, wherein: The acquiring the vehicle identification information of the target vehicle based on the first vehicle characteristic information further includes: In the case where the second message is not received, determining the first vehicle characteristic information as the target vehicle characteristic information; The target vehicle characteristic information is used to indicate the first vehicle characteristic information and the first time; or the first message includes the target vehicle identification information, the first vehicle characteristic information and the first time.
5. The method according to any one of claims 1 to 4, wherein: The first vehicle characteristic information includes at least one of the following: Vehicle static characteristic information and vehicle dynamic characteristic information; The vehicle static feature information includes at least one of the following: Color, model, license plate, and size; The vehicle dynamic feature information includes at least one of the following: Position, speed, direction and trajectory information, wherein the trajectory information is the driving trajectory of the target vehicle within the target time period.
6. The method according to any one of claims 1 to 4, wherein: The target vehicle is a non-networked vehicle, and obtaining the first perception data of the target vehicle includes: In the case where a third message including vehicle identification information sent by the target vehicle is not received, the target vehicle is sensed to obtain the first sensed data of the target vehicle.
7. The method according to claim 6, wherein: The method is performed by a first connected vehicle, and the method further includes: Detect the number of connected vehicles in the target area; When the number is less than a preset threshold, determining a distance between the first connected vehicle and a second connected vehicle, the second connected vehicle being the connected vehicle closest to the first connected vehicle in the target area; Calculating a perception area of the first connected vehicle within the target area based on a position of the first connected vehicle and a distance between the first connected vehicle and a second connected vehicle; Among them, the target vehicle is a non-networked vehicle in the perception area.
8. A vehicle identification information processing device, comprising: A first acquisition module, used to acquire first perception data of a target vehicle, wherein the first perception data includes first vehicle characteristic information of the target vehicle; A second acquisition module, used for 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 the network; An output module, configured to output a first message, wherein the first message includes the target vehicle identification information; The second acquisition module is used for: Based on the first vehicle characteristic information, generating first candidate vehicle identification information of the target vehicle, wherein the first candidate vehicle identification information is associated with a first time; matching the first vehicle characteristic information with the second vehicle characteristic information upon receiving a second message, the second message being used to indicate the second candidate vehicle identification information, the second vehicle characteristic information, and a second time; In a case where the first vehicle characteristic information matches the second vehicle characteristic information, determining the target vehicle identification information from the first candidate vehicle identification information and the second candidate vehicle identification information; Among them, when the first time is earlier than the second time, the target vehicle identification information is the first candidate vehicle identification information, and when the first time is later than the second time, the target vehicle identification information is the second candidate vehicle identification information.
9. The device according to claim 8, wherein: The first perception data includes a first vehicle perception time of perceiving the target vehicle, the first time is the first vehicle perception time, the second time is the second vehicle perception time, and the second vehicle perception time is the perception time when the device sending the second message perceives the vehicle corresponding to the second candidate vehicle identification information; 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.
10. The device according to claim 8, wherein: The second message includes the second candidate vehicle identification information, the second candidate vehicle identification information is used to indicate the second vehicle feature information and the second time, and the first candidate vehicle identification information is used to indicate the first vehicle feature information and the first time; or, The second message includes the second candidate vehicle identification information, the second vehicle characteristic information and the second time; when the target vehicle identification information is the first candidate vehicle identification information, 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 second candidate vehicle identification information, the first message includes the target vehicle identification information, the first vehicle characteristic information and the second time.
11. The device according to claim 8, wherein: The second acquisition module is also used for: In the case where the second message is not received, determining the first vehicle characteristic information as the target vehicle characteristic information; The target vehicle characteristic information is used to indicate the first vehicle characteristic information and the first time; or the first message includes the target vehicle identification information, the first vehicle characteristic information and the first time.
12. The device according to any one of claims 8 to 11, wherein: The first vehicle characteristic information includes at least one of the following: Vehicle static characteristic information and vehicle dynamic characteristic information; The vehicle static feature information includes at least one of the following: Color, model, license plate, and size; The vehicle dynamic feature information includes at least one of the following: Position, speed, direction and trajectory information, wherein the trajectory information is the driving trajectory of the target vehicle within the target time period.
13. The device according to any one of claims 8 to 11, wherein: The target vehicle is a non-networked vehicle, and the first acquisition module is used to: In the case where a third message including vehicle identification information sent by the target vehicle is not received, the target vehicle is sensed to obtain the first sensed data of the target vehicle.
14. The device according to claim 13, wherein: The device is a device in a first connected vehicle, and the device further comprises: A detection module, used to detect the number of connected vehicles in a target area; A determination module, configured to determine, when the number is less than a preset threshold, a distance between the first connected vehicle and a second connected vehicle, the second connected vehicle being the connected vehicle closest to the first connected vehicle in the target area; a calculation module, configured to calculate a perception area of the first connected vehicle within the target area based on a position of the first connected vehicle and a distance between the first connected vehicle and a second connected vehicle; Among them, the target vehicle is a non-networked vehicle in the perception area.
15. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, 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 enable the at least one processor to perform the method according to any one of claims 1 to 7.
16. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.
17. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 7.
18. An autonomous driving vehicle comprising the electronic device as claimed in claim 15.