Vehicle collected data feature and inter-vehicle data sharing method and device, computer equipment and medium
By realizing data sharing among vehicles, acquiring and weighting the characteristic data collected by each vehicle, the problem that the prior art cannot realize data sharing among vehicles is solved, driving safety is improved, and the risk of accidents is reduced.
Patent Information
- Application Number
- CN202411934201.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-26
- Publication Date
- 2025-04-25
AI Technical Summary
Existing roof lidar and end-to-end intelligent driving methods cannot realize data sharing between vehicles, resulting in the inability to effectively share vehicle identification information on complex road sections or highways, increasing the risk of accidents.
By obtaining the feature data collected by each vehicle, assigning feature attributes to it and giving weighted values, weighted fusion is used to obtain feature values, and reporting and summarizing it among different vehicles to realize data sharing between vehicles.
Through data sharing among vehicles, the risk of accidents can be reduced, especially on complex roads or highways, improving driving safety.
Smart Images
Figure CN119884710A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of data sharing, and more specifically, to a method, device, computer equipment and medium for sharing data features collected by vehicles and data between vehicles. Background Art
[0002] Existing roof-mounted laser radars are limited by their own height and the height of the vehicle in front, and can only see situations at a limited distance. The end-to-end intelligent driving method can only be used by the vehicle itself, and data sharing between vehicles cannot be achieved.
[0003] For example, on highways, the number of lanes temporarily diverted by cones that often appear decreases, and vehicles are traveling at higher speeds. Sometimes the vehicle in front will create a blind spot for the vehicle behind. At this time, if the vehicle passing in front or in the opposite direction or side uploads this information, the vehicle passing behind will be able to know the road conditions in advance.
[0004] For complex or important road sections, information identified from different directions and different vehicles can be shared synchronously to reduce the occurrence of accidents. Summary of the invention
[0005] The embodiments of the present application provide a method, apparatus, computer equipment and medium for sharing data features collected by vehicles and data features between vehicles, so as to share data features collected by vehicles and data features between vehicles to reduce the occurrence of accidents.
[0006] In a first aspect, the present application provides a method for sharing data features collected by a vehicle and between vehicles, including:
[0007] Acquire characteristic data collected from each vehicle, assign a number of characteristic attributes to each characteristic data, and assign a weighted value to each characteristic attribute corresponding to each characteristic data;
[0008] The characteristic attributes corresponding to each characteristic data are weightedly fused according to the weighted value to obtain the characteristic value of each characteristic data;
[0009] The characteristic values corresponding to the characteristic data collected by different vehicles are reported, and the total characteristic values corresponding to the characteristic data returned after aggregation are received.
[0010] In some instances, the feature attributes include feature codes, level attributes, and time attributes, wherein each feature data corresponds to a unique feature code, the level attributes are graded according to the severity of the impact and consequences on vehicle driving, and the time attribute represents the rate at which the validity of the feature data changes over time. The feature attributes can be increased or decreased according to actual conditions.
[0011] In some examples, a higher level of the level attribute indicates that the corresponding feature data is more important and the assigned weight value is greater.
[0012] In some examples, the time attribute has a step attribute, where the higher the rate of change in the validity of the feature data over time, the lower the corresponding time attribute level and the smaller the assigned weight value.
[0013] In some examples, the method further comprises:
[0014] When the distance between different vehicles is greater than a preset distance value, the characteristic value corresponding to the collected characteristic data is reported directly or through a repeater.
[0015] In some examples, the method further comprises:
[0016] When the distance between different vehicles is not greater than a preset distance value, the characteristic value corresponding to the collected characteristic data is reported, or the vehicles transmit the characteristic value to each other through a wireless network.
[0017] In some examples, the method further comprises:
[0018] The uploaded feature values are updated in real time.
[0019] In a second aspect, the present application provides a data feature collected by a vehicle and a data sharing device between vehicles, including:
[0020] The data collection module is used to obtain the characteristic data collected by each vehicle, assign a number of characteristic attributes to each characteristic data, and assign a weighted value to each characteristic attribute corresponding to each characteristic data;
[0021] The feature value calculation module is used to perform weighted fusion on the feature attributes corresponding to each feature data according to the weighted value to obtain the feature value of each feature data;
[0022] The interactive module is used to report the characteristic values corresponding to the characteristic data collected by different vehicles, and receive the total characteristic values corresponding to the characteristic data returned after aggregation.
[0023] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above methods when executing the computer program.
[0024] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of any of the above methods when executed by a processor.
[0025] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:
[0026] This application obtains the characteristic data collected by each vehicle, assigns several characteristic attributes to each characteristic data, assigns weighted values to each characteristic attribute corresponding to each characteristic data; weightedly fuses the characteristic attributes corresponding to each characteristic data according to the weighted values to obtain the characteristic values of each characteristic data; reports the characteristic values corresponding to the characteristic data collected by different vehicles, and receives the total characteristic values corresponding to each characteristic data returned after aggregation. Through this application, the data features collected by vehicles and the data features between vehicles can be shared to reduce accidents. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.
[0028] Figure 1 It is a schematic diagram of the data characteristics collected by vehicles and the method for sharing data between vehicles provided in an embodiment of the present application;
[0029] Figure 2 It is a schematic diagram of the data provided in the embodiment of the present application being transmitted to the requesting vehicle through a data center or a repeater;
[0030] Figure 3 It is a schematic diagram that the data provided by the embodiment of the present application is not transmitted to the requesting vehicle through a data center or a repeater;
[0031] Figure 4 is a schematic diagram of a device provided in an embodiment of the present application;
[0032] Figure 5 It is a schematic diagram of the structure of an embodiment of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0033] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.
[0034] In the following description, the specific embodiments of the present application will be described with reference to the steps and symbols performed by one or more computers, unless otherwise specified. Therefore, these steps and operations will be mentioned several times as being performed by a computer, and the computer execution referred to herein includes the operation of a computer processing unit by an electronic signal representing data in a structured form. This operation converts the data or maintains it at a location in the memory system of the computer, which can be reconfigured or otherwise change the operation of the computer in a manner familiar to testers in the field. The data structure maintained by the data is a physical location in the memory, which has specific characteristics defined by the data format. However, the principles of the present application are described in the above text, which does not represent a limitation, and testers in the field will understand that the following various steps and operations can also be implemented in hardware.
[0035] The term "module" or "unit" used in this article can be regarded as a software object executed on the computing system. The different components, modules, engines and services in this article can be regarded as implementation objects on the computing system. The apparatus and method in this article are preferably implemented in software, but can also be implemented in hardware, all within the scope of protection of this application.
[0036] Those skilled in the art will appreciate that, unless expressly stated otherwise, the singular forms "a", "an", "" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other elements, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" as used herein includes all or any unit and all combinations of one or more associated listed items.
[0037] In the first embodiment of the present application, a vehicle-collected data feature and a method for sharing data between vehicles are provided, such as Figure 1 As shown, the following steps are included:
[0038] S101: Acquire characteristic data collected from each vehicle, assign a number of characteristic attributes to each characteristic data, and assign a weighted value to each characteristic attribute corresponding to each characteristic data;
[0039] S102: performing weighted fusion on the feature attributes corresponding to each feature data according to the weighted value to obtain the feature value of each feature data;
[0040] S103: reporting the characteristic values corresponding to the characteristic data collected by different vehicles, and receiving the total characteristic value corresponding to each characteristic data returned after aggregation.
[0041] In some instances, feature attributes include feature codes, level attributes, and time attributes, wherein each feature data corresponds to a unique feature code, the level attributes are graded according to the severity of the impact and consequences on vehicle driving, and the time attributes represent the rate at which the validity of the feature data changes over time. The feature attributes can be increased or decreased according to actual conditions.
[0042] In some examples, a higher level of a level attribute indicates that the corresponding feature data is more important and is assigned a larger weight value.
[0043] In some instances, the time attribute has a step attribute, where the higher the rate at which the validity of the feature data changes over time, the lower the corresponding time attribute level and the smaller the assigned weight value.
[0044] Specifically, the vehicle collects events, and the events have characteristic attributes. Each collected event (such as a pothole on the road, a pedestrian crossing the road at an intersection) is called characteristic data. The characteristic data has attributes such as characteristic coding, level attributes, and time attributes. Other different attributes can be added later according to actual operation. Each attribute has a different dynamic weighted value, and the final value of a certain feature is obtained by comprehensive calculation of each attribute and weighted value.
[0045] The feature code is the unique code collected for a certain event.
[0046] The level attribute is divided into multiple levels according to the impact on vehicle driving and the severity of the consequences. The higher the level, the more important the feature data is, such as a pedestrian colliding with a vehicle. The lower the level, the less important the feature data is, such as a plastic bag on the road.
[0047] Time attributes are divided into multiple levels according to their effectiveness, indicating the rate at which their effectiveness changes over time. For the time attribute of feature data, the newer the data, the larger its weight value, which means the data is more reliable. As time goes by, the effectiveness of feature data will gradually decrease to achieve the credibility of road conditions. In theory, the effectiveness of the time attribute representation of all feature data will gradually decrease over time, but the rate of decrease varies according to actual conditions. Some feature data has long-term storage (ladder attributes), such as undulating road surfaces; some data has medium-term storage, such as roadside parking; and some data has short-term storage, such as encountered moving vehicles, non-motor vehicles, temporary traffic accidents, etc. For some very short-term feature data, such as motor and non-motor vehicles traveling in opposite directions, their effectiveness will gradually decrease to a very low level or become invalid over time.
[0048] The embodiment of the present application only takes a three-step time attribute example, and multiple step attributes of different time lengths can be added during operation.
[0049] After a vehicle passes a certain section of road, various feature data are collected and uploaded, including but not limited to parked vehicles on the roadside, road obstacles, encountered moving vehicles, and sudden accidents. Different feature data can be added / enriched during operation, such as same-direction and / or opposite-direction data.
[0050] The feature data collected by different vehicles are input into the large model of the data center for calculation. The data center will comprehensively calculate the data collected by different vehicles and push them to nearby vehicles.
[0051] In some instances, each vehicle uploads data to a data center via a wireless network; the amount of data collected by a single vehicle is very large, and uploading all the data may result in excessive transmission bandwidth and computing power. A single vehicle can extract the main feature values of data useful for controlling other vehicles (such as the position and size of ground undulations, the speed of vehicles in the same direction and oncoming directions, and the position of lanes) and upload them. Other data can be used only by the vehicle itself to reduce the problem of large workloads in data uploading and background system processing.
[0052] In the embodiments of the present application, emphasis is placed on information transmission between vehicles, and no excessive description is given to decision-making and specific vehicle control.
[0053] In some cases, when the distance between vehicles is relatively long, data can be uploaded to the data center directly or through a repeater. A repeater is a device that covers a certain range and plays a connecting role. For roads with fewer vehicles or where data collection is required, repeaters can be set up around them. After receiving the data, the repeater transmits the data to the data center via wireless and / or wired networks. The processed data can be transmitted to the required vehicles through the data center or repeaters, such as Figure 2 shown.
[0054] In some cases, when vehicles are close to each other, they can directly transmit information to each other through the wireless network while uploading to the data center, and the data can be relayed between vehicles. The same feature data can be collected and transmitted by multiple vehicles, and the same vehicle can also receive the same feature data sent by multiple vehicles. In this case, the data transmitted can be more than the data uploaded to the data center without going through the data center. Figure 3 The transmission method is not described here.
[0055] In the embodiment of the present application, the signal sending and receiving range can be dynamically adjusted according to the specific scenario.
[0056] In the embodiments of the present application, the feature data collection methods include but are not limited to the following methods: cameras, speed and / or acceleration sensors, temperature and humidity sensors, GPS, lidar, etc., and can be expanded according to the operating conditions.
[0057] In an embodiment of the present application, after the vehicle receives the characteristic data, it can display it through a large in-vehicle screen, a mobile phone, etc.
[0058] In an embodiment of the present application, for certain things, such as canvas, cardboard boxes, small potholes and other obstacles on the road that are not easy to identify accurately at one time, a single vehicle may only recognize the existence of an obstacle and upload its own recognized features to the data center. Vehicles passing behind will continue to identify on this basis to continuously improve the recognition accuracy.
[0059] In an embodiment of the present application, for things that existed in the early stage and were processed later, such as temporary roadblocks and shared bicycles, the vehicles passing by uploaded the characteristics of the things to the data center. If a certain number of vehicles pass by later and do not find the characteristics of the things, the characteristics of the things are removed in the data center, forming a closed loop for the processing of the things.
[0060] In the embodiment of the present application, the more vehicles pass through the same road section, the more accurate the generated feature data is.
[0061] In the embodiments of the present application, not only the data generated during human driving is uploaded and used, but also the data generated by intelligent assistance or automatic driving is uploaded and used. For example, during the intelligent assistance or automatic driving process, a vehicle detects an obstacle or accident somewhere. After uploading the data, the surrounding vehicles (mainly the rear) that are about to pass can obtain the message in advance, and the data is also processed according to a weighted value.
[0062] In the second embodiment of the present application, in order to better implement the method provided in the embodiment of the present application, the embodiment of the present application also provides a device based on the above method. The meanings of the terms are the same as those in the above method, and the specific implementation details can refer to the description in the method embodiment.
[0063] See also Figure 4 , Figure 4 A schematic diagram of the structure of a device provided in an embodiment of the present application, wherein the device 400 may include: a data acquisition module 401, a feature value calculation module 402 and an interaction module 403, wherein:
[0064] The data collection module 401 is used to obtain characteristic data collected from each vehicle, assign a number of characteristic attributes to each characteristic data, and assign a weighted value to each characteristic attribute corresponding to each characteristic data;
[0065] The feature value calculation module 402 is used to perform weighted fusion on the feature attributes corresponding to each feature data according to the weighted value to obtain the feature value of each feature data;
[0066] The interaction module 403 is used to report the characteristic values corresponding to the characteristic data collected from different vehicles, and receive the total characteristic values corresponding to the characteristic data returned after aggregation.
[0067] In the third embodiment of the present application, a computer device is also provided, such as Figure 5 As shown, it shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:
[0068] The computer device may include one or more processing core processors 501, one or more computer-readable storage media memories 502, a power supply 503, an input unit 504 and other components. Those skilled in the art will appreciate that Figure 5 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:
[0069] The processor 501 is the control center of the computer device. It uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and / or modules stored in the memory 502 and calling data stored in the memory 502, it executes various functions of the computer device and processes data, thereby monitoring the computer device as a whole. Optionally, the processor 501 may include one or more processing cores; preferably, the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operation storage medium, user interface and application program, etc., and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 501.
[0070] The memory 502 can be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the software programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating storage medium, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 502 may also include a controller to provide the processor 501 with access to the memory 502.
[0071] The computer device also includes a power supply 503 for supplying power to various components. Preferably, the power supply 503 can be logically connected to the processor 501 through a power management storage medium, so as to manage charging, discharging, and power consumption management through the power management storage medium. The power supply 503 can also include any components such as one or more DC or AC power supplies, recharge storage media, power failure detection circuits, power converters or inverters, and power status indicators.
[0072] The computer device may further include an input unit 504, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.
[0073] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 501 in the computer device will load the executable files corresponding to the processes of one or more application programs into the memory 502 according to the following instructions, and the processor 501 will run the application programs stored in the memory 502, thereby implementing the steps in the above method embodiment.
[0074] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.
[0075] To this end, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. The computer program is loaded by a processor to execute the steps in any method provided in the embodiment of the present application.
[0076] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.
[0077] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.
[0078] Since the computer program stored in the computer-readable storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects that can be achieved by any method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.
[0079] The above is a detailed introduction to the data characteristics collected by a vehicle and the method, device, computer equipment and medium for sharing data between vehicles provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the ideas of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present application.
Claims
1. A data feature collected by a vehicle and a method for sharing data between vehicles, characterized in that: include: Acquire characteristic data collected from each vehicle, assign a number of characteristic attributes to each characteristic data, and assign a weighted value to each characteristic attribute corresponding to each characteristic data; The characteristic attributes corresponding to each characteristic data are weightedly fused according to the weighted value to obtain the characteristic value of each characteristic data; The characteristic values corresponding to the characteristic data collected by different vehicles are reported, and the total characteristic values corresponding to the characteristic data returned after aggregation are received.
2. The method according to claim 1, characterized in that The characteristic attributes include characteristic codes, level attributes and time attributes, wherein each characteristic data corresponds to a unique characteristic code, the level attributes are graded according to the severity of the impact and consequences on vehicle driving, and the time attribute represents the rate of change of the effectiveness of the characteristic data with time. The characteristic attributes can be increased or decreased according to actual conditions.
3. The method according to claim 2, characterized in that The higher the level of the level attribute is, the more important the corresponding feature data is, and the larger the weight value assigned to it is.
4. The method according to claim 3, characterized in that The time attribute has a step attribute. As time changes, the higher the rate at which the validity of the feature data changes, the lower the corresponding time attribute level is, and the smaller the weighted value assigned is.
5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: When the distance between different vehicles is greater than a preset distance value, the characteristic value corresponding to the collected characteristic data is reported directly or through a repeater.
6. The method according to claim 5, characterized in that The method further comprises: When the distance between different vehicles is not greater than a preset distance value, the characteristic value corresponding to the collected characteristic data is reported, or the vehicles transmit the characteristic value to each other through a wireless network.
7. The method according to claim 6, characterized in that The method further comprises: The uploaded feature values are updated in real time.
8. A data feature collected by a vehicle and a data sharing device between vehicles, characterized in that: include: The data collection module is used to obtain the characteristic data collected by each vehicle, assign a number of characteristic attributes to each characteristic data, and assign a weighted value to each characteristic attribute corresponding to each characteristic data; The feature value calculation module is used to perform weighted fusion on the feature attributes corresponding to each feature data according to the weighted value to obtain the feature value of each feature data; The interactive module is used to report the characteristic values corresponding to the characteristic data collected by different vehicles, and receive the total characteristic values corresponding to the characteristic data returned after aggregation.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method according to any one of claims 1 to 7.