Vehicle Information Transmission Method, Device, Equipment and Storage Medium

Abstract

A vehicle information transmission method, device, equipment and storage medium provided by an embodiment of the present application. The method includes obtaining the characteristic information of a driver; obtaining a lighting control instruction according to the characteristic information; generating lighting information according to the lighting control instruction, and sending the lighting information to an external vehicle; receiving the lighting information of the external vehicle; and analyzing the lighting information to obtain the driving information of the external vehicle. The present application specifically generates a lighting control instruction according to the driver's characteristic information, and then sends lighting information to an external vehicle according to the lighting control instruction, rather than simply manually controlling the lighting to flash and transmit information to an external vehicle, realizing the accurate transmission of driver information between vehicles during oncoming or driving.

Description

Technical Field

[0001] This application relates to the field of automotive technologies, and particularly to a vehicle information transmission method, apparatus, device, and storage medium. Background Art

[0002] During existing passing or driving, the information conveyed by the vehicle - to - vehicle light communication is fixed. For example, flashing the headlights three times indicates that there is a vehicle fault to the other vehicle. And the light communication is achieved by manually controlling the vehicle's lights to flash. There may be a situation where the transmitted light communication does not match the information the driver wants to transmit. Therefore, the existing vehicle - to - vehicle light communication during passing or driving cannot accurately convey the information the driver wants to transmit, which is not conducive to passing and driving for both parties.

[0003] The above content is only used to assist in understanding the technical solution of this application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of this application is to provide a vehicle information transmission method, apparatus, device, and storage medium, aiming to solve the technical problem that the existing vehicle - to - vehicle light communication during passing or driving cannot accurately convey the information the driver wants to transmit.

[0005] To achieve the above purpose, this application provides a vehicle information transmission method, which includes:

[0006] Obtain the driver's characteristic information;

[0007] According to the characteristic information, obtain a light control instruction;

[0008] Generate light information according to the light control instruction, and send the light information to an external vehicle;

[0009] Receive the light information of the external vehicle;

[0010] Analyze the light information to obtain the driving information of the external vehicle.

[0011] Optionally, the step of obtaining a light control instruction according to the characteristic information includes:

[0012] Match the characteristic information with the first characteristic information in the local database to obtain a first similarity;

[0013] If the first similarity is greater than or equal to a first threshold, obtain the characteristic text corresponding to the first characteristic information as the driving information;

[0014] Compile the driving information based on the communication protocol to obtain a light control instruction.

[0015] Optionally, after the step of obtaining the characteristic information of the driver, the method further includes:

[0016] Obtaining the voice information of the driver;

[0017] Obtaining a lighting control instruction according to the voice information and the characteristic information.

[0018] Optionally, the step of obtaining a lighting control instruction according to the voice information and the characteristic information includes:

[0019] Identifying the voice information to obtain a voice text;

[0020] Matching the characteristic information with the first characteristic information in the local database to obtain a first similarity;

[0021] If the first similarity is greater than or equal to a first threshold, obtaining the characteristic text corresponding to the first characteristic information;

[0022] Comparing the voice text with the characteristic text to obtain a second similarity;

[0023] If the second similarity is greater than or equal to a second threshold, using the characteristic text as driving information;

[0024] Compiling the driving information based on a communication protocol to obtain a lighting control instruction.

[0025] Optionally, after the step of comparing the voice text with the driving information to obtain a second similarity, the method further includes:

[0026] If the second similarity is less than the second threshold, confirming the voice text as driving information or the characteristic text as driving information according to a preset rule;

[0027] The preset rule includes:

[0028] Comparing the usage times of the voice text and the characteristic text in historical data;

[0029] If the usage times of the voice text in historical data are greater than the usage times of the characteristic text in historical data, using the voice text as driving information;

[0030] If the usage times of the voice text in historical data are less than the usage times of the characteristic text in historical data, using the characteristic text as driving information;

[0031] If the usage times of the voice text in historical data are equal to the usage times of the characteristic text in historical data, obtaining the signal-to-noise ratio of the voice information;

[0032] If the signal-to-noise ratio is less than a preset threshold, the voice text is used as driving information.

[0033] Optionally, after the step of matching the feature information with the first feature information in the local database to obtain the first similarity, the method further includes:

[0034] If the first similarity is less than the first threshold, the feature information is matched with the second feature information in the platform data to obtain the third similarity;

[0035] If the third similarity is greater than or equal to the third threshold, the feature text corresponding to the second feature information is obtained as driving information, and the feature text and the feature information are associated and stored in the local database.

[0036] Optionally, the step of analyzing the light information to obtain the driving information of the external vehicle includes:

[0037] Analyzing the light information based on the communication protocol to obtain the driving information of the external vehicle.

[0038] In addition, to achieve the above object, the present application further provides a vehicle information transmission device, which includes:

[0039] A feature information acquisition module, configured to acquire the feature information of the driver;

[0040] An instruction generation module, configured to obtain a light control instruction according to the feature information;

[0041] A light control module, configured to generate light information according to the light control instruction and send the light information to an external vehicle;

[0042] A light information acquisition module, configured to receive the light information of the external vehicle;

[0043] An analysis module, configured to analyze the light information to obtain the driving information of the external vehicle.

[0044] In addition, to achieve the above object, the present application further provides a vehicle information transmission device, including a processor, a memory, and a vehicle information transmission program stored on the memory and executable on the processor. When the vehicle information transmission program is executed by the processor, the steps of the vehicle information transmission method described above are implemented.

[0045] In addition, to achieve the above object, the present application further provides a storage medium, including a processor, a memory, and a vehicle information transmission program stored on the memory and executable on the processor. When the vehicle information transmission program is executed by the processor, the steps of the vehicle information transmission method described above are implemented.

[0046] A vehicle information transmission method, device, equipment, and storage medium proposed in an embodiment of the present application. Compared with the prior art, in which the information conveyed by the light communication between vehicles during oncoming or driving is fixed and cannot accurately convey the information that the driver wants to transmit, the present application obtains the driver's characteristic information, then obtains a light control instruction according to the characteristic information, and finally generates light information according to the light control instruction and sends the light information to external vehicles. That is to say, in the present application, the light control instruction is specifically generated according to the driver's characteristic information, and then the light information is sent to external vehicles according to the light control instruction, rather than simply manually controlling the light to flash to transmit information to external vehicles. At the same time, when the vehicle receives the light information of an external vehicle, it analyzes the light information to obtain the driving information of the external vehicle. Therefore, the accurate transmission of driver information between vehicles during oncoming or driving is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application.

[0048] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0049] Figure 1 It is a schematic flowchart of the first embodiment of the vehicle information transmission method of the present application;

[0050] Figure 2 For Figure 1 It is a detailed flowchart of step S20 in

[0051] Figure 3 It is a schematic flowchart of the second embodiment of the vehicle information transmission method of the present application;

[0052] Figure 4 For Figure 3 It is a detailed flowchart of step A20 in

[0053] Figure 5 It is a structural block diagram of the first embodiment of the vehicle information transmission device of the present application;

[0054] Figure 6 It is a schematic structural diagram of a terminal device in the hardware operating environment related to the solution of the embodiment of the present application.

[0055] The realization of the purpose of the present application, functional features and advantages will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific embodiments

[0056] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0057] The embodiment of the present application provides a vehicle information transmission method. In the first embodiment of the vehicle information transmission method of the present application, with reference to Figure 1 , the vehicle information transmission method includes:

[0058] Step S10: Obtain the characteristic information of the driver.

[0059] In this embodiment, it should be noted that the application scenario of this embodiment is any moving vehicle and / or any started vehicle. A moving vehicle refers to a vehicle with a driving speed greater than 0 Km / h, and a started vehicle refers to a vehicle with a driving speed of 0 Km / h but already ignited.

[0060] The characteristic information of the driver includes posture characteristic information and facial characteristic information. Further, the step of obtaining the characteristic information of the driver may include:

[0061] Step S101: Obtain the face image and limb movement image of the driver;

[0062] Step S102: Identify the face image to determine whether the driver is the predetermined driver of the vehicle;

[0063] Step S103: If the driver is the predetermined driver of the vehicle, obtain the corresponding facial characteristic information according to the face image and obtain the corresponding posture characteristic information according to the limb movement image.

[0064] In this embodiment, it should be noted that one or more cameras installed in the vehicle cab can be used to photograph the face and limbs (hands) of the driver to obtain images or video clips including the face information and limb information of the driver.

[0065] If what is captured by the camera is an image, the face and limbs of the driver can be captured at a set time interval, or the face and limbs of the driver can be captured after receiving a capture instruction issued by the driver. The captured image is adjusted such as cropped and rotated to obtain the driver's face image and limb movement image. The capture instruction of the driver can be a voice instruction or a key instruction, and the set time interval can be set according to the actual situation and is not limited in this embodiment.

[0066] If what is captured by the camera is a video clip, real-time recording can be performed after receiving a capture instruction issued by the driver, and the real-time recording ends after receiving an end instruction issued by the driver to obtain a video clip; the captured video clip is used to equally spacedly determine each frame extraction time point from the shooting time point according to a preset time interval; the video frames corresponding to each frame extraction time point are extracted from the video clip; each video frame is segmented to obtain a face video frame and a limb movement video frame; the duplicate face video frames and limb movement video frames are deleted, and the remaining face video frames and limb movement video frames are the driver's face image and limb movement image. The capture instruction and the end instruction of the driver can both be voice instructions or key instructions, and the preset time interval can be set according to the actual situation and is not limited in this embodiment.

[0067] It should be noted that in this embodiment, after obtaining the driver's face image and limb movement image, the face image is recognized to determine whether the driver is the vehicle's predetermined driver, which can effectively prevent non-vehicle-permitted personnel from driving the vehicle and ensure the safety of the vehicle during driving.

[0068] Specifically, obtaining corresponding facial feature information according to the face image includes: segmenting the face image to obtain a facial contour image, an eyebrow image, an eye image, a nose image, and a mouth image, and the facial feature information is composed of the above facial contour image, eyebrow image, eye image, nose image, and mouth image.

[0069] Specifically, obtaining corresponding posture feature information according to the limb movement image includes: segmenting the limb movement image to obtain a limb image that only contains the limb (hand).

[0070] In a specific implementation process, for the segmentation of face images and the segmentation of limb movement images, an image segmentation algorithm based on edge detection can be adopted, that is, the edges of the limbs are extracted through an edge detection operator; the pixels within the edges of the extracted limbs are connected and labeled to obtain the segmentation regions. The edge detection operators include Roberts operator, Sobel operator, Rrewitt operator, Kirsch operator, Laplacian operator, etc. Additionally, for the segmentation of face images and the segmentation of limb movement images, an image segmentation algorithm based on an active contour model, an image segmentation algorithm based on deep learning, etc. can also be adopted. The above image segmentation algorithms are prior arts and will not be elaborated here.

[0071] Step S20: Obtain a lighting control instruction according to the feature information.

[0072] Refer to Figure 2 , wherein the step of obtaining a lighting control instruction according to the feature information includes:

[0073] Step S201: Match the feature information with the first feature information in the local database to obtain a first similarity.

[0074] Step S202: If the first similarity value is greater than or equal to the first threshold, obtain the feature text corresponding to the first feature information as driving information.

[0075] Step S203: If the first similarity is less than the first threshold, match the feature information with the second feature information in the platform database to obtain a third similarity.

[0076] Step S204: If the third similarity is greater than or equal to the third threshold, obtain the feature text corresponding to the second feature information as driving information, and store the feature text and the feature information in the local database in an associated manner.

[0077] Step S205: Compile the driving information based on the communication protocol to obtain a lighting control instruction.

[0078] It should be noted that in this embodiment, the feature information includes facial feature information and gesture feature information. The facial feature information includes facial contour images, eyebrow images, eye images, nose images, and mouth images. The gesture feature information includes limb images. The local database includes multiple feature data files, and each feature data file corresponds to the feature information one by one. For example, the facial contour image corresponds to the facial contour feature data file, and the eyebrow image corresponds to the eyebrow feature data file. Each feature data file contains several preset feature information as the first feature information, and each preset feature information is associated with a feature text. For example, the facial contour feature data file contains several preset facial contour images, and each preset facial contour image is associated with a feature text, which can be "overtaking", "decelerating for oncoming vehicle meeting", etc. Each vehicle has its corresponding local database, that is, it is easy to understand that all the first feature information in the local database is the first feature information of the driver permitted by the vehicle. The structural composition and the data content included in the platform database are the same as those of the local database. The only difference is that all the second feature information in the platform database is the second feature information of all drivers (with a driver's license).

[0079] In the specific implementation process, the facial contour image is matched one by one with several preset facial contour images in the facial contour feature data file in the local database to obtain multiple similarities; the maximum value among them is selected as the first similarity of the facial contour image as a feature information; the first similarity of the facial contour image as a feature information is compared with its corresponding first threshold; if the first similarity is greater than or equal to the first threshold, the feature text associated with the preset facial contour image corresponding to the first similarity is obtained; if the first similarity is less than the first threshold, the facial contour image is matched one by one with several preset facial contour images as the second feature information in the platform database to obtain multiple similarities; the maximum value among them is selected as the third similarity of the facial contour image as a feature information. If the third similarity is greater than or equal to the third threshold, the feature text associated with the preset facial contour image corresponding to the third similarity is obtained, and the feature text is stored in the facial contour feature data file in the local database in association with the facial contour image.

[0080] The same above steps as those for the facial contour image are executed for the eyebrow image, eye image, nose image, mouth image, and limb image to obtain the feature texts corresponding to each feature information. Among them, the first threshold / third threshold corresponding to each feature information can be the same or different, and can be set according to the actual situation, and is not specifically limited in this embodiment.

[0081] Select the feature text that appears most frequently in the feature texts corresponding to the facial contour image, eyebrow image, eye image, nose image, and mouth image, and combine it with the feature text corresponding to the limb image to form driving information. Then play the driving information in the form of voice for the driver to confirm. If the driver confirms, compile the driving information based on the communication protocol to obtain a lighting control instruction. It should be noted that in this embodiment, the driving information is obtained by combining the feature text corresponding to the facial feature information and the feature text corresponding to the posture feature information. That is, it is easy to understand that the feature texts corresponding to the facial feature information such as the facial contour image, eyebrow image, eye image, nose image, and mouth image in the same face image are the same. Select the feature text that appears most frequently in the feature texts corresponding to the facial contour image, eyebrow image, eye image, nose image, and mouth image, and combine it with the feature text corresponding to the limb image to form driving information. The face image is segmented into multiple parts, and each part is matched separately to obtain the feature text corresponding to each part. Select the feature text that appears most frequently as the feature text of the facial feature information. Compared with directly obtaining the feature text of the facial feature information by matching the entire face image, the accuracy of recognizing the feature text of the facial feature information is improved.

[0082] The communication protocol can be specified according to the actual application situation. For example, the lighting control instruction corresponding to the driving information of "overtaking in the left lane" is to control the left headlights to flash 3 times with light intensity A and flashing frequency B.

[0083] Step S30: Generate lighting information according to the lighting control instruction, and send the lighting information to external vehicles.

[0084] In this embodiment, the lighting control instruction includes the position of the vehicle lights, light intensity, and flashing frequency. The lighting control module in the vehicle generates lighting information according to the lighting control instruction. The generated lighting information includes the position of the flashing vehicle lights, the light intensity when the vehicle lights flash, and the flashing frequency, and sends the above lighting information to external vehicles. It should be noted that the external vehicles are the vehicles surrounding the current vehicle (the vehicle where the driver is located).

[0085] Step S40: Receive the lighting information of external vehicles.

[0086] In this embodiment, the lighting information of external vehicles is received by a camera installed outside the vehicle. The installation position of the camera outside the vehicle can be installed according to the actual application situation without damaging the original structure of the vehicle.

[0087] Step S50: Analyze the lighting information to obtain the driving information of external vehicles.

[0088] It should be noted that in this embodiment, the communication protocol includes several pieces of driving information and their corresponding lighting control instructions. Therefore, after receiving the lighting information of an external vehicle, the lighting control instructions can be inversely deduced, and then the driving information can be obtained according to the communication protocol.

[0089] Compared with the prior art where the information conveyed by the lighting communication between vehicles during oncoming or driving is fixed and cannot accurately convey the information that the driver wants to transmit, in this embodiment, by obtaining the characteristic information of the driver, and then according to the characteristic information, obtaining the lighting control instruction, and finally controlling the vehicle lights to flash according to the lighting control instruction and sending the lighting information to the external vehicle. That is to say, in this embodiment, the lighting control instruction is specifically generated according to the driver's characteristic information, and then the lighting information is sent to the external vehicle according to the lighting control instruction, rather than simply manually controlling the lighting to flash to transmit the information to the external vehicle. At the same time, when the vehicle receives the lighting information of the external vehicle, it analyzes the lighting information to obtain the driving information of the external vehicle. Therefore, the accurate transmission of the driver information between vehicles during oncoming or driving is realized.

[0090] In the second embodiment of the vehicle information transmission method of the present application, refer to Figure 3 , the vehicle information transmission method includes:

[0091] Step A10: Obtain the characteristic information and voice information of the driver.

[0092] In this embodiment, it should be noted that the voice information of the driver can be collected by a microphone installed in the vehicle cab. For example, real-time recording is performed after receiving the collection instruction issued by the driver, and the real-time recording ends after receiving the end instruction issued by the driver to obtain an audio. The collection instruction / end instruction can be a voice instruction or a key instruction. The voice information of the driver can be Mandarin or a dialect.

[0093] Step A20: Obtain the lighting control instruction according to the voice information and the characteristic information.

[0094] In this embodiment, on the basis of the first embodiment, the second embodiment adds voice information, compares the voice text obtained according to the voice information with the characteristic text obtained according to the characteristic information, and further improves the recognition accuracy of the driving information.

[0095] Refer to Figure 4 , wherein the step of obtaining the lighting control instruction according to the voice information and the characteristic information includes:

[0096] Step A201: Identify the voice information to obtain a voice text.

[0097] Specifically, the steps of recognizing the voice information to obtain the voice text include: constructing a preset acoustic model for voice recognition; training the preset acoustic model for voice recognition to obtain an acoustic model for voice; inputting the voice information into the acoustic model for voice, and outputting to obtain the voice text. In this embodiment, the acoustic model for voice recognition may be a Hidden Markov Model (HMM).

[0098] Step A202: Match the feature information with the first feature information in the local database to obtain a first similarity degree.

[0099] Step A303: If the first similarity degree is greater than or equal to the first threshold, obtain the feature text corresponding to the first feature information.

[0100] Step A204: If the first similarity degree is less than the first threshold, match the feature information with the second feature information in the platform database to obtain a third similarity degree.

[0101] Step A205: If the third similarity degree is greater than or equal to the third threshold, obtain the feature text corresponding to the second feature information, and store the feature text and the feature information in an associated manner in the local database.

[0102] The specific implementation processes of Steps A202 to A205 are the same as those of Steps S201 to S204 in the first embodiment, and will not be elaborated here.

[0103] Step A206: Compare the voice text with the feature text to obtain a second similarity degree.

[0104] Step A207: If the second similarity degree is greater than or equal to the second threshold, use the feature text as the driving information.

[0105] Step A208: If the second similarity degree is less than the second threshold, confirm the voice text as the driving information or the feature text as the driving information according to a preset rule

[0106] The preset rule includes:

[0107] Compare the usage times of the voice text and the feature text in the historical data;

[0108] If the usage times of the voice text in the historical data are greater than the usage times of the feature text in the historical data, use the voice text as the driving information;

[0109] If the usage times of the voice text in the historical data are less than the usage times of the feature text in the historical data, use the feature text as the driving information;

[0110] If the number of times the voice text is used in the historical data is equal to the number of times the feature text is used in the historical data, obtain the signal-to-noise ratio of the voice information.

[0111] If the signal-to-noise ratio is less than a preset threshold, use the voice text as driving information.

[0112] In this embodiment, when obtaining the voice information of the driver, there is more ambient noise in the environment where the driver is located, which will cause a certain deviation between the voice text obtained by recognizing the voice information and the driving information expressed by the driver. Therefore, when comparing the voice text with the feature text, the finally obtained second similarity is less than the second threshold. Therefore, when the second similarity is less than the second threshold, it is necessary to confirm whether the voice text or the feature text is used as driving information according to the preset rules, so as to ensure the accuracy of driving information recognition and then ensure the accurate transmission of driving information between vehicles.

[0113] Step A209: Compile the driving information based on the communication protocol to obtain a lighting control instruction.

[0114] It should be noted that in this embodiment, the communication protocol can be specified according to the actual application situation. For example, the lighting control instruction corresponding to the driving information of "overtaking in the left lane" is to control the left headlights to flash 3 times with a light intensity A and a flashing frequency B.

[0115] Step A30: Generate lighting information according to the lighting control instruction and send the lighting information to external vehicles.

[0116] In this embodiment, the lighting control instruction includes the position of the vehicle lights, the light intensity, and the flashing frequency. The lighting control module in the vehicle generates lighting information according to the lighting control instruction. The generated lighting information includes the position of the flashing vehicle lights, the light intensity when the vehicle lights flash, and the flashing frequency, and sends the above lighting information to external vehicles. It should be noted that the external vehicles are the vehicles surrounding the current vehicle (the vehicle where the driver is located).

[0117] Step A40: Receive the lighting information of external vehicles.

[0118] In this embodiment, the lighting information of external vehicles is received by a camera installed outside the vehicle. The installation position of the camera outside the vehicle can be installed according to the actual application situation without damaging the original structure of the vehicle.

[0119] Step A50: Analyze the lighting information to obtain the driving information of external vehicles.

[0120] It should be noted that, in this embodiment, the communication protocol includes several pieces of driving information and their corresponding lighting control instructions. Therefore, after receiving the lighting information of an external vehicle, the lighting control instructions can be inversely deduced, and then the driving information can be obtained according to the communication protocol.

[0121] It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0122] In addition, the embodiment of the present application also provides a vehicle information transmission device. Referring to Figure 5 , the vehicle information transmission device includes:

[0123] A feature information acquisition module 10, configured to acquire the feature information of the driver;

[0124] An instruction generation module 20, configured to obtain a lighting control instruction according to the feature information;

[0125] A lighting control module 30, configured to generate lighting information according to the lighting control instruction and send the lighting information to an external vehicle;

[0126] A lighting information acquisition module 40, configured to receive the lighting information of an external vehicle;

[0127] An analysis module 50, configured to analyze the lighting information to obtain the driving information of an external vehicle.

[0128] Optionally, the feature information acquisition module includes:

[0129] An image acquisition unit, configured to acquire the face image and limb movement image of the driver;

[0130] A facial feature information acquisition unit, configured to acquire the corresponding facial feature information according to the face image;

[0131] A posture feature information acquisition unit, configured to acquire the corresponding posture feature information according to the limb movement image.

[0132] Optionally, the vehicle information transmission device further includes:

[0133] A voice acquisition module, configured to acquire the voice information of the driver;

[0134] The instruction generation module is configured to obtain a lighting control instruction according to the voice information and the feature information.

[0135] Optionally, the instruction generation module includes:

[0136] A driving information acquisition unit, and the driving information acquisition unit is used for:

[0137] Match the feature information with the first feature information in the local database to obtain a first similarity value;

[0138] If the first similarity value is greater than or equal to a first threshold, obtain the feature text corresponding to the first feature information as driving information;

[0139] If the first similarity is less than the first threshold, match the feature information with the second feature information in the platform database to obtain a third similarity;

[0140] If the third similarity is greater than or equal to a third threshold, obtain the feature text corresponding to the second feature information as driving information, and store the feature text and the feature information in the local database in an associated manner;

[0141] An instruction compilation unit, configured to compile the driving information based on a communication protocol to obtain a lighting control instruction.

[0142] Optionally, the driving information acquisition unit is further configured to:

[0143] Recognize the voice information to obtain a voice text;

[0144] Compare the voice text with the feature text to obtain a second similarity;

[0145] If the second similarity is greater than or equal to a second threshold, use the feature text as driving information;

[0146] If the second similarity is less than the second threshold, confirm the voice text as driving information or the feature text as driving information according to a preset rule.

[0147] Optionally, the preset rule includes:

[0148] Compare the usage times of the voice text and the feature text in historical data;

[0149] If the usage times of the voice text in historical data are greater than the usage times of the feature text in historical data, use the voice text as driving information;

[0150] If the usage times of the voice text in historical data are less than the usage times of the feature text in historical data, use the feature text as driving information;

[0151] If the usage times of the voice text in historical data are equal to the usage times of the feature text in historical data, obtain the signal-to-noise ratio of the voice information;

[0152] If the signal-to-noise ratio is less than a preset threshold, the voice text is used as driving information.

[0153] The specific implementation of the vehicle information transmission device in this application is basically the same as that of the above-mentioned vehicle information transmission method embodiments, and will not be elaborated here.

[0154] In addition, the embodiments of this application also provide a vehicle information transmission device. As Figure 6 shown, Figure 6 is a schematic structural diagram of the hardware operating environment involved in the embodiment solution of this application.

[0155] As Figure 6 shown, the schematic structural diagram of the hardware operating environment of this vehicle information transmission device may include: a processor 1001, such as a CPU, a memory 1005, a user interface 1003, a network interface 1004, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0156] Optionally, the vehicle information transmission device may further include an RF (Radio Frequency) circuit, sensors, an audio circuit, a WiFi module, and so on.

[0157] Those skilled in the art can understand that Figure 6 the structure of the vehicle information transmission device shown in

[0158] As Figure 6 shown, in the memory 1005, which is a computer storage medium, there may be an operating system, a network communication module, a user interface module, and a vehicle information transmission program. Among them, the operating system is a program for managing and controlling the hardware and software resources of the vehicle information transmission device, and supports the operation of the vehicle information transmission program and other software or programs.

[0159] In Figure 6In the vehicle information transmission device shown, the user interface 1003 is mainly used to connect to a terminal and communicate data with the terminal, such as receiving requests sent by the terminal; the network interface 1004 is mainly used to communicate with a background server and communicate data with the background server; the processor 1001 can be used to call the vehicle information transmission program stored in the memory 1005 and execute the steps of the vehicle information transmission method as described above.

[0160] The specific implementation manner of the vehicle information transmission device of this application is basically the same as that of each embodiment of the above vehicle information transmission method, and will not be elaborated here.

[0161] In addition, an embodiment of this application also proposes a storage medium, on which a vehicle information transmission program is stored. When the vehicle information transmission program is executed by a processor, the steps of the vehicle information transmission method as described above are implemented.

[0162] The specific implementation manner of the storage medium of this application is basically the same as that of each embodiment of the above vehicle information transmission method, and will not be elaborated here.

[0163] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or device including that element.

[0164] The serial numbers of the embodiments of this application are only for description and do not represent the superiority or inferiority of the embodiments.

[0165] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation manner. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc) and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, device, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0166] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present application.

Claims

1. A vehicle information transmission method, characterized in that, The vehicle information transmission method includes: Obtain the characteristic information and voice information of the driver; Recognize the voice information to obtain a voice text; Obtain a lighting control instruction according to the characteristic information; The step of obtaining a lighting control instruction according to the characteristic information includes: Match the characteristic information with the first characteristic information in the local database to obtain a first similarity. Wherein, the characteristic information includes posture characteristic information and facial characteristic information, and the posture characteristic information is obtained according to the body movement image of the driver; If the first similarity is greater than or equal to a first threshold, obtain the characteristic text corresponding to the first characteristic information; Compare the voice text with the characteristic text to obtain a second similarity; If the second similarity is less than a second threshold, confirm the voice text as driving information or the characteristic text as driving information according to a preset rule; If the second similarity is greater than or equal to the second threshold, use the characteristic text as driving information; Compile the driving information based on a communication protocol to obtain a lighting control instruction; Generate lighting information according to the lighting control instruction and send the lighting information to an external vehicle; Receive the lighting information of the external vehicle; Analyze the lighting information to obtain the driving information of the external vehicle.

2. The vehicle information transmission method according to claim 1, wherein The preset rule includes: Compare the usage times of the voice text and the characteristic text in historical data; If the usage times of the voice text in historical data are greater than the usage times of the characteristic text in historical data, use the voice text as driving information; If the usage times of the voice text in historical data are less than the usage times of the characteristic text in historical data, use the characteristic text as driving information; If the usage times of the voice text in historical data are equal to the usage times of the characteristic text in historical data, obtain the signal-to-noise ratio of the voice information; If the signal-to-noise ratio is less than a preset threshold, use the voice text as driving information.

3. The vehicle information transmission method according to any one of claims 1 to 2, characterized in that, After the step of matching the characteristic information with the first characteristic information in the local database to obtain a first similarity, it further includes: If the first similarity is less than the first threshold, match the characteristic information with the second characteristic information in the platform database to obtain a third similarity; If the third similarity is greater than or equal to a third threshold, obtain the characteristic text corresponding to the second characteristic information as driving information, and store the characteristic text and the characteristic information in the local database in an associated manner.

4. The vehicle information transmission method according to claim 1, wherein The step of analyzing the lighting information to obtain the driving information of the external vehicle includes: Analyze the lighting information based on a communication protocol to obtain the driving information of the external vehicle.

5. A vehicle information transmission device, characterized in that, The vehicle information transmission device includes: A characteristic information acquisition module for acquiring the characteristic information and voice information of the driver; An instruction generation module, and the instruction generation module is used for: Obtain a lighting control instruction according to the characteristic information; The instruction generation module includes: A driving information acquisition unit, and the driving information acquisition unit is used for: Recognize the voice information to obtain a voice text; Match the feature information with the first feature information in the local database to obtain a first similarity. Among them, the feature information includes pose feature information and facial feature information, and the pose feature information is obtained according to the limb movement image of the driver; If the first similarity is greater than or equal to a first threshold, obtain the feature text corresponding to the first feature information; Compare the speech text with the feature text to obtain a second similarity; If the second similarity is less than a second threshold, confirm the speech text as driving information or the feature text as driving information according to a preset rule; If the second similarity is greater than or equal to the second threshold, use the feature text as driving information; An instruction compilation unit for compiling the driving information based on a communication protocol to obtain a lighting control instruction; A lighting control module for generating lighting information according to the lighting control instruction and sending the lighting information to an external vehicle; A lighting information acquisition module for receiving the lighting information of an external vehicle; An analysis module for analyzing the lighting information to obtain the driving information of an external vehicle.

6. A vehicle information transmission device, characterized in that, It includes a processor, a memory, and a vehicle information transmission program stored on the memory and executable on the processor. When the vehicle information transmission program is executed by the processor, the steps of the vehicle information transmission method according to any one of claims 1 to 4 are implemented.

7. A storage medium, characterized in that, The vehicle information transmission program is stored on the storage medium. When the vehicle information transmission program is executed by the processor, the steps of the vehicle information transmission method according to any one of claims 1 to 4 are implemented.

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