Vehicle control method and device and vehicle

Abstract

The invention discloses a vehicle control method and device and a vehicle, and belongs to the technical field of vehicles. Comprising the steps that under the condition that it is detected that a second vehicle emits a target lamp language, at least one candidate road scene is determined based on the target lamp language, the candidate road scene is a road scene corresponding to the target lamp language, the second vehicle is a vehicle around a first vehicle, and one candidate road scene corresponds to one scene judgment condition; determining a target road scene from the at least one candidate road scene, wherein the first vehicle meets a scene judgment condition corresponding to the target road scene; and controlling the first vehicle to output target reminding information based on the target lamp language and the target road scene. According to the method and the device, the corresponding reminding information is output by recognizing the sight light of the lamplight emitted by other vehicles and combining the target road scene where the vehicle is located, so that the more accurate reminding information is output to a driver, a more accurate driving intention can be transmitted to the driver, and the driving safety of the vehicle is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method, device and vehicle. Background Art

[0002] With the increasing needs of users, more and more functions are set up in vehicles. For example, the vehicle's light module can also display some light language, such as a bottle pattern in the vehicle's light module, so the following vehicle can know that there may be a baby in the front vehicle. For another example, the vehicle's light module can display a birthday cake pattern, so other vehicles can know that there may be a birthday occupant in this vehicle.

[0003] However, the above-mentioned light language is mostly entertainment functions. In the process of vehicle driving, in order to improve driving safety, it is more important to know some driving intentions conveyed by drivers of other vehicles. Therefore, a vehicle control method that can improve driving safety is urgently needed. Summary of the invention

[0004] The present application provides a vehicle control method, device, vehicle and storage medium, which can identify the light language emitted by other vehicles and output corresponding reminder information in combination with the road scene currently located by the vehicle, so that the driver of the vehicle can know the driving intention conveyed by other vehicles, thereby improving the driving safety of the vehicle. The technical solution includes the following contents.

[0005] In a first aspect, a vehicle control method is provided, the method comprising:

[0006] In the case where a second vehicle is detected to emit a target light signal, at least one candidate road scene is determined based on the target light signal, the candidate road scene being a road scene corresponding to the target light signal, the second vehicle being a vehicle around the first vehicle, and one candidate road scene corresponding to one scene judgment condition;

[0007] Determining a target road scene from the at least one candidate road scene, the first vehicle meeting a scene judgment condition corresponding to the target road scene;

[0008] Based on the target light language and the target road scene, the first vehicle is controlled to output target reminder information.

[0009] In the present application, when a second vehicle around a first vehicle is detected to emit a target light language, at least one candidate road scene can be determined based on the target light language, that is, the road scene where the first vehicle may be located is first determined, and then the target road scene is determined from at least one candidate road scene. Since one candidate road scene corresponds to one scene judgment condition, the above operation is to determine the candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle from at least one candidate road scene, that is, to determine the road scene where the first vehicle is currently located. Subsequently, based on the target light language and the target road scene, the first vehicle is controlled to output target reminder information. Since the driving intention represented by the same light language in different road scenes is also different, more accurate reminder information can be output to the driver based on the target light language and the target road scene, thereby conveying a more accurate driving intention to the driver, which can improve driving safety.

[0010] Optionally, in the case where the second vehicle is detected to emit a target light signal, before determining at least one candidate road scene based on the target light signal, the method further includes:

[0011] Acquiring light information of the second vehicle;

[0012] Performing color recognition and shape recognition on the light information of the second vehicle to determine the light type indicated by the light information; performing brightness analysis on the light information of the second vehicle to determine the number of flashes; and determining the target light language based on the light type and the number of flashes;

[0013] Alternatively, the light information of the second vehicle is judged to be on and off to generate a binary electrical signal; the binary electrical signal is converted into a target Morse code; based on the target Morse code, a corresponding light language is obtained from a preset correspondence relationship to be determined as the target light language, and the preset correspondence relationship is the correspondence between the Morse code and the light language.

[0014] Optionally, determining at least one candidate road scene based on the target light language includes:

[0015] Based on the target light language, a corresponding road scene is obtained from a target correspondence relationship and determined as the at least one candidate road scene, wherein the target correspondence relationship is a correspondence relationship between the light language and the road scene.

[0016] Optionally, determining the target road scene from the at least one candidate road scene includes:

[0017] For any one of the at least one candidate road scene, determining scene judgment information required for the scene judgment condition based on the scene judgment condition corresponding to the candidate road scene;

[0018] determining, based on a target parameter corresponding to the scene judgment information, whether the first vehicle satisfies a scene judgment condition corresponding to the candidate road scene;

[0019] The candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle is determined as the target road scene.

[0020] Optionally, the determining whether the first vehicle satisfies a scene judgment condition corresponding to the candidate road scene based on a target parameter corresponding to the scene judgment information includes:

[0021] In the case where the candidate road scene is the first road scene, a relative motion relationship is determined based on the relative position and relative speed of the first vehicle, and if the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the first vehicle is stationary, and the current traffic light state is green, then it is determined that the first vehicle meets the scene judgment condition corresponding to the first road scene, and the first road scene is a scene in which the vehicle in front remains stationary after the green light is on;

[0022] In the case where the candidate road scene is the second road scene, a relative motion relationship is determined based on the relative position and relative speed of the first vehicle, and if the relative motion relationship is that the first vehicle follows directly behind the second vehicle and the distance between the two vehicles is less than a preset distance threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the second road scene, and the second road scene is a scene in which the first vehicle and the second vehicle follow each other at a close distance;

[0023] In the case where the candidate road scene is the third road scene, if the relative movement directions of the first vehicle and the second vehicle are opposite, and the light information of the first vehicle is that the high beam is turned on, and the light intensity at the position of the first vehicle is less than or equal to a preset intensity threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the third road scene, and the third road scene is a scene where the high beam is turned on when there is an oncoming vehicle;

[0024] When the candidate road scene is the fourth road scene, if the relative movement direction of the first vehicle and the second vehicle is the same but they are in different lanes, and the steering wheel angle of the first vehicle is greater than a preset angle threshold or the light information of the first vehicle is that the left turn signal is on, it is determined that the first vehicle meets the scene judgment condition corresponding to the fourth road scene, and the fourth road scene is a scene of vehicle changing lanes.

[0025] Optionally, the controlling the first vehicle to output target reminder information based on the target road scene and the target light language includes:

[0026] When the target light language is high beam flashing at least once and the target road scene is a first road scene, controlling the first vehicle to output a first reminder message, wherein the first reminder message is used to remind the driver of the first vehicle to pass the traffic light in time;

[0027] When the target light language is that the brake light is on multiple times and the target road scene is the second road scene, controlling the first vehicle to output a second reminder message, where the second reminder message is used to remind the driver of the first vehicle to keep a safe distance;

[0028] When the target light language is high beam flashing multiple times and the target road scene is a third road scene, controlling the first vehicle to output a third reminder message, the third reminder message is used to remind the driver of the first vehicle to turn off the high beam in time;

[0029] When the target light language is high beam flashing once and the target road scene is a fourth road scene, controlling the first vehicle to output fourth reminder information, the fourth reminder information being used to remind the driver of the first vehicle that the second vehicle is allowed to change lanes;

[0030] When the target light language is high beam flashing multiple times and the target road scene is the fourth road scene, the first vehicle is controlled to output fifth reminder information, and the fifth reminder information is used to remind the driver of the first vehicle that the second vehicle is not allowed to change lanes.

[0031] Optionally, the method further comprises:

[0032] In the case where the second vehicle is not detected to emit the target light signal, determining a reference road scene from a plurality of road scenes, one of the road scenes corresponds to one light signal execution condition, and the first vehicle satisfies the light signal execution condition corresponding to the reference road scene;

[0033] Based on the reference road scene, determining a target execution light language;

[0034] The light language is executed based on the target to control the first vehicle to adjust the light parameters.

[0035] Optionally, the target execution light language includes a target light type and a target flashing number, and the controlling the first vehicle to adjust the light parameters based on the target execution light language includes:

[0036] The target light type light of the first vehicle is controlled to flash at the target flashing number.

[0037] In a second aspect, a vehicle control device is provided, the device comprising:

[0038] A first determination module is used to determine at least one candidate road scene based on the target light language when a second vehicle is detected to emit a target light language, wherein the candidate road scene is a road scene corresponding to the target light language, the second vehicle is a vehicle around the first vehicle, and one candidate road scene corresponds to one scene judgment condition;

[0039] A second determination module is used to determine a target road scene from the at least one candidate road scene, and the first vehicle meets a scene judgment condition corresponding to the target road scene;

[0040] The first control module is used to control the first vehicle to output target reminder information based on the target light language and the target road scene.

[0041] In a third aspect, a vehicle is provided, the vehicle comprising:

[0042] A memory for storing executable program codes;

[0043] The processor is used to call and run the executable program code from the memory so that the vehicle executes the above-mentioned vehicle control method.

[0044] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above-mentioned vehicle control method when executed by a processor.

[0045] In a fifth aspect, a computer program product comprising instructions is provided, which, when executed on a computer, enables the computer to execute the steps of the above-mentioned vehicle control method.

[0046] It can be understood that the beneficial effects of the second, third, fourth and fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] 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 ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 is a schematic diagram of a scenario of a vehicle control method provided in an embodiment of the present application;

[0049] Figure 2 is a flow chart of a vehicle control method provided by an embodiment of the present application;

[0050] Figure 3 is a flow chart of another vehicle control method provided by an embodiment of the present application;

[0051] Figure 4 This is a schematic diagram of an interface of a scene reminder interface provided in an embodiment of the present application;

[0052] Figure 5 is a structural schematic diagram of a vehicle control device provided in an embodiment of the present application;

[0053] Figure 6 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0055] It should be understood that the "multiple" mentioned in this application refers to two or more. In the description of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in order to facilitate the clear description of the technical solution of this application, the words "first" and "second" are used to distinguish between the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the words "first" and "second" do not limit the quantity and execution order, and the words "first" and "second" do not limit them to be different.

[0056] Before describing in detail the vehicle control method provided in the embodiment of the present application, the terms involved in the embodiment of the present application are first explained.

[0057] Light language: Light language refers to a way of conveying information or intentions through vehicle light signals, which can help drivers communicate effectively with other traffic participants. Common light language includes turn signals, brake lights, high and low beams flashing alternately, hazard warning lights flashing, etc., all of which can convey corresponding driving intentions to other traffic participants.

[0058] Morse code: Morse code is also called Morse code, which mainly consists of a short dot signal "." and a long signal "—" that lasts for a certain period of time. Morse code uses a combination of dot signals and long signals to represent characters, thereby transmitting information. For example, the Morse code for the letters A and B is: A: ".—", B: "—".

[0060] Large language model: The goal of a large language model is to understand and generate human language in order to have effective conversations and answer various questions. The "large" in a large language model mainly includes two meanings. On the one hand, it refers to the number of parameters of the model. In a large language model, the number of parameters is usually very large, reaching billions or even tens of billions, which enables the large language model to learn and represent very complex patterns. On the other hand, "large" also refers to the scale of training data. Generally speaking, a large language model is trained with very large-scale text data, which is equivalent to learning large-scale data through a large language model, thereby establishing connections between data, making the model's generalization ability very strong.

[0061] Large language models are usually trained to solve common language problems, such as text classification, question answering, text summarization, and text generation. In the embodiments of the present application, the operation of text summarization through a large language model is mainly involved.

[0062] The application scenarios of the embodiments of the present application are further described.

[0063] For example, Figure 1 It is a scene schematic diagram of a vehicle control method provided in an embodiment of the present application. The vehicle control method can be applied to various road scenes. Figure 1 Three scenarios are shown in Figure 1 , Figure 1 The system includes a first vehicle 101 and a second vehicle 102 .

[0064] Figure 1 (a) in FIG. 1 shows a scene in which a first vehicle 101 and a second vehicle 102 pass through a traffic light. Figure 1 In (a), the first vehicle 101 is located in front of the second vehicle 102, and the traffic light at the front intersection is green. However, the first vehicle 101 is still stationary, which causes the second vehicle 102 to be unable to pass.

[0065] Figure 1 (b) in FIG. 1 shows a scenario in which a first vehicle 101 and a second vehicle 102 are traveling in opposite directions. Figure 1 In (b), the first vehicle 101 and the second vehicle 102 are traveling towards each other, and the first vehicle 101 turns on the high beam for illumination. As shown in the figure, the light emitted by the high beam of the first vehicle 101 will illuminate the position of the second vehicle 102, which will cause the driver of the second vehicle 102 to be unable to see the road clearly.

[0066] Figure 1 (c) in FIG. 1 shows a scenario in which a first vehicle 101 follows a second vehicle 102. Figure 1In (c), the first vehicle 101 is traveling behind the second vehicle 102 , and the distance between the first vehicle 101 and the second vehicle 102 is very small, so there is a risk that the first vehicle 101 will rear-end the second vehicle 102 .

[0067] To this end, the present application provides a vehicle control method, which can be applied to vehicle driving scenarios, such as the above-mentioned scenarios.

[0068] Specifically, when the second vehicle 102 is detected to emit a target light signal, at least one candidate road scene is first determined based on the target light signal, that is, the road scene that the first vehicle 101 may be in is determined. Then, the road scene that the first vehicle 101 is actually currently in is determined from the at least one candidate road scene. Then, based on the target light signal and the target road scene, the first vehicle 101 is controlled to output the target reminder information.

[0069] For example, during the driving of the first vehicle 101, it is detected that the second vehicle 102 emits a target light signal of "high beam flashes once", and then based on the target light signal, at least one candidate road scene is determined to be the above Figure 1 (a) shows the road scene and Figure 1 For each road scene, it has a corresponding scene judgment condition to judge whether the first vehicle 101 satisfies the scene judgment condition, and then determines whether the first vehicle 101 satisfies the scene judgment condition. Figure 1 The road scene shown in (a) is shown in Figure 1. Finally, the target light message "high beam flashes once" and Figure 1 In the road scene shown in (a), the first vehicle 101 is controlled to output corresponding target reminder information, for example, "the green light is on, and the vehicle behind urges you to pass in time".

[0070] For another example, during the driving of the first vehicle 101, it is detected that the second vehicle 102 emits a target light signal of "high beam flashes multiple times", and then based on the target light signal, a candidate road scene is determined to be the above Figure 1 The road scene shown in (b) is then judged whether the first vehicle 101 meets the requirements. Figure 1 The scene judgment condition corresponding to the road scene shown in (b) of FIG. Figure 1 In the case of the scene judgment condition corresponding to the road scene shown in (b) in FIG, the target light language of “high beam flashes multiple times” and Figure 1 In the road scene shown in (b), the first vehicle 101 is controlled to output corresponding target reminder information, for example, "oncoming vehicle, please turn off the high beam in time".

[0071] In this way, by identifying the light language emitted by other vehicles and outputting corresponding reminder information in combination with the current road scene of the vehicle, more accurate reminder information can be output to the driver, thereby conveying more accurate driving intentions to the driver of the vehicle, thereby improving the driving safety of the vehicle.

[0072] The vehicle control method provided in the embodiment of the present application is explained in detail below.

[0073] Figure 2 is a flow chart of a vehicle control method provided by an embodiment of the present application. The method can be applied to the ECU (Electronic Control Unit) of a vehicle. Figure 2 , the method comprises the following steps.

[0074] Step 201: When a second vehicle is detected to emit a target light signal, at least one candidate road scene is determined based on the target light signal, the second vehicle is a vehicle around the first vehicle, and one candidate road scene corresponds to one scene judgment condition.

[0075] The second vehicle is a vehicle around the first vehicle, for example, the second vehicle is a vehicle in front of or behind the first vehicle, or the second vehicle is a vehicle in an opposite lane of the first vehicle, etc.

[0076] The target light language is a light language obtained by analyzing the light information of the second vehicle, which represents the intention conveyed by the driver of the second vehicle.

[0077] The candidate road scene is a road scene corresponding to the target light language. In the embodiment of the present application, a correspondence between the light language and the road scene can be pre-set. Therefore, after parsing the target light language, the corresponding candidate road scenes can be determined.

[0078] In the embodiment of the present application, each road scene corresponds to a scene judgment condition, and therefore, a candidate road scene also corresponds to a scene judgment condition. The scene judgment condition is used to determine which road scene the first vehicle is currently in.

[0079] In this case, by determining at least one candidate road scene based on the target light language, it is possible to first determine the road scene in which the first vehicle may be located, and then the scene in which the first vehicle is located can be determined more quickly later.

[0080] Specifically, the operation of step 201 may be: based on the target light language, a corresponding road scene is acquired from the target correspondence relationship to be determined as the at least one candidate road scene.

[0081] The target correspondence is the correspondence between the light language and the road scene. The target correspondence includes multiple light language and multiple road scenes, wherein one light language can correspond to one road scene or multiple road scenes.

[0082] The target correspondence relationship may be pre-set by a technician and stored in the first vehicle. In the embodiment of the present application, the target correspondence relationship may also be freely defined by a user.

[0083] The first vehicle may be provided with a custom entry for the target correspondence, such as a relationship custom control. When the user wants to customize the target correspondence, the user may operate the relationship custom control. For example, the user may click the relationship custom control, slide the relationship custom control, etc. to operate the relationship custom control.

[0084] Furthermore, after clicking the relationship customization control, a relationship customization interface can be displayed, on which the user can enter the road scene they want to set and set the corresponding light language. Since one road scene corresponds to one scene judgment condition, after setting a road scene, the scene judgment condition corresponding to the road scene can also be set.

[0085] The user can input the scene judgment condition corresponding to the road scene through voice, text, etc. When the voice information and text information input by the user are received, the text can be summarized through the large language model to generate the scene judgment condition corresponding to the road scene.

[0086] Specifically, the voice information or text information input by the user is input into the large language model, and the voice information or text information is processed by the large language model to generate the scene judgment conditions corresponding to the road scene.

[0087] For example, the large language model may be a model such as ChatGPT, GPT-4, or PaLM.

[0088] In this case, the user can describe the scene judgment condition to be set in his own language, and then the big language model will summarize the text to automatically generate the scene judgment condition corresponding to the road scene. In this way, the scene judgment condition corresponding to the road scene can be set more conveniently, thereby improving the user experience.

[0089] For example, Table 1 is an example of a target correspondence relationship. Referring to Table 1, the target correspondence relationship includes multiple light language and multiple road scenes. For example, if the target light language is "high beam flashes once", then at least one candidate road scene can be determined to be the first road scene and the third road scene from the following target correspondence relationship.

[0090] Table 1

[0091]

[0092]

[0093] The embodiment of the present application only uses the above Table 1 as an example to illustrate the target correspondence relationship, and does not constitute a limitation to the embodiment of the present application.

[0094] It is worth noting that, before step 201, the target light signal emitted by the second vehicle may also be determined.

[0095] A first possible implementation method is to obtain light information of a second vehicle; perform color recognition and shape recognition on the light information of the second vehicle to determine the light type indicated by the light information; perform brightness analysis on the light information of the second vehicle to determine the number of flashes; and determine a target light language based on the light type and the number of flashes.

[0096] Optionally, an image including the light of the second vehicle may be captured by the camera of the first vehicle, so that the image is the light information of the second vehicle. It should be understood that the camera of the first vehicle may continuously capture images of the second vehicle, that is, obtain multiple images of the light of the second vehicle that are in a time sequence relationship, that is, obtain the light information of the second vehicle.

[0097] Light type refers to the type of light on the vehicle. In the embodiment of the present application, the light type may include high beam, brake lights, hazard warning flashers, etc.

[0098] Since different types of lights on vehicles have different color characteristics and shape characteristics, the light information of the second vehicle can be color recognized and shape recognized to determine the type of light indicated by the light information. In addition, when the light flashes, there are obvious changes in brightness, so the number of flashes can be determined by performing brightness analysis on the light information.

[0099] In this case, it is equivalent to determining the target light language by analyzing the characteristics of the light information of the second vehicle, so that a more accurate target light language can be determined.

[0100] For example, if the light type is high beam and the number of flashes is 3, then the target light language can be determined as high beam flashes multiple times. For another example, if the light type is brake light and the number of flashes is 3, then the target light language can be determined as brake light on 3 times. For another example, if the light type is high beam and the number of flashes is 1, then the target light language can be determined as high beam flashes 1 time.

[0101] A second possible implementation method is to obtain light information of the second vehicle; input the light information of the second vehicle into a light language recognition model, process the light information through the light language recognition model, and output a target light language corresponding to the light information.

[0102] The light recognition model is used to recognize the light information of the second vehicle and obtain the light language emitted by the second vehicle.

[0103] It is worth noting that before the second vehicle light information is input into the light language recognition model, the light language recognition model can also be obtained by training through a server. The server is a computer device used to train the light language recognition model.

[0104] Specifically, the server may obtain multiple training samples, and use the multiple training samples to train the neural network model to obtain the light language recognition model. It should be understood that the multiple training samples are training samples that have been pre-processed such as cropping and denoising.

[0105] The multiple training samples may be pre-set. Each of the multiple training samples includes sample data and sample tags, the sample data is a set of time-series images containing lights, and the sample tags are light language indicated by the set of time-series images. That is, the input data in each of the multiple training samples is a set of time-series images containing lights, and the sample tags are light language indicated by the set of time-series images.

[0106] The neural network model may include multiple network layers, including an input layer, multiple hidden layers, and an output layer. The input layer is responsible for receiving input data; the output layer is responsible for outputting processed data; multiple hidden layers are located between the input layer and the output layer, responsible for processing data, and the multiple hidden layers are invisible to the outside. For example, the neural network model may be a deep neural network, and may be a convolutional neural network in a deep neural network.

[0107] When the server uses multiple training samples to train the neural network model, for each of the multiple training samples, the input data in the training sample can be input into the neural network model to obtain output data; the loss value between the output data and the sample label in the training sample is determined by the loss function; and the parameters in the neural network model are adjusted according to the loss value. After the parameters in the neural network model are adjusted based on each of the multiple training samples, the neural network model with the adjusted parameters is the light language recognition model.

[0108] A third possible implementation method is to obtain the light information of the second vehicle; determine whether the light information of the second vehicle is on or off to generate a binary electrical signal; convert the binary electrical signal into a target Morse code; and based on the target Morse code, determine a corresponding light language from a preset correspondence as the target light language.

[0109] A binary electrical signal may include a high-level signal (corresponding to the light being on), a low-level signal (corresponding to the light being off), and the duration of the corresponding signal. It may represent the on and off of a light, the duration of the light being on, and the duration of the light being off. For example, a binary electrical signal of high-delay(500)—low-dealy(100) means that the light is on for 500 milliseconds and then off, and the light is off for 100 milliseconds.

[0110] The preset corresponding relationship is the corresponding relationship between the Morse code and the light language. In the embodiment of the present application, the preset corresponding relationship can be customized by the user. For example, if a light language is set to SOS, the corresponding Morse code can be set to "…——…".

[0111] In this case, by setting the correspondence between the Morse code and the light language, some customized light languages ​​can also be recognized, so that the light language can be flexibly expanded.

[0112] In addition, by converting the light information of the second vehicle into a target Morse code and determining the target light language based on the target Morse code, the light information of the second vehicle is analyzed in detail, including analyzing the time when the light turns on and off each time, so that a more accurate target light language can be obtained.

[0113] Among them, the operation of converting the binary electrical signal into the target Morse code can be: deleting the low-level signal in the binary electrical signal; for the high-level signal in the binary electrical signal, determining the target Morse code corresponding to the high-level signal whose maintenance time is less than the preset time threshold as the dot signal ".", and determining the target Morse code corresponding to the high-level signal whose maintenance time is greater than or equal to the preset time threshold as the long signal "—".

[0114] The preset duration threshold may be set in advance, and the preset duration threshold may be set to be smaller.

[0115] In this case, when the holding time is less than the preset time threshold, it means that the holding time is short, that is, the time the light is on is short, and the target Morse code can be determined as a dot signal. When the holding time is greater than or equal to the preset time threshold, it means that the holding time is long, that is, the time the light is on is long, and the target Morse code can be determined as a long signal.

[0116] It is worth noting that at least one candidate road scene can be determined through the above step 201, that is, the road scene where the first vehicle may be located can be determined, and then the road scene where the first vehicle is actually currently located can be further determined, that is, continue to execute the following step 202.

[0117] Step 202: Determine a target road scene from the at least one candidate road scene, and the first vehicle meets a scene judgment condition corresponding to the target road scene.

[0118] In this case, it is equivalent to judging which candidate road scene among the at least one candidate road scene the first vehicle satisfies the scene judgment condition corresponding to, so that the candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle is the road scene (target road scene) in which the first vehicle is actually currently located.

[0119] Specifically, the operation of step 202 may include the following steps (1) to (3).

[0120] (1) For any one of the at least one candidate road scene, based on the scene judgment condition corresponding to the candidate road scene, determining the scene judgment information required for the scene judgment condition.

[0121] The scene judgment information is a parameter to be judged in the scene judgment condition, and whether the first vehicle meets the corresponding scene judgment condition is judged by judging whether the scene judgment information meets the corresponding requirements.

[0122] In the embodiment of the present application, the scene judgment information may include one or more. For example, the scene judgment information of a scene judgment condition includes vehicle speed, relative position, traffic light status, etc. In this case, it is determined whether the first vehicle meets the scene judgment condition by determining whether the vehicle speed, relative position and current traffic light status of the first vehicle meet specific requirements.

[0123] It is worth noting that after the scene judgment information required for the scene judgment condition is determined, the target parameters corresponding to each scene judgment information can also be obtained.

[0124] The target parameter refers to the specific parameter value corresponding to the scene judgment information. For example, if a scene judgment information is the state of a traffic light, then the target parameter corresponding to this scene judgment information can be green light, red light, yellow light, etc. For another example, if a scene judgment information is a relative position, then the target parameter corresponding to this scene judgment information can be that the first vehicle is 2 meters behind the second vehicle.

[0125] For example, the scene judgment information in a candidate road scene may include relative position, relative speed, and current traffic light status. Then, it can be obtained that the relative position is that the second vehicle is 2 meters behind the first vehicle, the relative speed is 0, and the current traffic light status is green.

[0126] The scene judgment information under another candidate road scene may include relative position and relative speed. Then, the relative position can be obtained as follows: the first vehicle is 1 meter behind the second vehicle, and the relative speed is 5 m / s (meters per second).

[0127] (2) Based on the target parameter corresponding to the scene judgment information, determine whether the first vehicle meets the scene judgment condition corresponding to the candidate road scene.

[0128] In this case, it is equivalent to that the scene judgment information corresponding to different road scenes is different, and whether the first vehicle meets the corresponding scene judgment condition is determined by determining whether the target parameter corresponding to each scene judgment information meets a specific condition. In this way, the road scene where the first vehicle is located can be determined more accurately.

[0129] Optionally, the embodiments of the present application may involve the following road scenarios, and the operation of step (2) may be implemented in the following situations.

[0130] In the first case, when the candidate road scene is the first road scene, the relative motion relationship is determined based on the relative position and relative speed of the first vehicle. If the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the first vehicle is stationary, and the current traffic light state is green, then it is determined that the first vehicle meets the scene judgment conditions corresponding to the first road scene.

[0131] The first road scene is a scene where the vehicle in front remains stationary after the green light comes on. According to the positional relationship between the first vehicle and the second vehicle, the first road scene may be a scene where the first vehicle in front remains stationary after the green light comes on, or a scene where the second vehicle in front remains stationary after the green light comes on.

[0132] In this case, when the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the first vehicle is in a stationary state, and the current traffic light state is green, it means that the target parameters corresponding to the various scene judgment information under the first road scene meet specific conditions, that is, they meet the scene judgment conditions corresponding to the first road scene, then it can be determined that the first vehicle meets the scene judgment conditions corresponding to the first road scene.

[0133] Optionally, the scene judgment information in the first road scene may also include the vehicle stationary time. In this case, if the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the first vehicle is stationary, and the vehicle stationary time is greater than the preset waiting time, and the current traffic light state is green, then it is determined that the first vehicle meets the scene judgment condition corresponding to the first road scene.

[0134] The vehicle stationary time refers to the length of time the vehicle remains stationary after the green light comes on.

[0135] The preset waiting time can be set according to the distance between the vehicle and the zebra crossing. For example, if the distance between the vehicle and the zebra crossing is 0-5 meters, the preset waiting time can be set to 2 seconds. For another example, if the distance between the vehicle and the zebra crossing is 5-10 meters, the preset waiting time can be set to 5 seconds.

[0136] In this road scene, there is a situation where there are multiple vehicles in front of the first vehicle. The first vehicle needs to wait for the multiple vehicles in front to start driving before it can pass, and this process takes a certain amount of time. The above operation is equivalent to considering the situation that the first vehicle needs time to pass in this case. In this way, it can be more accurately judged whether the first vehicle meets the scene judgment condition corresponding to the first road scene.

[0137] In the second case, when the candidate road scene is the second road scene, the relative motion relationship is determined based on the relative position and relative speed of the first vehicle. If the relative motion relationship is that the first vehicle follows directly behind the second vehicle and the distance between the two vehicles is less than the preset distance threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the second road scene.

[0138] The second road scene is a scene where the first vehicle and the second vehicle are following each other closely. According to the positional relationship between the first vehicle and the second vehicle, the second road scene may be a scene where the first vehicle is following the second vehicle closely or a scene where the second vehicle is following the first vehicle closely.

[0139] Since the relative position may include the distance between the first vehicle and the second vehicle and the relative motion direction of the two vehicles, the distance between the first vehicle and the second vehicle can be determined through the relative position, and then the relative motion relationship between the two vehicles can be determined.

[0140] When the first vehicle follows directly behind the second vehicle, it means that the first vehicle is following the second vehicle, and when the distance between the two vehicles is less than a preset distance threshold, it means that the distance between the first vehicle and the second vehicle is small, which means that the first vehicle is following the second vehicle at a close distance. It can be determined that the first vehicle meets the scene judgment condition corresponding to the second road scene.

[0141] In the third case, when the candidate road scene is the third road scene, if the relative movement directions of the first vehicle and the second vehicle are opposite, and the lighting information of the first vehicle is that the high beam is on, and the light intensity at the position of the first vehicle is less than or equal to the preset intensity threshold, it is determined that the first vehicle meets the scene judgment conditions corresponding to the third road scene.

[0142] The third road scene is a scene where the high beam is on when there is an oncoming vehicle. According to the positional relationship between the first vehicle and the second vehicle, the third road scene may specifically be a scene where the first vehicle turns on the high beam when the first vehicle and the second vehicle are traveling towards each other, or a scene where the second vehicle turns on the high beam.

[0143] Optionally, a light sensor may be installed on the first vehicle, and the light sensor may be used to collect light intensity at the location of the first vehicle.

[0144] The preset intensity threshold may be set in advance, and the preset intensity threshold may be set according to the light intensity at night, or the preset intensity threshold may be set to be smaller.

[0145] When the relative movement directions of the first vehicle and the second vehicle are opposite, it means that the first vehicle and the second vehicle are traveling towards each other, that is, the second vehicle is a vehicle in the opposite lane of the first vehicle. Afterwards, when the light intensity is less than or equal to the preset intensity threshold, it means that the first vehicle is located at night or in insufficient light, and the high beam of the first vehicle is on, it can be determined that the first vehicle meets the scene judgment condition corresponding to the third road scene.

[0146] In the fourth case, when the candidate road scene is the fourth road scene, if the relative movement directions of the first vehicle and the second vehicle are the same but they are in different lanes, and the steering wheel angle of the first vehicle is greater than a preset angle threshold or the light information of the first vehicle is that the left turn signal is on, it is determined that the first vehicle meets the scene judgment conditions corresponding to the fourth road scene.

[0147] The fourth road scene is a scene of a vehicle changing lanes. According to the positional relationship between the first vehicle and the second vehicle, the fourth road scene may be a scene of the first vehicle changing lanes or a scene of the second vehicle changing lanes.

[0148] The preset angle threshold can be set in advance, and the preset angle threshold can be set larger.

[0149] It should be understood that the fourth situation mentioned above includes two modes. In the first mode, when the relative movement direction of the first vehicle and the second vehicle is the same but they are in different lanes, it means that the first vehicle and the second vehicle are traveling in the same direction in different lanes, and when the steering wheel angle of the first vehicle is large, it means that the first vehicle may want to change lanes, then it is determined that the first vehicle meets the scene judgment condition corresponding to the fourth road scene. In the second mode, when the relative movement direction of the first vehicle and the second vehicle is the same but they are in different lanes, it means that the first vehicle and the second vehicle are traveling in the same direction in different lanes, and when the light information of the first vehicle shows that the left turn signal is on, it means that the first vehicle wants to change lanes, then it is determined that the first vehicle meets the scene judgment condition corresponding to the fourth road scene.

[0150] In a fifth case, when the candidate road scene is the fifth road scene, if the second vehicle remains stationary and the hazard warning lights of the second vehicle are turned on, it is determined that the first vehicle meets the scene judgment condition corresponding to the fifth road scene.

[0151] The fifth road scene is a scene in which a vehicle sends a distress signal. In an embodiment of the present application, the fifth road scene may include a scene in which a first vehicle sends a distress signal or a scene in which a second vehicle sends a distress signal.

[0152] When the second vehicle remains stationary and the hazard warning lights are on, it means that the second vehicle cannot drive normally. In this case, it can be determined that the first vehicle meets the fifth road scenario, that is, the first vehicle encounters a scenario in which the second vehicle sends a distress signal.

[0153] In the sixth case, when the candidate road scene is the sixth road scene, if the driving trajectory of the adjacent vehicle of the first vehicle deviates, it is determined that the first vehicle meets the scene judgment condition corresponding to the sixth road scene.

[0154] The sixth road scenario is a scenario in which an adjacent vehicle of the first vehicle has a driving problem.

[0155] In this case, if the driving track of the adjacent vehicle of the first vehicle deviates, it means that the driver of the adjacent vehicle may not be able to drive the vehicle normally. Then it can be determined that the first vehicle meets the scene judgment condition corresponding to the sixth road scene.

[0156] In this way, by performing the operation of the above step (2) on each candidate road scene in at least one candidate road scene, it is possible to determine which candidate road scene's scene judgment condition the first vehicle meets.

[0157] (3) Determine the candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle as the target road scene.

[0158] The first vehicle satisfies a scene judgment condition corresponding to a candidate road scene, indicating that the first vehicle is in such a scene at this time. Therefore, the candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle can be determined as the target road scene.

[0159] Step 203: Based on the target light language and the target road scene, control the first vehicle to output target reminder information.

[0160] The target reminder information is used to remind the second vehicle of the driving intention.

[0161] Since the driving intention represented by the same light language may be different in different road scenes, the first vehicle may be controlled to output target reminder information based on the target light language and the target road scene.

[0162] The target light language can indicate the driving intention of the driver of the second vehicle, and the target road scene refers to the road scene that the first vehicle is currently in. By combining the target light language and the target road scene to jointly output the target reminder information, more accurate reminder information can be output to the driver, thereby conveying a more accurate driving intention to the driver, thereby improving driving safety.

[0163] Optionally, methods of controlling the first vehicle to output target reminder information include but are not limited to voice broadcast, screen text output, pop-up window, etc.

[0164] Optionally, in an embodiment of the present application, the target light language and the target road scene may be input into a reminder information generation model, and corresponding target reminder information may be generated by the reminder information generation model.

[0165] The reminder information generation model may be a large language model, that is, a model obtained by training the large language model with large-scale data.

[0166] In this way, the target reminder information can be generated more conveniently through the reminder information generation model, thereby improving the output efficiency of the target reminder information.

[0167] In the embodiment of the present application, when several road scenes in the above step 202 are provided, the operation of step 203 can be implemented in the following situations.

[0168] In the first case, when the target light language is flashing the high beam at least once and the target road scene is the first road scene, the first vehicle is controlled to output the first reminder information.

[0169] The first reminder message is used to remind the driver of the first vehicle to pass the traffic light in time. For example, the first reminder message may be "the traffic light is currently green, and the vehicle behind urges you to pass in time."

[0170] When the target road scene is the first road scene, it means that the first vehicle remains stationary when the traffic light is green, and when the first vehicle receives a light signal from the second vehicle that the flash light flashes at least once, it means that the driver of the second vehicle is urging the first vehicle to pass as soon as possible, so the first reminder information can be output.

[0171] In the second case, when the target light language is the brake light lighting up multiple times and the target road scene is the second road scene, the first vehicle is controlled to output the second reminder information.

[0172] The second reminder message is used to remind the driver of the first vehicle to keep a safe distance during driving. For example, the first reminder message may be "The vehicle ahead reminds you that you are following too closely, please keep a safe distance."

[0173] When the target road scene is the second road scene, it means that the first vehicle is following the second vehicle closely, and when the light message of the brake lights of the second vehicle lighting up multiple times is received, it means that the driver of the second vehicle reminds the first vehicle not to follow too closely, so the second reminder information can be output.

[0174] In a third case, when the target light language is high beam flashing multiple times and the target road scene is a third road scene, the first vehicle is controlled to output a third reminder message.

[0175] The third reminder message is used to remind the driver of the first vehicle to turn off the high beam in time. For example, the third reminder message may be "the oncoming vehicle reminds you to turn off the high beam in time".

[0176] When the target road scene is the third road scene, it means that the first vehicle has turned on the flash lights when seeing an oncoming vehicle, and when receiving the light signal that the high beam of the second vehicle flashes multiple times, it means that the driver of the second vehicle reminds the first vehicle to turn off the flash lights, so the third reminder information can be output.

[0177] In a fourth case, when the target light language is high beam flashing once and the target road scene is the fourth road scene, the first vehicle is controlled to output a fourth reminder message.

[0178] The fourth reminder message is used to remind the driver of the first vehicle that the second vehicle is allowed to change lanes. For example, the fourth reminder message may be "the second vehicle allows you to change lanes."

[0179] When the target road scene is the fourth road scene, it means that the first vehicle wants to change lanes at this time, and when the high beam flashes once, it means that the driver of the second vehicle allows the first vehicle to change lanes. Therefore, the fourth reminder information can be output.

[0180] In a fifth case, when the target light language is high beam flashing multiple times and the target road scene is the fourth road scene, the first vehicle is controlled to output the fifth reminder information.

[0181] The fifth reminder message is used to remind the driver of the first vehicle that the second vehicle is not allowed to change lanes. For example, the fifth reminder message may be “Please note! The second vehicle does not allow you to change lanes”.

[0182] When the target road scene is the fifth road scene, it means that the first vehicle wants to change lanes at this time, and when the high beam flashes multiple times, it means that the driver of the second vehicle does not want the first vehicle to change lanes, so the fifth reminder information can be output.

[0183] In a sixth case, when the target light language is an SOS distress signal and the target road scene is a distress scene, the first vehicle is controlled to output a sixth reminder message.

[0184] The sixth reminder message is used to remind the second vehicle that it has sent a distress signal. For example, the sixth reminder message may be “The second vehicle has sent a distress signal, please pay attention!”.

[0185] When the target road scene is a distress scene and an "SOS distress" light message is received from a second vehicle, it indicates that the second vehicle may have a problem and cannot drive normally, etc., and a sixth reminder message may be output.

[0186] It is worth noting that through the above steps 201-203, when it is detected that the second vehicle triggers the target light language, the corresponding target reminder information can be output based on the target light language and the road scene in which the first vehicle is located to remind the second vehicle of the driving intention conveyed.

[0187] Figure 3 is a flow chart of another vehicle control method provided by an embodiment of the present application, such as Figure 3 As shown, in the embodiment of the present application, when the second vehicle is not detected to emit the target light signal, the following steps 301 to 303 may also be included.

[0188] Step 301: When the second vehicle is not detected to emit the target light signal, a reference road scene is determined from multiple road scenes, one road scene corresponds to one light signal execution condition, and the first vehicle satisfies the light signal execution condition corresponding to the reference road scene.

[0189] The reference road scene is a road scene where the first vehicle is located when no target light signal from the second vehicle is detected.

[0190] The light language execution conditions correspond to the road scenes. When the first vehicle meets the light language execution conditions of a road scene, the light language corresponding to the road scene can be executed, so that the light language execution conditions can indicate whether the first vehicle should send out the corresponding light language.

[0191] In this case, by determining a reference road scene from a plurality of road scenes, the road scene currently located by the first vehicle can be known, and then how to control the lights subsequently can be known.

[0192] Optionally, the operation of determining a reference road scene from a plurality of road scenes may include the following steps (1) to (3).

[0193] (1) Obtaining at least one of the relative motion parameters between the first vehicle and the second vehicle, the light intensity at the location of the first vehicle, the state of the traffic light, and the light information of the second vehicle.

[0194] The relative motion parameters may include parameters such as relative position, relative motion direction, relative speed, etc. The relative motion relationship between the first vehicle and the second vehicle may be determined by the relative motion parameters.

[0195] (2) For any one of the multiple road scenes, based on at least one of the relative motion parameters, the light intensity at the position of the first vehicle, the traffic light status, and the light information of the second vehicle, determining whether the first vehicle meets the light language execution condition corresponding to this road scene.

[0196] In the embodiment of the present application, the relative motion parameter includes at least one of the relative position, relative motion direction, and relative speed of the first vehicle and the second vehicle.

[0197] In this case, the operation of step (2) may include the following four cases.

[0198] In the first case, the relative motion relationship between the first vehicle and the second vehicle is determined based on the relative position, relative speed and relative motion direction; when the relative motion relationship is that the first vehicle follows directly behind the second vehicle and the second vehicle is stationary, and the traffic light state is green, it is determined that the first vehicle meets the light language execution conditions corresponding to the first road scene.

[0199] When the relative motion relationship is that the first vehicle follows the second vehicle directly behind and the second vehicle is stationary, it means that the first vehicle is behind the second vehicle and the second vehicle is currently stationary. Furthermore, when the traffic light is green, it means that the traffic light indicates that the vehicle can pass. In this case, the first road scenario that the vehicle in front remains stationary after the green light is on is satisfied, and it can be determined that the first vehicle meets the light language execution condition corresponding to the first road scenario.

[0200] In the second case, the relative motion relationship between the first vehicle and the second vehicle is determined based on the relative position, relative speed and relative motion direction; when the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the distance between the two vehicles is less than a preset distance threshold, it is determined that the first vehicle meets the light language execution conditions corresponding to the second road scene.

[0201] When the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the distance between the two vehicles is less than the preset distance threshold, it means that the second vehicle follows behind the first vehicle, and the distance between the first vehicle and the second vehicle is less than the preset distance threshold, that is, the distance between the first vehicle and the second vehicle is small, thereby satisfying the scenario that the second vehicle follows the first vehicle closely. It can be determined that the first vehicle meets the light language execution conditions corresponding to the third road scenario.

[0202] In the third case, when the relative motion relationship is that the first vehicle and the second vehicle are traveling towards each other, and the light intensity is less than or equal to the preset intensity threshold, and the light information of the second vehicle is that the high beam is on, it is determined that the first vehicle meets the light language execution conditions corresponding to the third road scene.

[0203] In the case where the relative motion relationship is that the first vehicle and the second vehicle are traveling towards each other, it means that the second vehicle is a vehicle in the opposite lane of the first vehicle. If the light intensity is less than or equal to the preset intensity threshold and the light information of the second vehicle is that the high beam is on, it means that the first vehicle is in an environment with insufficient light or is at night, and the second vehicle in the opposite lane has turned on the high beam. Thus, the scenario of the second vehicle turning on the high beam when the first vehicle and the second vehicle are traveling towards each other is met, and it can be determined that the first vehicle meets the light language execution condition corresponding to the third road scenario.

[0204] In the fourth case, the relative motion relationship between the first vehicle and the second vehicle is determined based on the relative position, relative speed and relative motion direction; when the relative motion relationship is that the first vehicle and the second vehicle are in different lanes and traveling in the same direction, and the light information of the second vehicle is that the left turn signal is on, it is determined that the first vehicle meets the light language execution conditions corresponding to the fourth road scene.

[0205] When the relative motion relationship is that the first vehicle and the second vehicle are in different lanes and traveling in the same direction, and the light information of the second vehicle is that the left turn signal is on, it means that the second vehicle wants to change lanes at this time, thereby satisfying the scenario of the second vehicle changing lanes. Therefore, it is determined that the first vehicle meets the light language execution conditions corresponding to the fourth road scenario.

[0206] (3) Determine the road scene corresponding to the light language execution condition satisfied by the first vehicle as the reference road scene.

[0207] The first vehicle meets the lighting execution conditions corresponding to a road scene, which indicates that the first vehicle is in such a scene at this time and can emit corresponding light language. Therefore, the candidate road scene corresponding to the light language execution conditions met by the first vehicle can be determined as the reference road scene.

[0208] Step 302: Determine the target execution light language based on the reference road scene.

[0209] The first vehicle meets the light language execution condition of a road scene, which means that the first vehicle needs to send out the corresponding light language to remind the second vehicle later. Therefore, the target execution light language can be determined based on the reference road scene.

[0210] In this case, by referring to the road scene and determining the target execution light language, the light language to be issued by the first vehicle can be known to convey its driving intention to the second vehicle.

[0211] Specifically, the operation of step 302 may be: based on the reference road scene, obtaining the corresponding light language from the target correspondence relationship and determining it as the target execution light language.

[0212] The target correspondence is the correspondence between the road scene and the light language. From the target correspondence, the light language that should be issued under the reference road scene can be learned.

[0213] In this way, by presetting the target correspondence, the target execution light language corresponding to the reference road scene can be directly determined from the target correspondence later, so that the target execution light language can be quickly determined, which improves the efficiency of determining the target execution light language.

[0214] Furthermore, when the reference road scene is not matched in the target correspondence, the following steps (1) to (2) may also be included.

[0215] (1) Based on the reference road scene, output scene reminder information.

[0216] The scene reminder information is used to remind the driver of the first vehicle of the current road scene. In the embodiment of the present application, the scene reminder information can also be used to remind the driver whether to issue a light signal. For example, the scene reminder information can be "the green light is on and the vehicle ahead is not passing. Should I issue a corresponding light signal?"

[0217] Optionally, methods of outputting scene reminder information include but are not limited to voice broadcast, pop-up reminder, etc.

[0218] When the scene reminder information is output through a pop-up window, a scene reminder interface may be displayed, on which the scene reminder information is displayed.

[0219] In an embodiment of the present application, the scene reminder interface may further include a confirmation button and a cancel button. The confirmation button is used to confirm the subsequent sending of the corresponding light language, and the cancel button is used to cancel the sending of the light language, that is, not sending the corresponding light language.

[0220] For example, Figure 4 This is a schematic diagram of a scene reminder interface, see Figure 4 , Figure 4 The scene reminder interface 401, the confirmation button 402 and the cancel button 403 are included. Figure 4 As shown, scene reminder information is displayed in scene reminder interface 401. When the driver is sure to send a light message, he can click confirmation button 402, and when the driver is sure not to send a light message, he can click cancel button 403.

[0221] Furthermore, when the driver determines to issue a light message, the light message execution instruction may also be input to the first vehicle.

[0222] The light language execution instruction may include the light language to be executed.

[0223] In the embodiment of the present application, the light language execution instruction can be input by voice input. In this way, the problem of reduced driving safety caused by the driver being distracted by the screen operation can be avoided.

[0224] In this case, that is, when the corresponding target light language cannot be matched from the target correspondence, the target light language can be determined by the driver issuing a light language execution instruction.

[0225] (2) In response to a light language execution instruction for scene reminder information, identifying the light language indicated by the light language execution instruction, and determining the light language indicated by the light language execution instruction as a target execution light language.

[0226] When a light language execution instruction is received, the light language indicated by the light language execution instruction can be first identified. Then the identified light language is determined as the target execution light language. In this way, the target execution light language can be determined based on the driver's wishes, so that the determination of the target execution light language is more flexible.

[0227] Optionally, the keywords of the light language indicated by the light language execution instruction can be identified by keyword recognition; the identified keywords are semantically reorganized to generate the target execution light language.

[0228] Keyword recognition is used to identify keywords in light language, such as light type, flashing times, etc. Semantic reorganization is used to reorganize multiple keywords into semantically coherent light language.

[0229] For example, the light language execution instruction may include keywords such as high beam and flash once, and keywords such as high beam and flash once can be identified through keyword recognition. Then, semantic reorganization of keywords such as high beam and flash once can obtain a light language such as high beam flash once, thereby generating a target execution light language.

[0230] In this way, through keyword recognition and semantic reorganization, gaze execution light language can be generated more conveniently, thereby improving the efficiency of determining the target execution light language.

[0231] Step 303: Execute the light language based on the target and control the first vehicle to adjust the light parameters.

[0232] In this case, by executing light language based on the target, the first vehicle is controlled to adjust the headlight parameters so that the corresponding light language can be sent to the second vehicle through the headlights, that is, the driving intention of the driver of the first vehicle can be conveyed to the second vehicle, thereby improving driving safety.

[0233] In an embodiment of the present application, the target execution light language may include the target light type and the target flashing times.

[0234] In this case, the operation of step 303 may be: controlling the light of the target light type of the first vehicle to flash at a target flashing number.

[0235] In the embodiment of the present application, the target light types may include brake lights, high beam lights, hazard warning flashers, etc.

[0236] Then the operation of controlling the light of the target light type of the first vehicle to flash at the target flashing times may include the following three situations.

[0237] In the first case, when the target light type is a brake light, the brake light of the first vehicle is controlled to turn on and off with a target number of flashes.

[0238] In a second case, when the target light type is a high beam, the high beam of the first vehicle is controlled to flash with a target flashing number.

[0239] In a third case, when the target light type is a hazard warning flasher, the hazard warning flasher of the first vehicle is controlled to flash at a target flashing number.

[0240] It should be noted that, in the embodiment of the present application, the target execution light language may also include the target retention time.

[0241] The target retention time is the time the light is kept when it is on, that is, the time each time the light is on. In this case, the operation of step 303 is: controlling the light of the target light type of the first vehicle to flash with the target number of flashes and keeping the target time each time it is on.

[0242] Then the corresponding three situations can be: when the target light type is a brake light, the brake light of the first vehicle is controlled to turn on and off with the target number of flashes, and the brake light is kept for the target duration each time it is on. When the target light type is a high beam, the high beam of the first vehicle is controlled to flash with the target number of flashes, and the high beam is kept for the target duration each time it is on. When the target light type is a hazard warning flasher, the hazard warning flasher of the first vehicle is controlled to flash with the target number of flashes, and the hazard warning flasher is kept for the target duration each time it is on.

[0243] It is worth noting that in some cases, the driver of the vehicle may not be familiar with the meaning of the light language, so even if the second vehicle sends a light language, the driver of the first vehicle may not be able to recognize the corresponding intention. The vehicle control method provided in the embodiment of the present application can transmit the driving intention of the second vehicle, so that the driver of the first vehicle can easily know the driving intention of the second vehicle, and can avoid the problem that the second vehicle sends a light language but the driver of the first vehicle does not notice and misses the corresponding intention, which can improve driving safety.

[0244] In an embodiment of the present application, when the ECU detects that a second vehicle around the first vehicle emits a target light language, it can first determine at least one candidate road scene based on the target light language, that is, first determine the road scene where the first vehicle may be located, and then determine the target road scene from at least one candidate road scene. Since one candidate road scene corresponds to one scene judgment condition, the above operation is to determine the candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle from at least one candidate road scene, that is, to determine the road scene where the first vehicle is currently located. Subsequently, based on the target light language and the target road scene, the first vehicle is controlled to output target reminder information. Since the driving intention represented by the same light language in different road scenes is also different, more accurate reminder information can be output to the driver based on the target light language and the target road scene, thereby conveying a more accurate driving intention to the driver, which can improve driving safety.

[0245] Figure 5 is a schematic diagram of the structure of a vehicle control device provided in an embodiment of the present application. The vehicle control device can be implemented by software, hardware or a combination of both to form part or all of a vehicle, and the vehicle can be as follows Figure 6 Vehicle shown. Figure 5The device includes: a first determining module 501, a second determining module 502 and a first control module 503.

[0246] A first determination module is used to determine at least one candidate road scene based on the target light language when detecting that the second vehicle emits a target light language, the candidate road scene being a road scene corresponding to the target light language, the second vehicle being a vehicle around the first vehicle, and one candidate road scene corresponding to one scene judgment condition;

[0247] A second determination module is used to determine a target road scene from the at least one candidate road scene, and the first vehicle meets a scene judgment condition corresponding to the target road scene;

[0248] The first control module is used to control the first vehicle to output target reminder information based on the target light language and the target road scene.

[0249] Optionally, the device further comprises:

[0250] An acquisition module, used for acquiring light information of a second vehicle;

[0251] A third determination module is used to perform color recognition and shape recognition on the light information of the second vehicle to determine the light type indicated by the light information; perform brightness analysis on the light information of the second vehicle to determine the number of flashes; and determine the target light language based on the light type and the number of flashes;

[0252] Alternatively, the fourth determination module is used to determine the on / off status of the light information of the second vehicle and generate a binary electrical signal; convert the binary electrical signal into a target Morse code; based on the target Morse code, obtain a corresponding light language from a preset correspondence relationship and determine it as the target light language, and the preset correspondence relationship is the correspondence between the Morse code and the light language.

[0253] Optionally, the first determining module is used to:

[0254] Based on the target light language, a corresponding road scene is obtained from a target correspondence relationship and determined as the at least one candidate road scene, where the target correspondence relationship is a correspondence relationship between the light language and the road scene.

[0255] Optionally, the second determining module is used to:

[0256] For any one of the at least one candidate road scene, determining scene judgment information required for the scene judgment condition based on the scene judgment condition corresponding to the candidate road scene;

[0257] determining, based on a target parameter corresponding to the scene judgment information, whether the first vehicle satisfies a scene judgment condition corresponding to the candidate road scene;

[0258] The candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle is determined as the target road scene.

[0259] Optionally, the second determining module is used to:

[0260] In the case where the candidate road scene is the first road scene, the relative motion relationship is determined based on the relative position and relative speed of the first vehicle. If the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the first vehicle is stationary, and the current traffic light state is green, then it is determined that the first vehicle meets the scene judgment condition corresponding to the first road scene, and the first road scene is a scene in which the vehicle in front remains stationary after the green light is on;

[0261] When the candidate road scene is the second road scene, the relative motion relationship is determined based on the relative position and relative speed of the first vehicle. If the relative motion relationship is that the first vehicle follows directly behind the second vehicle and the distance between the two vehicles is less than a preset distance threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the second road scene, and the second road scene is a scene in which the first vehicle and the second vehicle follow each other closely.

[0262] In the case where the candidate road scene is the third road scene, if the relative movement directions of the first vehicle and the second vehicle are opposite, and the light information of the first vehicle is that the high beam is turned on, and the light intensity at the position of the first vehicle is less than or equal to the preset intensity threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the third road scene, and the third road scene is a scene where the high beam is turned on when there is an oncoming vehicle;

[0263] When the candidate road scene is the fourth road scene, if the relative movement direction of the first vehicle and the second vehicle is the same but they are in different lanes, and the steering wheel angle of the first vehicle is greater than a preset angle threshold or the light information of the first vehicle is that the left turn signal is on, it is determined that the first vehicle meets the scene judgment conditions corresponding to the fourth road scene, and the fourth road scene is a scene of vehicle lane change.

[0264] Optionally, the first control module is used for:

[0265] When the target light language is that the high beam flashes at least once and the target road scene is the first road scene, controlling the first vehicle to output a first reminder message, where the first reminder message is used to remind the driver of the first vehicle to pass the traffic light in time;

[0266] When the target light language is that the brake light is on multiple times and the target road scene is the second road scene, controlling the first vehicle to output a second reminder message, the second reminder message is used to remind the driver of the first vehicle to keep a safe distance;

[0267] When the target light language is that the high beam flashes multiple times and the target road scene is the third road scene, controlling the first vehicle to output a third reminder message, the third reminder message is used to remind the driver of the first vehicle to turn off the high beam in time;

[0268] When the target light language is high beam flashing once and the target road scene is the fourth road scene, controlling the first vehicle to output fourth reminder information, the fourth reminder information is used to remind the driver of the first vehicle that the second vehicle is allowed to change lanes;

[0269] When the target light language is that the high beam flashes multiple times and the target road scene is the fourth road scene, the first vehicle is controlled to output a fifth reminder message, and the fifth reminder message is used to remind the driver of the first vehicle that the second vehicle is not allowed to change lanes.

[0270] Optionally, the device further comprises:

[0271] a fifth determination module, configured to determine, when the second vehicle is not detected to emit the target light signal, a reference road scene from a plurality of road scenes, one of the road scenes corresponding to a light signal execution condition, and the first vehicle satisfies the light signal execution condition corresponding to the reference road scene;

[0272] A sixth determination module, configured to determine a target execution light language based on a reference road scene;

[0273] The second control module is used to execute the light language based on the target and control the first vehicle to adjust the light parameters.

[0274] Optionally, the second control module is used for:

[0275] The target light type light of the first vehicle is controlled to flash at a target flashing number of times.

[0276] In an embodiment of the present application, when a second vehicle around a first vehicle is detected to emit a target light language, at least one candidate road scene can be determined based on the target light language, that is, the road scene where the first vehicle may be located is first determined, and then the target road scene is determined from at least one candidate road scene. Since one candidate road scene corresponds to one scene judgment condition, the above operation is to determine the candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle from at least one candidate road scene, that is, to determine the road scene where the first vehicle is currently located. Subsequently, based on the target light language and the target road scene, the first vehicle is controlled to output target reminder information. Since the driving intention represented by the same light language in different road scenes is also different, more accurate reminder information can be output to the driver based on the target light language and the target road scene, thereby conveying a more accurate driving intention to the driver, which can improve driving safety.

[0277] It should be noted that: when the vehicle control device provided in the above embodiment controls the vehicle to output corresponding reminder information, it only uses the division of the above-mentioned functional modules as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0278] The vehicle control device and vehicle control method embodiments provided in the above embodiments belong to the same concept. The specific working process of the units and modules in the above embodiments and the technical effects brought about can be found in the method embodiment part and will not be repeated here.

[0279] Figure 6 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application.

[0280] For example, Figure 6 As shown, the vehicle 600 includes: a memory 61 and a processor 60, wherein the memory 61 stores an executable program code 62, and the processor 60 is used to call and execute the executable program code 62 to perform the above-mentioned vehicle control method.

[0281] In this embodiment, the functional modules of the vehicle can be divided according to the above method example. For example, each functional module can be corresponded, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0282] In the case of dividing each functional module according to each function, the vehicle may include: a first determination module, a second determination module and a first control module. It should be noted that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here.

[0283] The vehicle provided in this embodiment is used to execute the above-mentioned vehicle control method, and thus can achieve the same effect as the above-mentioned implementation method.

[0284] In the case of an integrated unit, the vehicle may include a processing module and a storage module. The processing module may be used to control and manage the actions of the vehicle. The storage module may be used to support the vehicle in executing corresponding program codes and data.

[0285] The processing module may be a processor or a controller, which may implement or execute various exemplary logic blocks, modules and circuits shown in conjunction with the disclosure of the present application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module may be a memory.

[0286] This embodiment also provides a computer-readable storage medium, in which a computer program code is stored. When the computer program code is run on a computer, the computer executes the above-mentioned related method steps to implement the above-mentioned vehicle control method in the above-mentioned embodiment.

[0287] This embodiment also provides a computer program product. When the computer program product is run on a computer, the computer is enabled to execute the above-mentioned related steps to implement the above-mentioned vehicle control method in the above-mentioned embodiment.

[0288] Among them, the vehicle, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the method provided above and will not be repeated here.

[0289] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0290] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0291] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A vehicle control method, characterized in that: The method is applied to a first vehicle, and the method comprises: In the case where a second vehicle is detected to emit a target light signal, at least one candidate road scene is determined based on the target light signal, the candidate road scene being a road scene corresponding to the target light signal, the second vehicle being a vehicle around the first vehicle, and one candidate road scene corresponding to one scene judgment condition; Determining a target road scene from the at least one candidate road scene, the first vehicle meeting a scene judgment condition corresponding to the target road scene; Based on the target light language and the target road scene, the first vehicle is controlled to output target reminder information.

2. The method according to claim 1, characterized in that Before determining at least one candidate road scene based on the target light signal emitted by the second vehicle upon detecting the second vehicle detecting the target light signal, the method further includes: Acquiring light information of the second vehicle; Performing color recognition and shape recognition on the light information of the second vehicle to determine the light type indicated by the light information; performing brightness analysis on the light information of the second vehicle to determine the number of flashes; and determining the target light language based on the light type and the number of flashes; Alternatively, the light information of the second vehicle is judged to be on and off to generate a binary electrical signal; the binary electrical signal is converted into a target Morse code; based on the target Morse code, a corresponding light language is obtained from a preset correspondence relationship to be determined as the target light language, and the preset correspondence relationship is the correspondence between the Morse code and the light language.

3. The method according to claim 1, characterized in that The determining at least one candidate road scene based on the target light language includes: Based on the target light language, a corresponding road scene is obtained from a target correspondence relationship and determined as the at least one candidate road scene, wherein the target correspondence relationship is a correspondence relationship between the light language and the road scene.

4. The method according to claim 1, characterized in that The determining the target road scene from the at least one candidate road scene comprises: For any one of the at least one candidate road scene, determining scene judgment information required for the scene judgment condition based on the scene judgment condition corresponding to the candidate road scene; determining, based on a target parameter corresponding to the scene judgment information, whether the first vehicle satisfies a scene judgment condition corresponding to the candidate road scene; The candidate road scene corresponding to the scene judgment condition satisfied by the first vehicle is determined as the target road scene.

5. The method according to claim 4, characterized in that The determining, based on the target parameter corresponding to the scene judgment information, whether the first vehicle satisfies the scene judgment condition corresponding to the candidate road scene includes: In the case where the candidate road scene is the first road scene, a relative motion relationship is determined based on the relative position and relative speed of the first vehicle, and if the relative motion relationship is that the second vehicle follows directly behind the first vehicle and the first vehicle is stationary, and the current traffic light state is green, then it is determined that the first vehicle meets the scene judgment condition corresponding to the first road scene, and the first road scene is a scene in which the vehicle in front remains stationary after the green light is on; In the case where the candidate road scene is the second road scene, a relative motion relationship is determined based on the relative position and relative speed of the first vehicle, and if the relative motion relationship is that the first vehicle follows directly behind the second vehicle and the distance between the two vehicles is less than a preset distance threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the second road scene, and the second road scene is a scene in which the first vehicle and the second vehicle follow each other at a close distance; In the case where the candidate road scene is the third road scene, if the relative movement directions of the first vehicle and the second vehicle are opposite, and the light information of the first vehicle is that the high beam is turned on, and the light intensity at the position of the first vehicle is less than or equal to a preset intensity threshold, it is determined that the first vehicle meets the scene judgment condition corresponding to the third road scene, and the third road scene is a scene where the high beam is turned on when there is an oncoming vehicle; When the candidate road scene is the fourth road scene, if the relative movement direction of the first vehicle and the second vehicle is the same but they are in different lanes, and the steering wheel angle of the first vehicle is greater than a preset angle threshold or the light information of the first vehicle is that the left turn signal is on, it is determined that the first vehicle meets the scene judgment condition corresponding to the fourth road scene, and the fourth road scene is a scene of vehicle changing lanes.

6. The method according to claim 1, characterized in that The controlling the first vehicle to output target reminder information based on the target road scene and the target light language includes: When the target light language is high beam flashing at least once and the target road scene is a first road scene, controlling the first vehicle to output a first reminder message, wherein the first reminder message is used to remind the driver of the first vehicle to pass the traffic light in time; When the target light language is that the brake light is on multiple times and the target road scene is the second road scene, controlling the first vehicle to output a second reminder message, where the second reminder message is used to remind the driver of the first vehicle to keep a safe distance; When the target light language is high beam flashing multiple times and the target road scene is a third road scene, controlling the first vehicle to output a third reminder message, the third reminder message is used to remind the driver of the first vehicle to turn off the high beam in time; When the target light language is high beam flashing once and the target road scene is a fourth road scene, controlling the first vehicle to output fourth reminder information, the fourth reminder information being used to remind the driver of the first vehicle that the second vehicle is allowed to change lanes; When the target light language is high beam flashing multiple times and the target road scene is the fourth road scene, the first vehicle is controlled to output fifth reminder information, and the fifth reminder information is used to remind the driver of the first vehicle that the second vehicle is not allowed to change lanes.

7. The method according to claim 1, characterized in that The method further comprises: In the case where the second vehicle is not detected to emit the target light signal, determining a reference road scene from a plurality of road scenes, one of the road scenes corresponds to one light signal execution condition, and the first vehicle satisfies the light signal execution condition corresponding to the reference road scene; Based on the reference road scene, determining a target execution light language; The light language is executed based on the target to control the first vehicle to adjust the light parameters.

8. The method according to claim 7, characterized in that The target execution light language includes a target light type and a target flashing number, and the controlling the first vehicle to adjust the light parameters based on the target execution light language includes: The target light type light of the first vehicle is controlled to flash at the target flashing number.

9. A vehicle control device, characterized in that: The device comprises: A first determination module is used to determine at least one candidate road scene based on the target light language when a second vehicle is detected to emit a target light language, wherein the candidate road scene is a road scene corresponding to the target light language, the second vehicle is a vehicle around the first vehicle, and one candidate road scene corresponds to one scene judgment condition; A second determination module is used to determine a target road scene from the at least one candidate road scene, and the first vehicle meets a scene judgment condition corresponding to the target road scene; The first control module is used to control the first vehicle to output target reminder information based on the target light language and the target road scene.

10. A vehicle, characterized in that: The vehicle comprises: A memory for storing executable program codes; A processor, configured to call and run the executable program code from the memory so that the vehicle executes the method according to any one of claims 1 to 8.

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