A driving authorization control method, apparatus, device and medium

Abstract

The application discloses a driving authorization control method, device, equipment and medium, comprising: generating a gesture instruction when it is monitored that a user has a driving intention for a target vehicle, the gesture instruction comprising a target gesture that needs to be performed by the user; collecting a target image set of the user; determining at least one of an actual duration for which the user responds to the gesture instruction, an actual tremor frequency of a hand of the user, and a similarity degree between an actual gesture of the user and the target gesture according to the target image set; and determining whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency, and the similarity degree. The application can test at least one of a reaction ability, a hand stability, and an attention of the user, determine whether the user has a possibility of drunk driving, and authorize the user to drive only when it is determined that the user does not have the possibility of drunk driving, so that the probability of drunk driving is reduced, and driving safety is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, and in particular to a driving authorization control method, device, equipment and medium. BACKGROUND

[0002] Automobiles are becoming more and more popular, greatly facilitating people's life, and the safety of automobile driving is becoming more and more important. Among them, drunk driving is a driving behavior with extremely high harm.

[0003] Generally, the probability of drunk driving is reduced through self-management of the driver or supervision and reminder of the passenger, but the effect of these methods is not ideal. Therefore, how to reduce the probability of drunk driving is a problem to be solved at present. SUMMARY

[0004] The embodiments of the present application provide a driving authorization control method, device, equipment and medium, solve the technical problem that the probability of drunk driving cannot be effectively reduced in the prior art, and achieve the technical effect of reducing the probability of drunk driving.

[0005] In a first aspect, the present application provides a driving authorization control method, which comprises:

[0006] Generating a gesture instruction when it is monitored that the user has a driving intention for the target vehicle, the gesture instruction comprising a target gesture that needs to be performed by the user;

[0007] Collecting a target image set of the user;

[0008] Determining at least one of an actual duration for which the user responds to the gesture instruction, an actual tremor frequency of the user's hand, and a similarity degree between the actual gesture of the user and the target gesture from the target image set;

[0009] Determining whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency and the similarity degree.

[0010] Further, determining whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency and the similarity degree comprises:

[0011] When the actual duration is greater than a preset duration, or when the actual tremor frequency is greater than a preset tremor frequency, or when the similarity degree is less than a preset similarity threshold, the user is prohibited from being authorized to drive.

[0012] Further, determining the actual tremor frequency of the user's hand from the target image set comprises:

[0013] Determining the actual tremor frequency of a target point on the user's hand from the target image set.

[0014] Further, the target gesture comprises at least one of a static gesture and a dynamic gesture.

[0015] Further, the similarity degree between the actual gesture of the user and the target gesture is determined according to the target image set, comprising:

[0016] a similarity degree between an actual dynamic path of the user forming the actual gesture and a preset dynamic path of the target gesture is determined; and / or,

[0017] a similarity degree between an actual static form of the actual gesture of the user and a preset static form of the target gesture is determined.

[0018] Further, the driving authorization is determined according to the actual time length, the actual tremor frequency and the similarity degree, comprising:

[0019] a response decision value is determined according to the actual time length and the preset time length;

[0020] a stability decision value is determined according to the actual tremor frequency and the preset tremor frequency;

[0021] a similarity decision value is determined according to the similarity degree and a preset similarity threshold value;

[0022] a drunk driving decision value of the user is determined according to the response decision value and a corresponding response weight, the stability decision value and a corresponding stability weight, and the similarity decision value and a corresponding similarity weight;

[0023] the driving authorization is determined according to the drunk driving decision value and a preset decision value.

[0024] Further, the gesture instruction is generated when it is monitored that the user has a driving intention for the target vehicle, comprising:

[0025] when it is monitored that the driving seat of the target vehicle is occupied by the user, the safety belt of the driving seat is buckled up and the target vehicle receives an ignition signal, it is determined that the user has a driving intention for the target vehicle and the gesture instruction is generated.

[0026] In a second aspect, the present application provides a driving authorization control device, the device comprising:

[0027] an instruction generation module, configured to generate a gesture instruction when it is monitored that the user has a driving intention for a target vehicle, the gesture instruction comprising a target gesture required to be performed by the user;

[0028] an image acquisition module, configured to acquire a target image set of the user;

[0029] a parameter determination module, configured to determine at least one of an actual time length of the user responding to the gesture instruction, an actual tremor frequency of the hand of the user, and a similarity degree between the actual gesture of the user and the target gesture according to the target image set.

[0030] The authorization judgment module is configured to determine whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency, and the similarity degree.

[0031] Further, the authorization judgment module is configured to:

[0032] When the actual duration is greater than the preset duration, or when the actual tremor frequency is greater than the preset tremor frequency, or when the similarity degree is less than the preset similarity threshold, the user is prohibited from being authorized to drive.

[0033] Further, the stability determination module is configured to:

[0034] Determine the actual tremor frequency of the target point on the user's hand according to the target image set.

[0035] Further, the similarity degree determination module is configured to:

[0036] Determine the similarity degree between the actual dynamic path of the actual gesture formed by the user and the preset dynamic path of the target gesture; and / or,

[0037] Determine the similarity degree between the actual static form of the actual gesture of the user and the preset static form of the target gesture.

[0038] Further, the target gesture includes at least one of a static gesture and a dynamic gesture.

[0039] Further, the authorization judgment module is configured to:

[0040] Determine a response determination value according to the actual duration and the preset duration;

[0041] Determine a stability determination value according to the actual tremor frequency and the preset tremor frequency;

[0042] Determine a similarity determination value according to the similarity degree and the preset similarity threshold;

[0043] Determine a drunk driving determination value of the user according to the response determination value and the corresponding response weight, the stability determination value and the corresponding stability weight, and the similarity determination value and the corresponding similarity weight;

[0044] Determine whether to authorize the user to drive according to the drunk driving determination value and the preset determination value.

[0045] Further, the instruction generation module includes:

[0046] The monitoring submodule is configured to monitor whether the user is seated in the driving seat of the target vehicle, whether the safety belt of the driving seat is buckled, and whether the target vehicle receives an ignition signal;

[0047] The generating sub-module is configured to determine that the user has a driving intention for the target vehicle and generate a gesture instruction when it is monitored that the user is in the driving seat of the target vehicle, the safety belt of the driving seat is buckled, and the target vehicle receives an ignition signal.

[0048] In a third aspect, the present application provides an electronic device, comprising:

[0049] a processor;

[0050] a memory for storing processor-executable instructions;

[0051] The processor is configured to execute to implement the driving authorization control method as described above.

[0052] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the driving authorization control method as described above.

[0053] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0054] After it is monitored that the user has a driving intention for the target vehicle, the embodiment generates a gesture instruction to remind the user to perform a corresponding target gesture, collects images of the user, and determines whether the user has a possibility of drunk driving according to at least one of the response speed of the user to the gesture instruction, the stability of the hand of the user, and the similarity between the actual gesture of the user and the target gesture, and then determines whether to authorize the user to drive. It can be seen that the embodiment can collect images of the user's gesture and then determine whether the user has drunk driving, which can test at least one of the reaction ability, hand stability, and attention of the user, determine whether the user has drunk driving, and authorize the user to drive only when it is determined that the user does not have drunk driving, thereby reducing the probability of drunk driving and improving driving safety. On the other hand, the face information can be collected through image collection to avoid the driving seat from avoiding drunk driving monitoring of the driving seat through cheating behavior. Compared with the self-management of the driver or the supervision and reminding of the passenger, the image gesture monitoring method provided by the embodiment is more objective and has more constraints on the user, which can further reduce the probability of drunk driving and improve driving safety. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0056] Figure 1 A flowchart of a driving authorization control method provided for the present application is shown in the figure;

[0057] Figure 2 A structural diagram of a driving authorization control device provided for the present application is shown in the figure;

[0058] Figure 3 A structural diagram of an electronic device provided for the present application is shown in the figure. DETAILED DESCRIPTION

[0059] The embodiment of the present application provides a driving authorization control method, and solves the technical problem that the occurrence probability of drunk driving cannot be effectively reduced in the prior art.

[0060] The technical scheme of the embodiment of the present application is to solve the above technical problem, and the general idea is as follows:

[0061] A driving authorization control method, the method comprising: generating a gesture instruction when it is monitored that a user has a driving intention for a target vehicle, the gesture instruction comprising a target gesture that needs to be performed by the user; collecting a target image set of the user; determining at least one of an actual duration for which the user responds to the gesture instruction, an actual tremor frequency of a hand of the user, and a similarity degree between an actual gesture of the user and the target gesture according to the target image set; and determining whether to perform driving authorization on the user according to at least one of the actual duration, the actual tremor frequency and the similarity degree.

[0062] After it is monitored that the user has the driving intention for the target vehicle, the embodiment generates the gesture instruction to remind the user to perform the corresponding target gesture, collects the image of the user, determines whether the user has the possibility of drunk driving according to at least one of the response speed of the user to the gesture instruction, the stability of the hand of the user and the similarity degree between the actual gesture of the user and the target gesture, and then determines whether to perform driving authorization on the user. It can be seen that the embodiment can collect the image of the gesture of the user and then determine whether the user is drunk driving, on the one hand, the reaction ability, the hand stability and the attention of the user can be tested to determine whether the user has the possibility of drunk driving, and the driving authorization is performed on the user only when it is determined that the user does not have the possibility of drunk driving, so that the occurrence probability of drunk driving is reduced and the driving safety is improved. On the other hand, the face information can be collected through the image collection, so that the drunk driving monitoring of the driving position can be avoided through the cheating behavior of the driving position. Compared with the self-management of the driver or the supervision and reminding of the passenger, the image gesture monitoring manner provided by the embodiment is more objective and has more constraint on the user, so that the occurrence probability of drunk driving can be further reduced and the driving safety can be improved.

[0063] For better understanding of the above technical solutions, the above technical solutions will be described in detail below in combination with the drawings in the specification and specific embodiments.

[0064] Firstly, the term "and / or" appearing in the present document is only to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present document generally represents an "or" relationship between the front and rear associated objects.

[0065] The embodiment provides a driving authorization control method as shown in the figure. Figure 1 The method comprises steps S11-S14.

[0066] Step S11, generating a gesture instruction when it is monitored that the user has a driving intention for the target vehicle, the gesture instruction comprising a target gesture that needs to be performed by the user;

[0067] Step S12, collecting a target image set of the user;

[0068] Step S13, determining at least one of an actual duration for the user to respond to the gesture instruction, an actual tremor frequency of a hand of the user, and a similarity degree between an actual gesture of the user and the target gesture according to the target image set;

[0069] Step S14, determining whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency, and the similarity degree.

[0070] The driving authorization control method provided by the embodiment can be executed by the on-board controller of the target vehicle, or by the cloud server. When executed by the cloud server, a communication connection needs to be established between the cloud server and the target vehicle. The embodiment will be described hereinafter only by taking the on-board controller of the target vehicle as an example to execute the aforementioned driving authorization control method.

[0071] The target vehicle involved in the embodiment needs to be configured with a camera, which can be an infrared camera. The camera can collect images of the area where the driving seat of the target vehicle is located. The embodiment can be applied to most types of vehicles. For vehicles without a camera inside, a camera can also be added to achieve the same effect. It can be seen that the embodiment is simple to use, low in cost, and easy to install.

[0072] Regarding step S11, the gesture instruction is generated when it is monitored that the user has a driving intention for the target vehicle, and the gesture instruction comprises a target gesture that needs to be performed by the user.

[0073] The specific way of monitoring whether the user has a driving intention for the target vehicle is as follows:

[0074] The driving seat of the target vehicle is monitored to determine whether a user is present, whether the safety belt of the driving seat is buckled, and whether the target vehicle receives an ignition signal. When the driving seat has a user, the safety belt of the driving seat is buckled, and the target vehicle receives the ignition signal, it is determined that the user has a driving intention for the target vehicle.

[0075] It can be seen that monitoring whether the user has a driving intention for the target vehicle is actually to determine whether the target vehicle meets the following three conditions:

[0076] [Condition 1] The driving seat of the target vehicle is monitored to determine whether a user is present.

[0077] The driving seat of the target vehicle is monitored to determine whether a user is present, which can be determined by the signal change of the weight sensor or pressure sensor of the driving seat. For example, when the weight sensor detects that the weight of the driving seat exceeds a preset weight threshold, it can be determined that a user is present in the driving seat. In addition, the camera inside the target vehicle can also be used to collect images, and image recognition can be used to determine whether a user is present in the driving seat.

[0078] [Condition 2] The driving seat is monitored to determine whether the safety belt is buckled.

[0079] The driving seat is monitored to determine whether the safety belt is buckled, which can be determined by the safety belt buckle signal of the driving seat. This can be referred to related technology, and this embodiment will not be repeated.

[0080] [Condition 3] The target vehicle is monitored to determine whether it has received an ignition signal.

[0081] The vehicle controller can monitor whether the target vehicle receives an ignition signal. The ignition signal can be generated by the user turning the key of the target vehicle, or by the user touching the one-key start button, or by the user through voice control. The specific ignition method of the target vehicle can be determined, and this embodiment does not limit it.

[0082] When it is determined that the target vehicle meets the three conditions at the same time, it can be determined that the user has a driving intention for the target vehicle, and at this time the possibility of drunk driving of the user needs to be determined. Specifically, a gesture instruction is generated to prompt the user to perform a corresponding target gesture, and whether there is a possibility of drunk driving is determined according to the process of the user performing the target gesture.

[0083] The target gesture in the gesture instruction includes at least one of a static gesture and a dynamic gesture. The dynamic gesture refers to a gesture that is drawn by changing the hand action, such as a gesture of writing a "mouth" character in the air with fingers, and a gesture of changing the number of stretched fingers by stretching and contracting the fingers to express 1, 2, 3, 4, and 5. The static gesture refers to a gesture that is drawn by keeping the hand relatively still, such as extending two fingers and keeping still, and keeping the OK gesture and keeping still.

[0084] The target gesture in the gesture instruction can be randomly selected or sequentially selected from a pre-stored gesture library in the storage device of the target vehicle. The number of gestures included in the pre-stored gesture library can be greater than 5. The number of target gestures included in each gesture instruction can be at least 1.

[0085] The gesture instruction can be presented to the user by at least one of a display screen, a mobile terminal, and a voice prompt. For example, the gesture instruction can be presented to the user through the display screen of the target vehicle or the mobile terminal of the user, and the presentation content can be a picture, a video, or a combination of a picture and a video; the gesture instruction can be conveyed to the user through the car-mounted loudspeaker of the target vehicle.

[0086] Regarding step S12, a target image set of the user is collected.

[0087] At the same time or after step S11 is performed, that is, at the same time or after the gesture instruction is generated for the user, an image of the user is collected by the camera of the target vehicle to obtain a target image set. The target image set can be a picture set taken at a preset frequency, or can be a video, which is not limited in the embodiment.

[0088] The face of the user can be imaged by the camera, and the identity information of the current user is recognized through the face image to determine whether the current user is a legal user of the target vehicle, which can prevent illegal personnel from stealing the target vehicle to a certain extent. If the current user is a legal user, the historical record of the current user using the target vehicle can be queried to determine whether the current user has a history of drunk driving, which can provide a judgment tendency for subsequent determination of whether the user has a possibility of drunk driving this time, and can also adjust the difficulty of subsequent drunk driving judgment according to whether there is a history of drunk driving, for example, using a more accurate judgment method for judgment if there is a history of drunk driving, or increasing the difficulty of the target gesture to increase the constraint of the user's self-conscious avoidance of drunk driving behavior. In addition, the face of the driver's seat is imaged by the camera, which can also avoid the replacement of the user on the driver's seat by other people on the non-driver's seat for drunk driving judgment, effectively reducing the probability of cheating behavior.

[0089] The target image set of the user is mainly collected by collecting the hand image of the user. When the camera cannot collect the hand image of the user, at least one of the display screen, the mobile terminal and the voice prompt is used to remind the user to move the hand position, so that the camera can collect the hand image of the user. When the reminding times exceed the preset times (such as 2 times) or after the reminding for the preset time, the image collected by the camera still does not have the hand image of the user, which means that the attention of the user is distracted, and it may be drunk driving. In order to improve the driving safety, the driving authorization to the user can be prohibited, that is, the target vehicle is prohibited from responding to the driving operation of the user, and the probability of safety accidents is reduced.

[0090] After the target image set of the user is collected, step S13 is continued.

[0091] Regarding step S13, at least one of the actual time length of the user responding to the gesture instruction, the actual tremor frequency of the hand of the user in the target image set, and the similarity between the actual gesture of the user and the target gesture in the target image set is determined according to the target image set.

[0092] Step S13 can be divided into three parts, which will be described first.

[0093]

First part

[0094] The actual time length of the user responding to the gesture instruction is determined according to the target image set, that is, the reaction time of the user to start gesturing the target gesture with the hand after hearing or seeing the gesture instruction is determined according to the target image set. The longer the reaction time is, the more distracted the attention of the user is, and the higher the possibility of drunk driving is. The shorter the reaction time is, the more concentrated the attention of the user is, and the lower the possibility of drunk driving is.

[0095] The reaction time of different drivers under the condition of non-drinking driving can be counted and analyzed to determine the corresponding preset time length. The actual time length is compared with the preset time length (for example, 5 seconds) to measure whether the current user of the target vehicle has the situation of attention distraction.

[0096] When the actual time length is greater than the preset time length, it means that the attention of the user is relatively distracted, and it may be drunk driving. In order to ensure the safety of driving, the driving authorization to the user can be prohibited. When the actual time length is less than the preset time length, it means that the attention of the user is relatively concentrated, and the possibility of drunk driving is low.

[0097]

Second part

[0098] The user is stimulated by alcohol after drinking, and the hand is more likely to tremble, so the stability of the user's hand can be analyzed through the target image set to determine whether the user has the possibility of drunk driving. Specifically, the actual tremor frequency of the target point on the user's hand can be determined according to the target image set, and the actual tremor frequency of the target point on the hand is taken as the actual tremor frequency of the hand.

[0099] Wherein, the target point can be any point on the user's hand, and in general, in order to facilitate point identification, a relatively special point on the user's hand can be selected, such as a point at a finger joint, a point at the edge of the hand, or a point at a finger tip. The actual tremor frequency of the target point on the user's hand can be determined according to the target image set, and the actual tremor frequency of the target point on the hand is taken as the actual tremor frequency of the hand.

[0100] The preset tremor frequency can be determined according to the tremor frequency of different drivers in the non-drinking state. When the actual tremor frequency is greater than the preset tremor frequency, it means that the user's hand tremor frequency is high and the hand stability is poor, which has a high possibility of drunk driving. In order to ensure driving safety, the user can be prohibited from driving authorization. When the actual tremor frequency is less than the preset tremor frequency, it means that the user's hand tremor frequency is normal and the hand stability is good, which has a low possibility of drunk driving.

[0101]

Third part

[0102] Determining the similarity is to determine whether the actual gesture of the user responding to the gesture instruction is similar to the target gesture, which specifically compares the actual gesture of the user in the target image set with the target gesture.

[0103] When the target gesture is a dynamic gesture, the similarity between the actual dynamic path of the actual gesture formed by the user and the preset dynamic path of the target gesture can be determined, and the similarity between the actual dynamic path and the preset dynamic path is taken as the similarity between the actual gesture of the user and the target gesture.

[0104] When the target gesture is a static gesture, the similarity between the actual static form of the actual gesture of the user and the preset static form of the target gesture can be determined, and the similarity between the actual static form and the preset static form is taken as the similarity between the actual gesture and the target gesture.

[0105] A similar preset threshold can be set, and the similarity degree is compared with the similar preset threshold (for example, 90%). When the similarity degree is less than the similar preset threshold, it means that the actual gesture of the user is not standard, and the possibility of drunk driving is greater. In order to ensure driving safety, the user can be prohibited from being authorized to drive. When the similarity degree is greater than the similar preset threshold, it means that the actual gesture of the user is relatively standard, and the possibility of drunk driving is smaller.

[0106] As to step S14, whether to authorize the user to drive is determined according to at least one of the actual duration, the actual tremor frequency and the similarity degree.

[0107] According to at least one part of the actual duration, the actual tremor frequency and the similarity degree corresponding to the three parts respectively, whether the user has the possibility of drunk driving can be judged. In actual operation, any one part can be selected for implementation, and the accuracy is relatively low. Any two parts can be selected for implementation, and the accuracy will be improved. Of course, the three parts can be implemented together, and the accuracy will be further improved. The accuracy requirement can be selected according to the accuracy requirement.

[0108] It can be seen that the embodiment can judge the possibility of drunk driving of the user from three aspects of response speed, hand stability and gesture similarity degree respectively. When the three parts are implemented together, step S141-step S145 can be used for comprehensive evaluation.

[0109] Step S141, determining a response determination value according to the actual duration and the preset duration;

[0110] Step S142, determining a stability determination value according to the actual tremor frequency and the preset tremor frequency;

[0111] Step S143, determining a similarity determination value according to the similarity degree and the similar preset threshold;

[0112] Step S144, determining a drunk driving determination value of the user according to the response determination value and the corresponding response weight, the stability determination value and the corresponding stability weight, and the similarity determination value and the corresponding similarity weight;

[0113] Step S145, determining whether to authorize the user to drive according to the drunk driving determination value and the preset determination value.

[0114] The response determination value can be the ratio of the preset duration to the actual duration, or other values related to the ratio. When the actual duration is longer, the response determination value is smaller, which means that the response speed of the user is slower. Conversely, when the actual duration is shorter, the response determination value is larger, which means that the response speed of the user is faster.

[0115] Similarly, the stability determination value can be a ratio of the preset tremor frequency and the actual tremor frequency, or can also be other values related to the ratio. When the actual tremor frequency is greater, the stability determination value is smaller, meaning that the user's hand stability is lower; on the contrary, when the actual tremor frequency is smaller, the stability determination value is greater, meaning that the user's hand stability is higher.

[0116] In addition, the similarity determination value can be a ratio of the similarity degree and the similar preset threshold, or can also be other values related to the ratio. When the similarity degree is smaller, the similarity determination value is smaller, meaning that the actual gesture made by the user is relatively non-standard; on the contrary, when the similarity degree is greater, the similarity determination value is greater, meaning that the actual gesture made by the user is relatively standard.

[0117] According to the foregoing, the response determination value, the stability determination value, and the similarity determination value are determined, and then combined with the respective corresponding weights, the drunk driving determination value of the user this time can be obtained. The respective weights of the response determination value, the stability determination value, and the similarity determination value can be set according to the actual situation. In this embodiment, the response determination value corresponds to the response weight, the stability determination value corresponds to the stability weight, and the similarity determination value corresponds to the similarity weight. The response determination value is denoted as K1, the stability determination value is denoted as K2, the similarity determination value is denoted as K3, the response weight is denoted as α, the stability weight is denoted as β, and the similarity weight is denoted as θ, and then the drunk driving determination value X can be calculated through the following formula 1. The values of α, β, and θ are all less than 1, and the sum of α, β, and θ is 1, for example, α takes 0.2, β takes 0.5, and θ takes 0.3.

[0118] X = α * k1 + β * k2 + θ * k3 Formula 1

[0119] The greater the drunk driving determination value X, the smaller the possibility of the user's this time drunk driving, and the smaller the drunk driving determination value X, the greater the possibility of the user's this time drunk driving. A preset determination value can be determined based on big data statistics. When the drunk driving determination value does not exceed the preset determination value, it is determined that the user has the possibility of drunk driving, and then the driving authorization to the user is prohibited. When the drunk driving determination value exceeds this preset determination value, it can be determined that the user does not have drunk driving, and then the driving authorization to the user can be performed, at this time the target vehicle can continue to respond to the user's ignition operation and other driving operations to realize the driving right takeover of the target vehicle.

[0120] Of course, when any two parts are implemented together, similar principles such as steps S141 to S145 can also be used for implementation, which will not be described in detail in this embodiment.

[0121] After the execution of step S14, or during the execution of steps S11-S14, the gesture instruction corresponding to this time, the target image set, and whether to authorize the user to drive, and the like can be transmitted to the cloud server for storage, so as to facilitate data analysis of the driving behavior of the user through big data analysis in the future, and improve the judgment accuracy of drunk driving of each different user.

[0122] To sum up, after the driving intention of the user to the target vehicle is monitored in the embodiment, a gesture instruction is generated to remind the user to perform the corresponding target gesture, the user is image collected, and at least one of the response speed of the user to the gesture instruction, the stability of the hand of the user, and the similarity between the actual gesture of the user and the target gesture is determined to determine whether the user has the possibility of drunk driving, and then whether to authorize the user to drive. It can be seen that the embodiment can determine whether the user has the possibility of drunk driving by image collecting the gesture of the user and then judging drunk driving, on the one hand, at least one of the reaction ability, hand stability, and attention of the user can be tested to determine whether the user has the possibility of drunk driving, and the driving authorization is given to the user only when it is determined that there is no drunk driving, thereby reducing the probability of drunk driving and improving driving safety. On the other hand, the face information can be collected through image collection to avoid the driving seat from evading the drunk driving monitoring of the driving seat through cheating behavior. Compared with the self-management of the driver or the supervision and reminding of the passenger, the image gesture monitoring method provided by the embodiment is more objective and has more constraints on the user, so as to further reduce the probability of drunk driving and improve the driving safety.

[0123] In actual operation, the steps S11-S14 can be deformed, and the judgment and recognition process can be divided into two stages according to the dynamic gesture and the static gesture. The first stage is the dynamic gesture, corresponding to steps S21-S24, and the second stage is the static gesture, corresponding to steps S31-S34.

[0124] Step S21, when it is monitored that the user has the driving intention to the target vehicle, a first gesture instruction is generated, and the first gesture instruction includes a target dynamic gesture that needs to be performed by the user;

[0125] Step S22, a first target image set of the user is collected;

[0126] Step S23, at least one of a first actual time length of the user responding to the gesture instruction, a first actual tremor frequency of the hand of the user, and a first similarity between the first actual gesture of the user and the target dynamic gesture is determined according to the first target image set;

[0127] Step S24, whether to authorize the user to drive is determined according to at least one of the first actual time length, the first actual tremor frequency, and the first similarity.

[0128] That is, steps S21-S24 are for determining the possibility of drunk driving according to the dynamic gesture, when it is determined that the possibility of drunk driving is low according to the dynamic gesture, the driving authorization can be given to the user, so that the target vehicle can respond to the driving operation of the user.

[0129] When it is determined that the possibility of drunk driving is high according to the dynamic gesture, the driving authorization can be prohibited to the user, and the second stage is continued, that is, the possibility of drunk driving of the user is further determined according to the static gesture, and steps S31-S34 are executed.

[0130] Step S31, after it is determined that the driving authorization is prohibited to the user according to the dynamic gesture, a second gesture instruction is generated, the second gesture instruction includes a target static gesture that needs to be executed by the user;

[0131] Step S32, a second target image set of the user is collected;

[0132] Step S33, at least one of the second actual duration of the user responding to the gesture instruction, the second actual tremor frequency of the hand of the user, and the second similarity between the second actual gesture of the user and the target static gesture is determined according to the second target image set;

[0133] Step S34, whether to give the driving authorization to the user is determined according to at least one of the second actual duration, the second actual tremor frequency and the second similarity.

[0134] Steps S21-S24 and steps S31-S34 are similar to the principles of steps S11-S14, and the specific process can be referred to the related content of steps S11-S14. It should be noted that the accuracy of the drunk driving recognition determination of the dynamic gesture is lower than that of the static gesture, when the possibility of drunk driving of the user is high through the dynamic gesture recognition, the possibility of drunk driving of the user can be further determined through the static gesture, which can reduce the probability of misjudgment of drunk driving to a certain extent.

[0135] Of course, in actual operation, the static gesture recognition can be performed first, and then the dynamic gesture recognition is performed, only the static gesture recognition process and the dynamic gesture recognition process need to be adaptively adjusted, and the embodiment will not be repeated here.

[0136] Further, after it is determined that the driving authorization is given to the user, the user can normally drive the target vehicle, but the user may drink during driving. In order to reduce the probability of drunk driving of the user during driving, steps S41-S44 are further provided to monitor the behavior of the user during driving.

[0137] Step S41, monitoring whether the user has a diet action;

[0138] Step S42, after determining that the user has a diet action, generating a retest instruction, the retest instruction including a retest gesture that needs to be performed by the user;

[0139] Step S43, collecting a retest image set of the user;

[0140] Step S44, determining whether the target vehicle continues to respond to the driving operation of the user according to the retest image set.

[0141] Monitoring whether the user has a diet action can be achieved by image acquisition of the user through a camera, analyzing and determining the images of the user in the driving process to determine whether the user has a drinking or eating action.

[0142] When it is monitored that the user has a diet action, a retest instruction is generated, and the retest instruction is displayed to the user through at least one of a display screen, a mobile terminal and voice prompting. The retest instruction is used to remind the user to perform the corresponding retest gesture. In actual operation, performing the retest gesture by the user during driving increases the driving risk and poses a safety hazard. In order to reduce the safety hazard, the retest instruction can also include reminding the user to park on the side of the road in time and complete the retest gesture.

[0143] After the retest gesture is displayed to the user, a retest image set of the user can be collected, and at least one of an actual duration for which the user responds to the retest instruction, an actual tremor frequency of the hand of the user, and a similarity degree between an actual gesture of the user and the target gesture is determined according to the retest image set, and then it is determined whether to authorize the user to drive. The actual duration can be started to be counted after the user completes parking on the side of the road, which on the one hand improves the safety of the user during driving, and on the other hand can improve the accuracy of identifying whether the user has a drunk driving behavior.

[0144] It can be seen that, by image acquisition of the user during driving, and after monitoring that the user has a diet action, the drunk driving behavior of the user is retested to constrain the drinking behavior of the user during driving, so as to reduce the probability of drunk driving and improve driving safety.

[0145] Based on the same inventive concept, the embodiment provides a driving authorization control device as shown in Figure 2 The device comprises:

[0146] An instruction generation module 21 is configured to generate a gesture instruction when it is monitored that the user has a driving intention for the target vehicle, the gesture instruction including a target gesture that needs to be performed by the user;

[0147] An image acquisition module 22 is configured to collect a target image set of the user;

[0148] The parameter determination module 23 is configured to determine at least one of an actual duration for the user to respond to the gesture instruction, an actual tremor frequency of the hand of the user, and a similarity degree between the actual gesture of the user and the target gesture according to the target image set.

[0149] The authorization determination module 24 is configured to determine whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency, and the similarity degree.

[0150] Further, the authorization determination module 24 is configured to:

[0151] When the actual duration is greater than the preset duration, or when the actual tremor frequency is greater than the preset tremor frequency, or when the similarity degree is less than the preset similarity threshold, the authorization determination module 24 is configured to prohibit the user from being authorized to drive.

[0152] Further, the parameter determination module 23 is configured to:

[0153] The parameter determination module 23 is configured to determine an actual tremor frequency of the target point on the hand of the user according to the target image set.

[0154] Further, the parameter determination module 23 is configured to:

[0155] The parameter determination module 23 is configured to determine a similarity degree between an actual dynamic path of the actual gesture formed by the user and a preset dynamic path of the target gesture; and / or,

[0156] The parameter determination module 23 is configured to determine a similarity degree between an actual static form of the actual gesture of the user and a preset static form of the target gesture.

[0157] Further, the target gesture includes at least one of a static gesture and a dynamic gesture.

[0158] Further, the authorization determination module 24 is configured to:

[0159] The authorization determination module 24 is configured to determine a response determination value according to the actual duration and the preset duration.

[0160] The authorization determination module 24 is configured to determine a stability determination value according to the actual tremor frequency and the preset tremor frequency.

[0161] The authorization determination module 24 is configured to determine a similarity determination value according to the similarity degree and the preset similarity threshold.

[0162] The authorization determination module 24 is configured to determine a drunk driving determination value of the user according to the response determination value and a corresponding response weight, the stability determination value and a corresponding stability weight, and the similarity determination value and a corresponding similarity weight.

[0163] The authorization determination module 24 is configured to determine whether to authorize the user to drive according to the drunk driving determination value and a preset determination value.

[0164] Further, the instruction generation module 21 includes:

[0165] a monitoring submodule configured to monitor whether a driver seat of the target vehicle is occupied by a user, whether a seat belt of the driver seat is buckled, and whether the target vehicle receives an ignition signal;

[0166] a generating submodule configured to determine that the user has a driving intention for the target vehicle and generate a gesture instruction when it is monitored that the driver seat of the target vehicle is occupied by the user, the seat belt of the driver seat is buckled, and the target vehicle receives the ignition signal.

[0167] Based on the same inventive concept, the embodiment provides an electronic device as shown in the accompanying drawings. Figure 3 The electronic device comprises:

[0168] a processor 31;

[0169] a memory 32 configured to store instructions executable by the processor 31;

[0170] The processor 31 is configured to execute to implement the driving authorization control method provided in the foregoing.

[0171] Based on the same inventive concept, the embodiment provides a non-transitory computer-readable storage medium, when instructions in the storage medium are executed by the processor 31 of the electronic device, the electronic device can execute to implement the driving authorization control method provided in the foregoing.

[0172] Since the electronic device introduced in the embodiment is the electronic device used to implement the method of information processing in the embodiment, based on the method of information processing introduced in the embodiment, those skilled in the art can understand the specific implementation of the electronic device in the embodiment and its various forms, so the electronic device how to implement the method in the embodiment will not be introduced in detail. As long as the electronic device used to implement the method of information processing in the embodiment is implemented by those skilled in the art, it belongs to the scope of the present application.

[0173] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0174] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0175] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0176] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0177] While preferred embodiments of the application have been described, modifications and variations can be apparent to those skilled in the art once aware of the general underlying concepts. Accordingly, the appended claims intend to embrace all such modifications and variations as fall within the scope of the application.

[0178] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A driving authorization control method characterized by, The method comprises: generating a gesture instruction when it is monitored that a user has a driving intention for a target vehicle, the gesture instruction comprising a target gesture required to be performed by the user; collecting a target image set of the user; determining at least one of an actual duration for the user to respond to the gesture instruction, an actual tremor frequency of a hand of the user, and a similarity degree between an actual gesture of the user and the target gesture according to the target image set; determining whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency, and the similarity degree, comprising: determining a response decision value according to the actual duration and a preset duration; determining a stability decision value according to the actual tremor frequency and a preset tremor frequency; determining a similarity decision value according to the similarity degree and a preset similarity threshold value; determining a drunk driving decision value of the user according to the response decision value and a corresponding response weight, the stability decision value and a corresponding stability weight, and the similarity decision value and a corresponding similarity weight; determining whether to authorize the user to drive according to the drunk driving decision value and a preset decision value.

2. The method of claim 1, wherein, The determining whether to authorize the user to drive according to at least one of the actual duration, the actual tremor frequency, and the similarity degree comprises: when the actual duration is greater than the preset duration, or when the actual tremor frequency is greater than the preset tremor frequency, or when the similarity degree is less than the preset similarity threshold value, the user is prohibited from being authorized to drive.

3. The method of claim 1, wherein, The determining the actual tremor frequency of the hand of the user according to the target image set comprises: determining the actual tremor frequency of a target point on the hand of the user according to the target image set.

4. The method of claim 1, wherein, The target gesture comprises at least one of a static gesture and a dynamic gesture.

5. The method of claim 1, wherein, The determining the similarity degree between the actual gesture of the user and the target gesture according to the target image set comprises: determining a similarity degree between an actual dynamic path of the actual gesture formed by the user and a preset dynamic path of the target gesture; and / or determining a similarity degree between an actual static form of the actual gesture of the user and a preset static form of the target gesture.

6. The method of claim 1, wherein, The generating the gesture instruction when it is monitored that the user has the driving intention for the target vehicle comprises: when it is monitored that a seat of the target vehicle is occupied by the user, a seat belt of the seat is buckled up, and an ignition signal is received by the target vehicle, it is determined that the user has the driving intention for the target vehicle and the gesture instruction is generated.

7. A drive authorization control device characterized by comprising: The device comprises: an instruction generation module configured to generate a gesture instruction when it is monitored that a user has a driving intention for a target vehicle, the gesture instruction comprising a target gesture required to be performed by the user; an image collection module configured to collect a target image set of the user; a parameter determination module configured to determine at least one of an actual duration for the user to respond to the gesture instruction, an actual tremor frequency of a hand of the user, and a similarity degree between an actual gesture of the user and the target gesture according to the target image set; The authorization judgment module is configured to determine whether to perform driving authorization on the user according to at least one of the actual time length, the actual tremor frequency, and the similarity degree, determine a response determination value according to the actual time length and a preset time length, determine a stability determination value according to the actual tremor frequency and a preset tremor frequency, and determine a similarity determination value according to the similarity degree and a preset similarity threshold value; determine a drunk driving determination value of the user according to the response determination value and a corresponding response weight, the stability determination value and a corresponding stability weight, and the similarity determination value and a corresponding similarity weight; and determine whether to perform driving authorization on the user according to the drunk driving determination value and a preset determination value.

8. An electronic device, comprising: Comprise: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute to implement a driving authorization control method as claimed in any one of claims 1 to 6. 9.A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of an electronic device, enabling the electronic device to perform a driving authorization control method as claimed in any one of claims 1 to 6.

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