A driving speed control method, device, electronic device and storage medium

Abstract

The present invention discloses a driving speed control method, device, electronic device and storage medium. The method comprises: obtaining a monitoring video of a driver, the current driving speed of a vehicle and the driving condition of the vehicle; analyzing and identifying the monitoring video to obtain the driving state of the driver; matching from a preset driving rule library according to the driving condition and the driving state to obtain the target driving speed of the vehicle; generating a control signal according to the target driving speed and the current driving speed, and sending the control signal to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal. That is, in an embodiment of the present invention, the target driving speed of the vehicle is automatically determined by the driving state and the driving condition, and the vehicle driving is automatically controlled according to the target driving speed and the automatic driving system, and the erroneous driving operation is corrected in time; by real-time monitoring of the driver and the vehicle, the vehicle speed is controlled by using a monitoring terminal, and the accident rate of the vehicle is effectively reduced.

Description

Technical Field

[0001] The embodiments of the present invention relate to computer technology, and more particularly to a driving speed control method, device, electronic device and storage medium. Background Art

[0002] With the high frequency of vehicle use, vehicle driving safety has become a topic of concern, and the application of driver status monitoring and control instruments has become more and more extensive. In addition to monitoring the driving status of the driver during driving for safety management, it is also used in fleet management, insurance claims and administrative management of operating vehicles and dangerous goods transport vehicles. The existing driver status monitoring and control instruments mainly monitor the driver's bad behavior during driving, and provide timely warnings for behaviors that affect vehicle driving safety, prompting the driver to correct them to ensure driving safety. However, if the driver is in a pathological state, the warning reminder cannot guarantee driving safety. Summary of the invention

[0003] The present invention provides a driving speed control method, device, electronic equipment and storage medium, so as to realize the control of vehicle speed by using a monitoring terminal and effectively reduce the accident rate of the vehicle.

[0004] In a first aspect, an embodiment of the present invention provides a driving speed control method, which is applied to a monitoring device, and the method includes:

[0005] Obtaining monitoring video of the driver, the current speed of the vehicle and the driving condition of the vehicle;

[0006] Analyzing and identifying the monitoring video to obtain the driving status of the driver;

[0007] According to the driving condition and the driving state, a target driving speed of the vehicle is obtained by matching the preset driving rule library;

[0008] A control signal is generated according to the target driving speed and the current driving speed, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0009] Furthermore, the preset driving rule library is obtained in the following manner:

[0010] Obtain driving data of preset vehicles in the online database;

[0011] Determining a safety score corresponding to the driving data of the preset vehicle;

[0012] According to a preset safety threshold and the safety score, the driving data of the preset vehicle is screened to obtain target driving data;

[0013] The driver status, driving conditions and driving speed in the target driving data are associated and stored in the preset driving rule library.

[0014] Furthermore, the monitoring video is analyzed and identified to obtain the driving status of the driver, including:

[0015] The driving elements in the monitoring video are analyzed and identified to obtain the driving state of the driver, wherein the driving elements include the driver's body movements and the driver's facial information, and the driving state includes the type information of the driver's movements and the mental state of the driver's face.

[0016] Furthermore, the driver's facial information includes the frequency of eye movement, eye field of vision and the number of times the eyes are closed.

[0017] Further, according to the driving condition and the driving state, a target driving speed of the vehicle is obtained by matching from a preset driving rule library, including:

[0018] Searching for a driving condition and a driving state whose similarity with the driving condition of the vehicle and the driving state of the driver meets a preset similarity condition from the preset driving rule library, and obtaining a target driving condition and a target driving state;

[0019] The target driving condition and the driving speed corresponding to the target driving state are used as the target driving speed.

[0020] Further, searching the preset driving rule library for driving conditions and driving states whose similarity with the driving conditions of the vehicle and the driving state of the driver meets the preset similarity condition, and obtaining target driving conditions and target driving states, includes:

[0021] Calculating the similarity between the driving state of the driver and the driving state in the preset driving rule library in combination with the weights of the various driving elements, and calculating the similarity between the driving condition of the vehicle and the driving condition in the preset driving rule library;

[0022] By utilizing the similarity of the driving state and the similarity of the driving condition, the driving condition and the driving state with the greatest similarity to the driving condition of the vehicle and the driving state of the driver are selected from the preset driving rule library as the target driving condition and the target driving state.

[0023] Further, generating a control signal according to the target driving speed and the current driving speed includes:

[0024] determining a difference between the target driving speed and the current driving speed, and determining whether the difference is greater than zero;

[0025] When the difference is greater than zero, a control signal for increasing the travel speed is generated according to the difference;

[0026] When the difference is less than zero, a control signal for decreasing the travel speed is generated according to the difference.

[0027] In a second aspect, an embodiment of the present invention further provides a driving speed control device, the device comprising:

[0028] An information acquisition module, used to acquire monitoring video of the driver, the current speed of the vehicle and the driving conditions of the vehicle;

[0029] A state analysis module, used to analyze and identify the monitoring video to obtain the driving state of the driver;

[0030] A target matching module, used for matching the target driving speed of the vehicle from a preset driving rule library according to the driving condition and the driving state;

[0031] A signal generating module is used to generate a control signal according to the target driving speed and the current driving speed, and send the control signal to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0032] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0033] one or more processors;

[0034] a storage device for storing one or more programs,

[0035] When the one or more programs are executed by the one or more processors, the one or more processors implement the driving speed control method.

[0036] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the driving speed control method when executed by a processor.

[0037] In the embodiment of the present invention, the monitoring video of the driver, the current driving speed of the vehicle and the driving conditions of the vehicle are obtained; the monitoring video is analyzed and identified to obtain the driving state of the driver; the target driving speed of the vehicle is obtained by matching from the preset driving rule library according to the driving conditions and the driving state; a control signal is generated according to the target driving speed and the current driving speed, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal. That is, in the embodiment of the present invention, the target driving speed of the vehicle is automatically determined by the driving state and the driving conditions, and the vehicle driving is automatically controlled according to the target driving speed and the automatic driving system, so as to avoid accidents caused by the failure to correct the driving action in time when the driver is in an abnormal driving state; by real-time monitoring of the driver and the vehicle, the vehicle speed is controlled by using the monitoring terminal, and the accident rate of the vehicle is effectively reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flow chart of a driving speed control method provided by an embodiment of the present invention;

[0039] Figure 2 is another flow chart of the driving speed control method provided by an embodiment of the present invention;

[0040] Figure 3 is a structural schematic diagram of a driving speed control device provided by an embodiment of the present invention;

[0041] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0043] Figure 1 The present invention provides a flow chart of a driving speed control method according to an embodiment of the present invention. The method can be executed by a driving speed control device according to an embodiment of the present invention. The device can be implemented in software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device, such as a server. The following embodiments will be described by taking the device integrated into an electronic device as an example. Figure 1 , the method may specifically include the following steps:

[0044] S110, obtaining a monitoring video of the driver, the current speed of the vehicle, and the driving condition of the vehicle;

[0045] For example, the monitoring video may come from a video acquisition device, which may be a camera, a video recorder or other device with a video acquisition function, and is used to control the vehicle to drive safely by monitoring the driver and vehicle information in the video. The monitoring video may be a real-time monitoring video or a pre-collected monitoring video; when the monitoring video is a real-time monitoring video, the real-time monitoring video is used to obtain the driving status of the driver in real time, so as to monitor and control the vehicle in real time; when the monitoring video is a pre-collected monitoring video, the pre-collected monitoring video is used to test the safe driving of the vehicle to determine the accuracy and safety of determining the target driving speed through the driving status. The current speed of the vehicle can be the real-time speed of the vehicle obtained in real time by the high-precision GPS positioning module installed on the vehicle, or the real-time speed of the vehicle obtained in real time by the analysis module (TAX box) in the vehicle safety information comprehensive monitoring device. When the real-time speed of the vehicle obtained by the GPS positioning module and the TAX box in the vehicle is inconsistent, the real-time speed of the vehicle with higher accuracy can be selected by setting the accuracy; if the real-time speed of the vehicle obtained by either the GPS positioning module or the TAX box in the vehicle is wrong, the other correct real-time speed of the vehicle is used. The driving condition of the vehicle can be the scene condition of the vehicle driving determined according to the driving environment of the vehicle, such as: road shape, road light, number of pedestrians, number of lanes and dangerous objects, etc.

[0046] In a specific implementation, the monitoring video corresponding to the driver is collected from the cab of the vehicle according to the video acquisition device, and the current driving speed of the vehicle can be obtained in real time through the high-precision GPS positioning module installed on the vehicle and the parsing module in the comprehensive monitoring device for vehicle safety information inside the vehicle. The driving environment information of the vehicle is obtained by using the camera installed on the vehicle or the roadside unit installed on both sides of the road, and the scene conditions of the vehicle driving are determined according to the driving environment information of the vehicle to obtain the driving conditions of the vehicle. Among them, after obtaining multiple image frames corresponding to the driver in the time period corresponding to the monitoring video from the monitoring video, the multiple image frames in the monitoring video can be analyzed to obtain the driving status of the driver, and determine whether to generate a control signal according to the driving status.

[0047] S120, analyzing and identifying the monitoring video to obtain the driving status of the driver;

[0048] For example, the driving state can be determined based on the driver's behavior information in the monitoring video to determine the driver's safety level for driving the vehicle, where the driving state includes normal driving and abnormal driving state. The abnormal driving state can be the driver's bad behavior habits or abnormal driving behavior, such as: distracted driving such as not paying attention to the lookout, making phone calls, smoking, playing with mobile phones, etc.; fatigue driving such as sleeping, dull eyes, and not looking forward; driving with illness due to sudden illness; the normal driving state can be the driving state in which the driver performs standardized driving to ensure the safety of the vehicle and personnel, such as: looking at the driving direction, and all limbs are in the corresponding positions of the vehicle's driving control panel (hands on the steering wheel, left and right pedals in the specified positions, etc.). The basis for implementing the driving conditions is that the driver has a driving license and the driver's physical indicators meet the driving requirements before driving. .

[0049] In a specific implementation, the monitoring video is analyzed and identified, which can be the behavior identification of the driver in multiple frames of the monitoring video, and the abnormal behavior of the driver in the monitoring video is analyzed and identified, such as: distracted driving such as not paying attention to lookout, making phone calls while driving, smoking, playing with mobile phones, etc.; sleeping, dull eyes, eyes not looking forward, and sudden illness, etc. The driving state of the driver in the vehicle is determined to be normal driving or abnormal driving based on the abnormal behavior of the driver in the monitoring video. When the driving state is an abnormal driving state, the driver does not meet the driving conditions and cannot continue to drive the vehicle for driving, and needs to generate a control signal to automatically control the vehicle for driving; when the driver's driving state is normal driving, the driver meets the driving conditions and can continue to drive the vehicle on the preset road.

[0050] S130, obtaining a target driving speed of the vehicle by matching a preset driving rule library according to driving conditions and driving status;

[0051] For example, the preset driving rule library can be a database that associates and stores driving conditions, driving status, and driving speed by safely screening online data, and is used as a standard driving rule library to determine the target driving speed of the vehicle. The target driving speed can be a safe driving speed of the vehicle matched according to the driving conditions of the vehicle and the driving status of the driver.

[0052] In a specific implementation, the vehicle's driving conditions and the driver's driving status are used as search objects, and target driving data that is consistent with the vehicle's driving conditions and the driver's driving status is matched from a preset driving rule library, and the driving speed in the target driving data is used as the vehicle's target driving speed.

[0053] S140. Generate a control signal according to the target driving speed and the current driving speed, and send the control signal to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0054] For example, the control signal may be a control signal for instructing the automatic driving system to automatically drive the vehicle, i.e., a trigger signal of the automatic driving system, and the automatic driving system may control the vehicle to drive according to the control signal. The automatic driving system may be a vehicle driving system that fully automates and highly centrally controls the driving actions performed by the driver, and may have functions such as automatic wake-up and sleep of the train, automatic entry and exit of the parking lot, automatic cleaning, automatic driving, automatic parking, automatic opening and closing of doors, automatic recovery from faults, and multiple operating modes such as normal operation, degraded operation, and interrupted operation.

[0055] In a specific implementation, the driving action that the vehicle currently needs to take and the difference between the target driving speed and the current driving speed are determined according to the target driving speed and the current driving speed, and a control signal is generated according to the driving action and the difference between the target driving speed and the current driving speed, wherein the control signal includes a gear signal, acceleration / deceleration instructions and the target driving speed of the vehicle, the current driving speed can be made to reach the target driving speed according to the gear signal and the acceleration / deceleration instructions, or the gear signal and the acceleration / deceleration instructions can be generated according to the difference between the target driving speed and the current driving speed so that the vehicle reaches the target driving speed according to the difference.

[0056] In the embodiment of the present invention, the monitoring video of the driver, the current driving speed of the vehicle and the driving conditions of the vehicle are obtained; the monitoring video is analyzed and identified to obtain the driving state of the driver; the target driving speed of the vehicle is obtained by matching from the preset driving rule library according to the driving conditions and the driving state; a control signal is generated according to the target driving speed and the current driving speed, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal. That is, in the embodiment of the present invention, the target driving speed of the vehicle is automatically determined by the driving state and the driving conditions, and the vehicle driving is automatically controlled according to the target driving speed and the automatic driving system, so as to avoid accidents caused by the failure to correct the driving action in time when the driver is in an abnormal driving state; by real-time monitoring of the driver and the vehicle, the vehicle speed is controlled by using the monitoring terminal, and the accident rate of the vehicle is effectively reduced.

[0057] The following further describes the driving speed control method provided by the embodiment of the present invention. Figure 2 As shown, the method may specifically include the following steps:

[0058] S210, obtaining a monitoring video of the driver, the current driving speed of the vehicle, and the driving condition of the vehicle;

[0059] S220, analyzing and identifying driving elements in the monitoring video to obtain the driving state of the driver, where the driving elements include the driver's body movements and the driver's facial information, and the driving state includes the type information of the driver's movements and the mental state of the driver's face;

[0060] For example, the driver's body movements can be the driver's head posture, limb position and body posture. The driver's facial information can be the driver's facial skin color, eye closure duration, eye movement frequency, eye field of vision and number of eye closures. Among them, the eye movement frequency can be the number of eye movements of the driver within a preset time period or a fixed time period, which is used to determine whether the driver is distracted driving; the number of eye closures can be the number of eye closures of the driver within a preset time period or a fixed time period, which is used to determine whether the driver is fatigued driving; the eye field of vision can be the driver's field of vision determined by the angle of the driver's eye gaze during driving, which is used to determine whether the driver is looking at the driving direction. The type information of the driver's action may be the type information of the driver's action in the monitoring video, wherein the type information of the driver's action includes normal driving action and bad habit action. Normal driving action may be the driving action adopted by the driver under the premise of meeting the driver's operating specifications, which can make the vehicle drive safely on the road or track; bad habit action may be the driving action made by the driver during driving that does not meet the driver's operating specifications, such as: not paying attention to lookout, making a phone call, looking around, etc. The mental state of the driver's face may be the mental state of the driver determined by the driver's facial information, such as: pathological state, fatigue state, inattention and normal driving state.

[0061] In a specific implementation, the acquired monitoring video of the driver is analyzed for driving elements, wherein the driving elements include the driver's body movements and the driver's facial information. The driving elements in the monitoring video are analyzed, that is, the driver's body movements and the driver's facial information in the monitoring video are analyzed. The driver's driving state is determined according to the type information of the driver's body movements in the monitoring video and the mental state of the driver's face. The number of bad habit actions in the type information of the driver's actions in the monitoring video and the degree of influence of each bad habit action on driving safety can be counted, and the driver's driving state is determined in combination with the analysis of the driver's facial mental state. For example, when the mental state of the driver's face is pathological, the driver's bad habit actions and the driver's facial mental state are different when the driver's bad habit actions are fatigued. Among them, the driver's driving state is normal driving and abnormal driving. The driver's driving state can be quantitatively distinguished as a normal driving state or an abnormal driving state by setting a threshold of the number of bad habit actions, or the driver's driving state can be determined by the mental state of the driver's face, or the driver's driving state can be determined according to the weight of the driver's driving elements in the monitoring video.

[0062] Furthermore, the driver's facial information includes the frequency of eye movements, the range of eye vision and the number of times the eyes are closed.

[0063] In a specific implementation, the eyeball movement frequency can be the number of eyeball movement of the driver within a preset time period or a fixed duration, which is used to determine whether the driver is distracted while driving, or the number of eyeball movement of the driver per unit time; the number of eye closures can be the number of eyeball closures of the driver within a preset time period or a fixed duration, which is used to determine whether the driver is fatigued while driving; the eye sight range can be the driver's sight range determined by the angle of the driver's eye gaze during driving, which is used to determine whether the driver is looking at the driving direction. The driver's driving state can be determined based on the eyeball movement frequency, eye closure number and eye sight range in the driver's facial information. When the eyeball movement frequency is low, the driver may have dull eyes, sleep with eyes open, and distracted driving; when the number of eye closures is too many, the driver may be fatigued; when the eye sight range is different from the vehicle's driving direction, the driver may look around, which poses a safety hazard.

[0064] S230, searching a preset driving rule library for a driving condition and a driving state whose similarity with the driving condition of the vehicle and the driving state of the driver meets a preset similarity condition, and obtaining a target driving condition and a target driving state;

[0065] For example, the preset similarity condition may be a preset similarity threshold value according to actual demand or experimental data, and the driving condition and driving state in the target driving data that match the vehicle driving condition and the driver's driving state in the preset driving rule library are determined according to the preset similarity threshold value, and the driving speed in the target driving data is used as the target driving speed. The target driving condition may be a driving condition in the preset driving rule library that satisfies the preset similarity condition; the target driving state may be a driving state in the preset driving rule library that satisfies the preset similarity condition, wherein the target driving condition and the target driving speed belong to the same target driving data and are stored in the preset driving rule library.

[0066] In a specific implementation, the driving conditions and driving states in the target driving data that meet the preset similarity threshold are searched from the preset driving rule library according to the preset similarity condition, and the driving conditions and driving states in the target driving data that meet the preset similarity threshold are used as the target driving conditions and target driving states, and then the target driving speed of the vehicle is determined from the preset driving rule library according to the target driving conditions and target driving states, so that the automatic driving system determines the automatic driving operation of the vehicle according to the target driving speed, so that the vehicle reaches the target driving speed to ensure safe driving of the vehicle.

[0067] Furthermore, the preset driving rule library is obtained in the following manner:

[0068] Obtain driving data of preset vehicles in the online database;

[0069] Determine a safety score corresponding to the driving data of a preset vehicle;

[0070] According to the preset safety threshold and safety score, the driving data of the preset vehicle is screened to obtain the target driving data;

[0071] The driver status, driving conditions and driving speed in the target driving data are associated and stored in a preset driving rule library.

[0072] For example, the online database may be driving data information in various vehicle databases on the Internet, and the driving data information includes driving conditions, driving status, driving speed and accident rate, wherein the accident rate is the probability of an accident occurring under the driving conditions, driving status and driving speed for vehicles of the same model. The driving data of a preset vehicle may be driving data of a vehicle obtained from an online database of a preset vehicle model, that is, driving data of the vehicle in a real scene. The safety score corresponding to the driving data of the preset vehicle may be a driving safety score of the vehicle determined based on the accident rate and driving status in the driving data of the preset vehicle. A safety threshold may be preset based on actual needs or experimental data, and it may be determined whether to store the driving data of the preset vehicle in a preset rule base based on the safety threshold, and used to filter driving data that does not meet the safety threshold.

[0073] In a specific implementation, the driving data of the preset vehicle is obtained from the online database, and the safety score of each driving data corresponding to the preset vehicle in the online database is determined according to the accident rate and driving status in the driving data of the preset vehicle, and each driving data corresponding to the preset vehicle is screened according to the preset safety threshold, and the driving data that meets the preset safety threshold is retained as the target driving data, and the driver status, driving conditions and driving speed in the target driving data are associated and stored in the preset driving rule library. The driving data of the preset vehicle in the online database is sorted by screening by the preset safety threshold, and a preset driving rule library is determined to determine the target driving speed of the vehicle, wherein the target driving data of the preset driving rule library is updated in real time according to the data update speed in the online database.

[0074] Furthermore, searching the preset driving rule library for driving conditions and driving states whose similarity with the driving conditions of the vehicle and the driving state of the driver meets the preset similarity condition, and obtaining the target driving conditions and the target driving state, including:

[0075] Calculate the similarity between the driving state of the driver and the driving state in the preset driving rule library in combination with the weights of each driving factor, and calculate the similarity between the driving condition of the vehicle and the driving condition in the preset driving rule library;

[0076] By using the similarity of the driving state and the similarity of the driving condition, the driving condition and the driving state with the greatest similarity to the driving condition of the vehicle and the driving state of the driver are selected from the preset driving rule library as the target driving condition and the target driving state.

[0077] For example, the similarity of driving state can be the similarity between the driving state of the driver in the vehicle and the driving state in the target driving data of the preset driving rule library, which can be calculated by calculating the similarity between the driving state of the driver in the vehicle and the driving state in all the target driving data in the preset driving rule library. The similarity of driving conditions can be the similarity between the driving conditions of the vehicle and the driving conditions in the target driving data of the preset driving rule library, which can be calculated by calculating the similarity between the driving conditions of the vehicle and the driving conditions in all the driving data in the preset driving rule library. Among them, the similarity calculation of driving state needs to be determined in combination with driving factors.

[0078] In a specific implementation, the similarity between the driver's driving state and the driving state in the preset driving rule library can be determined by combining the weights of the driver's body movements and the driver's facial information corresponding to the driving state in the monitoring video, that is, the similarity of the driver's body movements and the driver's facial information is first determined, and the similarity of the driving state is determined by using the weights of the driver's body movements and the driver's facial information, the similarity of the driver's body movements and the similarity of the driver's facial information, and the similarity of the driving state according to the driving conditions of the vehicle and the driving conditions in the preset driving rule library. According to the similarity of the driving state and the similarity of the driving conditions, the similarity with the target driving data in the preset driving rule library is determined. When the similarity with the target driving data in the preset driving rule library reaches a preset similarity threshold, the target driving condition and the target driving state can be determined from the target driving data, or the driving condition and the driving state in the target driving data with the greatest similarity with the driving conditions of the vehicle and the driving state of the driver can be selected from the preset driving rule library as the target driving condition and the target driving state. Among them, the similarity with the target driving data in the preset driving rule library can be the cumulative sum of the similarity of the driving state and the similarity of the driving conditions, or it can be the similarity of the driving state and the similarity of the driving conditions calculated according to the weights of the two to obtain the similarity with the target driving data in the preset driving rule library.

[0079] S240, taking the driving speed corresponding to the target driving condition and the target driving state as the target driving speed;

[0080] In a specific implementation, the driving conditions and driving states in the target driving data that meet the preset similarity threshold are searched from the preset driving rule library according to the preset similarity condition, and the driving conditions and driving states in the target driving data that meet the preset similarity threshold are used as the target driving conditions and target driving states, and then the target driving speed of the vehicle is determined from the preset driving rule library according to the target driving conditions and target driving states, so that the automatic driving system determines the automatic driving operation of the vehicle according to the target driving speed, so that the vehicle reaches the target driving speed to ensure safe driving of the vehicle.

[0081] S250: Generate a control signal according to the target driving speed and the current driving speed, and send the control signal to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0082] Further, generating a control signal according to the target driving speed and the current driving speed includes:

[0083] Determine the difference between the target driving speed and the current driving speed, and determine whether the difference is greater than zero;

[0084] When the difference is greater than zero, a control signal for increasing the driving speed is generated according to the difference;

[0085] When the difference is less than zero, a control signal for decreasing the driving speed is generated according to the difference.

[0086] In a specific implementation, the difference between the target driving speed and the current driving speed can be the speed difference obtained by subtracting the target driving speed from the current driving speed, and the control signal is determined to control the vehicle driving speed by increasing the driving speed or decreasing the driving speed according to the positive or negative value of the speed difference, wherein the control signal for increasing the driving speed can be a signal for controlling the vehicle's driving speed to increase, and the control signal for decreasing the driving speed can be a signal for controlling the vehicle's driving speed to decrease. The difference between the target driving speed and the current driving speed is obtained by subtracting the target driving speed from the current driving speed, and it is determined whether the difference is greater than zero. When the difference is greater than zero, a control signal for increasing the driving speed is generated according to the difference; when the difference is less than zero, a control signal for decreasing the driving speed is generated according to the difference, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle according to the control signal.

[0087] In the embodiment of the present invention, the monitoring video of the driver, the current driving speed of the vehicle and the driving conditions of the vehicle are obtained; the monitoring video is analyzed and identified to obtain the driving state of the driver; the target driving speed of the vehicle is obtained by matching from the preset driving rule library according to the driving conditions and the driving state; a control signal is generated according to the target driving speed and the current driving speed, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal. That is, in the embodiment of the present invention, the target driving speed of the vehicle is automatically determined by the driving state and the driving conditions, and the vehicle driving is automatically controlled according to the target driving speed and the automatic driving system, so as to avoid accidents caused by the failure to correct the driving action in time when the driver is in an abnormal driving state; by real-time monitoring of the driver and the vehicle, the vehicle speed is controlled by using the monitoring terminal, and the accident rate of the vehicle is effectively reduced.

[0088] Figure 3 is a schematic diagram of the structure of the driving speed control device provided by an embodiment of the present invention, such as Figure 3 As shown, the driving speed control device includes:

[0089] The information acquisition module 310 is used to acquire the monitoring video of the driver, the current driving speed of the vehicle and the driving condition of the vehicle;

[0090] A state analysis module 320 is used to analyze and identify the monitoring video to obtain the driving state of the driver;

[0091] A target matching module 330 is used to match the target driving speed of the vehicle from a preset driving rule library according to the driving condition and the driving state;

[0092] The signal generating module 340 is used to generate a control signal according to the target driving speed and the current driving speed, and send the control signal to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0093] In one embodiment, the preset driving rule library is obtained by:

[0094] Obtain driving data of preset vehicles in the online database;

[0095] Determining a safety score corresponding to the driving data of the preset vehicle;

[0096] According to a preset safety threshold and the safety score, the driving data of the preset vehicle is screened to obtain target driving data;

[0097] The driver status, driving conditions and driving speed in the target driving data are associated and stored in the preset driving rule library.

[0098] In one embodiment, the state analysis module 320 analyzes and identifies the monitoring video to obtain the driving state of the driver, including:

[0099] The driving elements in the monitoring video are analyzed and identified to obtain the driving state of the driver, wherein the driving elements include the driver's body movements and the driver's facial information, and the driving state includes the type information of the driver's movements and the mental state of the driver's face.

[0100] In one embodiment, the driver's facial information collected by the state analysis module 320 includes eye movement frequency, eye sight range, and eye closing frequency.

[0101] In one embodiment, the target matching module 330 matches the target driving speed of the vehicle from a preset driving rule library according to the driving condition and the driving state, including:

[0102] Searching for a driving condition and a driving state whose similarity with the driving condition of the vehicle and the driving state of the driver meets a preset similarity condition from the preset driving rule library, and obtaining a target driving condition and a target driving state;

[0103] The target driving condition and the driving speed corresponding to the target driving state are used as the target driving speed.

[0104] In one embodiment, the target matching module 330 searches for driving conditions and driving states whose similarity with the driving conditions of the vehicle and the driving state of the driver meets a preset similarity condition from the preset driving rule library, and obtains target driving conditions and target driving states, including:

[0105] Calculating the similarity between the driving state of the driver and the driving state in the preset driving rule library in combination with the weights of the various driving elements, and calculating the similarity between the driving condition of the vehicle and the driving condition in the preset driving rule library;

[0106] By utilizing the similarity of the driving state and the similarity of the driving condition, the driving condition and the driving state with the greatest similarity to the driving condition of the vehicle and the driving state of the driver are selected from the preset driving rule library as the target driving condition and the target driving state.

[0107] In one embodiment, the signal generating module 340 generates a control signal according to the target driving speed and the current driving speed, including:

[0108] determining a difference between the target driving speed and the current driving speed, and determining whether the difference is greater than zero;

[0109] When the difference is greater than zero, a control signal for increasing the travel speed is generated according to the difference;

[0110] When the difference is less than zero, a control signal for decreasing the travel speed is generated according to the difference.

[0111] The device of the embodiment of the present invention obtains the monitoring video of the driver, the current driving speed of the vehicle and the driving conditions of the vehicle; analyzes and identifies the monitoring video to obtain the driving state of the driver; matches the preset driving rule library according to the driving conditions and driving state to obtain the target driving speed of the vehicle; generates a control signal according to the target driving speed and the current driving speed, and sends the control signal to the automatic driving system, so that the automatic driving system controls the vehicle driving according to the control signal. That is, the embodiment of the present invention automatically determines the target driving speed of the vehicle according to the driving state and driving conditions, and automatically controls the vehicle driving according to the target driving speed and the automatic driving system, so as to avoid accidents caused by the failure to correct the driving action in time when the driver is in an abnormal driving state; by real-time monitoring of the driver and the vehicle, the vehicle speed is controlled by using the monitoring terminal, and the accident rate of the vehicle is effectively reduced.

[0112] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. Figure 4 A block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 4 The electronic device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0113] like Figure 4 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0114] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0115] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0116] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0117] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0118] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0119] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the driving speed control method provided in the embodiment of the present invention, which includes:

[0120] Obtaining monitoring video of the driver, the current speed of the vehicle and the driving condition of the vehicle;

[0121] Analyzing and identifying the monitoring video to obtain the driving status of the driver;

[0122] According to the driving condition and the driving state, a target driving speed of the vehicle is obtained by matching the preset driving rule library;

[0123] A control signal is generated according to the target driving speed and the current driving speed, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0124] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, characterized in that when the program is executed by a processor, the driving speed control method is implemented, and the method includes:

[0125] Obtaining monitoring video of the driver, the current speed of the vehicle and the driving condition of the vehicle;

[0126] Analyzing and identifying the monitoring video to obtain the driving status of the driver;

[0127] According to the driving condition and the driving state, a target driving speed of the vehicle is obtained by matching the preset driving rule library;

[0128] A control signal is generated according to the target driving speed and the current driving speed, and the control signal is sent to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

[0129] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a device or a device or used in combination with it.

[0130] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0131] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0132] Computer program code for performing the operation of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0133] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A driving speed control method, characterized in that: Applied to monitoring equipment, including: Obtaining monitoring video of the driver, the current speed of the vehicle and the driving condition of the vehicle; Analyzing and identifying the monitoring video to obtain the driving status of the driver; According to the driving condition and the driving state, a target driving speed of the vehicle is obtained by matching the preset driving rule library; generating a control signal according to the target driving speed and the current driving speed, and sending the control signal to an automatic driving system so that the automatic driving system controls the vehicle to travel according to the control signal; The preset driving rule library is obtained in the following manner: Obtain driving data of preset vehicles in the online database; Determining a safety score corresponding to the driving data of the preset vehicle; According to a preset safety threshold and the safety score, the driving data of the preset vehicle is screened to obtain target driving data; The driver status, driving conditions and driving speed in the target driving data are associated and stored in the preset driving rule library.

2. The method according to claim 1, characterized in that: Analyzing and identifying the monitoring video to obtain the driving status of the driver includes: The driving elements in the monitoring video are analyzed and identified to obtain the driving state of the driver, wherein the driving elements include the driver's body movements and the driver's facial information, and the driving state includes the type information of the driver's movements and the mental state of the driver's face.

3. The method according to claim 2, characterized in that The driver's facial information includes the frequency of eye movement, eye sight range and number of eye closing times.

4. The method according to claim 2, characterized in that: According to the driving condition and the driving state, a target driving speed of the vehicle is obtained by matching from a preset driving rule library, including: Searching for a driving condition and a driving state whose similarity with the driving condition of the vehicle and the driving state of the driver meets a preset similarity condition from the preset driving rule library, and obtaining a target driving condition and a target driving state; The target driving condition and the driving speed corresponding to the target driving state are used as the target driving speed.

5. The method according to claim 4, characterized in that Searching the preset driving rule library for driving conditions and driving states whose similarity with the driving conditions of the vehicle and the driving state of the driver meets the preset similarity condition, and obtaining target driving conditions and target driving states, including: Calculating the similarity between the driving state of the driver and the driving state in the preset driving rule library in combination with the weights of the various driving elements, and calculating the similarity between the driving condition of the vehicle and the driving condition in the preset driving rule library; By utilizing the similarity of the driving state and the similarity of the driving condition, the driving condition and the driving state with the greatest similarity to the driving condition of the vehicle and the driving state of the driver are selected from the preset driving rule library as the target driving condition and the target driving state.

6. The method according to claim 1, characterized in that Generating a control signal according to the target driving speed and the current driving speed includes: determining a difference between the target driving speed and the current driving speed, and determining whether the difference is greater than zero; When the difference is greater than zero, a control signal for increasing the travel speed is generated according to the difference; When the difference is less than zero, a control signal for decreasing the travel speed is generated according to the difference.

7. A driving speed control device, characterized in that: include: An information acquisition module, used to acquire monitoring video of the driver, the current speed of the vehicle and the driving conditions of the vehicle; A state analysis module, used to analyze and identify the monitoring video to obtain the driving state of the driver; A target matching module, used for matching the target driving speed of the vehicle from a preset driving rule library according to the driving condition and the driving state; The preset driving rule library is obtained by: acquiring driving data of a preset vehicle in an online database; determining a safety score corresponding to the driving data of the preset vehicle; According to the preset safety threshold and the safety score, the driving data of the preset vehicle is screened to obtain target driving data; the driver state, driving condition and driving speed in the target driving data are associated and stored in the preset driving rule library; A signal generating module is used to generate a control signal according to the target driving speed and the current driving speed, and send the control signal to the automatic driving system so that the automatic driving system controls the vehicle driving according to the control signal.

8. An electronic device, characterized in that: The electronic device comprises: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the driving speed control method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the driving speed control method as described in any one of claims 1 to 6 is implemented.

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