CN113353086A - Vehicle control method and device and electronic equipment - Google Patents
Vehicle control method and device and electronic equipment Download PDFInfo
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- CN113353086A CN113353086A CN202110805488.5A CN202110805488A CN113353086A CN 113353086 A CN113353086 A CN 113353086A CN 202110805488 A CN202110805488 A CN 202110805488A CN 113353086 A CN113353086 A CN 113353086A
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- 238000012549 training Methods 0.000 claims description 3
- 206010039203 Road traffic accident Diseases 0.000 abstract description 17
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W40/09—Driving style or behaviour
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/221—Physiology, e.g. weight, heartbeat, health or special needs
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/223—Posture, e.g. hand, foot, or seat position, turned or inclined
Abstract
The embodiment of the application discloses a vehicle control method, a device and electronic equipment, which are used for acquiring first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information, body sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle. And aiming at the first driving information, determining a first risk grade corresponding to the driving vehicle according to the risk grade model, and aiming at the first risk grade, performing corresponding first intervention control on the driving vehicle. Therefore, when a driver drives, according to the risk level of the driving vehicle when the driver drives, the driver can perform corresponding intervention control on the driving, timely stop dangerous driving behaviors of the driver and reduce road traffic accidents.
Description
Technical Field
The present application relates to the field of automotive technologies, and in particular, to a vehicle control method and apparatus, and an electronic device.
Background
The automobile brings convenience to life of people, and meanwhile, a series of problems such as road traffic accidents are generated, wherein the proportion of automobile accidents caused by dangerous driving behaviors such as abnormal driving emotion and overstimulated driving of a driver is high. Therefore, how to timely stop dangerous driving behaviors of drivers so as to reduce road traffic accidents is a technical problem to be solved by technical personnel in the field.
Disclosure of Invention
The embodiment of the application aims to provide a vehicle control method which can timely stop dangerous driving behaviors of drivers and reduce road traffic accidents.
In a first aspect, an embodiment of the present application provides a vehicle control method, including:
acquiring first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle;
determining a first risk level corresponding to a driving vehicle according to a risk classification model aiming at the first driving information;
and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
In a second aspect, an embodiment of the present application provides a vehicle control apparatus, including:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring first driving information of a driver, and the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle;
the determining module is used for determining a first risk level corresponding to a driving vehicle according to a risk classification model aiming at the first driving information;
and the control module is used for carrying out corresponding first intervention control on the driving vehicle aiming at the first risk level.
In a third aspect, the present embodiments provide an electronic device, which includes a processor, a memory, and a program or an instruction stored on the memory and executable on the processor, and when executed by the processor, the program or the instruction implements the steps of the vehicle control method according to the first aspect.
In a fourth aspect, the present embodiments provide a readable storage medium, on which a program or instructions are stored, which when executed by a processor implement the steps of the vehicle control method according to the first aspect.
According to the technical scheme provided by the embodiment of the application, the first driving information of the driver is obtained, and the first driving information at least comprises at least two of facial expression information, body sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle. And aiming at the first driving information, determining a first risk grade corresponding to the driving vehicle according to the risk grade model, and aiming at the first risk grade, performing corresponding first intervention control on the driving vehicle. Therefore, when a driver drives, according to the risk level of the driving vehicle when the driver drives, the driver can perform corresponding intervention control on the driving, timely stop dangerous driving behaviors of the driver and reduce road traffic accidents.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart of a vehicle control method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a vehicle control method provided by an embodiment of the present application;
FIG. 3 is a schematic flow chart of a vehicle control method provided by an embodiment of the present application;
FIG. 4 is a schematic flow chart of a vehicle control method provided by an embodiment of the present application;
FIG. 5 is a schematic block diagram of a vehicle control apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device implementing an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application provides a vehicle control method. The following describes in detail a vehicle control method provided in the embodiments of the present application with reference to the accompanying drawings through specific embodiments and application scenarios thereof.
As shown in fig. 1, an execution subject of the method may be an on-board server, where the on-board server may be an independent server or a server cluster composed of a plurality of on-board servers, and the on-board server may be a server capable of performing vehicle safety control. The method may specifically comprise the steps of:
s101: the method comprises the steps of obtaining first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle.
Specifically, the facial expression information of the driver is facial expressions of the driver under different emotions, such as a facial expression under sad emotion, a facial expression under angry emotion, a facial expression under excited emotion, a facial expression under normal emotion, and the like. Specifically, the facial expression of the driver can be captured by the camera. In addition, the acquired first driving information of the driver can be stored to form a facial expression feature library, and the facial expression feature library is used as a sample set of the risk classification model. Furthermore, when facial expression information of the driver is collected, the language of the driver can be collected, and the relation between the emotion of the driver and the language characteristics is mined to be used as auxiliary data to perform auxiliary judgment on the driving risk of driving the vehicle.
The body sign information of the driver can be the body temperature of the driver collected through an infrared thermometer, the heart rate of the driver collected by wearable equipment (such as an intelligent bracelet and the like) and the like.
The driving behavior information of the driver can be historical driving behavior information and current driving behavior information of the driver, and the historical driving behavior information includes, but is not limited to, gear shifting sequence, accelerator pedal strength, lane changing times, times of rapid acceleration and rapid deceleration, average vehicle speed, reaction time and the like of the driver under different road conditions. The current driving behavior information includes, but is not limited to, a shift frequency, an acceleration condition, a deceleration condition, a lane change condition, and the like.
The vehicle driving data of the driving vehicle includes, but is not limited to, a driving vehicle speed, a driving acceleration, a tire pressure, a fuel consumption, and the like of the driving vehicle.
S102: for the first driving information, a first risk level of driving the vehicle is determined according to the risk wind level model.
In one possible implementation, the risk classification model is obtained by training and iterating facial expression information, physical sign information of the driver, driving behavior information of the driver, and vehicle driving information of the driving vehicle, which are sample sets, by using a neural network. The information in the sample set can be information of drivers and driving vehicles in different regions of the country, so that the data in the sample set is more representative.
Specifically, the risk classification model of driving a vehicle can be divided into four cases of high risk, medium risk, low risk and normal. And training the neural network by taking mass sample data as input of the neural network, wherein the trained neural network model can correspondingly determine the corresponding risk level according to the characteristics of each piece of information in the first driving information. For example, if the facial expression information in the first driving information is anger, the heart rate in the physical sign information of the driver is 85 times (the heart rate is too high), the shift frequency in the driving behavior information of the driver is too frequent and continues to be in an acceleration state, and the running vehicle speed of the driven vehicle exceeds a safe speed, it can be determined that the driven vehicle is currently in a high risk level (first risk level) by the risk classification model.
S103: and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
In particular, the driving vehicle may be subject to corresponding intervention controls for different risk levels in which the driving vehicle is exposed.
In one possible implementation, S103 includes: in the case where the first risk level is normal, the driven vehicle may be controlled to continue to normally run in the current running state (e.g., to run while keeping the current running vehicle speed) without intervening on the driven vehicle. And controlling the voice prompt of the driving vehicle under the condition that the first risk level is low risk, and specifically prompting the driver to pay attention to driving (such as prompting to reduce the speed, prompting the driver not to fatigue and the like) by using the vehicle-mounted sound. And under the condition that the first risk level is a medium risk, controlling the voice prompt of the driving vehicle and limiting the acceleration of the driving vehicle, specifically, adopting a vehicle-mounted sound to prompt a driver to pay attention to driving (such as prompting the deceleration) and limiting the acceleration of the driving vehicle.
Under the condition that the first risk level is high risk, controlling a voice prompt (such as a prompt for deceleration) of a driving vehicle and limiting the speed of the driving vehicle, and controlling the braking of the driving vehicle after detecting a vehicle collision signal, specifically adopting a vehicle-mounted sound box to prompt a driver to pay attention to the driving (such as the prompt for deceleration) and limit the torque and the steering wheel angle of the driving vehicle, and controlling the emergency braking of the driving vehicle to rapidly control the driving vehicle to stop driving after detecting the vehicle collision signal so as to avoid traffic accidents.
According to the technical scheme disclosed by the embodiment of the application, the first driving information of the driver is obtained, and the first driving information at least comprises at least two of facial expression information, body sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle. And aiming at the first driving information, determining a first risk grade corresponding to the driving vehicle according to the risk grade model, and aiming at the first risk grade, performing corresponding first intervention control on the driving vehicle. Therefore, when a driver drives, according to the risk level of the driving vehicle when the driver drives, the driver can perform corresponding intervention control on the driving, timely stop dangerous driving behaviors of the driver and reduce road traffic accidents. In addition, at least two kinds of the first driving information are sampled to be used as judgment bases of risk levels of driving the vehicle, and the accuracy is high.
As shown in fig. 2, an execution subject of the method may be an on-board server, where the on-board server may be an independent server or a server cluster composed of a plurality of on-board servers, and the on-board server may be a server capable of performing automobile safety control. The method may specifically comprise the steps of:
s201: the method comprises the steps of obtaining first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle.
S202: for the first driving information, a first risk level of driving the vehicle is determined according to the risk wind level model.
S203: and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
It is to be noted that S201 to S203 have the same or similar implementations as S101 to S103, which can be referred to each other, and the embodiments of the present application are not described herein again.
S204: and acquiring second driving information of the driver within preset time after the first intervention control is carried out, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle running information of the driving vehicle, and the information in the first driving information is the same as that in the second driving information.
The second driving information and the first driving information have the same or similar implementation manners, which may be referred to each other, and are not described herein again in this embodiment of the present application. The information in the first driving information and the information in the second driving information are the same, which means that the information type included in the first driving information is the same as the information type included in the second driving information, for example, if the facial expression information of the driver and the physical sign information of the driver are adopted in the first driving information, correspondingly, the facial expression information of the driver and the physical sign information of the driver are also adopted in the second driving information.
S205: for the second driving information, a second risk level of driving the vehicle is determined according to the risk wind level model.
Specifically, after the first intervention control is performed on the driving vehicle, it may be judged whether or not the driver takes the improvement measure within a preset time (e.g., 3 seconds). For example, when the first risk level is low risk, the driver is prompted by voice to decelerate and drive without fatigue, and then, within 3 seconds after the voice prompt, second driving information of the driver is collected and the second risk level is determined for the second driving information.
S206: and under the condition that the second risk level corresponding to the second driving information is the same as the first risk level, upgrading the first risk level.
Specifically, if the driver performs the improvement operation with respect to the prompt at the first risk level, the second risk level is lower than the first risk level, thereby reducing the risk of driving the vehicle. If the driver does not perform improvement operation on the prompt under the first risk level, the second risk level may be at the same level as the first risk level, so that the first risk level is upgraded to further perform warning action.
S207: and performing corresponding second intervention control on the driving vehicle according to the upgraded first risk level.
Specifically, when the first risk level is upgraded, the first risk level may be upgraded to a level higher than the first risk level, or the first risk level may be upgraded in a cross-level manner.
For example, if the first risk level is low risk and the driver does not take corrective action with respect to the indication of the first risk level, the low risk may be upgraded to medium risk and then intervention control corresponding to the medium risk may be performed on the driven vehicle. Or the first risk level is low risk, and the driver does not take improvement measures aiming at the prompt of the first risk level, so that the low risk can be upgraded to high risk in a cross-level manner, and then the driving vehicle is subjected to intervention control corresponding to the high risk to avoid traffic accidents.
Through the technical scheme disclosed by the embodiment of the application, when a driver drives, corresponding intervention control can be performed on the driving according to the risk level of a driving vehicle when the driver drives, dangerous driving behaviors of the driver are prevented in time, and road traffic accidents are reduced. In addition, when the driver does not take improvement measures aiming at the corresponding risk level, the risk level is upgraded, and the driver is subjected to intervention control on the driving vehicle according to the upgraded risk level, so that traffic accidents are further avoided.
As shown in fig. 3, an execution subject of the method may be an on-board server, where the on-board server may be an independent server or a server cluster composed of a plurality of on-board servers, and the on-board server may be a server capable of performing automobile safety control. The method may specifically comprise the steps of:
s301: the method comprises the steps of obtaining first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle.
S302: for the first driving information, a first risk level of driving the vehicle is determined according to the risk wind level model.
S303: and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
It is to be noted that S201 to S203 have the same or similar implementations as S101 to S103, which can be referred to each other, and the embodiments of the present application are not described herein again.
S304: and acquiring second driving information of the driver within preset time after the first intervention control is carried out, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle running information of the driving vehicle, and the information in the first driving information is the same as that in the second driving information.
The second driving information and the first driving information have the same or similar implementation manners, which may be referred to each other, and are not described herein again in this embodiment of the present application. The information in the first driving information and the information in the second driving information are the same, which means that the information type included in the first driving information is the same as the information type included in the second driving information, for example, if the facial expression information of the driver and the physical sign information of the driver are adopted in the first driving information, correspondingly, the facial expression information of the driver and the physical sign information of the driver are also adopted in the second driving information.
S305: and determining a third risk level of the driven vehicle according to the risk wind level model aiming at the second driving information.
Specifically, after the first intervention control is performed on the driving vehicle, it may be judged whether or not the driver takes the improvement measure within a preset time (e.g., 3 seconds). For example, when the first risk level is low risk, the driver is prompted by voice to decelerate and drive without fatigue, and then, within 3 seconds after the voice prompt, second driving information of the driver is collected, and a third risk level is determined for the second driving information.
S306: and degrading the first risk level under the condition that the third risk level corresponding to the second driving information is lower than the first risk level.
Specifically, if the driver performs the improvement operation with respect to the prompt at the first risk level, the second risk level is lower than the first risk level, thereby reducing the risk of driving the vehicle.
In one possible implementation, the first risk level is downgraded to a third risk level.
S307: and performing corresponding second intervention control on the driving vehicle aiming at the degraded first risk level.
Specifically, when the first risk level is degraded, the first risk level may be degraded to a level next to the first risk level, or the first risk level may be degraded across levels.
For example, if the first risk level is medium risk and the driver takes an improvement measure in response to the prompt of the first risk level, the medium risk may be degraded to low risk and then intervention control corresponding to the low risk may be performed on the driving vehicle. Alternatively, if the first risk level is medium risk and the driver does not take corrective action with respect to the prompt of the first risk level, the medium risk may be transgraded to normal.
Through the technical scheme disclosed by the embodiment of the application, when a driver drives, corresponding intervention control can be performed on the driving according to the risk level of a driving vehicle when the driver drives, dangerous driving behaviors of the driver are prevented in time, and road traffic accidents are reduced. In addition, when the driver takes an improvement measure aiming at the corresponding risk level, the risk level is degraded, and the driving vehicle is subjected to intervention control according to the degraded risk level, so that the situation that the user experience is reduced due to excessive intervention on the driving vehicle is avoided.
As shown in fig. 4, an execution subject of the method may be an on-board server, where the on-board server may be an independent server or a server cluster composed of a plurality of on-board servers, and the on-board server may be a server capable of performing automobile safety control. The method may specifically comprise the steps of:
s401: the method comprises the steps of obtaining first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle.
S402: for the first driving information, a first risk level of driving the vehicle is determined according to the risk wind level model.
S403: and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
It is to be noted that S401 to S403 have the same or similar implementations as S101 to S103, which may be referred to each other, and are not described herein again in this embodiment of the present application.
S404: and acquiring second driving information of the driver within preset time after the first intervention control is carried out, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle running information of the driving vehicle, and the information in the first driving information is the same as that in the second driving information.
The second driving information and the first driving information have the same or similar implementation manners, which may be referred to each other, and are not described herein again in this embodiment of the present application. The information in the first driving information and the information in the second driving information are the same, which means that the information type included in the first driving information is the same as the information type included in the second driving information, for example, if the facial expression information of the driver and the physical sign information of the driver are adopted in the first driving information, correspondingly, the facial expression information of the driver and the physical sign information of the driver are also adopted in the second driving information.
S405: for the second driving information, a fourth risk level of driving the vehicle is determined according to the risk wind level model.
Specifically, after the first intervention control is performed on the driving vehicle, it may be judged whether or not the driver takes the improvement measure within a preset time (e.g., 3 seconds). For example, when the first risk level is low risk, the driver is prompted by voice to decelerate and drive without fatigue, and then, within 3 seconds after the voice prompt, second driving information of the driver is collected, and a fourth risk level is determined for the second driving information.
S406: and controlling the driving vehicle to brake under the condition that the fourth risk level corresponding to the second driving information is higher than the first risk level.
Specifically, in the case that the fourth risk level is higher than the first risk level, it indicates that the driver not only does not take improvement measures, but also aggravates dangerous driving, and at this time, it is necessary to control the driving vehicle to make an emergency brake, so as to avoid traffic accidents caused by dangerous driving behaviors of the driver.
Through the technical scheme disclosed by the embodiment of the application, when a driver drives, corresponding intervention control can be performed on the driving according to the risk level of a driving vehicle when the driver drives, dangerous driving behaviors of the driver are prevented in time, and road traffic accidents are reduced. In addition, when the driver does not take improvement measures aiming at the corresponding risk level, the driver takes more dangerous behaviors, and controls the driving vehicle to emergently brake, so that traffic accidents are further avoided.
On the basis of the same technical concept, the embodiment of the present application further provides a vehicle control device corresponding to the vehicle control method provided by the foregoing embodiment, and fig. 5 is a schematic block diagram of the vehicle control device provided by the embodiment of the present application, and the vehicle control device is configured to execute the vehicle control method described in fig. 1 to fig. 4, and as shown in fig. 5, the vehicle control device includes: the device comprises an acquisition module 501, a determination module 502 and a control module 503.
The obtaining module 501 is configured to obtain first driving information of a driver, where the first driving information at least includes at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver, and vehicle driving information of a driving vehicle. The determining module 502 is configured to determine, according to the risk classification model, a first risk classification corresponding to the driving vehicle according to the first driving information. And a control module 503, configured to perform corresponding first intervention control on the driving vehicle for the first risk level.
According to the technical scheme disclosed by the embodiment of the application, the first driving information of the driver is obtained, and the first driving information at least comprises at least two of facial expression information, body sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle. And aiming at the first driving information, determining a first risk grade corresponding to the driving vehicle according to the risk grade model, and aiming at the first risk grade, performing corresponding first intervention control on the driving vehicle. Therefore, when a driver drives, according to the risk level of the driving vehicle when the driver drives, the driver can perform corresponding intervention control on the driving, timely stop dangerous driving behaviors of the driver and reduce road traffic accidents.
Optionally, the vehicle control apparatus further includes: an acquisition module II (not shown), an upgrade module (not shown), and a control module II (not shown).
And the second acquisition module is used for acquiring second driving information of the driver within preset time after the first intervention control is performed, wherein the second driving information at least comprises at least two of facial expression information of the driver, body sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle, and the first driving information and the second driving information are the same in information.
And the upgrading module is used for upgrading the first risk level under the condition that the second risk level corresponding to the second driving information is the same as the first risk level.
And the control module II is used for carrying out corresponding second intervention control on the driving vehicle according to the upgraded first risk level.
Optionally, the vehicle control apparatus further includes: an acquisition module III (not shown), a degradation module (not shown), and a control module III (not shown).
And the third acquisition module is used for acquiring second driving information of the driver within preset time after the first intervention control is performed, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of the driven vehicle, and the first driving information and the second driving information are the same in information.
And the degradation module is used for degrading the first risk level under the condition that the third risk level corresponding to the second driving information is lower than the first risk level.
And the control module III is used for carrying out corresponding second intervention control on the driving vehicle aiming at the degraded first risk level.
Optionally, the vehicle control apparatus further includes: an acquisition module IV (not shown in the figure) and a control module IV (not shown in the figure).
The acquisition module is used for acquiring second driving information of the driver within preset time after the first intervention control is carried out, the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle, and the first driving information and the second driving information are the same in information;
and the control module IV is used for controlling the driving vehicle to brake under the condition that the fourth risk level corresponding to the second driving information is higher than the first risk level.
Optionally, the control module 503 includes: a first control unit (not shown), a second control unit (not shown), a third control unit (not shown), and a fourth control unit (not shown).
A first control unit for controlling the driving vehicle to normally run in the current running state under the condition that the first risk level is normal;
the second control unit is used for controlling the voice prompt of the driving vehicle under the condition that the first risk level is low risk;
the third control unit is used for controlling the voice prompt of the driving vehicle and limiting the acceleration of the driving vehicle under the condition that the first risk level is the medium risk;
and the fourth control unit is used for controlling the voice prompt of the driving vehicle and limiting the speed of the driving vehicle under the condition that the first risk level is high risk, and controlling the driving vehicle to brake after detecting the vehicle collision signal.
The vehicle control device provided by the embodiment of the application can realize each process in the embodiment corresponding to the vehicle control method, and is not repeated here for avoiding repetition.
It should be noted that the vehicle control device provided in the embodiment of the present application and the vehicle control method provided in the embodiment of the present application are based on the same inventive concept, and therefore specific implementation of the embodiment may refer to implementation of the vehicle control method described above, and repeated details are not repeated.
On the basis of the same technical concept, the embodiment of the present application further provides an electronic device for executing the vehicle control method, and fig. 6 is a schematic structural diagram of an electronic device implementing various embodiments of the present invention, as shown in fig. 6. Electronic devices may vary widely in configuration or performance and may include one or more processors 601 and memory 602, where one or more stored applications or data may be stored in memory 602.
Wherein the memory 602 may be transient or persistent storage. The application program stored in memory 602 may include one or more modules (not shown), each of which may include a series of computer-executable instructions for the electronic device. Still further, the processor 601 may be arranged in communication with the memory 602 to execute a series of computer-executable instructions in the memory 602 on the electronic device. The electronic device may also include one or more power supplies 603, one or more wired or wireless network interfaces 604, one or more input-output interfaces 605, one or more keyboards 606.
Specifically, in this embodiment, the electronic device includes a processor, a communication interface, a memory, and a communication bus; the processor, the communication interface and the memory complete mutual communication through a bus; a memory for storing a computer program; a processor for executing the program stored in the memory, implementing the following method steps:
acquiring first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle;
aiming at the first driving information, determining a first risk grade corresponding to the driving vehicle according to the risk grade model;
and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
According to the vehicle control method provided by the embodiment of the application, the first driving information of the driver is obtained, and the first driving information at least comprises at least two of facial expression information, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of the driven vehicle. And aiming at the first driving information, determining a first risk grade corresponding to the driving vehicle according to the risk grade model, and aiming at the first risk grade, performing corresponding first intervention control on the driving vehicle. Therefore, when a driver drives, according to the risk level of the driving vehicle when the driver drives, the driver can perform corresponding intervention control on the driving, timely stop dangerous driving behaviors of the driver and reduce road traffic accidents.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to 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 flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may 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 flow or flows and/or block diagram block or blocks.
These computer program instructions may 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 instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may 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 flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A vehicle control method, characterized by comprising:
acquiring first driving information of a driver, wherein the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driving vehicle;
determining a first risk level corresponding to a driving vehicle according to a risk classification model aiming at the first driving information;
and correspondingly carrying out first intervention control on the driving vehicle aiming at the first risk level.
2. The vehicle control method according to claim 1, characterized in that, after said corresponding first intervention control on the driven vehicle, the method further comprises:
acquiring second driving information of the driver within a preset time after the first intervention control is performed, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle, and the first driving information and the second driving information are the same in information;
upgrading the first risk level under the condition that a second risk level corresponding to the second driving information is the same as the first risk level;
and performing corresponding second intervention control on the driving vehicle aiming at the upgraded first risk level.
3. The vehicle control method according to claim 1, characterized in that, after said corresponding first intervention control on the driven vehicle, the method further comprises:
acquiring second driving information of the driver within a preset time after the first intervention control is performed, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle, and the first driving information and the second driving information are the same in information;
degrading the first risk level under the condition that a third risk level corresponding to the second driving information is lower than the first risk level;
and performing corresponding second intervention control on the driving vehicle aiming at the degraded first risk level.
4. The vehicle control method according to claim 2 or 3, characterized in that the first risk level is upgraded to an upper level of the first risk level, or,
downgrading the first risk level to a third risk level.
5. The vehicle control method according to claim 1, characterized in that, after said corresponding first intervention control on the driven vehicle, the method further comprises:
acquiring second driving information of the driver within a preset time after the first intervention control is performed, wherein the second driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle, and the first driving information and the second driving information are the same in information;
and controlling the driving vehicle to brake under the condition that a fourth risk level corresponding to the second driving information is higher than the first risk level.
6. The vehicle control method according to claim 1, wherein the risk classification model is obtained by training and iterating facial expression information, physical sign information of the driver, driving behavior information of the driver, and vehicle driving information of the driven vehicle as a sample set using a neural network.
7. The vehicle control method according to claim 1, characterized in that said corresponding first intervention control of the driven vehicle for the first risk level comprises:
controlling the driving vehicle to normally run in a current running state under the condition that the first risk level is normal;
controlling the driving vehicle voice prompt if the first risk level is a low risk;
controlling the voice prompt of the driving vehicle and limiting the acceleration of the driving vehicle under the condition that the first risk level is the medium risk;
and under the condition that the first risk level is high risk, controlling the voice prompt of the driving vehicle and limiting the speed of the driving vehicle, and controlling the driving vehicle to brake after detecting a vehicle collision signal.
8. A vehicle control apparatus characterized by comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring first driving information of a driver, and the first driving information at least comprises at least two of facial expression information of the driver, physical sign information of the driver, driving behavior information of the driver and vehicle driving information of a driven vehicle;
the determining module is used for determining a first risk level corresponding to a driving vehicle according to a risk classification model aiming at the first driving information;
and the control module is used for carrying out corresponding first intervention control on the driving vehicle aiming at the first risk level.
9. An electronic device comprising a processor, a memory and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the steps of the vehicle control method according to any one of claims 1 to 7.
10. A readable storage medium, characterized in that the readable storage medium stores thereon a program or instructions which, when executed by a processor, implement the steps of the vehicle control method according to any one of claims 1-7.
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