CN112348718B - Intelligent auxiliary driving guiding method, intelligent auxiliary driving guiding device and computer storage medium - Google Patents
Intelligent auxiliary driving guiding method, intelligent auxiliary driving guiding device and computer storage medium Download PDFInfo
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Abstract
The invention discloses an intelligent auxiliary driving guiding method, which comprises the following steps: when the driver is judged to be a brand new driver through face recognition, providing instruction content of intelligent auxiliary driving functions for the driver; judging whether the vehicle is in a stationary state or not; when the vehicle is in a stationary state, the coaching content is continuously provided to the driver for the driver to learn the coaching content. The invention also discloses a device and a computer readable storage medium, which solve the problem that the intelligent auxiliary driving operation instruction content cannot be intelligently pushed to a driver in the prior art.
Description
Technical Field
The present invention relates to the field of intelligent driving technologies, and in particular, to an intelligent driving assistance guidance method, apparatus, and computer storage medium.
Background
At present, intelligent driving assistance (ADAS) operation instruction contents provided for a driver by an automobile central control are played after the user sends a request, and are not distinguished according to driver information, and the played contents are the same for all the users sending the request. The disadvantages of this technique are:
it is not known to most users which ADAS functions the car has nor is it known to which functions the user is unfamiliar with the skill of the operation and therefore does not actively make a request to the car central control.
Even if the user actively sends out a playing request, the guidance content which is played to all the users by the central control is the same, the learned users can feel tired when hearing the repeated guidance content, and the user viscosity is reduced. Therefore, there is also a problem in the prior art that the instruction content of the intelligent auxiliary driving operation instruction cannot be intelligently pushed to the driver.
Disclosure of Invention
The invention mainly aims to provide an intelligent auxiliary driving instruction method, an intelligent auxiliary driving instruction device and a computer storage medium, and aims to solve the problem that intelligent auxiliary driving instruction contents cannot be intelligently pushed to a driver in the prior art.
In order to achieve the above object, the present invention provides an intelligent driving assistance guidance method, comprising the steps of:
When judging that the driver is a brand new driver through face recognition, providing instruction content of intelligent auxiliary driving functions for the driver;
Judging whether the vehicle is in a stationary state or not;
And when the vehicle is in a stationary state, continuing to provide the guidance content to the driver for the driver to learn the guidance content.
In one embodiment, the instructional content is presented in at least one of the following forms:
audio files, video files, graphics files, network link files, and text files.
In an embodiment, further comprising:
and starting the face recognition system to judge whether the driver is a brand new driver.
In an embodiment, after the step of starting the face recognition system to determine whether the driver is a completely new driver, the method further includes:
And when the face recognition system judges that the driver is a non-brand new driver, the guidance content of the intelligent auxiliary driving function is not provided.
In an embodiment, after the step of not providing the guidance content of the intelligent driving assistance function when the face recognition system determines that the driver is not a brand new driver, the method further includes:
acquiring a target retrieval instruction corresponding to a target intelligent auxiliary driving function triggered by the driver at a target function starting component;
and determining corresponding instruction content in the instruction content according to the target retrieval instruction, and providing the corresponding instruction content for the driver for learning.
In one embodiment, the determining whether the vehicle is stationary includes:
acquiring the running speed of the vehicle through a vehicle sensor;
And judging whether the vehicle is in a static state or not according to the running speed.
In an embodiment, further comprising:
and stopping providing the coaching content to the driver when the vehicle is in a non-stationary state.
In an embodiment, after the step of stopping the providing of the guidance content to the driver when the vehicle is in a non-stationary state, the method further includes:
acquiring an operation instruction of the driver in real time;
and when an operation instruction of the driver for actively requesting to provide the guidance content is acquired, the guidance content is provided to the driver again so that the driver can learn the guidance content.
To achieve the above object, the present invention also provides an apparatus including a memory, a processor, and an intelligent auxiliary driving coaching program stored in the memory and executable on the processor, which when executed by the processor, implements the steps of the intelligent auxiliary driving coaching method as described above.
In order to achieve the above object, the present invention also provides a computer-readable storage medium storing an intelligent driving assistance guidance program that, when executed by a processor, implements the respective steps of the intelligent driving assistance guidance method described above.
According to the method, the device and the computer storage medium for determining the reasons of the display black screen, when the driver is judged to be a brand new driver through face recognition, the vehicle central control automatically provides the driver with guidance content of an intelligent auxiliary driving function, and the guidance content can be presented in the forms of audio files, video files, graphic files, network link files and text files; and then the vehicle central control synchronously judges whether the vehicle is in a stationary state, and when the judging result shows that the vehicle is in the stationary state, the vehicle central control continuously provides guidance content for a driver so that the driver can learn the guidance content of the intelligent auxiliary driving function. The driver is judged to be a brand new driver through face recognition, the instruction content of the intelligent auxiliary driving function is actively pushed to the driver, the instruction content of the intelligent auxiliary driving function is continuously provided to the driver when the vehicle is in a static state, and the driver is ensured to complete learning of the instruction content, so that the problem that instruction content of intelligent auxiliary driving operation instruction cannot be intelligently pushed to the driver in the prior art is solved.
Drawings
FIG. 1 is a schematic view of a device according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of the intelligent auxiliary driving direction method of the present invention;
FIG. 3 is a flow chart of a second embodiment of the intelligent auxiliary driving direction method of the present invention;
FIG. 4 is a flow chart of a third embodiment of the intelligent auxiliary driving direction method of the present invention;
FIG. 5 is a flow chart of a fourth embodiment of the intelligent auxiliary driving direction method of the present invention;
FIG. 6 is a flowchart of a fifth embodiment of the intelligent auxiliary driving direction method of the present invention;
FIG. 7 is a flowchart of a sixth embodiment of the intelligent auxiliary driving direction method of the present invention;
fig. 8 is a flowchart of a seventh embodiment of the intelligent auxiliary driving instruction method of the present invention.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The main solutions of the embodiments of the present invention are: when the driver is judged to be a brand new driver through face recognition, the vehicle central control automatically provides the driver with guiding content of the intelligent auxiliary driving function, and the guiding content can be presented in the forms of audio files, video files, graphic files, network link files and text files; and then the vehicle central control synchronously judges whether the vehicle is in a stationary state, and when the judging result shows that the vehicle is in the stationary state, the vehicle central control continuously provides guidance content for a driver so that the driver can learn the guidance content of the intelligent auxiliary driving function. The driver is judged to be a brand new driver through face recognition, the instruction content of the intelligent auxiliary driving function is actively pushed to the driver, the instruction content of the intelligent auxiliary driving function is continuously provided to the driver when the vehicle is in a static state, and the driver is ensured to complete learning of the instruction content, so that the problem that instruction content of intelligent auxiliary driving operation instruction cannot be intelligently pushed to the driver in the prior art is solved.
As an implementation manner, as shown in fig. 1, fig. 1 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
The processor 1100 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the methods described above may be performed by integrated logic circuitry in hardware or instructions in software in processor 1100. The processor 1100 described above may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 1200, and the processor 1100 reads information in the memory 1200, and in combination with its hardware, performs the steps of the method described above.
It is to be appreciated that memory 1200 in embodiments of the invention may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM) which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available, such as static random access memory (STATIC RAM, SRAM), dynamic random access memory (DYNAMIC RAM, DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate Synchronous dynamic random access memory (Double DATA RATE SDRAM, DDRSDRAM), enhanced Synchronous dynamic random access memory (ENHANCED SDRAM, ESDRAM), synchronous link dynamic random access memory (SYNCHLINK DRAM, SLDRAM), and Direct memory bus random access memory (DRRAM). The memory 1200 of the systems and methods described in embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
For a software implementation, the techniques described in embodiments of the present invention may be implemented by modules (e.g., procedures, functions, and so on) that perform the functions described in embodiments of the present invention. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
Based on the above-described structure, an embodiment of the present invention is presented.
Referring to fig. 2, fig. 2 is a first embodiment of the intelligent driving assistance guidance method of the present invention, which includes the steps of:
step S110, when the driver is judged to be a brand new driver through face recognition, guiding content of intelligent auxiliary driving functions is provided for the driver.
In this embodiment, the intelligent driving assistance system (ADVANCED DRIVING ASSISTANCE SYSTEM), i.e. the advanced driving assistance system, is to use various sensors (millimeter wave radar, laser radar, single/double camera and satellite navigation) installed on the vehicle to sense the surrounding environment at any time during the running process of the vehicle, collect data, perform static and dynamic object identification, detection and tracking, and combine with navigation map data to perform system operation and analysis, thereby enabling the driver to perceive possible danger in advance and effectively increasing the comfort and safety of the driving of the vehicle. Intelligent auxiliary driving coaching refers to coaching a user in learning an intelligent auxiliary driving function.
Face recognition is a biological recognition technology for carrying out identity recognition based on facial feature information of people. A series of related technologies, commonly referred to as image recognition and face recognition, are used to capture images or video streams containing faces with a camera or cameras, and automatically detect and track the faces in the images, thereby performing face recognition on the detected faces. The key of success of the face recognition system is whether to have a core algorithm of a tip or not, and the recognition result has practical recognition rate and recognition speed; the face recognition system integrates various professional technologies such as artificial intelligence, machine recognition, machine learning, model theory, expert system, video image processing and the like, and meanwhile, the theory and realization of intermediate value processing are combined, so that the face recognition system is the latest application of biological feature recognition, and the realization of core technology shows the conversion from weak artificial intelligence to strong artificial intelligence.
The face recognition system mainly comprises four components, namely: face image acquisition and detection, face image preprocessing, face image feature extraction, matching and recognition.
Face image acquisition: different face images can be acquired through the camera lens, such as static images, dynamic images, different positions, different expressions and the like, can be acquired well. When the user is in the shooting range of the acquisition device, the acquisition device can automatically search and shoot the face image of the user. Face detection: face detection is mainly used for preprocessing face recognition in practice, namely, accurately calibrating the position and the size of the face in an image. The mode features contained in the face image are quite rich, such as histogram features, color features, template features, structural features, haar features and the like. Face detection is to pick out the useful information and use these features to realize face detection. The main stream face detection method adopts an Adaboost learning algorithm based on the characteristics, and the Adaboost learning algorithm is a classification method, and combines a plurality of weaker classification methods together to form a new strong classification method. In the face detection process, an Adaboost algorithm is used for selecting some rectangular features (weak classifiers) which can represent the face most, the weak classifiers are constructed into a strong classifier according to a weighted voting mode, and then a plurality of strong classifiers obtained through training are connected in series to form a cascade classifier with a cascade structure, so that the detection speed of the classifier is effectively improved.
Preprocessing a face image: the image preprocessing for the face is a process of processing the image based on the face detection result and finally serving for feature extraction. The original image obtained by the system is limited by various conditions and randomly disturbed, so that the original image cannot be directly used, and the original image must be subjected to image preprocessing such as gray correction, noise filtering and the like at the early stage of image processing. For the face image, the preprocessing process mainly comprises light compensation, gray level transformation, histogram equalization, normalization, geometric correction, filtering, sharpening and the like of the face image.
Face image feature extraction: features that can be used by face recognition systems are generally classified into visual features, pixel statistics features, face image transform coefficient features, face image algebraic features, and the like. Face feature extraction is performed for certain features of the face. Face feature extraction, also known as face characterization, is a process of feature modeling of a face. The face feature extraction method is classified into two main types: one is a knowledge-based characterization method; the other is a characterization method based on algebraic features or statistical learning. The knowledge-based characterization method mainly obtains feature data which are helpful for face classification according to the shape description of face organs and the distance characteristics between the face organs, wherein feature components generally comprise Euclidean distance, curvature, angle and the like among feature points. The face is composed of parts such as eyes, nose, mouth, chin, etc., and the geometric description of these parts and the structural relationship between them can be used as important features for recognizing the face, and these features are called geometric features. Knowledge-based face representation mainly comprises a geometric feature-based method and a template matching method.
Face image matching and recognition: the extracted feature data of the face image is searched and matched with feature templates stored in a database, and when the similarity exceeds a threshold value, a matching result is output. Face recognition is to compare the face features to be recognized with the obtained face feature templates and judge the identity information of the face according to the similarity. This process is again divided into two categories: one is confirmation, which is a one-to-one image comparison process, and the other is recognition, which is a one-to-many image matching comparison process.
In the present embodiment, algorithms to which face recognition is mainly applied include, but are not limited to: a face Feature point-based recognition algorithm (Feature-based recognition algorithms); an entire face image based recognition algorithm (application-based recognition algorithms); template-based recognition algorithms (Template-based recognition algorithms); an algorithm (Recognition algorithms using neural network) for identification using a neural network.
In the present embodiment, when the driver is judged to be a brand new driver through face recognition, that is, it means that the driver does not operate to control the vehicle, the vehicle includes but is not limited to a car, SUV car, van, truck, JEEP car, etc. The central control of the automobile is used for controlling comfortable entertainment devices such as an automobile air conditioner, a sound box and the like. The automobile central control comprises a central control door lock system, and a driver can control the opening and closing of the whole automobile door and the glass lifting system through the automobile central control. The central control door lock system mainly has three functions of central control, speed control and independent control. The driver can control all door lock switches, and simultaneously, when the running speed reaches a certain value, the vehicle door is automatically locked, and other vehicle doors are independently opened and closed, so that the driver can independently control the vehicle door. The central control of the automobile also comprises a central control console and various vehicle controllers such as an acoustic control panel. The vehicle central control automatically provides the operation instruction content of the intelligent auxiliary driving function for the driver.
It should be noted that, the instruction content is presented in at least one form of the following files: audio files, video files, graphics files, network link files, and text files. The audio file may be provided to the driver for learning through the vehicle audio. The network link file refers to a file including network links, and when presented in the form of a network link file, the network links in the network link file may be displayed on a screen, and a driver may click on the displayed network links to acquire guidance content. The instructional content may preferably be presented in the form of an animation (UI design) of the intelligent driving assistance function.
Step S120, determining whether the vehicle is in a stationary state.
In the present embodiment, the vehicle center control automatically determines whether the vehicle is in a stationary state in synchronization with the operation guidance content of the intelligent auxiliary driving function provided to the driver.
And step S130, continuing to provide the guidance content to the driver when the vehicle is in a stationary state so that the driver can learn the guidance content.
In this embodiment, when the vehicle center control determination result indicates that the vehicle is in a stationary state, the guidance content of the intelligent auxiliary driving function is continuously provided to the driver for the driver to learn the guidance content.
In the technical scheme provided by the embodiment, when the driver is judged to be a brand new driver through face recognition, the vehicle central control automatically provides the guidance content of the intelligent auxiliary driving function for the driver, and the guidance content can be presented in the forms of an audio file, a video file, a graphic file, a network link file and a text file; and then the vehicle central control synchronously judges whether the vehicle is in a stationary state, and when the judging result shows that the vehicle is in the stationary state, the vehicle central control continuously provides guidance content for a driver so that the driver can learn the guidance content of the intelligent auxiliary driving function. The driver is judged to be a brand new driver through face recognition, the instruction content of the intelligent auxiliary driving function is actively pushed to the driver, the instruction content of the intelligent auxiliary driving function is continuously provided to the driver when the vehicle is in a static state, and the driver is ensured to complete learning of the instruction content, so that the problem that instruction content of intelligent auxiliary driving operation instruction cannot be intelligently pushed to the driver in the prior art is solved.
Referring to fig. 3, fig. 3 is a second embodiment of the intelligent auxiliary driving instruction method of the present invention, including:
compared with the first embodiment, the second embodiment includes step S210, and other steps are the same as those of the first embodiment, and will not be described again.
In step S210, the face recognition system is started to determine whether the driver is a brand new driver.
In this embodiment, after the vehicle is powered on, the face recognition system is automatically started to acquire the face information of the driver, and determine whether the driver is a brand new driver, and the face recognition system is described in detail in the above description, so that the description is omitted.
Step S220, when the driver is judged to be a brand new driver through face recognition, guiding content of the intelligent auxiliary driving function is provided for the driver.
Step S230, determining whether the vehicle is in a stationary state.
And step S240, when the vehicle is in a static state, continuing to provide the guidance content for the driver so that the driver can learn the guidance content.
In the technical scheme provided by the embodiment, after the vehicle is electrified, the face recognition system is automatically started to acquire the face information of the driver, and whether the driver is a brand new driver is judged, which is a precondition for actively providing guidance content of an intelligent auxiliary driving function for the driver.
Referring to fig. 4, fig. 4 is a third embodiment of the intelligent auxiliary driving instruction method of the present invention, including:
In step S310, the face recognition system is started to determine whether the driver is a brand new driver.
In step S320, when the face recognition system determines that the driver is a non-brand new driver, the guidance content of the intelligent driving assistance function is not provided.
In this embodiment, when the face recognition system determines that the driver is a non-brand new driver, it indicates that the driver has learned the guidance content of the intelligent auxiliary driving function before that, and therefore, the guidance content of the intelligent auxiliary driving function is not actively provided to the driver.
In the technical solution provided in this embodiment, when the face recognition system determines that the driver is a non-brand new driver, it indicates that the driver has previously learned the guidance content of the intelligent auxiliary driving function, so that the guidance content of the intelligent auxiliary driving function is not actively provided to the driver. Therefore, the problem that the learned user can feel tired when hearing the repeated instruction content and the viscosity of the user is reduced is solved.
Referring to fig. 5, fig. 5 is a fourth embodiment of the intelligent auxiliary driving instruction method of the present invention, including:
In step S410, the face recognition system is started to determine whether the driver is a brand new driver.
In step S420, when the face recognition system determines that the driver is a non-brand new driver, the guidance content of the intelligent driving assistance function is not provided.
Compared with the third embodiment, the fourth embodiment includes step S430 and step S440, and other steps are the same as those of the third embodiment, and will not be described again.
Step S430, obtaining a target retrieval instruction corresponding to the target intelligent auxiliary driving function triggered by the driver at the target function starting component.
In this embodiment, the target starting component may be a key that can be pressed up and down in the vehicle; a key capable of being pushed downwards and pulled upwards; a shift lever capable of being pulled left and right; a knob which can be rotated or a button which can slide left and right. Target intelligent driving assistance functions include, but are not limited to: an adaptive cruise ACC (Adaptive cruise control) function, a lane offset warning function, a lane keeping function, a collision avoidance or pre-collision function, a night vision function, an adaptive light control (ADAPTIVE LIGHT control) function, a pedestrian protection function, an automatic parking function, a traffic sign recognition (TRAFFIC SIGN recogntion) function, a blind spot detection (Blind spot detection) function, a driver fatigue detection (Driver drowsiness detection) function, a downhill control function, an electric car warning function, and the like. For example, if the intelligent auxiliary driving function corresponding to one button is a lane keeping function at the upper right side of the steering wheel of the vehicle, the driver presses the button to trigger a lane keeping function search command corresponding to the lane keeping function, and the vehicle central control acquires the command.
Step S440, corresponding instruction content is determined in the instruction content according to the target retrieval instruction, and the corresponding instruction content is provided for the driver for learning.
In this embodiment, when the vehicle central control acquires the lane keeping function search instruction, the guidance content corresponding to the lane keeping function is determined from the intelligent auxiliary driving function guidance content according to the lane keeping function search instruction, and the guidance content corresponding to the lane keeping function is provided for the driver to learn.
In the technical scheme provided by the embodiment, a target retrieval instruction corresponding to a target intelligent auxiliary driving function triggered by the driver at a target function starting component is obtained; preferably, the instruction is a lane keeping function search instruction, and the instruction content corresponding to the lane keeping function is determined from the instruction content of the intelligent auxiliary driving function according to the lane keeping function search instruction, and the instruction content corresponding to the lane keeping function is provided for the driver to learn. And correspondingly providing the target intelligent auxiliary driving function which the user wants to learn or know to the user, so that the experience of the user is improved.
Referring to fig. 6, fig. 6 is a fifth embodiment of the intelligent auxiliary driving instruction method of the present invention, including:
step S510, when the driver is judged to be a brand new driver through face recognition, guiding content of intelligent auxiliary driving functions is provided for the driver.
Compared with the first embodiment, the fifth embodiment includes step S520 and step S530, and other steps are the same as those of the first embodiment, and will not be described again.
Step S520, acquiring the running speed of the vehicle by a vehicle sensor.
In the present embodiment, the vehicle center control acquires the running speed of the vehicle from an engine speed sensor of the vehicle.
Step S530, determining whether the vehicle is in a stationary state according to the running speed.
In the present embodiment, the vehicle center control determines whether the vehicle is in a stationary state according to the acquired running speed, that is, the vehicle center control determines whether the acquired running speed is zero as a determination condition.
And step S540, continuing to provide the guidance content to the driver when the vehicle is in a stationary state so that the driver can learn the guidance content.
In the technical scheme provided by the embodiment, the vehicle central control obtains the running speed of the vehicle through an engine speed sensor of the vehicle; the vehicle central control judges whether the vehicle is in a static state according to the acquired running speed, namely, the vehicle central control takes the acquired running speed as a judging condition according to whether the acquired running speed is zero.
Referring to fig. 7, fig. 7 is a sixth embodiment of the intelligent auxiliary driving instruction method of the present invention, including:
In step S610, when it is determined that the driver is a brand new driver through face recognition, instructional contents of the intelligent auxiliary driving function are provided to the driver.
Step S620, acquiring the running speed of the vehicle by a vehicle sensor.
Step S630, determining whether the vehicle is in a stationary state according to the running speed.
Compared with the fifth embodiment, the sixth embodiment includes step S640, and other steps are the same as those of the fifth embodiment, and will not be described again.
Step S640 of stopping the providing of the guidance content to the driver when the vehicle is in a non-stationary state.
In this embodiment, when the running speed obtained by the vehicle central control is not zero, that is, the vehicle is in a non-stationary state, the provision of the guidance content of the intelligent auxiliary driving function to the driver is stopped, so that the driver is not interfered by the guidance content in the running process of the vehicle, for example, if the guidance content of the intelligent auxiliary driving function is continuously provided to the driver in the form of video, the driver may be interfered, the safety is affected, the interference of the problem is avoided in this embodiment, the vehicle safety of the user is effectively ensured, and meanwhile, the technology sense is very strong.
Referring to fig. 8, fig. 8 is a seventh embodiment of the intelligent auxiliary driving instruction method of the present invention, including:
In step S710, when it is determined that the driver is a brand new driver through face recognition, instructional contents of the intelligent auxiliary driving function are provided to the driver.
Step S720, acquiring the running speed of the vehicle through a vehicle sensor.
Step S730, determining whether the vehicle is in a stationary state according to the running speed.
Step S740, stopping providing the guidance content to the driver when the vehicle is in a non-stationary state.
Compared with the sixth embodiment, the seventh embodiment includes step S750, step S760, and other steps are the same as those of the sixth embodiment, and will not be described again.
Step S750, obtaining the operation instruction of the driver in real time.
In this embodiment, the vehicle central control acquires an operation instruction of the driver in real time, where the operation instruction refers to an operation instruction that the driver actively requests to provide instruction content of the intelligent auxiliary driving function. The user can give the instruction through a specific key button; the instruction can also be sent out by clicking a corresponding button on the vehicle display screen; and are not limited in this regard.
Step S760, when an operation instruction of the driver to actively request to provide the instructional content is acquired, the instructional content is provided to the driver again, so that the driver learns the instructional content.
In this embodiment, when the vehicle center controller acquires the operation instruction of the driver's initiative request to provide the guidance content of the intelligent auxiliary driving function, the guidance content of the intelligent auxiliary driving function is newly provided to the driver for the driver to learn. Because the vehicle is in a non-stationary state at this time, in order to ensure driving safety, it is preferable to learn the guidance content providing the intelligent auxiliary driving function to the user in the form of an audio file.
In the technical scheme provided by the embodiment, the vehicle central control acquires the operation instruction of the driver in real time, wherein the operation instruction refers to the operation instruction of the driver for actively requesting to provide the intelligent auxiliary driving function instruction content; when the vehicle central control acquires an operation instruction of the driver for actively requesting to provide the instruction content of the intelligent auxiliary driving function, the instruction content of the intelligent auxiliary driving function is provided to the driver again for the driver to learn. Because the vehicle is in a non-stationary state at this time, in order to ensure driving safety, it is preferable to learn the guidance content providing the intelligent auxiliary driving function to the user in the form of an audio file. Therefore, driving safety is guaranteed, and guiding content can be provided for a user to learn.
The present invention also provides an apparatus comprising a memory, a processor, and a determination program of a cause of display blackout stored in the memory and executable on the processor, which when executed by the processor, implements the respective steps of the determination method of a cause of display blackout as described above.
The present invention also provides a computer-readable storage medium storing a program for determining a cause of display blackout, which when executed by a processor, implements the steps of the method for determining a cause of display blackout as described above.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
It will be appreciated by those skilled in the art that 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 invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (4)
1. An intelligent driving assistance guidance method, characterized in that the intelligent driving assistance guidance method comprises the following steps:
starting a face recognition system to judge whether the driver is a brand new driver or not;
When judging that a driver is a brand new driver through face recognition, providing instruction content of intelligent auxiliary driving functions for the driver, wherein the intelligent auxiliary driving is an advanced driving auxiliary system which utilizes various sensors installed on a vehicle to sense surrounding environment at any time in the running process of the vehicle, collects data, performs identification, detection and tracking of static and dynamic objects, combines navigation map data and performs operation and analysis of the system, and the instruction content is presented in at least one form of the following documents: audio files, video files, graphics files, network link files, and text files;
Judging whether the vehicle is in a stationary state or not;
continuing to provide the coaching content to the driver while the vehicle is stationary for the driver to learn the coaching content;
stopping providing the coaching content to the driver when the vehicle is in a non-stationary state;
the determining whether the vehicle is in a stationary state includes:
acquiring the running speed of the vehicle through a vehicle sensor;
Judging whether the vehicle is in a static state or not according to the running speed;
after the step of starting the face recognition system to determine whether the driver is a brand new driver, the method further includes:
when the face recognition system judges that the driver is a non-brand new driver, the guidance content of the intelligent auxiliary driving function is not provided;
after the step of not providing the guidance content of the intelligent driving assistance function when the face recognition system judges that the driver is not a brand new driver, the method further comprises:
The method comprises the steps of acquiring a target retrieval instruction corresponding to a target intelligent auxiliary driving function triggered by a target function starting component by a driver, wherein the target function starting component is a key capable of being pressed up and down, a deflector rod capable of being pulled left and right, a rotary knob or a button capable of sliding left and right in a vehicle, and the target intelligent auxiliary driving function comprises the following steps: the vehicle comprises a self-adaptive cruising function, a lane deviation alarming function, a lane keeping function, a collision avoidance or pre-collision function, a night vision function, a self-adaptive light control function, a pedestrian protection function, an automatic parking function, a traffic sign recognition function, a blind spot detection function, a driver fatigue detection function, a downhill control function and an electric vehicle alarming function;
and determining corresponding instruction content in the instruction content according to the target retrieval instruction, and providing the corresponding instruction content for the driver for learning.
2. The intelligent driving assistance guidance method according to claim 1, characterized in that after the step of stopping the providing of the guidance content to the driver when the vehicle is in a non-stationary state, further comprises:
acquiring an operation instruction of the driver in real time;
and when an operation instruction of the driver for actively requesting to provide the guidance content is acquired, the guidance content is provided to the driver again so that the driver can learn the guidance content.
3. An apparatus comprising a memory, a processor, and an intelligent auxiliary driving coaching program stored in the memory and executable on the processor, which when executed by the processor, implements the steps of the intelligent auxiliary driving coaching method of any of claims 1-2.
4. A computer readable storage medium, characterized in that the computer readable storage medium stores an intelligent auxiliary driving coaching program that, when executed by a processor, implements the steps of the intelligent auxiliary driving coaching method according to any one of claims 1-2.
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