CN119037459A

CN119037459A - Method and device for determining vehicle safe driving reminding strategy and electronic equipment

Info

Publication number: CN119037459A
Application number: CN202411116746.9A
Authority: CN
Inventors: 刘莉莉; 林杰; 张银友; 梁婷; 崔宇健; 林之鹏
Original assignee: FAW Group Corp
Current assignee: FAW Group Corp
Priority date: 2024-08-14
Filing date: 2024-08-14
Publication date: 2024-11-29

Abstract

The present invention discloses a method, device and electronic device for determining a vehicle safe driving reminder strategy. The method includes: obtaining the driving state information of the target vehicle and the behavior information of the driver, wherein the behavior information includes the driver's eye state information and hand movement trajectory information; performing a vehicle risk assessment on the behavior information based on the driving state information to obtain a target assessment result, wherein the target assessment result is used to determine whether the target vehicle is in a safe driving state; determining a safe driving reminder strategy according to the target assessment result, wherein the safe driving reminder strategy is used to remind the driver to drive safely. The present invention solves the technical problems of the single form and low efficiency of the method for determining the vehicle safe driving reminder strategy in the related art.

Description

Method and device for determining vehicle safe driving reminding strategy and electronic equipment

Technical Field

The invention relates to the technical field of vehicles, in particular to a method and a device for determining a vehicle safe driving reminding strategy and electronic equipment.

Background

Traffic safety problems have been a major problem worldwide. Particularly, in the case of fatigue driving of a driver, its ability to perceive the surrounding environment, its ability to judge traveling, and its ability to operate the vehicle are greatly affected. This is more likely to cause traffic accidents, resulting in irrecoverable losses.

However, most of the current detection of fatigue driving depends on technologies such as infrared sensors. Although these techniques can provide some assistance, their range of application and detection accuracy remain limited. In addition, although there are studies to analyze the risk behaviors of drivers through linear regression analysis, these methods focus on only a single risk factor and cannot comprehensively evaluate various risk factors during driving. Such a judgment method not only risks erroneous judgment, but also easily affects the normal driving of the driver. Therefore, the existing vehicle safe driving reminder strategy is relatively single in form and low in efficiency.

In view of the above problems, no effective solution has been proposed at present.

Disclosure of Invention

The embodiment of the invention provides a method and a device for determining a vehicle safe driving reminding strategy and electronic equipment, which at least solve the technical problems of single form and low efficiency of the method for determining the vehicle safe driving reminding strategy in the related technology.

According to one embodiment of the invention, a method for determining a safe driving reminding strategy of a vehicle is provided, which comprises the steps of obtaining driving state information of a target vehicle and behavior information of a driver, wherein the behavior information comprises eye state information and hand movement track information of the driver, carrying out vehicle risk assessment on the behavior information based on the driving state information to obtain a target assessment result, wherein the target assessment result is used for determining whether the target vehicle is in a safe driving state, and determining the safe driving reminding strategy according to the target assessment result, wherein the safe driving reminding strategy is used for reminding the driver of safe driving.

Optionally, acquiring the eye state information of the driver includes acquiring video information of the driver, and analyzing the video information by using a deep learning algorithm to obtain the eye state information.

Optionally, acquiring the hand movement track information of the driver comprises acquiring first voltage information and preset time information in response to the sensor device detecting the hand of the driver, performing noise reduction processing on the first voltage information to obtain target voltage information, and determining the hand movement track information based on the target voltage information and the preset time information.

Optionally, performing risk assessment on the behavior information based on the driving state information to obtain a target assessment result comprises performing vehicle risk assessment on the eye state information based on the driving state information to obtain a first assessment result, performing vehicle risk assessment on the hand movement track information based on the driving state information to obtain a second assessment result, and determining the target assessment result based on the first assessment result and the second assessment result.

Optionally, the vehicle risk assessment is performed on the eye state information based on the driving state information to obtain a first assessment result, wherein the first assessment result comprises that the eye state information is compared with a preset eye height difference threshold value to obtain a comparison result in response to the target vehicle being in a driving state, and the first assessment result is determined to be in a non-safe driving state for the driver in response to the comparison result determining that the eye state information is smaller than the preset eye height difference threshold value.

Optionally, vehicle risk assessment is performed on the mobile track information of the mobile station based on the driving state information to obtain a second assessment result, wherein the step of performing regression analysis on the mobile track information of the mobile station to obtain an analysis result is performed in response to the target vehicle being in the driving state, and the step of determining that the second assessment result is that the driver is in the unsafe driving state in response to the analysis result being greater than or equal to the risk threshold.

Optionally, determining the target evaluation result based on the first evaluation result and the second evaluation result includes determining that the target vehicle is in a non-safe driving state in response to the first evaluation result and the second evaluation result determining that the driver is in a non-safe driving state.

Optionally, determining the safe driving reminder strategy according to the target evaluation result comprises executing the safe driving reminder strategy in response to determining that the target evaluation result is that the target vehicle is in an unsafe driving state.

According to one embodiment of the invention, the device for determining the safe driving reminding strategy of the vehicle comprises an acquisition module, an evaluation module and a determination module, wherein the acquisition module is used for acquiring the driving state information of the target vehicle and the behavior information of the driver, the behavior information comprises the eye state information and the hand movement track information of the driver, the evaluation module is used for performing vehicle risk evaluation on the behavior information based on the driving state information to obtain a target evaluation result, the target evaluation result is used for judging whether the target vehicle is in a safe driving state or not, and the determination module is used for determining the safe driving reminding strategy according to the target evaluation result.

Optionally, the acquisition module is further used for acquiring video information of the driver and analyzing the video information by using a deep learning algorithm to obtain eye state information.

Optionally, the acquisition module is further used for acquiring the first voltage information and the preset time information in response to the detection of the hand of the driver by the sensor equipment, the determination device of the vehicle safe driving reminding strategy further comprises a processing module used for conducting noise reduction processing on the first voltage information to obtain target voltage information, and the determination module is further used for determining hand movement track information based on the target voltage information and the preset time information.

Optionally, the evaluation module is further used for performing vehicle risk evaluation on the eye state information based on the driving state information to obtain a first evaluation result, performing vehicle risk evaluation on the hand movement track information based on the driving state information to obtain a second evaluation result, and the determination module is further used for determining a target evaluation result based on the first evaluation result and the second evaluation result.

Optionally, the processing module is further configured to compare the eye state information with a preset eye height difference threshold value in response to the target vehicle being in a driving state, and the determining module is further configured to determine that the first evaluation result is that the driver is in a non-safe driving state in response to the comparison result determining that the eye state information is smaller than the preset eye height difference threshold value.

Optionally, the processing module is further configured to perform regression analysis on the hand movement track information in response to the target vehicle being in a driving state to obtain an analysis result, and the determining module is further configured to determine that the second evaluation result is that the driver is in a non-safe driving state in response to the analysis result being greater than or equal to a risk threshold.

Optionally, the determining module is further configured to determine, in response to the first evaluation result and the second evaluation result, that the driver is in the unsafe driving state, that the target evaluation result is that the target vehicle is in the unsafe driving state.

Optionally, the processing module is further configured to execute a safe driving reminding policy in response to determining that the target evaluation result is that the target vehicle is in the unsafe driving state.

According to one embodiment of the invention, the electronic equipment further comprises a memory and a processor, wherein the memory stores an executable program, and the processor is used for running the program, and the method for determining the vehicle safe driving reminding strategy is executed when the program runs.

According to an embodiment of the present invention, there is further provided a computer readable storage medium, the computer readable storage medium including a stored executable program, wherein when the executable program runs, a device on which the computer readable storage medium is controlled to execute the above-described determination method of the vehicle safe driving reminding policy.

According to an embodiment of the present invention, there is also provided a computer program product including a computer program which, when executed by a processor, implements the above-mentioned method for determining a safe driving reminder strategy for a vehicle.

According to the method and the device for determining the safe driving reminding strategy, the mode of acquiring the driving state information of the target vehicle and the behavior information of the driver is adopted, the vehicle risk assessment is carried out on the behavior information based on the driving state information to obtain the target assessment result, and finally the safe driving reminding strategy is determined according to the target assessment result, so that the purpose of rapidly and accurately judging whether the driver is in the safe driving state is achieved, the technical effects of comprehensively judging whether the vehicle is in the safe driving state according to different factors and improving the determining efficiency of the vehicle safe driving reminding strategy are achieved, and the technical problems that the determining method of the vehicle safe driving reminding strategy in the related art is single in form and low in efficiency are solved.

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 specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 is a flow chart of a method of determining a safe driving reminder strategy for a vehicle, according to one embodiment of the invention;

FIG. 2 is a schematic diagram of a method of determining a safe driving reminder strategy for a vehicle according to one embodiment of the invention;

FIG. 3 is a schematic illustration of a method of determining a safe-driving reminder strategy for a vehicle, according to one embodiment of the invention;

FIG. 4 is a schematic illustration of a method of determining a safe-driving reminder strategy for a vehicle, according to one embodiment of the invention;

FIG. 5 is a flow chart of a method of determining a safe-driving reminder strategy for a vehicle, according to yet another embodiment of the present invention;

fig. 6 is a block diagram of a configuration of a determination device of a safe driving reminder strategy for a vehicle according to one embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

According to an embodiment of the present invention, there is provided a method embodiment of a method for determining a safe driving reminder strategy for a vehicle, it being noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer-executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different from that herein.

The method embodiments may be performed in an electronic device or similar computing device that includes a memory and a processor. Taking an example of operation on a vehicle terminal, the vehicle terminal may include one or more processors (which may include, but are not limited to, a central Processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU), a Digital Signal Processing (DSP) chip, a microprocessor (Micro Controller Unit, MCU), a programmable logic device (Field Programmable GATE ARRAY, FPGA), a neural network processor (Neural-network Processor Unit, NPU), a tensor processor (Tensor Processing Unit, TPU), an artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) type processor, etc., and a memory for storing data. Alternatively, the vehicle terminal may further include a transmission device, an input-output device, and a display device for a communication function. It will be appreciated by those skilled in the art that the above description of the structure is merely illustrative and is not intended to limit the structure of the vehicle terminal. For example, the vehicle terminal may also include more or fewer components than the above structural description, or have a different configuration than the above structural description.

The memory may be used to store a computer program, for example, a software program of an application software and a module, for example, a computer program corresponding to a method for determining a vehicle safe driving reminding policy in an embodiment of the present invention, and the processor executes various functional applications and data processing by running the computer program stored in the memory, that is, implements the method for determining a vehicle safe driving reminding policy described above. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory. In some examples, the memory may further include memory remotely located with respect to the processor, the remote memory being connectable to the mobile terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission means is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission means comprises a network adapter (Network Interface Controller, simply referred to as NIC) that can be connected to other network devices via a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used to communicate with the internet wirelessly.

Display devices may be, for example, touch screen type liquid crystal displays (Liquid Crustal Display, LCDs) and touch displays (also referred to as "touch screens" or "touch display screens"). The liquid crystal display may enable a user to interact with a user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GRAPHICAL USER INTERFACE, GUI) with which a user can interact with the GUI by touching finger contacts and/or gestures on the touch-sensitive surface, where the human-machine interaction functionality optionally includes interactions such as creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving electronic mail, talking interfaces, playing digital video, playing digital music and/or web browsing, etc., executable instructions for performing the human-machine interaction functionality described above are configured/stored in one or more processor-executable computer program products or readable storage mediums.

Fig. 1 is a flowchart of a method for determining a safe driving reminder strategy for a vehicle according to one embodiment of the present invention, as shown in fig. 1, the method comprising the steps of:

step S10, acquiring running state information of a target vehicle and behavior information of a driver, wherein the behavior information comprises eye state information and hand movement track information of the driver;

in step S10, the running state information of the target vehicle is used to indicate that the target vehicle is in a power-on non-running state or running state.

The eye state information of the driver is used for representing the height difference between the upper eyelid and the lower eyelid of the driver in the driving process.

The hand movement track information is used for representing the movement distance and time between the hand and the center console during driving of the driver.

Step S12, carrying out vehicle risk assessment on the behavior information based on the running state information to obtain a target assessment result, wherein the target assessment result is used for determining whether the target vehicle is in a safe running state or not;

Specifically, when the target vehicle is in a driving state, vehicle risk assessment is performed on behavior information of the driver to determine that the driver is in a safe driving state, and then a target assessment result is obtained to determine whether the target vehicle is in the safe driving state in the current driving process.

Step S14, determining a safe driving reminding strategy according to the target evaluation result, wherein the safe driving reminding strategy is used for reminding a driver of safe driving.

In step S14, the above-mentioned safe driving reminding strategy includes, but is not limited to, (1) installing a vibrator at the position of a seat or a steering wheel, when the real-time monitoring device judges that the target vehicle is in an unsafe driving state, the vibrator generates vibration to remind the driver, and simultaneously, the voice alarm sends out a reminder to remind the driver of driving safety, (2) setting a remote reminding device to remind the driver through a remote audio/video phone in order to avoid the fault of the real-time monitoring device, and (3) when the target vehicle is still in the unsafe driving state after the two strategies are used, controlling the target vehicle to start an automatic safe driving mode, wherein the direction and the speed and other conventional control parameters are uniformly transmitted to the automatic driving mode to control.

Specifically, fig. 2 is a schematic diagram of a method for determining a vehicle safe driving reminding policy according to an embodiment of the present invention, as shown in fig. 2, a vehicle smart card (INTELLIGENT CARD for Vehicles) card is inserted into a card reader, and after the card reader identifies the vehicle IC card, a target vehicle, a real-time monitoring device, an alarm device and a remote reminding device are all in an on state. The camera in the real-time monitoring device is utilized to acquire eye state information of a driver, and the time detector and the infrared sensor in the real-time monitoring device acquire movement distance and time between hands of the driver and the center console, namely hand movement track information. And transmitting the acquired behavior information of the driver to the processor, and further evaluating whether the driver is in a safe driving state or not, so as to judge whether the target vehicle is in a safe driving state or not. When the target vehicle is judged to be in the unsafe driving state, the alarm device executes a vehicle safe driving reminding strategy so as to remind a driver of paying attention to driving safety, wherein the alarm device comprises a vibrator, a voice alarm and a remote reminding device. In order to avoid the fault of the real-time monitoring device, a remote reminding device is arranged, the driver is reminded through a remote audio-video telephone, when the target vehicle is still in the unsafe driving state after the two strategies are used, the target vehicle is controlled to start an automatic safe driving mode, and the direction and the speed and other conventional control parameters are uniformly transmitted to the automatic driving mode to be controlled.

Based on the steps S10 to S14, the method adopts a mode of acquiring the running state information of the target vehicle and the behavior information of the driver, carries out vehicle risk assessment on the behavior information based on the running state information to obtain a target assessment result, and finally determines a safe driving reminding strategy according to the target assessment result, thereby achieving the purpose of rapidly and accurately judging whether the driver is in a safe driving state, realizing the technical effects of comprehensively judging whether the vehicle is in the safe driving state by different factors and improving the determination efficiency of the safe driving reminding strategy of the vehicle, and further solving the technical problems of single form and low efficiency of the determination method of the safe driving reminding strategy of the vehicle in the related technology.

Optionally, in step S10, acquiring eye state information of the driver includes:

Step S101, collecting video information of a driver;

Step S102, analyzing the video information by using a deep learning algorithm to obtain eye state information.

Specifically, the camera is arranged in front of the driver, video information of the driver is collected, the collected video information is analyzed by using a face recognition algorithm, and the maximum height difference between upper and lower eyelid of the driver is obtained.

Based on the steps S101 to S102, the video information of the driver is acquired, the video information is analyzed by a deep learning algorithm to obtain eye state information, the real-time monitoring of the state of the driver can be ensured by acquiring the video information of the driver in real time, the unsafe driving state can be found in time, the video information is analyzed by the deep learning algorithm, and the recognition accuracy of the eye state information can be improved.

Optionally, in step S10, acquiring the hand movement trajectory information of the driver includes:

step S103, in response to the sensor device detecting the hand of the driver, acquiring first voltage information and preset time information;

Step S104, noise reduction processing is carried out on the first voltage information to obtain target voltage information;

Step S105, determining hand movement trajectory information based on the target voltage information and the preset time information.

Specifically, fig. 3 is a schematic diagram of a determining method of a safe driving reminding strategy of a vehicle according to another embodiment of the present invention, and as shown in fig. 3, an infrared sensor 1, an infrared sensor 2 and an infrared sensor 3 are respectively installed at different positions of a central control function control area of the vehicle. Such as air conditioning buttons, wind direction control buttons, and air volume control buttons. The three infrared sensors are used for measuring the moving distance and time between the hand and the center console in the driving process of the driver. The infrared sensor emits infrared light toward the driver's hand, and reflects and absorbs the infrared light through the hand to determine whether the driver's hand is detected. When the infrared sensor detects the hand of the driver, the voltage value is output by measuring the amount of absorbed infrared light, and the distance between the hand and the infrared sensor is calculated. But when the distance between the driver's hand and the infrared sensor is collected, the infrared sensor generates noise in the process, and the generated noise may cause the raw data of the measured voltage value to be difficult to analyze. Therefore, in order to more accurately collect distance data between the hands of the driver and the center console, a filter device such as a filter is used for filtering noise of the infrared sensor.

Still further, a multi-function data acquisition (Multifunction Data Acquisition, MDAQ) device is employed to collect more accurate frame data of the distance and time of movement of the driver's hand and the infrared sensor. In order to monitor the measurement of the exact distance between the driver's hand and the infrared sensors collected from the data acquisition device, the distance between the driver's hand and each of the three infrared sensors, as well as the total time, are acquired in real time using graphical programming language software (Labview).

Based on the steps S103 to S105, the first voltage information and the preset time information are acquired in response to the detection of the hands of the driver by the sensor equipment, noise reduction processing is carried out on the first voltage information to obtain target voltage information, hand movement track information is determined based on the target voltage information and the preset time information, noise of the infrared sensor is filtered by using a filter and other filtering devices, measurement errors can be reduced, accuracy of the hand movement track information is improved, and the movement condition of the hands of the driver can be monitored more comprehensively by installing the infrared sensor in a vehicle central control function control area, so that more comprehensive hand movement track information is obtained.

Optionally, in step S12, performing risk assessment on the behavior information based on the driving state information, and obtaining the target assessment result includes:

Step S121, carrying out vehicle risk assessment on eye state information based on the driving state information to obtain a first assessment result;

Step S122, carrying out vehicle risk assessment on the mobile track information of the hand based on the running state information to obtain a second assessment result;

Step S123, determining a target evaluation result based on the first evaluation result and the second evaluation result.

Specifically, in the driving process of the target vehicle, vehicle risk assessment is performed on eye state information of a driver to obtain a first assessment result, wherein the first assessment result is used for representing whether the driver is in a non-safe driving state. And in the running process of the target vehicle, carrying out vehicle risk assessment on the hand movement track information of the driver to obtain a second assessment result, wherein the second assessment result is used for representing whether the driver is in a non-safe driving state. And determining whether the target vehicle is in a safe driving state according to the first evaluation result and the second evaluation result.

Based on the steps S121 to S123, the vehicle risk assessment is carried out on the eye state information based on the driving state information to obtain a first assessment result, the vehicle risk assessment is carried out on the hand movement track information based on the driving state information to obtain a second assessment result, and the target assessment result is determined based on the first assessment result and the second assessment result, so that the purpose of rapidly and accurately judging whether a driver is in a safe driving state is achieved, the technical effects of judging whether the vehicle is in the safe driving state or not according to different factors and improving the determination efficiency of the vehicle safe driving reminding strategy are achieved, and the technical problems that the determination method of the vehicle safe driving reminding strategy in the related art is single in form and low in efficiency are solved.

Optionally, in step S121, performing vehicle risk assessment on the eye state information based on the driving state information, and obtaining the first assessment result includes:

step S1211, in response to the target vehicle being in a driving state, comparing the eye state information with a preset eye height difference threshold value to obtain a comparison result;

In step S1212, in response to the comparison result determining that the eye state information is less than the preset eye height difference threshold, the first evaluation result is determined that the driver is in the unsafe driving state.

Specifically, when the target vehicle is in a driving state, video information acquired by the camera is subjected to a face recognition algorithm to obtain the maximum height difference between the upper eyelid and the lower eyelid. And determining a preset eye height difference threshold according to the height difference between the upper eyelid and the lower eyelid when the driver is in good condition. After continuously processing a plurality of video information, comparing the maximum height difference between the upper eyelid and the lower eyelid of the driver with a preset eye height difference threshold. And if the maximum height difference between the upper eyelid and the lower eyelid of the driver is lower than a preset threshold value, judging that the driver is in an unsafe driving state.

Based on the steps S1211 to S1212, the eye state information is compared with the preset eye height difference threshold value to obtain a comparison result in response to the target vehicle being in a driving state, the first evaluation result is determined to be that the driver is in an unsafe driving state in response to the comparison result being determined to be that the eye state information is smaller than the preset eye height difference threshold value, the real-time video information is adopted for analysis, the change of the driver state can be more accurately captured, more timely risk evaluation is provided, and personalized risk evaluation can be carried out according to the actual state of the driver through the preset eye height difference threshold value instead of the unified standard, so that the evaluation accuracy is improved.

Optionally, in step S122, performing vehicle risk assessment on the hand movement track information based on the driving state information, and obtaining the second assessment result includes:

Step S1221, performing regression analysis on the mobile track information of the hand in response to the target vehicle being in a driving state, so as to obtain an analysis result;

step S1222, in response to the analysis result being greater than or equal to the risk threshold, determining that the second evaluation result is that the driver is in the unsafe driving state.

Specifically, the collected frame data is processed by adopting a linear regression analysis mode, wherein the frame data refers to frame data of a moving distance and time between a driver hand and an infrared sensor, which are collected by adopting MDAQ equipment. The linear regression equation obtained from the frame data is shown in expression (1).

Where Ev _i represents a result of analysis of hand movement trajectory information corresponding to the ith frame data, u ^IR1、u^IR2、u^IR3 represents distances between the hand and the three sensors, u ^t represents movement times of the hand at the three infrared sensors, β ₀、β₁、β₂、β₃、β₄ represents a regression coefficient, and i represents the ith frame data, respectively.

Specifically, the risk threshold is set according to frame data acquired when the driver's state is good. And (3) calculating a hand movement track information analysis result corresponding to the ith frame data according to the currently acquired frame data in the expression (1), and comparing the analysis result with a risk threshold. If the analysis result of the hand movement track information corresponding to the currently collected frame data is greater than or equal to the risk threshold value, the second evaluation result is determined that the driver is in the unsafe driving state.

Specifically, fig. 4 is a schematic diagram of a method for determining a safe driving reminding strategy of a vehicle according to one embodiment of the present invention, and as shown in fig. 4, first, a multifunctional data acquisition (Multifunction Data Acquisition, MDAQ) device is used to collect more accurate frame data of the movement distance and time of the driver's hand and the infrared sensor in real time. Secondly, in order to collect distance data between the hands of the driver and the center console more accurately, a filter device such as a filter is adopted to filter noise of the infrared sensor. Then, the collected frame data of the driver is processed by adopting a linear regression method and a regression coefficient is calculated. And finally, calculating a hand movement track information analysis result corresponding to the ith frame data according to the currently acquired frame data and the expression (1), and comparing the analysis result with a risk threshold. If the analysis result of the hand movement track information corresponding to the currently collected frame data is greater than or equal to the risk threshold value, the second evaluation result is determined that the driver is in the unsafe driving state. If the analysis result of the hand movement track information corresponding to the currently collected frame data is smaller than the risk threshold value, the second evaluation result is determined that the driver is in a safe driving state.

Based on the steps S1221 to S1222, in response to the target vehicle being in a driving state, carrying out regression analysis on the hand movement track information to obtain an analysis result, and in response to the analysis result being greater than or equal to a risk threshold, determining that the second evaluation result is that the driver is in a non-safe driving state, modeling and analyzing the driver behavior by adopting a linear regression method, so that the evaluation result is more scientific and accurate, setting the risk threshold based on frame data acquired by the driver when the state is good, enabling the evaluation result to have more pertinence and practicability, and flexibly determining whether the driver is in the safe driving state according to a comparison result of the hand movement track information analysis result and the risk threshold.

Optionally, in step S123, determining the target evaluation result based on the first evaluation result and the second evaluation result includes:

In step S1231, in response to the first evaluation result and the second evaluation result determining that the driver is in the unsafe driving state, the target evaluation result is determined that the target vehicle is in the unsafe driving state.

Specifically, when both the first evaluation result and the second evaluation result are determined that the driver is in the unsafe driving state, the target evaluation result is determined that the target vehicle is in the unsafe driving state.

Based on the step S1231, the driver is determined to be in the unsafe driving state in response to the first evaluation result and the second evaluation result, and the target evaluation result is determined to be that the target vehicle is in the unsafe driving state, so as to achieve the purpose of rapidly and accurately judging whether the driver is in the safe driving state, thereby realizing the technical effects of judging whether the vehicle is in the safe driving state by combining different factors, improving the determination efficiency of the vehicle safe driving reminding strategy, and further solving the technical problems of single form and low efficiency of the determination method of the vehicle safe driving reminding strategy in the related art.

Optionally, in step S14, determining the safe driving alert strategy according to the target evaluation result includes:

in step S141, in response to determining that the target evaluation result is that the target vehicle is in the unsafe driving state, a safe driving alert strategy is executed.

Specifically, when the target evaluation result is determined that the target vehicle is in the unsafe driving state, a safe driving reminding strategy is executed. The vibrator arranged at the positions of the seat and the steering wheel generates vibration to remind a driver, and the voice alarm sends out reminding to remind the driver of driving safety; and setting a remote reminding device, and reminding a driver through a remote audio/video telephone. When the target vehicle is still in the unsafe driving state after the strategy is used, the control target vehicle starts an automatic safe driving mode, and conventional control parameters such as the direction, the vehicle speed and the like are uniformly transmitted to the automatic driving mode for control.

Specifically, the driver can be stimulated to feel and feel simultaneously through the vibrator at the positions of the seat and the steering wheel and the voice alarm, and the reminding efficiency and effect are improved. The intensity of the vibrator and the content and intonation of the voice alarm can be adjusted according to the preference and response characteristics of the driver so as to adapt to the requirements of different drivers. Through remote reminding device, relevant personnel can real-time supervision vehicle state, in time provides feedback and suggestion to the driver, reinforcing safety guarantee. When the driver does not react to the prompt or the vehicle is still in an unsafe state, the intervention of the automatic safe driving mode can reduce human errors and improve driving safety.

Based on the above step S141, in response to determining that the target vehicle is in the unsafe driving state as the target evaluation result, the safe driving reminding strategy is executed, which helps to reduce traffic accidents caused by inattention or fatigue driving of the driver by identifying and reminding the driver of the safe driving in advance.

Fig. 5 is a flowchart of a method for determining a safe driving reminder strategy for a vehicle according to another embodiment of the present invention, as shown in fig. 5, the method comprising the steps of:

Step S501, acquiring running state information of a target vehicle and behavior information of a driver, wherein the behavior information comprises eye state information and hand movement track information of the driver;

Step S502, in response to the target vehicle being in a driving state, comparing the eye state information with a preset eye height difference threshold value to obtain a comparison result;

Step S503, determining that the first evaluation result is that the driver is in the unsafe driving state in response to the comparison result determining that the eye state information is smaller than the preset eye height difference threshold value;

step S504, carrying out regression analysis on the mobile track information of the hand in response to the target vehicle being in a running state, so as to obtain an analysis result;

Step S505, determining that the second evaluation result is that the driver is in the unsafe driving state in response to the analysis result being greater than or equal to the risk threshold;

Step S506, in response to the first evaluation result and the second evaluation result determining that the driver is in the unsafe driving state, determining that the target evaluation result is that the target vehicle is in the unsafe driving state;

In step S507, in response to determining that the target evaluation result is that the target vehicle is in the unsafe driving state, a safe driving reminder strategy is executed.

Based on the steps S501 to S507, the method for acquiring the running state information of the target vehicle and the behavior information of the driver is adopted, the vehicle risk assessment is carried out on the behavior information based on the running state information to obtain a target assessment result, and finally, the safe driving reminding strategy is determined according to the target assessment result, so that the aim of rapidly and accurately judging whether the driver is in a safe driving state is fulfilled, the technical effects of comprehensively judging whether the vehicle is in the safe driving state according to different factors and improving the determining efficiency of the safe driving reminding strategy of the vehicle are realized, and the technical problems that the determining method of the safe driving reminding strategy of the vehicle in the related art is single in form and low in efficiency are solved.

From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.

The embodiment of the invention also provides a device for determining the vehicle safe driving reminding strategy, which is used for realizing the embodiment and the preferred implementation mode, and the description is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Fig. 6 is a block diagram of a configuration of a determination device of a safe driving reminder strategy for a vehicle according to one embodiment of the present invention. As shown in fig. 6, the apparatus includes:

An obtaining module 601, configured to obtain driving state information of a target vehicle and behavior information of a driver, where the behavior information includes eye state information and hand movement track information of the driver;

The evaluation module 602 is configured to perform vehicle risk evaluation on the behavior information based on the driving state information to obtain a target evaluation result, where the target evaluation result is used to determine whether the target vehicle is in a safe driving state;

the determining module 603 is configured to determine a safe driving reminding policy according to the target evaluation result.

Optionally, the obtaining module 601 is further configured to collect video information of the driver, and analyze the video information by using a deep learning algorithm to obtain eye state information.

Optionally, the acquiring module 601 is further configured to acquire the first voltage information and the preset time information in response to the sensor device detecting the hand of the driver, the determining device of the vehicle safe driving reminding policy further includes a processing module 604 configured to perform noise reduction processing on the first voltage information to obtain the target voltage information, and the determining module 603 is further configured to determine the hand movement track information based on the target voltage information and the preset time information.

Optionally, the evaluation module 602 is further configured to perform vehicle risk evaluation on the eye state information based on the driving state information to obtain a first evaluation result, perform vehicle risk evaluation on the hand movement track information based on the driving state information to obtain a second evaluation result, and the determination module 306 is further configured to determine a target evaluation result based on the first evaluation result and the second evaluation result.

Optionally, the processing module 604 is further configured to compare the eye state information with a preset eye height difference threshold value in response to the target vehicle being in a driving state, and the determining module 603 is further configured to determine that the first evaluation result is that the driver is in a non-safe driving state in response to the comparison result determining that the eye state information is less than the preset eye height difference threshold value.

Optionally, the processing module 604 is further configured to perform regression analysis on the hand movement track information to obtain an analysis result in response to the target vehicle being in a driving state, and the determining module 603 is further configured to determine that the second evaluation result is that the driver is in a non-safe driving state in response to the analysis result being greater than or equal to the risk threshold.

Optionally, the determining module 603 is further configured to determine that the target evaluation result is that the target vehicle is in the unsafe driving state in response to the first evaluation result and the second evaluation result determining that the driver is in the unsafe driving state.

Optionally, the processing module 604 is further configured to execute a safe driving alert strategy in response to determining that the target evaluation result is that the target vehicle is in a non-safe driving state.

It should be noted that each of the above modules may be implemented by software or hardware, and the latter may be implemented by, but not limited to, the above modules all being located in the same processor, or each of the above modules being located in different processors in any combination.

Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:

step S1, acquiring running state information of a target vehicle and behavior information of a driver, wherein the behavior information comprises eye state information and hand movement track information of the driver;

step S2, carrying out vehicle risk assessment on the behavior information based on the running state information to obtain a target assessment result, wherein the target assessment result is used for determining whether the target vehicle is in a safe running state or not;

And step S3, determining a safe driving reminding strategy according to the target evaluation result, wherein the safe driving reminding strategy is used for reminding a driver of safe driving.

Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:

Alternatively, in the present embodiment, the storage medium may include, but is not limited to, a USB flash disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, etc. various media in which a computer program may be stored.

Alternatively, in the present embodiment, the above-described computer program product may be provided as a computer program that performs the steps of:

Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.

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.

In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. The storage medium includes a U disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, etc. which can store the program code.

The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims

1. A method for determining a safe driving reminder strategy for a vehicle, comprising:

acquiring running state information of a target vehicle and behavior information of a driver, wherein the behavior information comprises eye state information and hand movement track information of the driver;

Performing vehicle risk assessment on the behavior information based on the running state information to obtain a target assessment result, wherein the target assessment result is used for determining whether the target vehicle is in a safe running state or not;

And determining a safe driving reminding strategy according to the target evaluation result, wherein the safe driving reminding strategy is used for reminding the driver of safe driving.

2. The method for determining a safe driving reminder strategy for a vehicle according to claim 1, wherein acquiring the eye state information of the driver comprises:

collecting video information of the driver;

and analyzing the video information by using a deep learning algorithm to obtain the eye state information.

3. The method for determining a safe driving reminder strategy for a vehicle according to claim 1, wherein acquiring the hand movement trajectory information of the driver comprises:

Acquiring first voltage information and preset time information in response to the sensor device detecting the hands of the driver;

Noise reduction processing is carried out on the first voltage information to obtain target voltage information;

and determining the hand movement track information based on the target voltage information and the preset time information.

4. The method for determining a safe driving reminder policy for a vehicle according to claim 1, wherein performing a vehicle risk assessment on the behavior information based on the driving state information, obtaining a target assessment result includes:

Performing vehicle risk assessment on the eye state information based on the driving state information to obtain a first assessment result;

Performing vehicle risk assessment on the hand movement track information based on the driving state information to obtain a second assessment result;

and determining a target evaluation result based on the first evaluation result and the second evaluation result.

5. The method of determining a safe driving reminder policy for a vehicle according to claim 4, wherein performing a vehicle risk assessment on the eye state information based on the driving state information, obtaining a first assessment result includes:

Responding to the target vehicle in a running state, and comparing the eye state information with a preset eye height difference threshold value to obtain a comparison result;

And responding to the comparison result to determine that the eye state information is smaller than the preset eye height difference threshold value, and determining that the first evaluation result is that the driver is in a non-safe driving state.

6. The method for determining a safe driving reminder policy for a vehicle according to claim 5, wherein performing a vehicle risk assessment on the hand movement trajectory information based on the driving state information, obtaining a second assessment result includes:

responding to the running state of the target vehicle, carrying out regression analysis on the hand movement track information to obtain an analysis result;

And determining that the second evaluation result is that the driver is in an unsafe driving state in response to the analysis result being greater than or equal to a risk threshold.

7. The method of determining a safe driving reminder strategy for a vehicle according to claim 6, wherein determining a target evaluation result based on the first evaluation result and the second evaluation result comprises:

And in response to the first evaluation result and the second evaluation result, determining that the driver is in the unsafe driving state, determining that the target evaluation result is that the target vehicle is in the unsafe driving state.

8. The method for determining a safe driving reminder strategy for a vehicle according to claim 7, wherein determining the safe driving reminder strategy according to the target evaluation result comprises:

And executing a safe driving reminding strategy in response to determining that the target evaluation result is that the target vehicle is in an unsafe driving state.

9. A determination apparatus for a safe driving reminder strategy for a vehicle, comprising:

The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring running state information of a target vehicle and behavior information of a driver, wherein the behavior information comprises eye state information and hand movement track information of the driver;

The evaluation module is used for carrying out vehicle risk evaluation on the behavior information based on the running state information to obtain a target evaluation result, wherein the target evaluation result is used for judging whether the target vehicle is in a safe running state or not;

And the determining module is used for determining a safe driving reminding strategy according to the target evaluation result.

10. An electronic device, comprising:

a memory storing an executable program;

A processor for running the program, wherein the program, when run, performs the method of determining a safe driving reminder strategy for a vehicle as claimed in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored executable program, wherein the executable program, when run, controls a device in which the storage medium is located to perform the method of determining the safe driving reminder strategy for a vehicle according to any one of claims 1 to 8.

12. A computer program product comprising a computer program which, when executed by a processor, implements the method of determining a safe-driving reminder strategy for a vehicle according to any one of claims 1 to 8.