A method for predicting and intelligently controlling vehicle behavior on highways

Abstract

The present invention relates to the field of vehicle control technology, and relates to a method for predicting and intelligently controlling vehicle behavior on a highway. The method performs temperature information monitoring and image monitoring on a target intelligent vehicle, and then analyzes the seat temperature and internal occupant movements of the target intelligent vehicle. The method is also used for image monitoring and analysis of the driver, and sends the images to a vehicle terminal platform for corresponding operation processing. By monitoring and analyzing the smoking of the internal occupants of the vehicle, the riding comfort of the internal occupants of the vehicle is improved to a certain extent, thereby avoiding harm to the health of all occupants of the vehicle, and is not conducive to interfering with the driver's vision to a certain extent. The method avoids a decrease in the driver's reaction ability to a certain extent, reduces the risk of driving, and brings the most extreme safety and convenience to people's travel, making the vehicle popular with customers.

Description

Technical Field

[0001] The invention belongs to the technical field of vehicle control and relates to a method for predicting and intelligently controlling vehicle behavior on a highway. Background Art

[0002] Vehicle control on highways plays a vital role in ensuring traffic safety, improving road efficiency and reducing environmental pollution. First, effective vehicle control can significantly reduce the incidence of traffic accidents and protect the lives of drivers and passengers; second, reasonable speed control and traffic management can optimize traffic flow, reduce congestion, and improve the capacity of highways, thereby improving economic benefits and travel efficiency; therefore, the implementation of efficient vehicle control measures is a necessary condition to ensure the safe, efficient and environmentally friendly operation of highways.

[0003] 1. There is currently a lack of smoking monitoring and demand analysis for people inside vehicles, which to a certain extent reduces the riding comfort of people inside the vehicle, and thus endangers the health of all people in the vehicle. The smoke in the car reduces visibility and interferes with the driver's vision. Moreover, excessive smoke concentration in the car will reduce the oxygen concentration, which will also reduce the driver's reaction ability, increasing the risk of driving.

[0004] 2. The current lack of analysis and control of vehicle seat temperature is not conducive to improving the physical comfort of personnel to a certain extent, leading to quality problems in vehicle seats, and also reducing the service life and safety of vehicle seats.

[0005] 3. The current lack of monitoring and analysis of distracted driving by vehicle drivers makes it impossible to provide people with the ultimate safety and convenience when traveling, making the vehicles unpopular with customers and reducing passenger satisfaction to a certain extent. Summary of the invention

[0006] In view of the above problems existing in the prior art, the present invention provides a method for predicting and intelligently controlling vehicle behavior on a highway, which is used to solve the above technical problems.

[0007] In order to achieve the above purpose and other purposes, the technical solution adopted by the present invention is as follows:

[0008] The present invention provides a method for predicting and intelligently controlling highway vehicle behavior, the method comprising:

[0009] The target smart vehicle is monitored for temperature information using the monitoring instrument provided by the target smart vehicle, and the internal image of the target smart vehicle is monitored using the high-definition camera deployed on the target smart vehicle;

[0010] According to the temperature information corresponding to the target smart vehicle and the vehicle interior monitoring image, the seat temperature of the target smart vehicle is adjusted and controlled through the vehicle terminal platform;

[0011] According to the vehicle interior monitoring image of the target intelligent vehicle, corresponding image-related operations are performed on the target intelligent vehicle through the vehicle terminal platform;

[0012] The high-definition camera deployed on the target smart vehicle monitors the driving image of the vehicle driver, and based on the corresponding monitored driving image of the vehicle driver, reminds the vehicle driver corresponding to the target smart vehicle through the vehicle terminal platform;

[0013] The vehicle terminal platform performs corresponding operation processing according to the operation instructions corresponding to the target intelligent vehicle.

[0014] In a possible implementation, the temperature information corresponding to the target smart vehicle includes an outside temperature and an inside temperature.

[0015] In a possible implementation manner, the seat temperature of the target smart vehicle is adjusted and controlled, and the specific adjustment and control process is as follows:

[0016] A1. According to the temperature information corresponding to the target smart vehicle, the outside temperature and the inside temperature of the target smart vehicle are extracted and recorded as and , and then use the calculation formula , calculate the appropriate seat temperature T corresponding to the target intelligent vehicle, where They represent the highest and lowest temperatures suitable for human body stored in the vehicle database, respectively. Represented as the initial seat temperature corresponding to the target smart vehicle.

[0017] A2. Based on the vehicle interior monitoring image corresponding to the target intelligent vehicle, the positions of the corresponding personnel inside the target intelligent vehicle are extracted, and the internal model diagram corresponding to the target intelligent vehicle is extracted from the vehicle database. The internal seat positions of the target intelligent vehicle are extracted from the internal model diagram corresponding to the target intelligent vehicle, and the positions of the corresponding personnel inside the target intelligent vehicle are compared with the internal seat positions corresponding to the target intelligent vehicle, thereby obtaining the corresponding seat positions of the corresponding personnel inside the target intelligent vehicle.

[0018] A3. The seat positions and suitable seat temperatures corresponding to each person in the target smart vehicle are sent to the vehicle terminal platform. The vehicle terminal platform adjusts and controls the seat positions corresponding to each person in the target smart vehicle according to the suitable seat temperatures corresponding to the target smart vehicle.

[0019] In a possible implementation manner, the corresponding image-related operation is performed on the target intelligent vehicle, and the specific operation process is as follows:

[0020] B1. Focus the vehicle interior monitoring image corresponding to the target smart vehicle on the facial image of the target smart vehicle driver, extract the eye contour, mouth contour and nose contour of the target smart vehicle driver, and then obtain the position coordinates corresponding to the center point of the eye, mouth center point and nose center point of the target smart vehicle driver, thereby using them as the identity feature information corresponding to the target smart vehicle driver.

[0021] B2. Match the identity feature information corresponding to the target smart vehicle driver with the identity feature information of each target smart vehicle driver stored in the vehicle database, and then obtain the corresponding identity of the target smart vehicle driver by matching, and extract the habit information corresponding to the target smart vehicle driver based on the habit information corresponding to each target smart vehicle driver stored in the vehicle database, wherein the habit information includes the headrest height, seat back curvature, seat height and the distance between the seat and the steering wheel corresponding to each historical driving.

[0022] B3. Then, the mean formula is used to calculate the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver, and the calculations are sent to the vehicle terminal platform. The vehicle terminal platform adjusts the vehicle driver position of the target smart vehicle accordingly based on the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver.

[0023] In a possible implementation manner, the performing of the corresponding image-related operation on the target intelligent vehicle specifically includes:

[0024] C1. Focus the vehicle interior monitoring image corresponding to the target smart vehicle on the hand images of each person inside the target smart vehicle, and match the hand images corresponding to each person inside the target smart vehicle with the set smoking reference hand images. If the hand image of the driver of the target smart vehicle is identified to be consistent with the smoking reference hand image, send an early warning instruction to the vehicle terminal platform for corresponding early warning processing. If the hand image of the non-driver of the target smart vehicle is identified to be consistent with the smoking reference hand image, start the photoelectric smoke sensor deployed in the target smart vehicle, detect the smoke concentration inside the target smart vehicle, and record it as ND, open all the windows of the target smart vehicle, and turn on the air purification system of the target smart vehicle at the same time.

[0025] C2. Obtain the driving speed of the target smart vehicle according to the dashboard of the target smart vehicle and record it as , and then use the calculation formula , calculate the wind speed corresponding to the target intelligent vehicle's driving speed , where b represents the wind speed coefficient factor corresponding to the set vehicle speed.

[0026] C3. Based on the analysis formula , the smoke odor dissipation completion time t corresponding to the target intelligent vehicle is calculated, where c represents the wind volume coefficient factor corresponding to the set wind speed, They represent the reference window area and the reference vehicle interior volume corresponding to the target intelligent vehicle stored in the vehicle database, DW represents the smoke content that can be diluted by the set unit wind volume, t' represents the current time, Indicates the time required to dilute a set unit of smoke content.

[0027] C4. Send the smoke odor dissipation completion time corresponding to the target smart vehicle to the vehicle terminal platform, and the vehicle terminal platform will close the windows of the target smart vehicle after the smoke odor dissipation completion time corresponding to the target smart vehicle.

[0028] In a possible implementation manner, the reminder operation is performed on the vehicle driver corresponding to the target smart vehicle, and the specific operation process is as follows:

[0029] D1. Focus the corresponding monitored driving image of the vehicle driver on the vehicle driver's face image, thereby identifying the corresponding number of blinks and yawns of the vehicle driver within a set time period, and record them as ZY and HQ respectively.

[0030] D2. Using calculation formula , calculate the driving fatigue assessment coefficient corresponding to the vehicle driver , where t1 represents the duration corresponding to the set time period, ZY' and HQ' represent the permitted blinking frequency and permitted yawning frequency of the vehicle driver respectively, and d1 and d2 represent the influence factors corresponding to the set blinking and yawning respectively.

[0031] D3. Compare the driving fatigue assessment coefficient corresponding to the vehicle driver with the set vehicle driver reference fatigue assessment coefficient. If the driving fatigue assessment coefficient corresponding to the vehicle driver is greater than the vehicle driver reference fatigue assessment coefficient, the vehicle driver is determined to be fatigued driving, and then the vehicle terminal platform is activated and the voice warning method is turned on to intervene.

[0032] In a possible implementation manner, the reminding operation for the vehicle driver corresponding to the target smart vehicle specifically includes:

[0033] E1. Extract the route map corresponding to the target smart vehicle's current trip from the vehicle database, and then obtain the number of high-speed exits corresponding to the target smart vehicle's current trip. When the target smart vehicle identifies the need to exit the high-speed, focus the corresponding monitored driving image of the vehicle driver on the vehicle dashboard image, thereby identifying the corresponding turn signal status, steering wheel angle and vehicle speed of the vehicle.

[0034] E2. Match and compare the turn signal state of the vehicle with the set standard turn signal state for exiting the highway. If the turn signal state of the vehicle matches the standard turn signal state for exiting the highway, the target intelligent vehicle is determined to be ready to exit the highway, and the turn signal preparation coefficient of the target intelligent vehicle is recorded as , otherwise the turn signal preparation coefficient of the target intelligent vehicle is recorded as , thus obtaining the turn signal preparation coefficient of the target intelligent vehicle ,in, The value is or ,and > .

[0035] E3. According to the analysis method of the turn signal preparation coefficient of the target intelligent vehicle, the steering wheel preparation coefficient and the speed preparation coefficient of the target intelligent vehicle are obtained by similar analysis, and they are recorded as .

[0036] E4. Use the calculation formula , calculate the driving concentration evaluation coefficient corresponding to the target intelligent vehicle driver , where g1, g2 and g3 represent the influencing factors corresponding to the set turn signal, steering wheel and vehicle speed respectively.

[0037] E5. Compare the driving concentration assessment coefficient corresponding to the target intelligent vehicle driver with the set driver concentration reference assessment coefficient. If the driving concentration assessment coefficient corresponding to the target intelligent vehicle driver is less than the driver concentration reference assessment coefficient, the target intelligent vehicle driver is judged to be distracted driving, and then the vehicle terminal platform is activated and the voice warning method is turned on to intervene.

[0038] In one possible implementation, the method includes a vehicle database in actual application, which is used to store a route map corresponding to the target smart vehicle's current trip, a reference window area and a reference vehicle interior volume corresponding to the target smart vehicle, a minimum temperature value and a maximum temperature value suitable for the human body, and is also used to store an internal model diagram corresponding to the target smart vehicle, identity feature information of each driver of the target smart vehicle, and habit information corresponding to each driver of the target smart vehicle.

[0039] Another aspect of the present invention provides a highway vehicle behavior prediction and intelligent control device, including an electronic device and a computer-readable storage medium;

[0040] The electronic device comprises a processor, a memory and a communication bus, wherein the memory stores a computer-readable program executable by the processor;

[0041] The communication bus realizes the connection and communication between the processor and the memory;

[0042] When the processor executes the computer readable program, the steps in the above-mentioned method for predicting and intelligently controlling highway vehicle behavior are implemented;

[0043] The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the above-mentioned method for predicting and intelligently controlling highway vehicle behavior.

[0044] As described above, the highway vehicle behavior prediction and intelligent control method provided by the present invention has at least the following beneficial effects:

[0045] (1) The present invention provides a method for predicting and intelligently controlling vehicle behavior on a highway. The method monitors the temperature information and images of a target intelligent vehicle, and then analyzes the seat temperature and internal occupant movements of the target intelligent vehicle. The method is also used to monitor and analyze the driver's images and send them to the vehicle terminal platform for corresponding operation processing. The vehicle seat temperature is analyzed and controlled, which improves the occupant's physical comfort to a certain extent, thereby avoiding quality problems with the vehicle seats and improving the service life and safety of the vehicle seats to a certain extent.

[0046] (2) The embodiments of the present invention improve the riding comfort of the occupants of the vehicle to a certain extent by monitoring and analyzing the smoking needs of the occupants of the vehicle, thereby avoiding harm to the health of all occupants of the vehicle, and to a certain extent, not interfering with the driver's vision, and to a certain extent avoiding a decrease in the driver's reaction ability, thereby reducing the risk of driving.

[0047] (3) The embodiments of the present invention provide the ultimate safety and convenience for people's travel by monitoring and analyzing the distracted driving of vehicle drivers, making the vehicles popular with customers and improving passenger satisfaction to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0049] Figure 1 It is a schematic diagram of the connection of each step of the method of the present invention.

[0050] Figure 2 It is a schematic diagram of the structure of the device shown in the present invention. DETAILED DESCRIPTION

[0051] The above contents in combination with the implementation of the present invention are merely examples and explanations of the concept of the present invention. The technical personnel in the relevant technical field may make various modifications or supplements to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0052] Example 1

[0053] See also Figure 1 As shown, a highway vehicle behavior prediction and intelligent control method comprises the following steps:

[0054] Vehicle information monitoring: monitor the temperature information of the target smart vehicle based on the monitoring instrument provided by the target smart vehicle.

[0055] Based on the above embodiment, the temperature information corresponding to the target smart vehicle includes the outside temperature, the inside temperature and the inside humidity.

[0056] Vehicle image monitoring: monitoring the interior image of the target smart vehicle based on the high-definition camera deployed on the target smart vehicle.

[0057] Seat temperature control, based on the temperature information corresponding to the target smart vehicle and the vehicle's internal monitoring image, the seat temperature of the target smart vehicle is adjusted and controlled through the vehicle terminal platform.

[0058] On the basis of the above embodiment, the seat temperature of the target smart vehicle is adjusted and controlled, and the specific adjustment and control process is as follows:

[0059] A1. According to the temperature information corresponding to the target smart vehicle, the outside temperature and the inside temperature of the target smart vehicle are extracted and recorded as and , and then use the calculation formula , calculate the appropriate seat temperature T corresponding to the target intelligent vehicle, where They represent the highest and lowest temperatures suitable for human body stored in the vehicle database, respectively. Represented as the initial seat temperature corresponding to the target smart vehicle.

[0060] A2. Based on the vehicle interior monitoring image corresponding to the target intelligent vehicle, the positions of the corresponding personnel inside the target intelligent vehicle are extracted, and the internal model diagram corresponding to the target intelligent vehicle is extracted from the vehicle database. The internal seat positions of the target intelligent vehicle are extracted from the internal model diagram corresponding to the target intelligent vehicle, and the positions of the corresponding personnel inside the target intelligent vehicle are compared with the internal seat positions corresponding to the target intelligent vehicle, thereby obtaining the corresponding seat positions of the corresponding personnel inside the target intelligent vehicle.

[0061] In a specific embodiment, the corresponding positions of each person inside the target smart vehicle are compared with the corresponding internal positions of the target smart vehicle. The specific comparison process is as follows: according to the corresponding positions of each person inside the target smart vehicle, the distances corresponding to the corresponding positions of each person inside the target smart vehicle and the driving position are extracted, and the distances corresponding to the corresponding positions of each person inside the target smart vehicle and the driving position are compared with the preset standard distances corresponding to the internal positions of the target smart vehicle and the driving position, thereby obtaining the seat positions corresponding to each person inside the target smart vehicle.

[0062] A3. The seat positions and suitable seat temperatures corresponding to each person in the target smart vehicle are sent to the vehicle terminal platform. The vehicle terminal platform adjusts and controls the seat positions corresponding to each person in the target smart vehicle according to the suitable seat temperatures corresponding to the target smart vehicle.

[0063] The embodiment of the present invention analyzes and controls the seat temperature of the vehicle, thereby improving the physical comfort of the personnel to a certain extent, thereby avoiding quality problems of the vehicle seats, and improving the service life and safety of the vehicle seats to a certain extent.

[0064] Vehicle image analysis: Based on the internal monitoring image of the target smart vehicle, corresponding image-related operations are performed on the target smart vehicle through the vehicle terminal platform.

[0065] On the basis of the above embodiment, the corresponding image-related operation is performed on the target intelligent vehicle, and the specific operation process is as follows:

[0066] B1. Focus the vehicle interior monitoring image corresponding to the target smart vehicle on the facial image of the target smart vehicle driver, extract the eye contour, mouth contour and nose contour of the target smart vehicle driver, and then obtain the position coordinates corresponding to the center point of the eye, mouth center point and nose center point of the target smart vehicle driver, thereby using them as the identity feature information corresponding to the target smart vehicle driver.

[0067] In a specific embodiment, the position coordinates of the center points of the eyes, mouth and nose of the target smart vehicle driver are obtained. The specific obtaining process is as follows: a perpendicular bisector is drawn with the center of the eyebrows as the center, and a line perpendicular to the perpendicular bisector is drawn with the highest point of the eyebrow peak to form a facial rectangular coordinate system. According to the corresponding center point positions of the eyes, mouth and nose, the position coordinates of the center points of the eyes, mouth and nose of the target smart vehicle driver are obtained.

[0068] B2. Match the identity feature information corresponding to the target smart vehicle driver with the identity feature information of each target smart vehicle driver stored in the vehicle database, and then obtain the corresponding identity of the target smart vehicle driver by matching, and extract the habit information corresponding to the target smart vehicle driver based on the habit information corresponding to each target smart vehicle driver stored in the vehicle database, wherein the habit information includes the headrest height, seat back curvature, seat height and the distance between the seat and the steering wheel corresponding to each historical driving.

[0069] In a specific embodiment, the identity corresponding to the driver of the target intelligent vehicle is obtained by matching, and the specific matching process is as follows:

[0070] B2-1. Extract the eye center position coordinates, mouth center position coordinates, and nose center position coordinates corresponding to the target intelligent vehicle driver from the identity feature information corresponding to the target intelligent vehicle driver.

[0071] B2-2. Obtain the identity images of each driver of the target intelligent vehicle stored in the vehicle database, and generate the identity feature information corresponding to each driver of the target intelligent vehicle according to the generation method of the identity feature information corresponding to the driver of the target intelligent vehicle, and then obtain the eye center position coordinates, mouth center position coordinates, and nose center position coordinates of each driver of the target intelligent vehicle.

[0072] B2-3, according to the eye center position coordinates of the target intelligent vehicle driver and the eye center position coordinates of each driver of the target intelligent vehicle, use the calculation formula , calculate the eye position coordinate difference between the target intelligent vehicle driver and each driver of the target intelligent vehicle ,in, It is represented by the eye center position coordinates corresponding to the target intelligent vehicle driver. The coordinates of the eye center point of the i-th driver of the target intelligent vehicle are represented by , i represents the number of each driver of the target intelligent vehicle, i=1,2,...y, and the coordinate difference of the mouth position and the coordinate difference of the nose position of the target intelligent vehicle driver and each driver of the target intelligent vehicle are calculated in the same way according to the calculation method of the eye position coordinate difference between the target intelligent vehicle driver and each driver of the target intelligent vehicle, and are recorded as .

[0073] B2-4. By calculating the formula , calculate the identity matching coefficient between the target intelligent vehicle driver and each driver of the target intelligent vehicle ,in, They respectively represent the coordinate differences of the permitted eyes, mouth, and nose corresponding to the set personnel, and f1, f2, and f3 respectively represent the influence weights corresponding to the set eye position coordinate difference, mouth position coordinate difference, and nose position coordinate difference.

[0074] B2-5. Sort the identity matching coefficients corresponding to the target smart vehicle driver and each driver of the target smart vehicle in descending order, and then use the corresponding identity of the person with the first-ranked identity matching coefficient as the corresponding identity of the target smart vehicle driver.

[0075] B3. Then, the mean formula is used to calculate the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver, and the calculations are sent to the vehicle terminal platform. The vehicle terminal platform adjusts the vehicle driver position of the target smart vehicle accordingly based on the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver.

[0076] In a specific embodiment, the average formula is used to calculate the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target intelligent vehicle driver. The specific calculation formula is as follows: , calculate the comfortable driving headrest height corresponding to the target intelligent vehicle driver , where h represents the number corresponding to each historical driving. , j represents the total number of historical driving, It is represented as the headrest height corresponding to the hth historical driving.

[0077] The comfortable driving headrest height corresponding to the target smart vehicle driver is calculated in the same way as the calculation method, and the comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver are calculated.

[0078] On the basis of the above embodiment, the corresponding image-related operation is performed on the target intelligent vehicle, and the specific operation process also includes:

[0079] C1. Focus the vehicle interior monitoring image corresponding to the target smart vehicle on the hand images of each person inside the target smart vehicle, and match the hand images corresponding to each person inside the target smart vehicle with the set smoking reference hand images. If the hand image of the driver of the target smart vehicle is identified to be consistent with the smoking reference hand image, send an early warning instruction to the vehicle terminal platform for corresponding early warning processing. If the hand image of the non-driver of the target smart vehicle is identified to be consistent with the smoking reference hand image, start the photoelectric smoke sensor deployed in the target smart vehicle, detect the smoke concentration inside the target smart vehicle, and record it as ND, open all the windows of the target smart vehicle, and turn on the air purification system of the target smart vehicle at the same time.

[0080] In a specific embodiment, the hand images corresponding to each person inside the target smart vehicle are matched with the set smoking hand images, and the specific matching process is as follows: the hand images of each person inside the target smart vehicle are focused on the finger gap images of each person inside the target smart vehicle, and the finger clamping images of each person inside the target smart vehicle are extracted from the finger gap images of each person inside the target smart vehicle. The finger clamping images of each person inside the target smart vehicle are matched and compared with the set standard smoking finger clamping images. If the finger clamping image of a person inside the target smart vehicle is consistent with the set standard smoking finger clamping image, the chromaticity value and temperature of the item clamped by the fingers of the person inside the target smart vehicle are further extracted. If the chromaticity value and temperature of the item clamped by the fingers of the person inside the target smart vehicle match the set cigarette lighting chromaticity value and temperature, the person inside the target smart vehicle is determined to be a smoker.

[0081] C2. Obtain the driving speed of the target smart vehicle according to the dashboard of the target smart vehicle and record it as , and then use the calculation formula , calculate the wind speed corresponding to the target intelligent vehicle's driving speed , where b represents the wind speed coefficient factor corresponding to the set vehicle speed.

[0082] C3. Based on the analysis formula , the smoke odor dissipation completion time t corresponding to the target intelligent vehicle is calculated, where c represents the wind volume coefficient factor corresponding to the set wind speed, They represent the reference window area and the reference vehicle interior volume corresponding to the target intelligent vehicle stored in the vehicle database, DW represents the smoke content that can be diluted by the set unit wind volume, t' represents the current time, Indicates the time required to dilute a set unit of smoke content.

[0083] C4. Send the smoke odor dissipation completion time corresponding to the target smart vehicle to the vehicle terminal platform, and the vehicle terminal platform will close the windows of the target smart vehicle after the smoke odor dissipation completion time corresponding to the target smart vehicle.

[0084] The embodiments of the present invention improve the riding comfort of the occupants of the vehicle to a certain extent by monitoring and analyzing the smoking needs of the occupants of the vehicle, thereby avoiding harm to the health of all occupants of the vehicle, and to a certain extent not interfering with the driver's vision, and to a certain extent avoiding a decrease in the driver's reaction ability, thereby reducing the risk of driving.

[0085] Driver monitoring: High-definition cameras installed on target smart vehicles monitor the driving images of vehicle drivers.

[0086] Driver analysis: Based on the monitored driving images of the vehicle driver, the vehicle driver corresponding to the target intelligent vehicle is reminded through the vehicle terminal platform.

[0087] On the basis of the above embodiment, the reminder operation is performed on the vehicle driver corresponding to the target smart vehicle, and the specific operation process is as follows:

[0088] D1. Focus the corresponding monitored driving image of the vehicle driver on the vehicle driver's face image, thereby identifying the corresponding number of blinks and yawns of the vehicle driver within a set time period, and record them as ZY and HQ respectively.

[0089] D2. Using calculation formula , calculate the driving fatigue assessment coefficient corresponding to the vehicle driver , where t1 represents the duration corresponding to the set time period, ZY' and HQ' represent the permitted blinking frequency and permitted yawning frequency of the vehicle driver respectively, and d1 and d2 represent the influence factors corresponding to the set blinking and yawning respectively.

[0090] D3. Compare the driving fatigue assessment coefficient corresponding to the vehicle driver with the set vehicle driver reference fatigue assessment coefficient. If the driving fatigue assessment coefficient corresponding to the vehicle driver is greater than the vehicle driver reference fatigue assessment coefficient, the vehicle driver is determined to be fatigued driving, and then the vehicle terminal platform is activated and the voice warning method is turned on to intervene.

[0091] On the basis of the above embodiment, the reminder operation for the vehicle driver corresponding to the target smart vehicle further includes:

[0092] E1. Extract the route map corresponding to the target smart vehicle's current trip from the vehicle database, and then obtain the number of high-speed exits corresponding to the target smart vehicle's current trip. When the target smart vehicle identifies the need to exit the high-speed, focus the corresponding monitored driving image of the vehicle driver on the vehicle dashboard image, thereby identifying the corresponding turn signal status, steering wheel angle and vehicle speed of the vehicle.

[0093] E2. Match and compare the turn signal state of the vehicle with the set standard turn signal state for exiting the highway. If the turn signal state of the vehicle matches the standard turn signal state for exiting the highway, the target intelligent vehicle is determined to be ready to exit the highway, and the turn signal preparation coefficient of the target intelligent vehicle is recorded as , otherwise the turn signal preparation coefficient of the target intelligent vehicle is recorded as , thus obtaining the turn signal preparation coefficient of the target intelligent vehicle ,in, The value is or ,and > .

[0094] E3. According to the analysis method of the turn signal preparation coefficient of the target intelligent vehicle, the steering wheel preparation coefficient and the speed preparation coefficient of the target intelligent vehicle are obtained by similar analysis, and they are recorded as .

[0095] E4. Use the calculation formula , calculate the driving concentration evaluation coefficient corresponding to the target intelligent vehicle driver , where g1, g2 and g3 represent the influencing factors corresponding to the set turn signal, steering wheel and vehicle speed respectively.

[0096] E5. Compare the driving concentration assessment coefficient corresponding to the target intelligent vehicle driver with the set driver concentration reference assessment coefficient. If the driving concentration assessment coefficient corresponding to the target intelligent vehicle driver is less than the driver concentration reference assessment coefficient, the target intelligent vehicle driver is judged to be distracted driving, and then the vehicle terminal platform is activated and the voice warning method is turned on to intervene.

[0097] The embodiments of the present invention provide the most extreme safety and convenience for people's travel by monitoring and analyzing the distracted driving of vehicle drivers, making the vehicles popular with customers and improving the satisfaction of passengers to a certain extent.

[0098] The vehicle terminal platform receives the corresponding operation instructions of the target intelligent vehicle and performs corresponding operation processing.

[0099] On the basis of the above embodiments, the method includes a vehicle database in actual application, which is used to store the route map corresponding to the target smart vehicle's current trip, the reference window area and reference vehicle interior volume corresponding to the target smart vehicle, the minimum temperature value and the maximum temperature value suitable for the human body, and is also used to store the internal model diagram corresponding to the target smart vehicle, the identity feature information of each driver of the target smart vehicle, and the habit information corresponding to each driver of the target smart vehicle.

[0100] Example 2

[0101] According to an exemplary embodiment, a logistics express automated sorting device based on barcode recognition includes: an electronic device and a computer-readable storage medium;

[0102] Figure 2 It is a structural diagram of an automated logistics express sorting device based on barcode recognition provided in an embodiment of the present application. The device may have relatively large differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPU) and one or more memories, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor to implement the above-mentioned highway vehicle behavior prediction and intelligent control method.

[0103] The electronic device comprises a processor, a memory and a communication bus, wherein the memory stores a computer-readable program executable by the processor;

[0104] The communication bus realizes the connection and communication between the processor and the memory;

[0105] The processor implements the above-mentioned highway vehicle behavior prediction and intelligent control method by calling the computer program stored in the memory and executing the computer readable program;

[0106] The computer-readable storage medium stores one or more programs. When executed on an electronic device, the one or more programs can be executed by one or more processors to provide a user input interface to implement the above-mentioned highway vehicle behavior prediction and intelligent control method.

[0107] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0108] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0109] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0110] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting and intelligently controlling vehicle behavior on a highway, characterized in that: The method includes: The target smart vehicle is monitored for temperature information using the monitoring instrument provided by the target smart vehicle, and the internal image of the target smart vehicle is monitored using the high-definition camera deployed on the target smart vehicle; According to the temperature information corresponding to the target smart vehicle and the vehicle interior monitoring image, the seat temperature of the target smart vehicle is adjusted and controlled through the vehicle terminal platform; The temperature information corresponding to the target smart vehicle includes the outside temperature and the inside temperature of the vehicle; The seat temperature of the target intelligent vehicle is adjusted and controlled, and the specific adjustment and control process is as follows: A1. According to the temperature information corresponding to the target smart vehicle, the outside temperature and the inside temperature of the target smart vehicle are extracted and recorded as and , and then use the calculation formula , calculate the appropriate seat temperature T corresponding to the target intelligent vehicle, where They represent the highest and lowest temperatures suitable for human body stored in the vehicle database, respectively. It is represented as the initial seat temperature corresponding to the target smart vehicle; A2. According to the vehicle interior monitoring image corresponding to the target intelligent vehicle, the positions of the personnel corresponding to the target intelligent vehicle are extracted from it, and the internal model diagram corresponding to the target intelligent vehicle is extracted from the vehicle database, and the internal seat positions of the target intelligent vehicle are extracted from the internal model diagram corresponding to the target intelligent vehicle, and the positions of the personnel corresponding to the target intelligent vehicle are compared with the internal seat positions corresponding to the target intelligent vehicle, so as to obtain the seat positions corresponding to the personnel in the target intelligent vehicle; A3. Send the seat positions and suitable seat temperatures corresponding to each person in the target smart vehicle to the vehicle terminal platform, and the vehicle terminal platform adjusts and controls the seat positions corresponding to each person in the target smart vehicle according to the suitable seat temperatures corresponding to the target smart vehicle; According to the vehicle interior monitoring image of the target intelligent vehicle, corresponding image-related operations are performed on the target intelligent vehicle through the vehicle terminal platform; The specific operation process of performing corresponding image-related operations on the target intelligent vehicle also includes: C1. Focus the vehicle interior monitoring image corresponding to the target smart vehicle on the hand images of each person inside the target smart vehicle, match the hand images corresponding to each person inside the target smart vehicle with the set smoking reference hand images, and if the hand image of the driver of the target smart vehicle is identified to be consistent with the smoking reference hand image, send an early warning instruction to the vehicle terminal platform for corresponding early warning processing, and if the hand image of the non-driver of the target smart vehicle is identified to be consistent with the smoking reference hand image, start the photoelectric smoke sensor deployed in the target smart vehicle, detect the smoke concentration inside the target smart vehicle, and record it as ND, and open all the windows of the target smart vehicle, and turn on the air purification system of the target smart vehicle at the same time; C2. Obtain the driving speed of the target smart vehicle according to the dashboard of the target smart vehicle and record it as , and then use the calculation formula , calculate the wind speed corresponding to the target intelligent vehicle's driving speed , where b represents the wind speed coefficient factor corresponding to the set vehicle speed; C3. Based on the analysis formula , the smoke odor dissipation completion time t corresponding to the target intelligent vehicle is calculated, where c represents the wind volume coefficient factor corresponding to the set wind speed, They represent the reference window area and the reference vehicle interior volume corresponding to the target intelligent vehicle stored in the vehicle database, DW represents the smoke content that can be diluted by the set unit air volume, t' represents the current time, It is expressed as the time required to dilute the set unit smoke content; C4. Send the smoke odor dissipation completion time corresponding to the target smart vehicle to the vehicle terminal platform, and the vehicle terminal platform will close the windows of the target smart vehicle after the smoke odor dissipation completion time corresponding to the target smart vehicle; The high-definition camera deployed on the target smart vehicle monitors the driving image of the vehicle driver, and based on the corresponding monitored driving image of the vehicle driver, reminds the vehicle driver corresponding to the target smart vehicle through the vehicle terminal platform; The reminder operation for the vehicle driver corresponding to the target smart vehicle specifically includes: E1. Extract the route map corresponding to the target smart vehicle's current trip from the vehicle database, and then obtain the number of high-speed exits corresponding to the target smart vehicle's current trip. When the target smart vehicle identifies that it needs to exit the high-speed, focus the corresponding monitored driving image of the vehicle driver on the vehicle dashboard image, thereby identifying the corresponding turn signal state, steering wheel angle and vehicle speed of the vehicle; E2. Match and compare the turn signal state of the vehicle with the set standard turn signal state for exiting the highway. If the turn signal state of the vehicle matches the standard turn signal state for exiting the highway, the target intelligent vehicle is determined to be ready to exit the highway, and the turn signal preparation coefficient of the target intelligent vehicle is recorded as , otherwise the turn signal preparation coefficient of the target intelligent vehicle is recorded as , thus obtaining the turn signal preparation coefficient of the target intelligent vehicle ,in, The value is or ,and > ; E3. According to the analysis method of the turn signal preparation coefficient of the target intelligent vehicle, the steering wheel preparation coefficient and the speed preparation coefficient of the target intelligent vehicle are obtained by similar analysis, and they are recorded as ; E4. Use the calculation formula , calculate the driving concentration evaluation coefficient corresponding to the target intelligent vehicle driver , where g1, g2 and g3 represent the influencing factors corresponding to the set turn signal, steering wheel and vehicle speed respectively; E5. Compare the driving concentration evaluation coefficient corresponding to the target intelligent vehicle driver with the set driver concentration reference evaluation coefficient. If the driving concentration evaluation coefficient corresponding to the target intelligent vehicle driver is less than the driver concentration reference evaluation coefficient, the target intelligent vehicle driver is determined to be distracted driving, and then the vehicle terminal platform is activated to start the voice warning mode for intervention; The vehicle terminal platform performs corresponding operation processing according to the operation instructions corresponding to the target intelligent vehicle.

2. A highway vehicle behavior prediction and intelligent control method according to claim 1, characterized in that: The specific operation process of performing corresponding image-related operations on the target intelligent vehicle is as follows: B1. Focus the vehicle interior monitoring image corresponding to the target intelligent vehicle on the face image of the target intelligent vehicle driver, extract the eye contour, mouth contour and nose contour of the target intelligent vehicle driver, and then obtain the position coordinates corresponding to the eye center point, mouth center point and nose center point of the target intelligent vehicle driver, thereby using them as the identity feature information corresponding to the target intelligent vehicle driver; B2, matching the identity feature information corresponding to the target smart vehicle driver with the identity feature information of each target smart vehicle driver stored in the vehicle database, thereby matching the identity of the target smart vehicle driver, and extracting the habit information corresponding to the target smart vehicle driver according to the habit information corresponding to each target smart vehicle driver stored in the vehicle database, wherein the habit information includes the headrest height, seat back curvature, seat height and the distance between the seat and the steering wheel corresponding to each historical driving; B3. Then, the mean formula is used to calculate the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver, and the calculations are sent to the vehicle terminal platform. The vehicle terminal platform adjusts the vehicle driver position of the target smart vehicle accordingly based on the comfortable driving headrest height, comfortable backrest curvature, comfortable driving seat height and comfortable driving seat spacing corresponding to the target smart vehicle driver.

3. A highway vehicle behavior prediction and intelligent control method according to claim 1, characterized in that: The specific operation process of reminding the driver of the target smart vehicle is as follows: D1, focusing the corresponding monitored driving image of the vehicle driver on the vehicle driver's face image, thereby identifying the corresponding number of blinks and yawns of the vehicle driver within a set time period, and recording them as ZY and HQ respectively; D2. Using calculation formula , calculate the driving fatigue assessment coefficient corresponding to the vehicle driver , where t1 represents the duration of the set time period, ZY' and HQ' represent the permitted blinking frequency and permitted yawning frequency of the vehicle driver, respectively, and d1 and d2 represent the influence factors of the set blinking and yawning, respectively; D3. Compare the driving fatigue assessment coefficient corresponding to the vehicle driver with the set vehicle driver reference fatigue assessment coefficient. If the driving fatigue assessment coefficient corresponding to the vehicle driver is greater than the vehicle driver reference fatigue assessment coefficient, the vehicle driver is determined to be fatigued driving, and then the vehicle terminal platform is activated and the voice warning method is turned on to intervene.

4. A highway vehicle behavior prediction and intelligent control method according to claim 3, characterized in that: The reminder operation for the vehicle driver corresponding to the target smart vehicle specifically includes: E1. Extract the route map corresponding to the target smart vehicle's current trip from the vehicle database, and then obtain the number of high-speed exits corresponding to the target smart vehicle's current trip. When the target smart vehicle identifies that it needs to exit the high-speed, focus the corresponding monitored driving image of the vehicle driver on the vehicle dashboard image, thereby identifying the corresponding turn signal state, steering wheel angle and vehicle speed of the vehicle; E2. Match and compare the turn signal state of the vehicle with the set standard turn signal state for exiting the highway. If the turn signal state of the vehicle matches the standard turn signal state for exiting the highway, the target intelligent vehicle is determined to be ready to exit the highway, and the turn signal preparation coefficient of the target intelligent vehicle is recorded as , otherwise the turn signal preparation coefficient of the target intelligent vehicle is recorded as , thus obtaining the turn signal preparation coefficient of the target intelligent vehicle ,in, The value is or ,and > ; E3. According to the analysis method of the turn signal preparation coefficient of the target intelligent vehicle, the steering wheel preparation coefficient and the speed preparation coefficient of the target intelligent vehicle are obtained by similar analysis, and they are recorded as ; E4. Use the calculation formula , calculate the driving concentration evaluation coefficient corresponding to the target intelligent vehicle driver , where g1, g2 and g3 represent the influencing factors corresponding to the set turn signal, steering wheel and vehicle speed respectively; E5. Compare the driving concentration assessment coefficient corresponding to the target intelligent vehicle driver with the set driver concentration reference assessment coefficient. If the driving concentration assessment coefficient corresponding to the target intelligent vehicle driver is less than the driver concentration reference assessment coefficient, the target intelligent vehicle driver is judged to be distracted driving, and then the vehicle terminal platform is activated and the voice warning method is turned on to intervene.

5. The method for predicting and intelligently controlling highway vehicle behavior according to claim 1 is characterized by: In actual application, the method includes a vehicle database, which is used to store the route map corresponding to the target intelligent vehicle's current trip, the reference window area and reference vehicle interior volume corresponding to the target intelligent vehicle, the minimum temperature value and the maximum temperature value suitable for the human body, and is also used to store the internal model diagram corresponding to the target intelligent vehicle, the identity feature information of each driver of the target intelligent vehicle, and the habit information corresponding to each driver of the target intelligent vehicle.

6. A highway vehicle behavior prediction and intelligent control device, characterized in that: It is implemented based on a highway vehicle behavior prediction and intelligent control method as described in any one of claims 1 to 5, and includes an electronic device and a computer-readable storage medium; The electronic device comprises a processor, a memory and a communication bus, wherein the memory stores a computer-readable program executable by the processor; The communication bus realizes the connection and communication between the processor and the memory; When the processor executes the computer-readable program, the steps in the highway vehicle behavior prediction and intelligent control method as described in any one of claims 1 to 5 are implemented; The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in a highway vehicle behavior prediction and intelligent control method as described in any one of claims 1-5.

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