CN111572549A - Driving environment adjusting method and system, storage medium and electronic equipment - Google Patents
Driving environment adjusting method and system, storage medium and electronic equipment Download PDFInfo
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- 238000012216 screening Methods 0.000 claims description 3
- 230000037237 body shape Effects 0.000 claims description 2
- 230000036544 posture Effects 0.000 description 35
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
- B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
- B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
- B60N2/0224—Non-manual adjustments, e.g. with electrical operation
- B60N2/0244—Non-manual adjustments, e.g. with electrical operation with logic circuits
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
- B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
- B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
- B60N2/0224—Non-manual adjustments, e.g. with electrical operation
- B60N2/0244—Non-manual adjustments, e.g. with electrical operation with logic circuits
- B60N2/0268—Non-manual adjustments, e.g. with electrical operation with logic circuits using sensors or detectors for adapting the seat or seat part, e.g. to the position of an occupant
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/223—Posture, e.g. hand, foot, or seat position, turned or inclined
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Abstract
The invention provides a driving environment adjusting method and system based on sitting posture habits, a storage medium and electronic equipment. The driving environment adjusting method based on the sitting posture habit comprises the following steps: acquiring first characteristic information representing sitting habit of a user; determining an expected state parameter of a target seat based on the first characteristic information; acquiring current state parameters of the target seat; determining an adjustment trajectory for the target seat based on the current state parameter and the expected state parameter; adjusting the target seat from a current state to a desired state based on the adjustment trajectory. The invention can flexibly meet the requirement of the user on automatic adjustment of the driving environment of the shared vehicle according to the sitting habit of the user.
Description
Technical Field
The present invention relates to a vehicle seat, and more particularly, to a driving environment adjusting method and system based on sitting posture habit, a storage medium, and an electronic device.
Background
In recent years, with the development of intelligent automobiles, the adjustment mode of the automobile seat is more and more intelligent and humanized.
Chinese utility model patent (publication No. CN203372086U) discloses a system for adjusting a motor vehicle seat based on user dimensions, specifically the following steps for adjusting a motor vehicle seat: in a first step, data about the user are acquired, wherein morphological data, in particular dimensions of a limb or a body part of the user, are included. In a second step, these morphological data are used to derive therefrom a model of the user's body, in particular of the respective position of the user's limbs. Third, the seat adjustment is determined using the determination obtained in the previous step. Finally, the elements for the motorized adjustment of the seat 1 are controlled according to the parameters determined in the previous step. In summary, the embodiment described in this patent aims at acquiring morphological data of the user and acquiring dimensions of these morphological data to infer the adjustment to be made to the seat.
However, the above-mentioned invention patents are limited at least in that: the adjustments to be made to the seat are inferred mechanically from the scale of the user's morphological data and are generally applicable only to the user's private car.
Disclosure of Invention
The invention provides a driving environment adjusting method and system based on sitting posture habits, a storage medium and electronic equipment, and aims to solve the problems in the prior art.
According to an aspect of the present invention, there is provided a driving environment adjusting method based on sitting posture habits, the driving environment adjusting method including:
acquiring first characteristic information representing sitting habit of a user;
determining an expected state parameter of a target seat based on the first characteristic information;
acquiring current state parameters of the target seat;
determining an adjustment trajectory for the target seat based on the current state parameter and the expected state parameter;
adjusting the target seat from a current state to a desired state based on the adjustment trajectory.
In an embodiment of the present invention, the storing the first feature information in a cloud, and the acquiring the first feature information representing the sitting habit of the user includes:
acquiring order information of a user, wherein the order information comprises a user ID;
first characteristic information representing the sitting habit of the user is obtained from a cloud terminal based on the user ID.
In an embodiment of the present invention, the user ID is associated with at least one group of first characteristic information, and each group of first characteristic information at least corresponds to one driving scenario; the obtaining of the first feature information representing the sitting habit of the user from the cloud based on the user ID includes:
determining a current driving scene;
and acquiring first characteristic information representing the sitting habit of the user in the current driving scene from a cloud terminal based on the user ID.
In an embodiment of the invention, the determining the current driving scenario comprises one or more of the following steps:
determining whether a person is in a rear row of the target seat;
determining a current time period;
determining the current road condition; and
the current weather conditions are determined.
In an embodiment of the present invention, after the adjusting the target seat from the current state to the desired state based on the adjustment track, the method further includes:
acquiring second characteristic information representing the current sitting posture of the user;
and storing the second characteristic information to a cloud end or a mobile storage device so as to update the first characteristic information.
In an embodiment of the present invention, the acquiring second feature information representing a current sitting posture of the user includes:
acquiring images of a plurality of angles of the current sitting posture of a user through a plurality of cameras;
and extracting the second characteristic information from the images of the plurality of angles based on a Harris corner algorithm.
In an embodiment of the present invention, the first feature information is stored in a mobile storage device, and the obtaining the first feature information representing the sitting habit of the user includes:
and communicating with the mobile storage device in a wired or wireless mode to acquire first characteristic information representing sitting habits of the user from the mobile storage device.
In an embodiment of the present invention, the characteristic information includes at least one of height, body type, angle between arm and trunk, angle between trunk and thigh, angle between thigh and shank, and angle between shank and foot.
In an embodiment of the present invention, the first feature information is obtained via an image having a user sitting posture captured by a camera module.
In an embodiment of the present invention, the obtaining the current state parameter of the target seat includes:
and screening candidate vehicle types provided for the user based on the first characteristic information.
According to another aspect of the present invention, there is provided a driving environment adjusting system based on sitting posture habit, comprising:
the first acquisition module is used for acquiring first characteristic information representing sitting habit of a user;
a first determination module for determining an expected state parameter of a target seat based on the first characteristic information;
the second acquisition module is used for acquiring the current state parameters of the target seat;
the second determining module is used for determining the adjusting track of the target seat according to the current state parameter and the expected state parameter;
and the adjusting module is used for adjusting the target seat from the current state to the expected state based on the adjusting track.
According to a further aspect of the invention, a storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, performs the method as described above.
According to still another aspect of the present invention, there is provided an electronic apparatus including:
a processor;
a storage medium having stored thereon a computer program which, when executed by the processor, performs the method as described above.
The invention can flexibly meet the requirement of the user on automatic adjustment of the driving environment of the shared vehicle according to the sitting habit of the user, and realizes that the same user can obtain the experience of the same driving environment when driving different automobiles.
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In order to make the aforementioned and other objects, features, and advantages of the present invention comprehensible, embodiments accompanied with figures are described below.
FIG. 1 is a flow chart of the driving environment adjusting method based on sitting posture habit of the present invention.
FIG. 2 is a flowchart of a driving environment adjusting method based on sitting posture habit according to an embodiment of the invention.
FIG. 3 is a partial flowchart of a driving environment adjustment method based on sitting posture habits according to an embodiment of the invention.
FIG. 4 is a flow chart of a driving environment adjustment method based on sitting posture habits according to another embodiment of the invention.
FIG. 5 is a partial flowchart of a driving environment adjustment method based on sitting posture habits according to an embodiment of the invention.
FIG. 6 is a flow chart of a driving environment adjustment method based on sitting posture habits according to another embodiment of the invention.
Fig. 7 is an application effect diagram of the sitting habit based driving environment adjusting method of the invention.
FIG. 8 is a flow chart illustrating adjustment of a seat state parameter according to an embodiment of the present invention.
FIG. 9 is a block diagram of a driving environment adjustment system based on sitting posture habits according to an embodiment of the present invention.
Fig. 10 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
In order to make the description of the present invention more complete and complete, reference is made to the various embodiments illustrated in the figures and described below, in which like numerals represent the same or similar elements. In other instances, well-known elements and steps have not been described in detail in order to avoid unnecessarily obscuring the present invention.
In the description of the embodiments and the claims, reference to "connected" may generally mean that one element is indirectly coupled to another element through another element or that one element is directly connected to another element without the need for other elements.
In the description of the embodiments and the claims, reference to "connected" may generally refer to one component being in wired and/or wireless communication, indirectly, with another component through the other component or one component being physically connected to the other component without the other component.
In the embodiments and claims, the articles "a" and "an" may refer broadly to one or more than one, unless the context specifically states otherwise.
As used herein, "about" or "approximately" is intended to modify any slightly variable quantity without changing its nature. Unless otherwise specified, the range of error for values modified by "about", "about" or "approximately" is generally tolerated within twenty percent, preferably within ten percent, and more preferably within five percent.
According to an aspect of the present invention, there is provided a driving environment adjusting method based on sitting posture habits. FIG. 1 is a flow chart of the driving environment adjusting method based on sitting posture habit of the present invention. As shown in fig. 1, the driving environment adjusting method based on sitting posture habit includes:
s1, acquiring first characteristic information representing sitting habit of a user;
specifically, the current user side device can obtain first characteristic information representing sitting habits of the user from a cloud or a mobile storage device through a communication module. The first characteristic information can be obtained by acquiring an image representing the sitting habit of the user through the camera module at least once by at least one user end device, processing the acquired image through the image processing module, and then storing the first characteristic information in a cloud or a mobile storage device. The user side equipment comprises a camera module, a communication module, an image processing module and an adjusting module for adjusting the seat posture. The first characteristic information comprises at least one of the height, the body type, the angle between the arm and the trunk, the angle between the trunk and the thigh, the angle between the thigh and the shank, and the angle between the shank and the foot of the user. When the first feature information is stored in the cloud, the stored first feature information should also include a user ID matching the first feature information.
S2, determining expected state parameters of a target seat based on the first characteristic information;
specifically, the first characteristic information may be input into existing simulation software to simulate spatial three-dimensional data of a human body when a user uses the target seat according to a sitting habit, and an image processing module of the current user end device determines an expected state parameter of the target seat according to the spatial three-dimensional data.
S3, acquiring the current state parameters of the target seat;
specifically, the spatial three-dimensional data of the target seat in the current environment may be obtained by a camera module of the current user end device, and then the current state parameter of the target seat is calculated by the image processing module.
S4, determining the adjustment track of the target seat based on the current state parameter and the expected state parameter.
Specifically, the distance and the angle to be adjusted of the target seat can be simulated by comparing the current state parameter of the target seat with the expected state parameter through the image processing module of the current user end device.
S5, adjusting the target seat from the current state to the expected state based on the adjustment track.
Specifically, the target seat may be adjusted from the current state to the desired state by an adjustment module of the current customer premises device based on the distance and angle to be adjusted.
The invention can flexibly meet the requirement of the user on automatic adjustment of the driving environment of the shared vehicle according to the sitting habit of the user, and realizes that the same user can obtain the experience of the same driving environment when driving different automobiles.
It should be noted that the driving environment adjustment method of the present invention can be applied to shared vehicles. Including but not limited to sharing cars, trains, planes, etc. Of course, the driving environment adjusting method can be applied not only to the shared transportation means, but also to private cars, even to environments with conditions such as movie theaters and the like. The driving environment should be understood in a corresponding broad sense and is not limited to the environment of a vehicle occupant.
Example 1
FIG. 2 is a flowchart of a driving environment adjusting method based on sitting posture habit according to an embodiment of the invention. Fig. 7 is an application effect diagram of the sitting habit based driving environment adjusting method of the invention. As shown in fig. 1, taking the example that the driving environment adjusting method based on sitting posture habit is applied to a shared automobile, the driving environment adjusting method includes:
s100, obtaining order information of a user, wherein the order information comprises a user ID;
s200, first characteristic information representing sitting habits of the user is obtained from a cloud terminal based on the user ID. Regarding the cloud storage technology, taking a C/S server architecture mode as an example, the sensorless uploading and downloading can be completely realized from the time of starting login to the time of capturing the first characteristic information according to the hundred thousand-level personnel storage quantity estimation, and the response time is within 500 ms. When the user sits in the vehicle, the cloud data is captured and completed. As can be seen from fig. 7, the first characteristic information includes at least one of a height, a body shape, an angle between an arm and a trunk, an angle γ between a trunk and a thigh, an angle β between a thigh and a calf, and an angle α between a calf and a foot of the user. In addition, the angle θ between the head and the arm, the angle η between the arm and the steering wheel, and the like may be further included. The first characteristic information is obtained through an image with a user sitting posture, which is shot by a camera module; the user uploads the first characteristic information to the cloud, and when the vehicle is selected, the candidate vehicle models provided for the user can be screened based on the first characteristic information. In other words, the lender of the shared automobile may provide the selectable vehicle types to the specific user according to the first characteristic information.
S300, determining expected state parameters of a target seat based on the first characteristic information;
specifically, the first characteristic information can be input into existing simulation software to simulate the three-dimensional spatial data of the human body in the vehicle when the user uses the target seat according to the sitting habit, and accordingly the expected state parameter of the target seat is determined.
S400, acquiring current state parameters of the target seat;
specifically, the current spatial three-dimensional data of the target seat in the vehicle may be obtained through a camera module, and then the current state parameter of the target seat may be obtained through calculation according to the current spatial three-dimensional data.
S500, determining an adjusting track of the target seat based on the current state parameter and the expected state parameter;
in particular, the distance and angle to be adjusted of the target seat may be simulated by comparing the current state parameters of the target seat with the expected state parameters.
S600, adjusting the target seat from the current state to the expected state based on the adjusting track. That is, the target seat is adjusted from the current state to the expected state according to the distance and the angle to be adjusted.
By way of further example of shared automobile rentals: the user leaves the city in which he lives, and usually needs to use a car rental service during the journey: according to the embodiment, the user can save personal driving habits (at least including sitting habits) to the cloud before leaving; after the target city is reached, selecting a proper car renting website and loading personal information; therefore, the vehicle models with unqualified heights can be automatically omitted during vehicle selection, or the vehicle models with insufficient space in the vehicle can be adjusted according to personal habits. Also manually marked disfavored car brands may be included. Thus, the appropriate shared automobile is selected within the habit range of the user. The experience of the same driving environment can be obtained when the same user drives different automobiles.
The invention can flexibly meet the requirement of the user on automatic adjustment of the driving environment of the shared vehicle according to the sitting habit of the user.
FIG. 3 is a partial flowchart of a driving environment adjustment method based on sitting posture habits according to an embodiment of the invention. As shown in fig. 3, each user ID may be associated with at least one set of first characteristic information, and each set of first characteristic information may correspond to at least one driving scenario. The step S200 includes:
s210, determining a current driving scene;
specifically, the determining the current driving scene includes one or more of the following steps S211 to S214:
and S211, determining whether the rear row of the target seat is occupied. Accordingly, the driving scene may be divided into two cases, i.e., a case where the rear row of the target seat is occupied and a case where the rear row of the target seat is unoccupied.
S212, determining the current time period. Accordingly, the driving scene can be divided into two cases, i.e., daytime and nighttime.
And S213, determining the current road condition. Accordingly, the driving scenario may be divided into: the current road is congested, the current road is smooth, the current road is flat, the current road is a mountain road and the like.
And S214, determining the current weather condition. Accordingly, the driving scenario may be divided into: the current weather is clear, the current haze concentration is higher than a preset value, the current weather is heavy rain and the like.
The driving scenes may exist individually or in combination.
S220, first characteristic information representing sitting habits of the user in the current driving scene is obtained from the cloud based on the user ID. The cloud end stores multiple groups of first characteristic information corresponding to the user ID, a driving scene is used as a set, and the multiple sets respectively comprise one group of first characteristic information; each set of first characteristic information may also be simultaneously classified into a plurality of sets (driving scenes).
The invention can flexibly meet the requirement of the user on automatic adjustment of the driving environment of the shared vehicle according to the sitting habit of the user. The state parameters of the seat do not need to be set mechanically according to the height and the weight of the user. In addition, the related data of personal preference such as the air conditioner temperature and the volume of the vehicle-mounted sound equipment which are frequently set by the user can be stored to the cloud end for the user to reserve. The experience of the same driving environment can be obtained when the same user drives different automobiles.
FIG. 4 is a flow chart of a driving environment adjustment method based on sitting posture habits according to another embodiment of the invention. Fig. 7 is an application effect diagram of the sitting habit based driving environment adjusting method of the invention. As shown in fig. 4, after step S600, the method further includes:
s700, acquiring second characteristic information representing the current sitting posture of the user; specifically, as shown in fig. 5, the obtaining of the second feature information representing the current sitting posture of the user may include:
s710, acquiring images of a plurality of angles of the current sitting posture of a user through a plurality of cameras; a plurality of cameras are arranged in the vehicle to acquire images with user sitting postures from multiple angles, and the accuracy of characteristic information extraction can be improved. As can be seen from fig. 7, the second characteristic information includes the height, body type, angle between the arm and the trunk, angle γ between the trunk and the thigh, angle β between the thigh and the calf, and angle α between the calf and the foot of the user. In addition, the angle θ between the head and the arm, the angle η between the arm and the steering wheel, and the like may be further included.
S720, extracting the second characteristic information from the images of the plurality of angles based on a Harris corner algorithm. In this embodiment, by using a Harris corner algorithm, an image edge feature and a gray feature are fused by using a method of fitting and weighting a weighted plane approximate gray surface and a principal curvature amplitude value of a related pixel, so that the accuracy of corner detection can be improved, and the error rate of angle calculation can be reduced. The invention does not limit the technical means adopted by image processing, as long as the second characteristic information representing the current sitting posture of the user can be extracted. It should be noted that, in this embodiment, after data representing the current sitting posture of the user is initially extracted, the data generally needs to be cleaned, data that significantly exceeds a reasonable range is removed, and then an average value of remaining data is taken as the second feature information as needed. The acquisition method of the first characteristic information can be consistent with the acquisition mode of the second characteristic information (the specific implementation mode can refer to paper number 1000-3428 (2013) 12-0167-04, and the website address: https:// wenku.baidu.com/view/4 eefd27088486262605. html).
It should be noted that, based on the development of the current image processing technology, the single measurement time is extremely short, and the duration of the whole recording process can be effectively controlled. FIG. 8 is a flow chart illustrating adjustment of a seat state parameter according to an embodiment of the present invention. As shown in fig. 8, wherein the angles of the at least three target nodes may include α, β, γ, η, θ shown in fig. 7. The folding angle can be adjusted to be higher or lower for the whole seat posture in a slight angle increasing or decreasing mode. The cleaning of the data may specifically include: and (4) carrying out six times of measurement, screening out the data with the deviation of more than 20 percent, reserving numerical values within a reasonable range, and then calculating and taking an average value.
S800, storing the second characteristic information to a cloud end to update the first characteristic information.
Specifically, the second characteristic information in the current driving scene can be stored in a cloud database and classified into corresponding sets according to the requirements of the user. And if the first characteristic information exists in the set, replacing the first characteristic information with the second characteristic information. Therefore, the driving habits of the user can be updated in real time, and the requirement of the user on automatic adjustment of the driving environment during riding is met.
In addition, if the corresponding first characteristic information cannot be acquired from the cloud based on the user ID, the first characteristic information of the user close to the user body type can be called as required and recommended to the current user, so that the driving environment can be adjusted correspondingly. For the occasions without cameras and other equipment around the seat, the seat state parameters matched with the characteristic information can be directly stored in a cloud or a mobile storage device and used as a direct basis for adjusting the seat state parameters. Need not to start the camera this moment, can directly snatch the anticipated state parameter of the seat of individual high in the clouds storage, carry out automatically regulated in view of the above. Thereafter, manual adjustment is again possible. After the manual adjustment is completed, the adjustment of the state parameters of the seat can be selected to be one-time operation or needs to be synchronized to a cloud end or a local storage device. The method can adjust at least one seat in a vehicle by one key for all seats in a vehicle, such as renting a shared car. Therefore, the requirement of the user for automatically adjusting the driving environment when riding the car can be met.
In addition, for public transport vehicles such as trains and airplanes which support seat selection and ticket purchase, the ticket selling platform can store seat state parameters commonly used by users in the ticket selling platform. After the passenger buys the ticket, the ticket buying platform sends the seat state parameters commonly used by the passenger to the corresponding seat so as to automatically adjust the seat state, and the passenger does not need to manually adjust the seat state after getting on the vehicle. If the manual adjustment of the seat state occurs, the seat adjustment parameters of the ticketing platform can be updated accordingly. Therefore, the requirement of the user for automatically adjusting the driving environment when riding the car can be met. The experience of the same driving environment can be obtained when the same user drives different automobiles.
Example 2
FIG. 6 is a flow chart of a driving environment adjustment method based on sitting posture habits according to another embodiment of the invention. As can be seen from comparing steps S100-S800 in fig. 4 with steps S10-S70 in fig. 6, the present embodiment is different from embodiment 1 mainly in that the first feature information is stored in a mobile storage device such as an NFC card, and the mobile storage device can be carried around. Therefore, the shared automobile can communicate with the mobile storage device in a wired or wireless mode to acquire the first characteristic information representing the sitting habit of the user from the mobile storage device. Further, after second characteristic information representing the current sitting posture of the user is obtained, the second characteristic information can be saved to the mobile storage device to update the first characteristic information. Therefore, the driving habit of the user can be updated in real time, and the requirement of the user on automatic adjustment of the driving environment during riding is met.
In summary, the present invention can adopt a local storage scheme independent of a network, store the expected state parameters of the seat on a storage chip that can be carried at any time, and guide the expected state parameters into the seat through NFC or other methods, thereby realizing automatic adjustment of the vehicle. The expected state parameters of the seat can be stored in the cloud by adopting a cloud storage scheme, the cloud data is acquired on a specific component in a code scanning or biological information identification mode, the image is acquired and matched at the local end, and the operation steps are simplified.
According to another aspect of the invention, a driving environment adjusting system based on sitting posture habits is provided, and is used for realizing the driving environment adjusting method. FIG. 9 is a block diagram of a driving environment adjustment system based on sitting posture habits according to an embodiment of the present invention. As shown in fig. 9, the driving environment adjustment system 600 includes: a first obtaining module 601, a first determining module 602, a second obtaining module 603, a second determining module 604, and an adjusting module 605. The first obtaining module 601 is configured to obtain first feature information representing a sitting habit of a user; the first determining module 602 is configured to determine an expected state parameter of a target seat based on the first characteristic information; the second obtaining module 603 is configured to obtain a current status parameter of the target seat; the second determining module 604 is configured to determine an adjustment trajectory of the target seat according to the current state parameter and the expected state parameter; the adjustment module 605 is configured to adjust the target seat from a current state to a desired state based on the adjustment trajectory. It should be understood by those skilled in the art that the respective modules in the driving environment adjusting system are respectively used for executing the corresponding steps in the driving environment adjusting method. While only some modules of the driving environment adjusting system are listed above, it can be understood from the above driving environment adjusting method disclosed in the present invention that the driving environment adjusting system may further include some other modules for assisting in performing the relevant steps of the driving environment adjusting method, and the specific functions thereof may refer to the relevant description of the foregoing driving environment adjusting method, and will not be described in detail herein. In addition, the same module may be used to execute a plurality of specific steps of the driving environment adjusting method. For example, the first obtaining module is further configured to obtain order information of the user, where the order information includes a user ID. In addition, fig. 7 is only a schematic illustration of the driving environment adjusting system provided by the present invention, and the splitting, combining and adding of modules are within the protection scope of the present invention without departing from the concept of the present invention. The driving environment adjusting system provided by the invention can be realized by software, hardware, firmware, plug-in and any combination thereof, and the invention is not limited by the invention.
Fig. 10 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention. Fig. 10 depicts a program product 700 for implementing the driving environment adjustment method described above, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer, according to an embodiment of the present invention. However, the program product of the present invention is not limited thereto, and in this document, the readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device, the technical effects of which can be seen with reference to the above description.
The program product 700 may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In an exemplary embodiment of the invention, there is also provided an electronic device that may include a processor and a memory for storing executable instructions of the processor. Wherein the processor is configured to execute the driving environment adjusting method in the above embodiment through executing the executable instructions, and the technical effects thereof can be referred to the above related description.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 400 according to this embodiment of the invention is described below with reference to fig. 11. The electronic device 400 shown in fig. 11 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 11, electronic device 400 is embodied in the form of a general purpose computing device. The components of electronic device 400 may include, but are not limited to: at least one processing unit 410, at least one memory unit 420, a bus 430 that connects the various system components (including the memory unit 420 and the processing unit 410), a display unit 440, and the like.
Wherein the storage unit stores program code executable by the processing unit 410 to cause the processing unit 410 to perform the steps according to various exemplary embodiments of the present invention described in the driving environment adjusting method described above in the present specification. For example, the processing unit 410 may perform the method as shown in fig. 1.
The storage unit 420 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)4201 and/or a cache memory unit 4202, and may further include a read only memory unit (ROM) 4203.
The storage unit 420 may also include a program/utility 4204 having a set (at least one) of program modules 4205, such program modules 4205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 400 may also communicate with one or more external devices 500 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 400, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 400 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 450. Also, the electronic device 400 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 460. The network adapter 460 may communicate with other modules of the electronic device 400 via the bus 430. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, or a network device, etc.) to execute the driving environment adjusting method according to the present invention.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (13)
1. A driving environment adjusting method based on sitting posture habits is characterized by comprising the following steps:
acquiring first characteristic information representing sitting habit of a user;
determining an expected state parameter of a target seat based on the first characteristic information;
acquiring current state parameters of the target seat;
determining an adjustment trajectory for the target seat based on the current state parameter and the expected state parameter;
adjusting the target seat from a current state to a desired state based on the adjustment trajectory.
2. The driving environment adjustment method of claim 1, wherein the first characteristic information is stored in a cloud, and the obtaining the first characteristic information representing sitting habits of the user comprises:
acquiring order information of a user, wherein the order information comprises a user ID;
first characteristic information representing the sitting habit of the user is obtained from a cloud terminal based on the user ID.
3. The driving environment adjustment method according to claim 2, wherein the user ID is associated with at least one set of first characteristic information, each set of first characteristic information corresponding to at least one driving scenario; the obtaining of the first feature information representing the sitting habit of the user from the cloud based on the user ID includes:
determining a current driving scene;
and acquiring first characteristic information representing the sitting habit of the user in the current driving scene from a cloud terminal based on the user ID.
4. The driving environment adjustment method of claim 3, wherein the determining a current driving scenario comprises one or more of:
determining whether a person is in a rear row of the target seat;
determining a current time period;
determining the current road condition; and
the current weather conditions are determined.
5. The driving environment adjustment method according to claim 1, wherein after the target seat is adjusted from the current state to the desired state based on the adjustment trajectory, further comprising:
acquiring second characteristic information representing the current sitting posture of the user;
and storing the second characteristic information to a cloud end or a mobile storage device so as to update the first characteristic information.
6. The driving environment adjustment method according to claim 5, wherein the acquiring of the second characteristic information representing the current sitting posture of the user includes:
acquiring images of a plurality of angles of the current sitting posture of a user through a plurality of cameras;
and extracting the second characteristic information from the images of the plurality of angles based on a Harris corner algorithm.
7. The driving environment adjustment method according to claim 1, wherein the first characteristic information is stored in a mobile storage device, and the acquiring the first characteristic information representing sitting habits of the user comprises:
and communicating with the mobile storage device in a wired or wireless mode to acquire first characteristic information representing sitting habits of the user from the mobile storage device.
8. The driving environment adjustment method according to any one of claims 1 to 7, wherein the characteristic information includes at least one of a height, a body shape, an angle of an arm to a trunk, an angle of a trunk to a thigh, an angle of a thigh to a calf, and an angle of a calf to a foot.
9. The driving environment adjustment method according to any one of claims 1 to 7, wherein the first characteristic information is obtained via an image with a user sitting posture taken by a camera module.
10. The driving environment adjustment method according to any one of claims 1 to 7, wherein the acquiring of the current state parameter of the target seat includes:
and screening candidate vehicle types provided for the user based on the first characteristic information.
11. A driving environment adjustment system based on sitting posture habits, comprising:
the first acquisition module is used for acquiring first characteristic information representing sitting habit of a user;
a first determination module for determining an expected state parameter of a target seat based on the first characteristic information;
the second acquisition module is used for acquiring the current state parameters of the target seat;
the second determining module is used for determining the adjusting track of the target seat according to the current state parameter and the expected state parameter;
and the adjusting module is used for adjusting the target seat from the current state to the expected state based on the adjusting track.
12. A storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, performs the method according to any one of claims 1 to 10.
13. An electronic device, characterized in that the electronic device comprises:
a processor;
storage medium having stored thereon a computer program which, when executed by the processor, performs the method of any of claims 1 to 10.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112339622A (en) * | 2020-11-10 | 2021-02-09 | 宁波均联智行科技股份有限公司 | Seat adjusting method and device and vehicle-mounted system |
| CN113029058A (en) * | 2021-03-10 | 2021-06-25 | 中国第一汽车股份有限公司 | Pose parameter acquisition method and device, vehicle and storage medium |
| CN113212257A (en) * | 2021-05-18 | 2021-08-06 | 中国第一汽车股份有限公司 | Automatic driver seat position adjusting method, device, terminal and storage medium based on Internet of vehicles |
| CN113734012A (en) * | 2021-07-29 | 2021-12-03 | 岚图汽车科技有限公司 | Control method and device for vehicle central armrest |
| CN113954703A (en) * | 2021-11-29 | 2022-01-21 | 东风汽车有限公司东风日产乘用车公司 | Vehicle space adjusting method, electronic device, and storage medium |
| CN114889540A (en) * | 2022-05-13 | 2022-08-12 | 重庆金康赛力斯新能源汽车设计院有限公司 | Driving posture state adjusting method and device, computer equipment and storage medium |
| CN114954151A (en) * | 2022-05-11 | 2022-08-30 | 重庆金康赛力斯新能源汽车设计院有限公司 | Method and device for automatically adjusting seat, computer equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105599642A (en) * | 2015-12-18 | 2016-05-25 | 小米科技有限责任公司 | Automatic adjusting method, device and terminal for seat |
| WO2018034121A1 (en) * | 2016-08-15 | 2018-02-22 | アイシン精機 株式会社 | Vehicular seat adjustment device, position adjustment control device, and vehicular seat adjustment method |
| CN108460707A (en) * | 2018-03-12 | 2018-08-28 | 林为庆 | A kind of the operation intelligent supervision method and its system of student |
| CN108515882A (en) * | 2018-03-30 | 2018-09-11 | 天津经纬恒润科技有限公司 | A kind of automotive seat adjusting method and device |
| CN108770351A (en) * | 2018-04-25 | 2018-11-06 | 深圳市元征软件开发有限公司 | Seat method of adjustment and seat adjusting apparatus |
| CN110466458A (en) * | 2019-08-23 | 2019-11-19 | 广州小鹏汽车科技有限公司 | A kind of control method, system and the vehicle of the car-mounted device being electrically adjusted |
| CN110723085A (en) * | 2019-09-29 | 2020-01-24 | 绿驰汽车科技集团有限公司 | Personalized adjusting method and system for vehicle function equipment |
-
2020
- 2020-05-13 CN CN202010402443.9A patent/CN111572549A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105599642A (en) * | 2015-12-18 | 2016-05-25 | 小米科技有限责任公司 | Automatic adjusting method, device and terminal for seat |
| WO2018034121A1 (en) * | 2016-08-15 | 2018-02-22 | アイシン精機 株式会社 | Vehicular seat adjustment device, position adjustment control device, and vehicular seat adjustment method |
| CN108460707A (en) * | 2018-03-12 | 2018-08-28 | 林为庆 | A kind of the operation intelligent supervision method and its system of student |
| CN108515882A (en) * | 2018-03-30 | 2018-09-11 | 天津经纬恒润科技有限公司 | A kind of automotive seat adjusting method and device |
| CN108770351A (en) * | 2018-04-25 | 2018-11-06 | 深圳市元征软件开发有限公司 | Seat method of adjustment and seat adjusting apparatus |
| CN110466458A (en) * | 2019-08-23 | 2019-11-19 | 广州小鹏汽车科技有限公司 | A kind of control method, system and the vehicle of the car-mounted device being electrically adjusted |
| CN110723085A (en) * | 2019-09-29 | 2020-01-24 | 绿驰汽车科技集团有限公司 | Personalized adjusting method and system for vehicle function equipment |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112339622A (en) * | 2020-11-10 | 2021-02-09 | 宁波均联智行科技股份有限公司 | Seat adjusting method and device and vehicle-mounted system |
| CN113029058A (en) * | 2021-03-10 | 2021-06-25 | 中国第一汽车股份有限公司 | Pose parameter acquisition method and device, vehicle and storage medium |
| CN113212257A (en) * | 2021-05-18 | 2021-08-06 | 中国第一汽车股份有限公司 | Automatic driver seat position adjusting method, device, terminal and storage medium based on Internet of vehicles |
| CN113734012A (en) * | 2021-07-29 | 2021-12-03 | 岚图汽车科技有限公司 | Control method and device for vehicle central armrest |
| CN113734012B (en) * | 2021-07-29 | 2022-11-29 | 岚图汽车科技有限公司 | Control method and device for vehicle central armrest |
| CN113954703A (en) * | 2021-11-29 | 2022-01-21 | 东风汽车有限公司东风日产乘用车公司 | Vehicle space adjusting method, electronic device, and storage medium |
| CN114954151A (en) * | 2022-05-11 | 2022-08-30 | 重庆金康赛力斯新能源汽车设计院有限公司 | Method and device for automatically adjusting seat, computer equipment and storage medium |
| CN114889540A (en) * | 2022-05-13 | 2022-08-12 | 重庆金康赛力斯新能源汽车设计院有限公司 | Driving posture state adjusting method and device, computer equipment and storage medium |
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