Self-adaptive in-vehicle space configuration method and device, control equipment, system and product

Abstract

The embodiment of the invention discloses a self-adaptive in-vehicle space configuration method and device, control equipment, a system and a product, which are applied to the control equipment and comprise the following steps: receiving sensor data collected by an intelligent sensor network deployed in a vehicle; according to the sensor data, determining a seat occupation condition, rear-row space information and information of a to-be-loaded object, and according to the seat occupation condition, the rear-row space information and the information of the to-be-loaded object, determining an in-vehicle space configuration scheme; a seat adjusting instruction is sent to an executing mechanism according to the in-vehicle space configuration scheme, so that the executing mechanism adjusts in-vehicle seats according to the seat adjusting instruction until the in-vehicle space meets the in-vehicle space configuration scheme. According to the technical scheme, the in-vehicle space configuration scheme is determined according to the sensor data, the in-vehicle seats are adjusted according to the in-vehicle space configuration scheme, the optimal space layout of the in-vehicle seats is provided through dynamic adjustment, the in-vehicle space is utilized to the maximum extent, and the use convenience of a user is improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of intelligent control technology, and in particular to an adaptive vehicle interior space configuration method, device, control equipment, system and product. Background Art

[0002] In the automotive industry, efficient use of interior space has always been one of the key directions of design and innovation. At present, car seat configuration mainly relies on manual adjustment, such as foldable rear seats to increase trunk space. Some high-end models are equipped with electric adjustment seats, but they are mainly limited to the adjustment of seat tilt angle and front and rear position, and cannot actively adjust the space configuration according to the number of passengers and usage scenarios. Summary of the invention

[0003] The embodiments of the present disclosure provide a method, device, control equipment, system and product for adaptively configuring the interior space of a vehicle, which improve the efficiency and accuracy of matching.

[0004] In a first aspect, an adaptive in-vehicle space configuration method is provided, which is applied to a control device, and includes:

[0005] Receive sensor data collected by the smart sensor network deployed in the vehicle;

[0006] Determine seat occupancy, rear space information and information about objects to be loaded according to the sensor data, and determine a vehicle interior space configuration plan according to the seat occupancy, rear space information and information about objects to be loaded;

[0007] A seat adjustment instruction is sent to an actuator according to the in-vehicle space configuration plan, so that the actuator adjusts the in-vehicle seat according to the seat adjustment instruction until the in-vehicle space satisfies the in-vehicle space configuration plan.

[0008] In a second aspect, an adaptive vehicle interior space configuration device is provided, comprising:

[0009] A data receiving module, used to receive sensor data collected by a smart sensor network deployed in the vehicle;

[0010] a scheme determination module, configured to determine seat occupancy, rear space information, and information about objects to be loaded according to the sensor data, and determine an in-vehicle space configuration scheme according to the seat occupancy, rear space information, and information about objects to be loaded;

[0011] The adjustment module is used to send a seat adjustment instruction to the actuator according to the in-vehicle space configuration plan, so that the actuator adjusts the in-vehicle seat according to the seat adjustment instruction until the in-vehicle space meets the in-vehicle space configuration plan.

[0012] In a third aspect, a control device is provided, including:

[0013] one or more processors;

[0014] a storage device for storing one or more programs,

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement the adaptive vehicle interior space configuration method as described in the first aspect above.

[0016] In a fourth aspect, an adaptive in-vehicle space configuration system is provided, comprising: an intelligent sensor network, an actuator, and a control device as described in the third aspect; the control device is connected to the intelligent sensor network and the actuator respectively;

[0017] The intelligent sensor network is used to collect sensor data and transmit the sensor data to the control device; the intelligent sensor network includes at least one sensor;

[0018] The actuator is used to adjust the seat in the vehicle according to the seat adjustment instruction.

[0019] In a fifth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method for adaptive in-vehicle space configuration as described in the first aspect is implemented.

[0020] In a sixth aspect, a computer program product is provided, the computer program product comprising a computer program, and the computer program, when executed by a processor, implements the adaptive in-vehicle space configuration method as described in the first aspect above.

[0021] The disclosed embodiments disclose an adaptive in-vehicle space configuration method, device, control device, system and product, including: applied to a control device, including: receiving sensor data collected by an intelligent sensor network deployed in the vehicle; determining seat occupancy, rear space information and information of objects to be loaded according to the sensor data, and determining an in-vehicle space configuration scheme according to the seat occupancy, the rear space information and the information of objects to be loaded; sending seat adjustment instructions to an actuator according to the in-vehicle space configuration scheme, so that the actuator adjusts the in-vehicle seats according to the seat adjustment instructions until the in-vehicle space meets the in-vehicle space configuration scheme. This technical solution determines the in-vehicle space configuration scheme according to the sensor data and adjusts the in-vehicle seats according to the in-vehicle space configuration scheme, provides the best spatial layout of the in-vehicle seats through dynamic adjustment, reduces the complexity of operation, maximizes the use of the in-vehicle space, and improves user convenience.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the embodiments of the present disclosure. Other features of the embodiments of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 is a flow chart of an adaptive in-vehicle space configuration method provided by Embodiment 1 of the present disclosure;

[0025] Figure 2 is a schematic structural diagram of an adaptive in-vehicle space configuration device provided in the second disclosed embodiment;

[0026] Figure 3 is a structural diagram of a control device provided in Embodiment 3 of the present disclosure;

[0027] Figure 4 It is a structural diagram of an adaptive in-vehicle space configuration system provided in Embodiment 4 of the present disclosure. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solutions of the embodiments of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the embodiments of the present disclosure.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0030] Embodiment 1

[0031] Figure 1 This is a flowchart of an adaptive in-vehicle space configuration method provided in the first embodiment of the present disclosure. This embodiment is applicable to the case of adaptively configuring the in-vehicle space. The method can be executed by an adaptive in-vehicle space configuration device. The adaptive in-vehicle space configuration device can be implemented in the form of hardware and / or software. The adaptive in-vehicle space configuration device can be applied to control devices, including but not limited to computers, computers, terminals, servers and other devices with data processing capabilities. The control device may include a vehicle, and the vehicle may have functions such as automatic driving or assisted driving. Figure 1 As shown, the method includes:

[0032] S110: Receive sensor data collected by a smart sensor network deployed in the vehicle.

[0033] In this embodiment, the smart sensor network may include at least one sensor, such as a weight sensor, a proximity sensor, an object detection sensor, a space dimension measurement sensor, and / or a pressure sensor, etc. The sensors in the smart sensor network may be distributed at key locations in the vehicle, including under the seat, at the edge of the door, and / or at the roof, etc.

[0034] Exemplarily, a weight sensor can be installed under a seat in the car to detect the weight on the seat, determine whether there is a passenger sitting on it and the approximate weight of the passenger. With this information, the number and distribution of passengers can be inferred. Proximity sensors can be deployed near doors, windows and other key areas to detect the approach of passengers or objects, and can also be used to monitor the opening and closing status of doors, passengers entering and exiting, and other behaviors. Pressure sensors can be installed on seats or on the floor inside the car to detect pedaling force, which is used to accurately locate the distribution of passengers and objects in the car. Object detection sensors and space dimension measurement sensors can be used to monitor the information of the rear space and objects to be loaded in real time. Object detection sensors use infrared, ultrasonic and other technologies to detect objects and measure distances.

[0035] Continuing with the above description, the smart sensor network can be used to collect sensor data, and the sensor data can include data from at least two sensors; the smart sensor network can transmit the collected sensor data to the control device, and the control device can be used to receive the sensor data transmitted by the smart sensor, wherein the control device can be used to analyze data and generate solutions. Exemplarily, the control device can be a central control unit (CCU).

[0036] S120, determining seat occupancy, rear space information, and information about objects to be loaded based on sensor data, and determining an in-vehicle space configuration plan based on the seat occupancy, rear space information, and information about objects to be loaded.

[0037] Specifically, after receiving the sensor data, the control device can process the received sensor, such as data fusion processing. The control device can determine the seat occupancy, rear space information and information about the object to be loaded based on the sensor data, wherein the seat occupancy can be whether someone is sitting on the seat in the car or whether there is an object placed on the seat, that is, the occupancy of the seat in the car; the rear space information can be the space information in the car except the driver's seat and the co-driver's seat and / or the space information of the trunk of the vehicle, such as: for a four-seater car, the rear space is the space information behind the driver's seat and the co-driver's seat, and the information about the object to be loaded can be the information about the object that the user needs to place in the car.

[0038] Continuing with the above description, after determining the seat occupancy status, rear space information and information about objects to be loaded through sensor data, the interior space configuration plan can be determined based on the seat occupancy status, rear space information and information about objects to be loaded, wherein the interior space configuration plan can be a movement plan for the interior seats. Exemplarily, the interior space configuration plan can include: moving the front seats forward, moving the front seats backward, moving the rear seats forward, moving the rear seats backward, folding the front seats down and / or folding the rear seats down.

[0039] S130. Sending a seat adjustment instruction to the actuator according to the in-vehicle space configuration plan, so that the actuator adjusts the in-vehicle seat according to the seat adjustment instruction until the in-vehicle space satisfies the in-vehicle space configuration plan.

[0040] Specifically, after the control device determines the in-vehicle space configuration scheme according to the seat occupancy status, the rear space information, and the information of the object to be loaded, the control device may send a seat adjustment instruction to the actuator according to the obtained in-vehicle space configuration scheme. The actuator may receive the seat adjustment instruction sent by the control device, and adjust the in-vehicle seat according to the seat adjustment instruction, wherein the seat adjustment instruction may be an instruction for adjusting the in-vehicle seat.

[0041] Among them, the actuator may include basic mechanical structures and electronic control systems such as electric motors and transmission tracks. The actuator may adjust the seats in the vehicle according to the seat adjustment instructions, such as: automatically folding the rear seats, adjusting the front and rear positions of the rear seats and / or other adjustable components in the vehicle, such as: interior partitions, etc.

[0042] This embodiment provides an adaptive in-vehicle space configuration method, including: receiving sensor data collected by an intelligent sensor network deployed in the vehicle; determining seat occupancy, rear space information, and information about objects to be loaded based on the sensor data, and determining an in-vehicle space configuration scheme based on the seat occupancy, rear space information, and information about objects to be loaded; sending seat adjustment instructions to an actuator based on the in-vehicle space configuration scheme, so that the actuator adjusts the in-vehicle seats based on the seat adjustment instructions until the in-vehicle space meets the in-vehicle space configuration scheme. This technical solution determines the in-vehicle space configuration scheme based on sensor data and adjusts the in-vehicle seats based on the in-vehicle space configuration scheme, provides the best spatial layout of the in-vehicle seats through dynamic adjustment, reduces operational complexity, maximizes the use of the in-vehicle space, and improves user convenience.

[0043] As an optional implementation of this embodiment, the adaptive in-vehicle space configuration method provided in this embodiment may further include:

[0044] a1) Obtain user preferences through the user interface;

[0045] In this embodiment, the user interface includes a touch screen and / or a semantic recognition module, and user preferences can be obtained through the user interface, wherein the user preferences can include seat movement distance information set by the user. For example, the user preference can be that the front and rear distance of each seat movement set by the user is 1 cm. The user preference can also be the maximum distance that the seat in the car moves forward or backward set by the user, such as: the user preference can be that the maximum forward movement of the rear seat in the car is 10 cm.

[0046] b1) Upon obtaining the user's preferences, the seat is adjusted in real time according to the user's preferences.

[0047] Specifically, after obtaining the user preference through the user interface, the seat in the car can be adjusted in real time according to the user preference. It should be noted that the user can also directly adjust the seat in the car through the user interface.

[0048] Optionally, determining the seat occupancy status, rear space information, and information of the object to be loaded according to the sensor data includes:

[0049] a2) fusing the data of each sensor based on a data fusion algorithm to obtain fused data; the data fusion algorithm includes a Kalman filter algorithm and / or a weighted average algorithm;

[0050] It can be known that after acquiring the sensor data, the control device can fuse the acquired sensor data based on the data fusion algorithm. The main goal of data fusion is to integrate the data acquired from multiple sensors, improve the accuracy and reliability of the data, and ultimately use it to more accurately identify and optimize the state inside the vehicle. Among them, the data fusion algorithm can be an algorithm for fusing data. In this embodiment, the data fusion algorithm can include a Kalman filter algorithm and / or a weighted average algorithm.

[0051] Among them, Kalman Filter (KF) is a recursive estimation method that can use noisy and uncertain measurements in dynamic systems to estimate the system state. It is very suitable for sensor data fusion, especially when the signal is noisy or the signal is not completely reliable. The steps of using Kalman filtering for data fusion mainly include: using the previous state of Kalman filtering and control input u k Predict current state and state covariance

[0052]

[0053] Among them, A can be the state transfer matrix, B can be the control input matrix, Q can be the process noise covariance matrix, and A T It can be the transposed matrix of the state transfer matrix.

[0054] Calculate the measurement residual (the difference between the predicted observation and the actual observation) based on the current state y k , the measurement residual can be expressed as: Among them, z k It can be sensor data, and H can be the measurement matrix. The Kalman gain K is calculated based on the state covariance. k , used to adjust the predicted state, Kalman gain Kk It can be expressed as: Where R is the covariance matrix of the measurement noise, and H T It can be the transposed matrix of the measurement matrix.

[0055] The state estimate and covariance are updated using the Kalman gain and measurement residuals: The state estimate can be expressed as The calculation formula can be expressed as: The state covariance can be expressed as The calculation formula can be expressed as: By recursively updating the predicted and actual values, the Kalman filter provides a stable and highly accurate state estimate in dynamic systems.

[0056] In this embodiment, weighted averaging is another simple and effective multi-sensor data fusion method. It obtains fused data by weighted averaging the sensor data according to the reliability of each sensor. The steps of the weighted averaging method mainly include: determining the corresponding weight w according to the performance, reliability and other attributes of each sensor i . These weights usually satisfy: The data x of each sensor i Multiply by the corresponding weight, and then sum to get the final fusion data The formula can be expressed as:

[0057] For example, for the data fusion of the weight sensor and the pressure sensor, the weight sensor data is represented as x1, the weight of the weight sensor data can be represented as w1, the pressure sensor data is represented as x2, the weight of the pressure sensor data can be represented as w2, then the fused data can be represented as: It should be noted that when the data of the weight sensor and the pressure sensor are fused using the weighted average method, if the weight sensor signal is more reliable, the weight w1>w2 can be set.

[0058] Exemplarily, the Kalman filter can be used to predict changes in passenger weight and sensor calibration; the proximity sensor data at different locations can be integrated using the weighted average method; the Kalman filter can be used to track the movements of passengers entering and exiting the door to ensure real-time and accuracy; when the data of infrared sensors and ultrasonic sensors are fused using the weighted average method, the weighted value can be set according to the accuracy and error of different sensors; the Kalman filter can be used to dynamically correct and fuse object measurement data to ensure the reliability of object detection and size measurement.

[0059] By fusing sensor data through data fusion algorithms, the impact of a single sensor noise on the overall system can be reduced. Multi-sensor data fusion can provide more accurate measurement results. When a sensor fails, the system can rely on data from other sensors to maintain normal operation of the system. In summary, by combining algorithms such as Kalman filters and weighted average methods, the accuracy and reliability of sensor data can be effectively improved, thereby achieving accurate identification and optimization of the vehicle's internal status.

[0060] b2) According to the fused data, the seat occupancy status, rear space information and information of the objects to be loaded inside the vehicle are determined based on an object recognition algorithm.

[0061] It can be known that after the acquired sensor data is fused by the data fusion algorithm to obtain fused data, the seat occupancy status, rear space information and information of the object to be loaded in the vehicle can be determined based on the fused data and the object recognition algorithm. Among them, the object recognition algorithm can be an algorithm that can recognize objects. For example, the object recognition algorithm can be a convolutional neural network algorithm, a target detection algorithm, etc.

[0062] For example, based on the fusion data of the weight sensor and the pressure sensor, the object recognition algorithm can be used to determine whether the seat is in use and the distribution of passengers; based on the fusion data of the object detection sensor and the space dimension measurement sensor, the object recognition algorithm can be used to realize real-time monitoring of the rear space and the information of the objects to be loaded.

[0063] In this embodiment, the seat occupancy status inside the vehicle may be whether there are people and / or objects on the vehicle seats, the rear space information may be the space information inside the vehicle excluding the driver's seat and the co-driver's seat, and the information on objects to be loaded may be the information on objects that the user needs to place in the vehicle.

[0064] As an optional implementation manner of this embodiment, determining the in-vehicle space configuration scheme according to the seat occupancy status, the rear space information and the information of the object to be loaded includes:

[0065] According to the seat occupancy status, the rear space information and the information of the object to be loaded, the in-vehicle space configuration scheme is determined based on preset adjustment rules and user preferences.

[0066] In this embodiment, after obtaining the seat occupancy status, the rear space information and the information of the object to be loaded, the in-vehicle space configuration scheme can be determined based on the seat occupancy status, the rear space information and the information of the object to be loaded, based on the preset adjustment rules and user preferences. Among them, the preset adjustment rules may include a preset moving distance of each movement of the in-vehicle seat and / or the maximum distance that the in-vehicle seat can move. Specifically, the in-vehicle space configuration scheme can also be determined based on a dynamic programming algorithm, preset adjustment rules, user preferences, seat occupancy status, the rear space information and the information of the object to be loaded, wherein the dynamic programming algorithm may be an algorithm that can implement dynamic programming.

[0067] The adaptive in-vehicle space configuration method provided in this embodiment determines the in-vehicle space configuration plan through an intelligent sensor network, actively adjusts the space configuration according to the number of passengers and usage scenarios, and realizes real-time dynamic adjustment of seats to meet the needs of different passengers and usage scenarios. The user does not need to intervene directly, and this technical solution can independently complete the space configuration adjustment.

[0068] The beneficial effects of this technical solution include: enhanced flexibility and practicality, and maximizing the use of in-vehicle space through intelligent dynamic adjustment of seat configuration, whether it is to improve comfort when the number of passengers changes, or to optimize the cargo area when a large amount of loading space is required. At the same time, it can adapt to a variety of usage needs, from carrying passengers to loading, from long-distance travel to daily commuting, and can dynamically adjust to provide the best space layout. The technical solution of this embodiment is easier to operate, and there is no need for users to manually adjust the seats, which improves ease of use. Users can start and complete adjustments through simple voice commands or preset start conditions, reducing the complexity of operations and increasing convenience of use. The use of dynamic programming algorithms and efficient mechanical structures ensures that seat adjustments are completed quickly, improves system response speed, and enhances user satisfaction.

[0069] Embodiment 2

[0070] Figure 2 is a schematic diagram of the structure of an adaptive in-vehicle space configuration device provided in the second embodiment of the present disclosure; Figure 2 As shown, the device includes: a data receiving module 210, a solution determining module 220, and an adjustment module 230.

[0071] The data receiving module 210 is used to receive sensor data collected by the intelligent sensor network deployed in the vehicle;

[0072] a scheme determination module 220, for determining seat occupancy, rear space information and information of objects to be loaded according to the sensor data, and determining an in-vehicle space configuration scheme according to the seat occupancy, the rear space information and the information of the objects to be loaded;

[0073] The adjustment module 230 is used to send a seat adjustment instruction to the actuator according to the in-vehicle space configuration plan, so that the actuator adjusts the in-vehicle seat according to the seat adjustment instruction until the in-vehicle space meets the in-vehicle space configuration plan.

[0074] Embodiment 2 of the present disclosure provides an adaptive in-vehicle space configuration device, which provides an optimal spatial layout of in-vehicle seats through dynamic adjustment, reduces operational complexity, maximizes the use of in-vehicle space, and improves user convenience.

[0075] Furthermore, the device also includes:

[0076] A preference acquisition module, used to acquire user preferences through a user interface;

[0077] The real-time adjustment module is used to adjust the seat in real time according to the user preferences when the user preferences are obtained.

[0078] Further, the sensor data includes data from at least two sensors;

[0079] The solution determination module 220 is further used for:

[0080] The data of each sensor is fused based on a data fusion algorithm to obtain fused data; the data fusion algorithm includes a Kalman filter algorithm and / or a weighted average algorithm;

[0081] According to the fused data, the seat occupancy status inside the vehicle, the rear space information and the information of the object to be loaded are determined based on the object recognition algorithm.

[0082] Furthermore, the solution determination module 220 is also used to:

[0083] According to the seat occupancy status, the rear space information and the information of the object to be loaded, the in-vehicle space configuration scheme is determined based on preset adjustment rules and user preferences.

[0084] The adaptive in-vehicle space configuration device provided in the embodiments of the present disclosure can execute the adaptive in-vehicle space configuration method provided in any embodiment of the embodiments of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0085] Embodiment 3

[0086] Figure 3A schematic diagram of a control device 10 that can be used to implement an embodiment of the present disclosure is shown. The control device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present disclosure described and / or claimed herein.

[0087] like Figure 3 As shown, the control device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the control device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0088] A number of components in the control device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the control device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0089] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microprocessor, etc. The processor 11 executes the various methods and processes described above, such as the adaptive in-vehicle space configuration method.

[0090] In some embodiments, the adaptive in-vehicle space configuration method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the control device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the adaptive in-vehicle space configuration method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the adaptive in-vehicle space configuration method in any other appropriate manner (e.g., by means of firmware).

[0091] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0092] The computer programs for implementing the methods of the embodiments of the present disclosure may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0093] In the context of the disclosed embodiments, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0094] To provide interaction with a user, the systems and techniques described herein may be implemented on a control device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the control device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0095] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0096] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0097] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in the embodiments of the present disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions of the embodiments of the present disclosure can be achieved, and this document does not limit this.

[0098] The above specific implementations do not constitute a limitation on the protection scope of the embodiments of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the embodiments of the present disclosure shall be included in the protection scope of the embodiments of the present disclosure.

[0099] The embodiments of the present disclosure also provide a computer program product, including a computer program and / or instructions, which, when executed by a processor, implements the adaptive in-vehicle space configuration method provided in any embodiment of the present application.

[0100] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to write computer program codes for performing the operation of the disclosed embodiments, the programming languages ​​including object-oriented programming languages, such as Java, Smalltalk, C++, and also including conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0101] Note that the above are only preferred embodiments of the embodiments of the present disclosure and the technical principles used. Those skilled in the art will understand that the embodiments of the present disclosure are not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the embodiments of the present disclosure. Therefore, although the embodiments of the present disclosure are described in more detail through the above embodiments, the embodiments of the present disclosure are not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the embodiments of the present disclosure, and the scope of the embodiments of the present disclosure is determined by the scope of the attached claims.

[0102] Embodiment 4

[0103] Embodiment 4 of the present disclosure provides an adaptive in-vehicle space configuration system. The system includes an intelligent sensor network, an actuator, and a control device provided by any of the above embodiments; the control device is connected to the intelligent sensor network and the actuator respectively; the intelligent sensor network is used to collect sensor data and transmit the sensor data to the control device; the intelligent sensor network includes at least one sensor; the actuator is used to adjust the seat in the vehicle according to the seat adjustment instruction.

[0104] Specifically, Figure 4 A schematic diagram of the structure of an adaptive in-vehicle space configuration system 40 provided in this embodiment is shown in FIG. Figure 4 As shown, the system includes: an intelligent sensor network 401, an actuator 402 and a control device 403, wherein the control device is connected to the intelligent sensor network and the actuator respectively, the intelligent sensor network includes at least two sensors, the intelligent sensor network obtains sensor data, and transmits the obtained sensor data to the control device, the control device is used to receive the sensor data, determine the seat occupancy, rear space information and information of the object to be loaded according to the sensor data, and determine the in-vehicle space configuration scheme according to the seat occupancy, the rear space information and the information of the object to be loaded; the control device sends a seat adjustment instruction to the actuator according to the in-vehicle space configuration scheme. The actuator can receive the adjustment instruction sent by the control device, and adjust the seat in the vehicle according to the received seat adjustment instruction.

[0105] It should be noted that the adaptive in-vehicle space configuration system provided in this embodiment may also include: a user interface; the user interface is connected to the control device; the user interface includes a touch screen and / or a voice recognition module; the user interface is used to obtain user preferences through the user interface; when the user preferences are obtained, the seat is adjusted in real time according to the user preferences.

[0106] Specifically, the user can input user preferences through the touch screen and / or voice recognition module. After the user interface obtains the user preferences, the seat in the car is adjusted in real time according to the obtained user preferences, wherein the user preferences include seat movement distance information set by the user.

[0107] The adaptive in-vehicle space configuration system provided in the fourth embodiment can be used to execute the adaptive in-vehicle space configuration method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

Claims

1. An adaptive vehicle interior space configuration method, characterized in that: Applied to a control device, the method comprises: Receive sensor data collected by the smart sensor network deployed in the vehicle; Determine seat occupancy, rear space information and information about objects to be loaded according to the sensor data, and determine a vehicle interior space configuration plan according to the seat occupancy, rear space information and information about objects to be loaded; A seat adjustment instruction is sent to an actuator according to the in-vehicle space configuration plan, so that the actuator adjusts the in-vehicle seat according to the seat adjustment instruction until the in-vehicle space satisfies the in-vehicle space configuration plan.

2. The method according to claim 1, characterized in that Also includes: Acquiring user preferences through the user interface; When the user preferences are obtained, the seat is adjusted in real time according to the user preferences.

3. The method according to claim 1, characterized in that The sensor data includes data of at least two sensors; The determining of seat occupancy, rear space information and information of objects to be loaded according to the sensor data includes: The data of each sensor is fused based on a data fusion algorithm to obtain fused data; the data fusion algorithm includes a Kalman filter algorithm and / or a weighted average algorithm; According to the fused data, the seat occupancy status inside the vehicle, the rear space information and the information of the object to be loaded are determined based on the object recognition algorithm.

4. The method according to claim 3, characterized in that The determining of the in-vehicle space configuration scheme according to the seat occupancy status, the rear space information and the information of the object to be loaded includes: According to the seat occupancy status, the rear space information and the information of the object to be loaded, the in-vehicle space configuration scheme is determined based on preset adjustment rules and user preferences.

5. An adaptive in-vehicle space configuration device, characterized in that: include: A data receiving module, used to receive sensor data collected by a smart sensor network deployed in the vehicle; a scheme determination module, configured to determine seat occupancy, rear space information, and information about objects to be loaded according to the sensor data, and determine an in-vehicle space configuration scheme according to the seat occupancy, rear space information, and information about objects to be loaded; The adjustment module is used to send a seat adjustment instruction to the actuator according to the in-vehicle space configuration plan, so that the actuator adjusts the in-vehicle seat according to the seat adjustment instruction until the in-vehicle space meets the in-vehicle space configuration plan.

6. A control device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the adaptive vehicle interior space configuration method as described in any one of claims 1-4.

7. An adaptive in-vehicle space configuration system, characterized in that: include: Intelligent sensor network, actuator and control device as claimed in claim 6; The control device is connected to the intelligent sensor network and the actuator respectively; The intelligent sensor network is used to collect sensor data and transmit the sensor data to the control device; the intelligent sensor network includes at least one sensor; The actuator is used to adjust the seat in the vehicle according to the seat adjustment instruction.

8. The system according to claim 7, characterized in that The system also includes: a user interface The user interface is connected to the control device; the user interface includes a touch screen and / or a voice recognition module; The user interface is used to obtain user preferences through the user interface; When the user preferences are obtained, the seat is adjusted in real time according to the user preferences.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the adaptive vehicle interior space configuration method as described in any one of claims 1-4 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the adaptive vehicle interior space configuration method as claimed in any one of claims 1 to 4.

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