A vehicle cabin control method and device, vehicle and storage medium

Abstract

The present disclosure provides a vehicle cabin control method and device, a vehicle and a storage medium, and relates to the fields of intelligent cabin and AI automobile. The method comprises the following steps: determining a travel scenario, setting a travel time and a first time according to travel schedule information of a user, the first time being earlier than the set travel time; determining travel characteristic information of the user in response to reaching the first time, the travel characteristic information being obtained by analyzing collected information of at least one first device in communication with the vehicle; and pre-adjusting the vehicle cabin based on the travel characteristic information. The method performs cross-scene data fusion between the vehicle and the Internet of Things device, determines the travel characteristic information based on the collected information of the first device, and then pre-adjusts the cabin individually, so that the user can experience the cabin state that adapts to the user's travel needs when getting into the vehicle. In this way, the cabin adjustment is more accurately matched with the actual travel needs of the user, thereby effectively improving the effect of cabin pre-adjustment and the user's experience.

Description

Technical Field

[0001] This disclosure relates to the fields of smart cockpit and AI automotive technology, and in particular to a vehicle cockpit control method, device, vehicle, and storage medium. Background Technology

[0002] With the rapid development of intelligent cockpit technology, users' demands for driving and riding comfort are increasing, as is their need for the cockpit to proactively sense and meet personalized settings. Currently, the vehicle cockpit typically performs pre-emptive control operations such as seat adjustment and air conditioning activation by sending commands to the user. However, this method relies on active user intervention, resulting in poor pre-adjustment effectiveness and a less than ideal user comfort and experience. Summary of the Invention

[0003] To overcome the problems existing in the related technologies, this disclosure provides a vehicle cockpit control method, device, vehicle, and storage medium.

[0004] According to a first aspect of the present disclosure, a vehicle cockpit control method is provided, comprising: determining a travel scenario, a set travel time for the travel scenario, and a first time based on a user's travel schedule information, wherein the first time is earlier than the set travel time; in response to arriving at the first time, determining the user's travel characteristic information, wherein the travel characteristic information is obtained by analyzing information collected by at least one first device communicating with the vehicle; and pre-adjusting the vehicle's cockpit based on the travel characteristic information.

[0005] This method integrates vehicle data with a first device (an IoT device) across different scenarios. Based on the information collected by the first device, it analyzes and determines the user's travel characteristics. Then, based on these characteristics, it performs personalized pre-adjustments to the cabin, ensuring the user experiences a cabin configuration tailored to their travel needs upon boarding. This approach allows for more precise cabin adjustments to match the user's actual travel requirements, effectively improving the pre-adjustment process and enhancing the user experience.

[0006] In conjunction with the first aspect, in some possible implementations, the vehicle cabin is pre-adjusted based on travel characteristic information, including: determining a target seat in the cabin based on the number of travelers in the travel characteristic information; and adjusting the position of the target seat based on the luggage size and number of luggage compartments in the travel characteristic information.

[0007] In this embodiment, the target seats to be activated can be determined based on the number of travelers, and the position of the target seats can be adjusted in combination with the actual size and quantity of luggage. This allows the cabin space layout to be adapted to the user's travel loading needs, effectively improving the cabin pre-adjustment effect and the comfort experience of cabin use.

[0008] In conjunction with the first aspect, in some possible implementations, the position of the target seat is adjusted based on the luggage size and number of luggage in the travel characteristic information, including: determining the total volume of the luggage based on the luggage size and number of luggage; and moving the target seat a first distance if the total volume of the luggage is greater than the preset trunk volume, the first distance being determined based on the total volume of the luggage, the preset trunk volume, and the trunk cross-sectional area.

[0009] In this embodiment, a first distance is determined based on the total volume of the luggage compartment, the preset trunk volume, and the trunk cross-sectional area, allowing for accurate determination of the target seat's movement distance. This ensures that the trunk space after the target seat is moved can meet the luggage placement requirements. This effectively improves the utilization efficiency of cabin space and enhances passenger comfort.

[0010] In conjunction with the first aspect, in some possible implementations, pre-adjusting the vehicle cabin based on travel characteristic information also includes: pre-adjusting the tailgate opening angle based on the number of luggage compartments in the travel characteristic information.

[0011] In this embodiment, the tailgate opening angle can be adapted to the number of suitcases, so that users do not need to manually adjust the tailgate when placing suitcases. The tailgate opening angle adjustment in the cabin is more in line with the user's suitcase placement needs, improving the convenience of luggage placement and further enhancing the user experience.

[0012] In conjunction with the first aspect, in some possible implementations, the tailgate opening angle is pre-adjusted based on the number of suitcases in the travel characteristic information, including: adjusting the tailgate opening angle to a first angle when the number of suitcases is less than a first quantity threshold; adjusting the tailgate opening angle to a second angle when the number of suitcases is greater than or equal to the first quantity threshold and less than a second quantity threshold, wherein the second angle is greater than the first angle; and adjusting the tailgate opening angle to a third angle when the number of suitcases is greater than or equal to the second quantity threshold, wherein the third angle is greater than the second angle.

[0013] In this embodiment, a precise adaptation of the tailgate opening angle is achieved through a tiered threshold system, ensuring that the tailgate opening angle matches the luggage placement requirements. This allows for more refined adjustment of the tailgate opening angle within the cabin, improving the effectiveness of cabin pre-adjustment.

[0014] In conjunction with the first aspect, in some possible implementations, pre-adjusting the vehicle cabin based on travel characteristic information further includes: pre-adjusting the cabin temperature based on a second time in the travel characteristic information; the second time is used to characterize the user's actual departure time.

[0015] In this embodiment, the second time when the user actually leaves home is used as the benchmark for cabin temperature pre-adjustment. This ensures that the start time of cabin temperature adjustment matches the user's actual travel time, accurately controlling the start timing of temperature pre-adjustment, improving the accuracy of cabin temperature adjustment, and further enhancing the user experience.

[0016] In conjunction with the first aspect, in some possible implementations, the cabin temperature is pre-adjusted based on the second time in the travel characteristic information, including: acquiring first location information and second location information, where the first location information is used to characterize the vehicle's location and the second location information is used to characterize the user's departure location; determining the third time when the user is expected to board the vehicle based on the second time, the first location information, and the second location information; and controlling the air conditioning in the cabin to pre-adjust the cabin temperature based on the third time.

[0017] In this embodiment, the cabin temperature pre-adjustment time can accurately match the user's expected third time to board the vehicle, avoiding energy waste caused by adjusting the temperature too early, and also preventing the user from feeling uncomfortable after boarding due to adjusting too late. This greatly improves the timeliness and accuracy of cabin temperature adjustment, making the cabin temperature adjustment more in line with the user's actual travel experience.

[0018] In conjunction with the first aspect, in some possible implementations, based on a third time, the air conditioning in the cabin is controlled to pre-adjust the cabin temperature, including: acquiring the ambient temperature of the vehicle; determining a fourth time for the air conditioning to be pre-activated based on the ambient temperature, the target temperature, and the third time; and controlling the air conditioning to operate at the fourth time so that the cabin temperature reaches the target temperature at the third time.

[0019] In this embodiment, the air conditioning operation is controlled based on the fourth time, which enables the air conditioning to start at the right time and match the temperature adjustment requirements. This ensures the temperature comfort of the cabin and avoids the energy loss caused by the air conditioning starting too early, thus achieving precise pre-adjustment of cabin temperature.

[0020] In conjunction with the first aspect, in some possible implementations, controlling the air conditioner operation at a fourth time includes at least one of the following: controlling the air conditioner to operate at a target air volume; controlling the air conditioner to operate in a target operating mode; controlling the air conditioner to operate at a target wind speed; wherein the target air volume and / or target operating mode are determined based on seasonal information and / or ambient temperature, the target wind speed is determined based on the travelers and the areas corresponding to the air conditioner's air outlets, and in the case of children among the travelers, the wind speed of the air outlet corresponding to the child seat area is lower than the wind speed of the air outlet corresponding to other areas.

[0021] In this embodiment, the air conditioning operation can be finely controlled from three air conditioning operating parameters: target air volume, target operating mode, and target wind speed, so that the air conditioning operating parameters are adapted to the ambient temperature and seasonal characteristics, thereby improving the effect of cabin temperature regulation.

[0022] In conjunction with the first aspect, in some possible implementations, the travel scenario, the set travel time for the travel scenario, and the first time are determined based on the user's travel schedule information, including: extracting time keywords, location keywords, and / or scenario keywords from the travel schedule information; determining the travel scenario based on the time keywords, location keywords, and / or scenario keywords, or determining the travel scenario based on location keywords and / or scenario keywords; determining the set travel time based on the time keywords; and determining the first time based on the set travel time and a preset duration.

[0023] In this embodiment, precise identification of the travel scenario is achieved by comprehensively judging time keywords, location keywords, and scenario keywords extracted from the travel schedule information, so that the triggering of cabin pre-adjustment is more in line with the user's actual travel plan. Furthermore, determining the first time based on the set travel time and preset duration improves the flexibility and accuracy of cabin pre-adjustment, making it more in line with the user's personalized travel needs.

[0024] In conjunction with the first aspect, in some possible implementations, determining a user's travel characteristic information includes at least one of the following: acquiring at least one of the following from a camera device in at least one first device: the number of travelers, suitcase size, number of suitcases, and a second time; acquiring at least one of the following from a door lock device in at least one first device: the number of travelers and the second time; acquiring at least one of the following from a suitcase device in at least one first device: the size of the suitcase and the number of suitcases; determining at least one of the following from images captured by the camera device: the number of travelers, suitcase size, number of suitcases, and the second time; determining at least one of the following from unlocking information collected by the door lock device; and determining at least one of the following from suitcase information collected by the suitcase device: the size of the suitcase and the number of suitcases.

[0025] In this embodiment, by collecting and analyzing multi-dimensional data from multiple types of first devices, accurate determination of travel characteristic information can be achieved. This effectively avoids the limitations and errors of data collected from a single device, ensuring the authenticity and completeness of travel characteristic information. Consequently, the pre-adjustment of the cabin matches the user's travel needs, significantly improving the accuracy and comfort of cabin pre-adjustment. Furthermore, the multi-device data acquisition method also enhances adaptability and expands application scenarios.

[0026] According to a second aspect of the present disclosure, a vehicle cabin control device is provided, comprising: a scenario determination module, configured to determine a travel scenario, a set travel time for the travel scenario, and a first time, wherein the first time is earlier than the set travel time, based on a user's travel schedule information; a travel characteristic determination module, configured to determine the user's travel characteristic information in response to the arrival of the first time, wherein the travel characteristic information is obtained by analyzing information collected by at least one first device communicating with the vehicle; and a control module, configured to pre-adjust the vehicle cabin based on the travel characteristic information.

[0027] In conjunction with the second aspect, in some possible implementations, the control module is used to: determine the target seat in the cabin based on the number of travelers in the travel characteristic information; and adjust the position of the target seat based on the luggage size and number of luggage in the travel characteristic information.

[0028] In conjunction with the second aspect, in some possible implementations, the control module is also used to: pre-adjust the opening angle of the tailgate of the cabin based on the number of suitcases in the travel characteristic information.

[0029] In conjunction with the second aspect, in some possible implementations, the control module is also used to: pre-adjust the cabin temperature based on a second time in the travel characteristic information; the second time is used to characterize the user's actual departure time.

[0030] According to a third aspect of the present disclosure, a vehicle is provided, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the vehicle cockpit control method of the first aspect and any alternative embodiment.

[0031] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, which, when instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to perform the vehicle cockpit control method as described in the first aspect and any alternative embodiment.

[0032] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the vehicle cockpit control method of the first aspect and any alternative implementation.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0035] Figure 1 A flowchart of a vehicle cockpit control method provided in this disclosure embodiment;

[0036] Figure 2 A flowchart illustrating a method for pre-adjusting a vehicle's cabin, as provided in an embodiment of this disclosure; Figure 3 This is a schematic diagram of the structure of a vehicle cockpit control device provided in an embodiment of the present disclosure; Figure 4 A block diagram of a vehicle provided in an embodiment of this disclosure. Detailed Implementation

[0037] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0038] Numerous specific details are set forth in the following description to provide a full understanding of this disclosure. However, this disclosure can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this disclosure. Therefore, this disclosure is not limited to the specific implementations disclosed below.

[0039] The terminology used in one or more embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this disclosure. The singular forms “a,” “the,” and “the” as used in one or more embodiments of this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this disclosure refers to and includes any or all possible combinations of one or more associated listed items.

[0040] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this disclosure, and similarly, second may also be referred to as first. Depending on the context, the word “if” as used herein may be interpreted as “when”, “in response to a determination”, or “when…”.

[0041] With the rapid development of intelligent cockpit technology, users' demands for driving and riding comfort are increasing, as is their need for the cockpit to proactively sense and meet personalized settings. Currently, the vehicle cockpit typically performs pre-emptive control operations such as seat adjustment and air conditioning activation by sending commands to the user. However, this method relies on active user operation and cannot accurately match actual travel needs to achieve more proactive adjustments, resulting in poor pre-adjustment effects and a less than ideal user comfort and experience.

[0042] To address the aforementioned technical problems, this disclosure provides a vehicle cockpit control method, device, server, vehicle, and storage medium. This method can utilize Internet of Things (IoT) devices (e.g., smart home devices) to determine information characterizing a user's travel features, such as their home behavior and current status, and based on this travel feature information, achieve personalized pre-adjustment of the vehicle's cockpit. This allows for more precise matching of cockpit adjustments to the user's actual travel needs, thereby effectively improving the pre-adjustment effect and user experience.

[0043] The vehicle cockpit control method provided in this disclosure can be applied to application scenarios where IoT devices (e.g., smart home devices) and intelligent connected vehicles work together. Examples of IoT devices include, but are not limited to, smart cameras, smart door locks, and smart suitcases.

[0044] In this disclosed embodiment, the collection, storage, use, processing, transmission, provision, and application of user personal information (including image information, fingerprint information, etc.) all comply with relevant laws and regulations and do not violate public order and good morals. It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notification and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0045] The solutions provided by the embodiments of this disclosure will now be described in conjunction with the accompanying drawings.

[0046] The vehicle cockpit control method provided in this disclosure can be applied to the vehicle itself, for example, executed by a vehicle control system with integrated cockpit control functions, or by a processor or cockpit control module in the vehicle. This disclosure does not limit its application. The following examples illustrate vehicle cockpit control methods executed by vehicles, using some embodiments of this disclosure as examples. Figure 1A flowchart of a vehicle cockpit control method provided in this disclosure embodiment is shown below. Figure 1 As shown, the vehicle cockpit control method includes the following steps S101-S103: Step S101: Based on the user's travel schedule information, determine the travel scenario, the set travel time for the travel scenario, and the first time.

[0047] In this embodiment of the disclosure, firstly, the user's travel schedule information can be obtained. For example, the travel schedule information could be: Saturday 9:00 AM, family trip to scenic spot A. Further, based on this travel schedule information, the travel scenario and initial time can be determined.

[0048] The travel scenario can be a pre-defined target scenario requiring cabin pre-adjustment, such as a leisure trip or business trip. The set travel time is the planned travel time specified in the travel schedule information, and the first time can be determined based on the set travel time, being earlier than that set travel time. This allows for the pre-adjustment of the cabin to be executed in advance based on the first time.

[0049] Step S102: In response to the arrival time, determine the user's travel characteristic information.

[0050] Upon arrival, the user's travel characteristics can be determined by analyzing information collected from at least one first device communicating with the vehicle. This first device is an Internet of Things (IoT) device (smart home device) communicating with the vehicle, such as a smart camera, smart door lock, or smart suitcase. Travel characteristics can include the user's home behavior, travel status, and luggage characteristics—features that characterize travel patterns. This allows for the determination of the user's actual travel needs based on the travel characteristics, enabling further cabin pre-adjustment. Communication between the first device and the vehicle can be direct or indirect, such as directly establishing a communication connection between the smart door lock and the vehicle, or indirectly connecting through the user's terminal device (e.g., a mobile phone or wearable device). This disclosure does not limit the scope of the communication.

[0051] In one implementation, travel characteristic information can be obtained by the vehicle through at least one first device, that is, travel characteristic information can be determined by at least one first device based on the analysis of the collected information.

[0052] In another implementation, travel characteristic information can also be determined by analyzing information collected by the vehicle based on at least one first device.

[0053] Step S103: Based on travel characteristic information, pre-adjust the vehicle cabin.

[0054] Furthermore, based on the travel characteristic information determined in S102, users' travel needs can be analyzed to pre-adjust the vehicle cabin in a personalized manner to meet those needs.

[0055] For example, pre-adjusting the cabin may include: identifying a target seat to be used in the cabin, adjusting the position of the target seat, pre-adjusting the tailgate opening angle, and pre-adjusting the cabin temperature.

[0056] The vehicle cockpit control method provided in this disclosure integrates cross-scenario data from the vehicle and a first device (Internet of Things device). Based on the information collected by the first device, it analyzes and determines the user's travel characteristics. Then, based on these travel characteristics, it performs personalized pre-adjustments to the cockpit, ensuring the user experiences a cockpit state suited to their travel needs upon boarding. This method allows for more precise cockpit adjustment to match the user's actual travel requirements, effectively improving the pre-adjustment effect and user experience.

[0057] In some embodiments of this disclosure, Figure 2 The flowchart illustrates a method for pre-adjusting a vehicle's cabin, as provided in this embodiment of the disclosure. Figure 2 As shown, the above-mentioned S103, based on travel characteristic information, pre-adjusts the vehicle's cabin, including the following steps S1031-S1032: Step S1031: Based on the number of travelers in the travel characteristic information, determine the target seats in the cabin.

[0058] In this embodiment, the travel characteristic information may include the number of travelers. Based on the number of travelers, seats matching the number of travelers can be selected from all seats in the vehicle cabin according to the seating layout rules, and these seats can be used as target seats.

[0059] For example, when there are 2 passengers, the 2 seats in the first row of the cabin can be identified as target seats. When there are 4 passengers, the 2 seats in the first row and the 2 seats in the second row of the cabin can be identified as target seats. When there are 6 passengers, the 2 seats in the first row, the 2 seats in the second row, and the 2 seats in the third row of the cabin can be identified as target seats.

[0060] Step S1032: Adjust the position of the target seat based on the luggage size and number of luggage in the travel feature information.

[0061] In this embodiment, the travel characteristic information may further include: luggage size and number of luggage compartments. Based on the luggage size and number of luggage compartments, the position of the target seat can be adjusted so that the vehicle's trunk volume can accommodate all the luggage compartments.

[0062] The method provided in this embodiment can determine the target seats to be used based on the number of travelers, and adjust the position of the target seats in combination with the actual size and quantity of luggage. This allows the cabin space layout to be adapted to the user's travel loading needs. While ensuring that the trunk can accommodate all luggage, the cabin space is utilized more efficiently. Users do not need to manually adjust the seats and plan the trunk space, which effectively improves the pre-adjustment effect of the cabin and the comfort experience of using the cabin.

[0063] In some embodiments of this disclosure, S1032, adjusting the position of the target seat based on the luggage size and number of luggage in the travel characteristic information, includes: First, determine the total volume of the suitcases based on their dimensions and the number of suitcases.

[0064] For example, for each suitcase, its volume can be calculated based on its dimensions, such as length, width, and height. Then, the volumes of all suitcases are added together to obtain the total volume. In this way, the required trunk space for a trip can be quantified based on the total volume of the suitcases.

[0065] Then, if the total volume of the luggage compartment is greater than the preset trunk volume, the target seat is moved a first distance.

[0066] In this embodiment, the determined total volume of the luggage compartment is compared with the preset trunk volume of the vehicle's trunk. This preset trunk volume is the usable trunk volume when the vehicle is in its standard state and the seats are not adjusted. If the total volume of the luggage compartment is greater than the preset trunk volume, it indicates that the trunk space needs to be expanded to accommodate all the luggage. In this case, the first distance that the target seat needs to move can be calculated based on the excess volume and the cross-sectional area of ​​the trunk. That is, the first distance can be determined based on the total volume of the luggage compartment, the preset trunk volume, and the cross-sectional area of ​​the trunk.

[0067] Specifically, the first distance can be determined by subtracting the preset trunk volume from the total volume of the suitcase, and then dividing the difference by the trunk's cross-sectional area. For example, if the preset trunk volume is 0.3 cubic meters, the total suitcase volume is 0.4 cubic meters, and the trunk's cross-sectional area is 0.5 square meters, then the excess volume is 0.1 cubic meters, resulting in a first distance of 0.2 meters, meaning the target seat needs to move forward 0.2 meters. If the total suitcase volume is less than or equal to the preset trunk volume, the calculation result is negative or zero, and the target seat does not need to move. This first distance drives the corresponding target seat to move, thus meeting the suitcase placement requirements.

[0068] The method provided in this embodiment determines a first distance for accurately moving the target seat based on the total volume of the luggage compartment, the preset trunk volume, and the cross-sectional area of ​​the trunk. This ensures that the trunk space after the target seat is moved can meet the luggage placement requirements. In this way, the luggage placement needs are met while also taking into account the rationality of the seat seating space, thereby improving the utilization efficiency of the cabin space and the comfort of the passengers.

[0069] In some embodiments, to ensure the comfort of the target seats after they have been moved, the position and state of the target seats after the move must meet a first condition (i.e., ergonomic standards). For example, the first condition may include: the distance between the target seats is greater than a first distance threshold (e.g., 60cm), and / or the backrest angle of the target seats is within a first preset angle range (e.g., 100°-110°).

[0070] In some embodiments of this disclosure, see also [link to previous document]. Figure 2 The aforementioned S103, which involves pre-adjusting the vehicle's cabin based on travel characteristic information, also includes: Step S1033: Based on the number of suitcases in the travel characteristic information, pre-adjust the opening angle of the tailgate of the cabin.

[0071] In this embodiment, the opening angle of the electric tailgate can also be adjusted according to the number of suitcases and the preset matching rules between the number of suitcases and the tailgate opening angle.

[0072] In this disclosure, the execution order of S1033 is not specifically limited. S1033 can be executed before S1031, S1033 can be executed after S1032, or S1033 can be executed simultaneously with S1031 or S1032.

[0073] The method provided in this embodiment can adapt the tailgate opening angle according to the number of suitcases, eliminating the need for users to manually adjust the tailgate when placing suitcases. This adapts to the placement needs of different types of luggage, improving the convenience of luggage placement. Simultaneously, it also avoids wasted space caused by excessive tailgate opening, making the tailgate opening angle adjustment in the cabin more suitable for users' luggage placement needs, further enhancing the user experience.

[0074] In some embodiments of this disclosure, the aforementioned S1033, pre-adjusting the tailgate opening angle based on the number of suitcases in the travel characteristic information, includes: adjusting the tailgate opening angle to a first angle when the number of suitcases is less than a first quantity threshold; adjusting the tailgate opening angle to a second angle when the number of suitcases is greater than or equal to the first quantity threshold and less than a second quantity threshold, wherein the second angle is greater than the first angle; and adjusting the tailgate opening angle to a third angle when the number of suitcases is greater than or equal to the second quantity threshold, wherein the third angle is greater than the second angle.

[0075] In this embodiment, based on the number of suitcases, the tailgate opening angle can be pre-adjusted according to the principle that the more suitcases there are, the larger the tailgate opening angle. Specifically, the number of suitcases can be compared with a preset first quantity threshold and a second quantity threshold in sequence, and the corresponding opening angle can be matched according to the comparison result.

[0076] The first and second quantity thresholds, as well as the first, second, and third angles, can all be preset according to the maximum opening angle of the vehicle's tailgate and application requirements. For example, the first quantity threshold can be set to 4, the second quantity threshold can be set to 6, and the corresponding first, second, and third angles can be set to 70°, 90°, and 120° respectively.

[0077] The method provided in this embodiment achieves precise adaptation of the tailgate opening angle through graded threshold values, ensuring that the tailgate opening angle matches the luggage placement requirements. This guarantees both ease of luggage placement and avoids wasted space caused by excessive tailgate opening, allowing for more precise adjustment of the tailgate opening angle and improving the effectiveness of cabin pre-adjustment.

[0078] In some embodiments of this disclosure, see also [link to previous document]. Figure 2 The aforementioned S103, which involves pre-adjusting the vehicle's cabin based on travel characteristic information, also includes: Step S1034: Based on the second time in the travel characteristic information, pre-adjust the cabin temperature.

[0079] In this embodiment, the cabin temperature can also be pre-adjusted based on a second time. The second time represents the user's actual departure time. For example, the second time can be determined based on information collected by a first device (e.g., a camera, door lock, etc.). Thus, using the second time as a time reference, the start time for pre-adjusting the cabin temperature can be accurately determined to ensure that the cabin temperature reaches the preset target temperature when the user arrives at the vehicle and gets in.

[0080] In this disclosure, the execution order of S1034 is not specifically limited. S1034 can be executed before S1031, and S1033 can be executed after S1032 or S1033. Alternatively, S1034 can be executed simultaneously with S1031, S1032 or S1033.

[0081] The method provided in this embodiment uses the second time when the user actually leaves home as the benchmark for cabin temperature pre-adjustment, so that the start time of cabin temperature adjustment matches the user's actual travel time, accurately controls the start timing of temperature pre-adjustment, improves the accuracy of cabin temperature adjustment, and further enhances the user experience.

[0082] In some embodiments of this disclosure, the above-mentioned S1034, pre-adjusting the cabin temperature based on the second time in the travel characteristic information, specifically includes: First, obtain the first location information and the second location information.

[0083] In this embodiment, the first location information represents the vehicle's location, and the second location information represents the user's departure location. The vehicle's current first location information can be obtained through the vehicle positioning module. The user's second location information can be the user's home address. The second location information can be obtained through the user's preset home location or historical trip data. The first and second location information provide the basic data for subsequent trip time calculation.

[0084] Then, based on the second time, the first location information, and the second location information, the third time when the user is expected to board the vehicle is determined.

[0085] Specifically, based on the acquired first and second location information, the actual distance between the user and the vehicle can be determined. Combined with real-time traffic data, the user's speed at which they arrive at the vehicle can be determined. The estimated travel time from the user's starting point to the vehicle's location is then calculated using distance and speed as the starting point. Finally, by adding this estimated travel time to the second time point, the estimated third time for the user to board the vehicle can be determined.

[0086] Furthermore, based on the third time, the air conditioning in the cabin is controlled to pre-adjust the cabin temperature.

[0087] Specifically, based on the third time the user expects to get into the vehicle, the air conditioning can be turned on in advance. By completing the temperature adjustment before the third time, the cabin temperature can be ensured to reach the preset target temperature when the user expects to get into the vehicle.

[0088] The method provided in this embodiment accurately acquires the location information of the vehicle and the user's departure point, calculates the estimated third time of boarding the vehicle based on the user's actual departure time, and controls the air conditioning start time based on this third time. This allows the cabin temperature pre-adjustment time to accurately match the user's estimated third time of boarding, avoiding energy waste caused by adjusting the temperature too early and preventing discomfort after boarding due to adjusting it too late. This significantly improves the timeliness and accuracy of cabin temperature adjustment, making the cabin temperature adjustment more suitable for the user's actual travel experience.

[0089] In some embodiments of this disclosure, the aforementioned control of the cabin air conditioning pre-adjusts the cabin temperature, including: First, obtain the ambient temperature of the vehicle.

[0090] In this embodiment, the ambient temperature data of the vehicle's surroundings can be collected in real time by the ambient temperature sensor mounted on the vehicle, providing an accurate temperature reference for the pre-adjustment of the air conditioning.

[0091] Then, based on the ambient temperature, target temperature, and third time, the fourth time for pre-starting the air conditioner is determined.

[0092] Specifically, the target temperature can be the user's preset cabin comfort temperature. The vehicle can determine the required adjustment time for temperature adjustment based on the temperature difference between the ambient temperature and the target temperature, combined with the cabin's temperature control capability (i.e., temperature adjustment rate). By advancing this adjustment time backward from the third time point, the fourth time for the air conditioning to turn on can be determined. The larger the temperature difference, the longer the required adjustment time, and the greater the interval between the fourth and third times.

[0093] For example, if the ambient temperature is 35℃ and the target temperature is 25℃, the temperature difference is 10℃. If the temperature adjustment rate is 1℃ per minute, the adjustment time is 10 minutes. If the third time is 9:30 AM, then the fourth time is 9:10 AM.

[0094] Next, the air conditioning will be controlled in the fourth time period so that the cabin temperature reaches the target temperature in the third time period.

[0095] For example, in response to the arrival of the fourth time, an operation command can be sent to the air conditioning control module to initiate the air conditioning temperature control adjustment operation, pre-adjust the cabin temperature until the cabin temperature reaches the target temperature in the third time.

[0096] The method provided in this embodiment accurately determines the fourth time for pre-starting the air conditioner based on the vehicle's actual ambient temperature, combined with the target temperature and the expected third time of boarding, and controls the air conditioner operation based on this fourth time. This ensures that the air conditioner's start time matches the temperature adjustment needs, allowing the cabin temperature to reach the target temperature by the third time the user is expected to board, guaranteeing cabin temperature comfort while avoiding energy waste caused by premature air conditioner operation, thus achieving precise pre-adjustment of cabin temperature.

[0097] In some embodiments of this disclosure, controlling the air conditioner to operate at the fourth time includes at least one of the following: controlling the air conditioner to operate at a target air volume; controlling the air conditioner to operate in a target operating mode; and controlling the air conditioner to operate at a target fan speed.

[0098] In this embodiment, the target air volume and / or target operating mode can be determined based on seasonal information and / or ambient temperature. The target air volume and / or target operating mode are determined based on seasonal information and / or ambient temperature, while the target wind speed is determined based on the number of travelers and the area corresponding to the air conditioning vents. If there are children among the travelers, the wind speed at the vent corresponding to the child seat area is lower than the wind speed at the vents corresponding to other areas.

[0099] In one example, the target airflow of the air conditioner can be determined according to preset matching rules based on the acquired seasonal information and ambient temperature. Different seasons and ambient temperature ranges correspond to different airflow levels, and the airflow level can be preset according to the cabin temperature control requirements. After the air conditioner is turned on in the fourth time period, it operates according to the target airflow. For example, in the high temperatures of summer, the target airflow is set to level 5. In the low temperatures of winter, the target airflow is set to level 3. In the comfortable temperatures of spring and autumn, the target airflow is set to level 2.

[0100] In another example, the target operating mode of the air conditioner can be matched based on the acquired seasonal information and ambient temperature. The target mode can be one of the following: internal circulation mode, external circulation mode, cooling mode, heating mode, or automatic mode. The air conditioner operates according to this target mode after starting in the fourth time period to adapt to the cabin temperature requirements under different seasons and ambient temperatures. For example, in the high temperatures of summer, the target operating mode is determined to be internal circulation and cooling mode. In the low temperatures of winter, the target operating mode is determined to be external circulation and heating mode. In the comfortable temperatures of spring and autumn, the target operating mode is determined to be automatic mode.

[0101] In another example, target wind speeds can be set for different areas based on the number of passengers and the cabin area corresponding to the air conditioning vents. If a child is detected among the passengers (e.g., by identifying child features through camera equipment or based on user-preset family member information), the wind speed of the vents corresponding to the child seat area can be individually reduced, and the wind speed in that area will be lower than the wind speed of the vents in other areas of the cabin.

[0102] The method provided in this embodiment allows for precise control of air conditioning operation based on three parameters: target airflow, target operating mode, and target fan speed. This ensures that the air conditioning operating parameters are adapted to the ambient temperature and seasonal characteristics, improving the efficiency and effectiveness of cabin temperature regulation. Furthermore, the method allows for differentiated settings of the air outlet fan speed based on the composition of travelers. In scenarios where children are present, the fan speed at the air outlet corresponding to the child seat area can be reduced. This makes the pre-adjustment of cabin temperature more user-friendly and precise, further enhancing the comfort of the cabin environment.

[0103] In some embodiments of this disclosure, step S101, determining the travel scenario, the set travel time for the travel scenario, and the first time based on the user's travel schedule information, includes: First, extract time keywords, location keywords, and / or scenario keywords from the travel itinerary information.

[0104] In this embodiment, a scene recognition algorithm can be used to extract keywords from travel schedule information. Time keywords are information representing the travel time in the schedule, such as "9:00" and "8:30". Location keywords are information representing the travel destination in the schedule, such as "scenic spot", "airport", and "train station". Scene keywords are information representing the travel behavior in the schedule, such as "traveling", "business trip", and "going to work".

[0105] In one implementation, the aforementioned travel schedule information can be obtained through cloud services by synchronizing data with a schedule application (e.g., calendar app, office scheduling software) that supports the user's second device (e.g., mobile phone, smartwatch, etc.).

[0106] Then, the travel scenario is determined based on time keywords, as well as location keywords and / or scenario keywords, or vice versa. The travel time is set based on time keywords.

[0107] For example, the extracted time keywords, location keywords, and scenario keywords can be matched with a preset scenario rule library to identify whether the corresponding scenario belongs to a travel scenario that requires cabin pre-adjustment.

[0108] In one example, the travel scenario can be determined based on time keywords, as well as location keywords and / or scenario keywords. Specifically, the travel scenario can be determined based on time keywords and location keywords, or it can be determined based on time keywords and scenario keywords, or it can be determined based on time keywords, location keywords, and scenario keywords.

[0109] For example, when the time keyword is "Saturday 9:00" and the location keyword is "Scenic Spot A", matching with the scenario rule base determines the travel scenario as a leisure trip (i.e., a travel scenario requiring pre-adjustment of the cabin). When the time keyword is "Saturday 9:00" and the scenario keyword is "travel", matching with the scenario rule base determines the travel scenario as a leisure trip (i.e., a travel scenario requiring pre-adjustment of the cabin). When the time keyword is "Monday 9:00", the location keyword is "Company B", and the scenario keyword is "going to work", matching with the scenario rule base determines the travel scenario as a work scenario (i.e., a scenario that does not require pre-adjustment of the cabin).

[0110] In another example, the travel scenario can also be determined based on location keywords and / or scenario keywords. Specifically, the travel scenario can be determined based on time keywords, scenario keywords, or both location keywords and scenario keywords.

[0111] For example, when the location keyword is "Scenic Spot A", matching with the scenario rule base determines the travel scenario to be a leisure trip (i.e., a travel scenario requiring pre-adjustment of the cabin). When the scenario keyword is "business trip", matching with the scenario rule base determines the travel scenario to be a business trip (i.e., a travel scenario requiring pre-adjustment of the cabin). When the location keyword is "Train Station C" and the scenario keyword is "seeing off", matching with the scenario rule base determines the travel scenario to be a multi-person travel scenario (i.e., a travel scenario requiring pre-adjustment of the cabin).

[0112] In another example, specific time information can be extracted based on time keywords to determine the set travel time. For example, 9 o'clock can be extracted from "Saturday 9:00" and that time (9 o'clock) can be determined as the set travel time for this travel scenario, that is, the time when the user plans to depart.

[0113] Next, the first time will be determined based on the set travel time and preset duration.

[0114] For example, in one implementation, based on the determined travel time, a time point earlier than the set travel time can be determined by combining it with a preset duration (e.g., 30 minutes), and this time point is designated as the first time. For example, when the set travel time is 9:00 AM and the preset duration is 30 minutes, the first time is 8:30 AM.

[0115] In another implementation, different preset durations can be set based on travel scenarios and user behavior habits to determine the first time according to different travel scenarios, thereby optimizing the first time and making it closer to the user's travel needs. The operation process of pre-adjusting the cabin can be performed in advance before the user travels.

[0116] For example, in a travel scenario where it's a leisure trip, travelers and users typically carry more luggage, and the cabin pre-adjustment process involves more items and takes longer. Therefore, the preset time can be set to a longer duration, such as 30 minutes. In a business trip scenario, travelers and users usually carry less luggage, and the cabin pre-adjustment process involves fewer items and takes shorter. Therefore, the preset time can be set to a shorter duration, such as 15 minutes.

[0117] The method provided in this embodiment achieves accurate identification of travel scenarios by comprehensively judging time keywords, location keywords, and scenario keywords extracted from travel schedule information, so that the triggering of cabin pre-adjustment is more in line with the user's actual travel plan. Furthermore, by determining the first time based on the set travel time and preset duration, it ensures that cabin pre-adjustment has sufficient execution time and that the triggering time matches the user's travel time, improving the flexibility and accuracy of cabin pre-adjustment and making it more tailored to the user's personalized travel needs.

[0118] In some embodiments of this disclosure, step S102, determining the user's travel characteristic information, includes at least one of the following: acquiring at least one of the following from the travel characteristic information: number of travelers, suitcase size, number of suitcases, and second time from a camera device in at least one first device; acquiring at least one of the following from a door lock device in at least one first device: number of travelers and second time; acquiring at least one of the following from a suitcase device in at least one first device: suitcase size and number of suitcases; determining at least one of the following from the images captured by the camera device: number of travelers, suitcase size, number of suitcases, and second time; determining at least one of the following from the following from the unlocking information collected by the door lock device; and determining at least one of the following from the following from the suitcase information collected by the suitcase device: suitcase size and number of suitcases.

[0119] In this embodiment, at least one of the following in the travel characteristic information—number of travelers, suitcase size, number of suitcases, and second time—can be obtained by the camera device through information collection and analysis, and can be directly acquired by the vehicle to determine the user's travel characteristic information.

[0120] For example, the camera device can be installed in areas frequently used by users, such as the living room, entryway, and doorway. Upon arrival, the camera device can start operating after receiving a data collection command. It analyzes the captured images using a built-in human recognition algorithm to identify the number of people preparing to leave and uses this number as the total number of travelers. Simultaneously, the camera device also performs target detection and recognition on suitcases in the images, using image recognition algorithms to estimate the size of each suitcase and count the number of suitcases appearing in the images. Furthermore, the camera device can analyze the time users leave their homes through continuously captured images. For example, the time when all people have left the frame and no one reappears within a preset time is designated as the second time. In this way, the vehicle can directly obtain at least one of the following travel characteristic information from the camera device: the number of travelers, suitcase size, number of suitcases, and the second time.

[0121] At least one of the number of travelers and the second time in the travel characteristic information can also be obtained by the door lock device through information collection and analysis, and can be directly obtained by the vehicle to determine the user's travel characteristic information.

[0122] For example, the door lock device can record the type of each unlocking operation, such as fingerprint unlocking, facial recognition unlocking, or password unlocking, and identify the identity information of the unlocking user. For instance, it can determine whether the unlocker is a resident user through pre-set fingerprint or facial feature data. When multiple resident users' fingerprints or faces trigger the door lock unlocking operation consecutively within a short period of time, such as 10 minutes, the door lock device counts the number of users corresponding to these unlocking operations and uploads this number as auxiliary verification data for the number of people leaving the premises. At the same time, the door lock device can also record the time of the last locking operation in real time, and if there is no unlocking operation within a subsequent preset time (e.g., 1 minute), this time point is determined as the user's second time, i.e., the actual time of leaving the premises. If the user does not leave the premises through the smart door lock, such as leaving through the balcony or back door, the door lock device cannot collect the time of leaving the premises, and in this case, it can be corrected by combining data from the camera device.

[0123] At least one of the luggage size and number of luggage in the travel characteristic information can also be obtained by the luggage device through information collection and analysis, and directly obtained by the vehicle to determine the user's travel characteristic information.

[0124] For example, the luggage compartment device can have a built-in weight sensor and size detection module, automatically initiating detection during the user's luggage packing process. For instance, when the luggage compartment is opened and closed more than three times, or the weight sensor detects a weight change exceeding 2 kg, the luggage compartment device can determine that the user is packing, and then collect its own size information, such as length, width, and height, and distinguish different luggage compartments through device identification. If the user has multiple luggage compartments, each luggage compartment device uploads its own size data and device identification, allowing the vehicle to count the number of luggage compartments and summarize the size information. For non-smart luggage compartments (without built-in weight sensors and size detection modules), the size and quantity of luggage compartments can also be identified through detection images captured by a camera device to ensure comprehensive data collection.

[0125] The number of travelers, luggage size, number of luggage, and at least one of the travel characteristic information can also be determined by analyzing the information collected by the vehicle based on the camera equipment.

[0126] For example, the vehicle can also acquire raw detection image data collected by camera equipment and perform image analysis processing. For instance, by processing the detection images using deep learning and image recognition algorithms, human silhouettes can be identified and counted to determine the number of travelers. For suitcases, image segmentation and object detection techniques can be used to extract the suitcase area from the detection image. Combined with known reference objects in the detection image, such as door frame width, the size of the suitcase can be determined, and the number of suitcases can be counted. Simultaneously, by analyzing the movement trajectory and disappearance time of human targets in a continuous sequence of detection images, the time when the user left home can be inferred as a secondary time.

[0127] At least one of the number of travelers and the second time in the travel characteristic information can also be determined by analyzing the information collected by the vehicle based on the door lock device.

[0128] For example, the vehicle can also obtain the time, unlocking method, and user identification of each unlocking event recorded by the door lock device. By analyzing the unlocking information, the number of resident users who unlocked the door within a preset time window, such as 30 minutes before departure, can be counted, and this number can be used as the number of travelers. Simultaneously, the time of the last locking event with no subsequent unlocking can be determined as the second time. For example, if the door lock device records that user A unlocked the door with their fingerprint at 8:30 AM, user B unlocked it with their face at 8:31 AM, and the door was locked at 8:32 AM, then the number of travelers is determined to be 2, and the second time is determined to be 8:32 AM.

[0129] At least one of the luggage size and number of luggage compartments in the travel characteristic information can also be determined by analyzing the information collected by the vehicle based on the luggage compartment equipment.

[0130] For example, the vehicle can also acquire luggage compartment device data: device identification, size data, weight data, and other luggage compartment information for each luggage compartment. The number of luggage compartments can be determined based on the number of device identifications, and the luggage compartment dimensions can be obtained by summing the size data of each luggage compartment. For instance, when the luggage compartment with device ID 001 uploads a size of 60cm × 40cm × 30cm, and the luggage compartment with device ID 002 uploads a size of 50cm × 40cm × 30cm, it can be determined that there are 2 luggage compartments, and the corresponding luggage compartment size data can be determined.

[0131] The method provided in this embodiment, through multi-dimensional data collection and analysis from multiple types of first devices, can accurately determine travel characteristic information, effectively avoiding the limitations and errors of data collected from a single device, ensuring the authenticity and completeness of travel characteristic information. This allows the pre-adjustment of the cabin to match the user's travel needs, significantly improving the accuracy and comfort of cabin pre-adjustment. Simultaneously, the multi-device data acquisition method also enhances adaptability and expands application scenarios.

[0132] In some embodiments of this disclosure, a vehicle cockpit control device is also provided, which can be configured to perform... Figure 1 or Figure 2 The method shown. Figure 3 This is a schematic diagram of the structure of a vehicle cockpit control device provided in an embodiment of the present disclosure, as shown below. Figure 3 As shown, the vehicle cockpit control device 300 includes: a scenario determination module 301, used to determine a travel scenario, a set travel time for the travel scenario, and a first time, wherein the first time is earlier than the set travel time, based on the user's travel schedule information; a travel characteristic determination module 302, used to determine the user's travel characteristic information in response to the arrival of the first time, wherein the travel characteristic information is obtained by analyzing information collected by at least one first device communicating with the vehicle; and a control module 303, used to pre-adjust the vehicle's cockpit based on the travel characteristic information.

[0133] In summary, the vehicle cockpit control device provided in this embodiment can determine the travel scenario and the first moment through the scenario determination module, and determine the user's travel characteristic information based on the information collected by the first device through the travel characteristic determination module. Then, the control module can perform personalized pre-adjustment of the cockpit based on the travel characteristic information, so that the user can experience a cockpit state adapted to their travel needs when getting into the vehicle. In this way, the device can make the cockpit adjustment more accurately match the user's actual travel needs, thereby effectively improving the effect of cockpit pre-adjustment and the user experience.

[0134] In some embodiments of this disclosure, the control module 303 is configured to: determine a target seat in the cabin based on the number of travelers in the travel characteristic information; and adjust the position of the target seat based on the size and number of suitcases in the travel characteristic information.

[0135] In some embodiments of this disclosure, the control module 303 is configured to: determine the total volume of the luggage based on the luggage size and the number of luggage compartments; and, if the total volume of the luggage is greater than a preset trunk volume, move the target seat a first distance, the first distance being determined based on the total volume of the luggage, the preset trunk volume, and the trunk cross-sectional area.

[0136] In some embodiments of this disclosure, the control module 303 is further configured to: pre-adjust the opening angle of the tailgate of the cabin based on the number of suitcases in the travel characteristic information.

[0137] In some embodiments of this disclosure, the control module 303 is further configured to: adjust the tailgate opening angle to a first angle when the number of suitcases is less than a first quantity threshold; adjust the tailgate opening angle to a second angle when the number of suitcases is greater than or equal to the first quantity threshold and less than a second quantity threshold, wherein the second angle is greater than the first angle; and adjust the tailgate opening angle to a third angle when the number of suitcases is greater than or equal to the second quantity threshold, wherein the third angle is greater than the second angle.

[0138] In some embodiments of this disclosure, the control module 303 is further configured to: pre-adjust the cabin temperature based on a second time in the travel characteristic information; the second time is used to characterize the user's actual departure time.

[0139] In some embodiments of this disclosure, the control module 303 is further configured to: acquire first location information of the vehicle and second location information of the user's departure point; determine a third time when the user is expected to board the vehicle based on the second time, the first location information and the second location information; and control the air conditioning in the cabin to pre-adjust the temperature of the cabin based on the third time.

[0140] In some embodiments of this disclosure, the control module 303 is further configured to: acquire the ambient temperature of the vehicle; determine a fourth time for pre-activating the air conditioner based on the ambient temperature, the target temperature, and the third time; and control the air conditioner to operate at the fourth time so that the cabin temperature reaches the target temperature at the third time.

[0141] In some embodiments of this disclosure, the control module 303 is further configured to: control the air conditioner to operate at a target air volume; control the air conditioner to operate in a target operating mode; control the air conditioner to operate at a target wind speed; wherein the target air volume and / or target operating mode are determined based on seasonal information and / or ambient temperature, and the target wind speed is determined based on the travelers and the area corresponding to the air conditioner's air outlet. In the case of children among the travelers, the wind speed of the air outlet corresponding to the child seat area is less than the wind speed of the air outlet corresponding to other areas.

[0142] In some embodiments of this disclosure, the scenario determination module 301 is used to: extract time keywords, location keywords and / or scenario keywords from travel schedule information; determine a travel scenario based on time keywords, location keywords and / or scenario keywords, or determine a travel scenario based on location keywords and / or scenario keywords; determine a set travel time based on time keywords; and determine a first time according to the set travel time and preset duration.

[0143] In one implementation, the scenario determination module 301 may include a schedule information determination unit and a travel scenario recognition unit. For example, the schedule information determination unit can be integrated into the vehicle's infotainment system, enabling data synchronization of travel schedule information with the user's mobile terminal (such as a mobile phone or smartwatch)'s schedule application (such as a calendar app or office scheduling software) via cloud services. The travel scenario recognition unit can extract at least one of the time keywords, location keywords, and scenario keywords from the travel schedule information using a built-in scenario recognition algorithm, and determine the travel scenario.

[0144] In some embodiments of this disclosure, the travel feature determination module 302 is configured to: acquire at least one of the following from travel feature information: number of travelers, suitcase size, number of suitcases, and second time from a camera device in at least one first device; acquire at least one of the following from a door lock device in at least one first device: number of travelers and second time; acquire at least one of the following from a suitcase device in at least one first device: suitcase size and number of suitcases; determine at least one of the following from images acquired by the camera device: number of travelers, suitcase size, number of suitcases, and second time; determine at least one of the following from unlocking information acquired by the door lock device: number of travelers and second time; and determine at least one of the following from suitcase information acquired by the suitcase device: suitcase size and number of suitcases.

[0145] In one implementation, the travel feature determination module 302 may include: a first device data acquisition unit, which can be used to acquire at least one of the following from travel feature information: number of travelers, suitcase size, number of suitcases, and second time.

[0146] In some embodiments of this disclosure, a vehicle is also provided. Figure 4 This is a block diagram of a vehicle provided in an embodiment of this disclosure. For example, vehicle 400 can be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. Vehicle 400 can be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0147] Reference Figure 4 The vehicle 400 may include various subsystems, such as an infotainment system 410, a perception system 420, a decision control system 430, a drive system 440, and a computing platform 450. The vehicle 400 may also include more or fewer subsystems, and each subsystem may include multiple components. Furthermore, each subsystem and component of the vehicle 400 can be interconnected via wired or wireless means.

[0148] In some embodiments, the infotainment system 410 may include a communication system, an entertainment system, and a navigation system, etc.

[0149] The perception system 420 may include several sensors for sensing information about the environment surrounding the vehicle 400. For example, the perception system 420 may include a global positioning system (which may be GPS, BeiDou, or other positioning systems), an inertial measurement unit (IMU), lidar, millimeter-wave radar, ultrasonic radar, and a camera device.

[0150] The decision control system 430 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0151] The drive system 440 may include components that provide powered motion to the vehicle 400. In one embodiment, the drive system 440 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of internal combustion engines, electric motors, and compressed air engines. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0152] Some or all of the functions of the vehicle 400 are controlled by a computing platform 450. The computing platform 450 may include at least one processor 451 and a memory 452, the processor 451 being able to execute instructions 453 stored in the memory 452.

[0153] Processor 451 can be any conventional processor, such as a commercially available CPU. Processors may also include graphics processing units (GPUs), field-programmable gate arrays (FPGAs), systems-on-chips (SoCs), application-specific integrated circuits (ASICs), or combinations thereof.

[0154] The memory 452 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0155] In addition to instruction 453, memory 452 can also store data, such as road maps, route information, vehicle position, direction, speed, and other data. The data stored in memory 452 can be used by computing platform 450.

[0156] In this embodiment of the disclosure, processor 451 may execute instructions 453 to complete all or part of the steps of the above-described vehicle cockpit control method.

[0157] This disclosure also provides a non-transitory computer-readable storage medium, wherein when the instructions in the storage medium are executed by the processor of a mobile terminal, the mobile terminal is able to perform the steps of the vehicle cockpit control method provided in this disclosure.

[0158] This disclosure also provides a computer program product, including a computer program that is processed by a processor to perform the steps of the vehicle cockpit control method provided in this disclosure.

[0159] Furthermore, the term “exemplary” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as advantageous compared to other aspects or designs. Rather, the use of the term “exemplary” is intended to present the concept in a concrete manner. As used herein, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless otherwise specified or clear from the context, “X applies A or B” is intended to mean any of the natural inclusive arrangements. That is, “X applies A or B” satisfies any of the foregoing instances if X applies A; X applies B; or both X applies A and B. Additionally, unless otherwise specified or clear from the context to refer to the singular form, the articles “a” and “an” as used in this application and the appended claims are generally understood to mean “one or more.”

[0160] Similarly, although this disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components described above (e.g., elements, resources, etc.), unless otherwise indicated, the terminology used to describe such components is intended to correspond to any component (functionally equivalent) that performs the specific function of the described component, even if structurally not equivalent to the disclosed structure. Furthermore, although specific features of this disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations, as may be desired and advantageous to any given or particular application. Moreover, with regard to the terms “comprising,” “owning,” “having,” “having,” or variations thereof as used in the detailed description or claims, such terms are intended to be inclusive in a manner similar to the term “including.”

[0161] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0162] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A vehicle cockpit control method, characterized in that, include: Based on the user's travel schedule information, determine the travel scenario, the set travel time for the travel scenario, and the first time, wherein the first time is earlier than the set travel time; In response to the arrival of the first time, the user's travel characteristic information is determined, which is obtained by analyzing information collected by at least one first device communicating with the vehicle; Based on the travel characteristic information, the vehicle's cabin is pre-adjusted.

2. The method according to claim 1, characterized in that, The pre-adjustment of the vehicle's cabin based on the travel characteristic information includes: Based on the number of travelers in the travel characteristic information, the target seats in the cabin are determined; The position of the target seat is adjusted based on the luggage size and number of luggage in the travel feature information.

3. The method according to claim 2, characterized in that, The step of adjusting the position of the target seat based on the luggage size and number of luggage in the travel feature information includes: The total volume of the suitcase is determined based on the suitcase dimensions and the number of suitcases. If the total volume of the luggage compartment is greater than the preset trunk volume, the target seat is moved a first distance, which is determined based on the total volume of the luggage compartment, the preset trunk volume, and the cross-sectional area of ​​the trunk.

4. The method according to claim 1, characterized in that, The step of pre-adjusting the vehicle's cabin based on the travel characteristic information further includes: Based on the number of suitcases in the travel characteristic information, the opening angle of the tailgate of the cabin is pre-adjusted.

5. The method according to claim 4, characterized in that, The step of pre-adjusting the tailgate opening angle based on the number of suitcases in the travel characteristic information includes: If the number of suitcases is less than a first quantity threshold, the tailgate opening angle is adjusted to a first angle; When the number of suitcases is greater than or equal to the first quantity threshold and less than the second quantity threshold, the tailgate opening angle is adjusted to the second angle, which is greater than the first angle. If the number of suitcases is greater than or equal to the second quantity threshold, the tailgate opening angle is adjusted to a third angle; wherein the third angle is greater than the second angle.

6. The method according to any one of claims 1-5, characterized in that, The step of pre-adjusting the vehicle's cabin based on the travel characteristic information further includes: Based on the second time in the travel characteristic information, the temperature of the cabin is pre-adjusted; the second time is used to characterize the user's actual departure time.

7. The method according to claim 6, characterized in that, The pre-adjustment of the cabin temperature based on the second time in the travel characteristic information includes: Acquire first location information and second location information, wherein the first location information is used to characterize the location of the vehicle and the second location information is used to characterize the location of the user's departure point; Based on the second time, the first location information, and the second location information, the third time when the user is expected to board the vehicle is determined; Based on the third time, the air conditioning in the cabin is controlled to pre-adjust the temperature of the cabin.

8. The method according to claim 1, characterized in that, The step of determining the travel scenario, the set travel time for the travel scenario, and the first time based on the user's travel schedule information includes: Extract time keywords, location keywords, and / or scene keywords from the travel itinerary information; The travel scenario is determined based on the time keyword, the location keyword, and / or the scene keyword; or the travel scenario is determined based on the location keyword and / or the scene keyword; the set travel time is determined based on the time keyword. The first time is determined based on the set travel time and preset duration.

9. The method according to claim 1, characterized in that, The determination of the user's travel characteristic information includes at least one of the following: The travel characteristic information is obtained from the camera device in the at least one first device, including at least one of the following: number of travelers, suitcase size, number of suitcases, and second time. The number of travelers and at least one of the second time are obtained from the door lock device in the at least one first device; Obtain at least one of the suitcase size and the number of suitcases from the suitcase device in the at least one first device; Based on the images captured by the camera device, determine at least one of the following: the number of travelers, the size of the suitcases, the number of suitcases, and the second time period; Based on the unlocking information collected by the door lock device, determine at least one of the number of travelers and the second time period; Based on the luggage information collected by the luggage device, at least one of the luggage size and the number of luggage is determined.

10. A vehicle cockpit control device, characterized in that, include: The scenario determination module is used to determine the travel scenario, the set travel time of the travel scenario, and the first time based on the user's travel schedule information, wherein the first time is earlier than the set travel time. A travel characteristic determination module is used to determine the user's travel characteristic information in response to the arrival at the first time, wherein the travel characteristic information is obtained by analyzing information collected by at least one first device communicating with the vehicle; The control module is used to pre-adjust the vehicle's cabin based on the travel characteristic information.

11. The apparatus according to claim 10, characterized in that, The control module is configured to perform at least one of the following: Based on the number of travelers in the travel characteristic information, the target seats in the cabin are determined; Based on the luggage size and number of luggage in the travel feature information, adjust the position of the target seat; Based on the number of suitcases in the travel characteristic information, the opening angle of the tailgate of the cabin is pre-adjusted; Based on the second time in the travel characteristic information, the temperature of the cabin is pre-adjusted; the second time is used to characterize the user's actual departure time.

12. A vehicle, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the method according to any one of claims 1 to 9.

13. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the mobile terminal, the mobile terminal is able to perform the method as described in any one of claims 1 to 9.

14. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 9.

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