Methods, devices, controllers, vehicles, media and products for alerting lost items

Abstract

This application discloses a method, device, controller, vehicle, medium, and product for reminding passengers of lost items. It involves acquiring detection data collected from passengers in a vehicle; identifying the risk level of lost items for each passenger based on the detection data; and performing a corresponding item loss reminder operation on the passenger. Therefore, by identifying the risk level of lost items for each passenger based on the detection data collected from passengers in the vehicle, and then providing targeted item loss reminders based on that risk level, accurate and effective item loss reminders can be achieved, thereby improving the efficiency of item loss reminders.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, device, controller, vehicle, medium, and product for reminding users of items that have been lost. Background Technology

[0002] Passengers are prone to leaving items behind while traveling, which greatly affects their travel experience. Therefore, it's possible to remind passengers of forgotten items while they are on the bus. Current methods for reminding passengers of forgotten items often involve broadcasting a voice reminder when the passenger is about to arrive at their stop.

[0003] However, this method of reminding passengers of lost items cannot accurately and effectively remind them of lost items, resulting in low efficiency. Summary of the Invention

[0004] This application provides a method, device, controller, vehicle, medium, and product for reminding passengers of lost items. It can provide targeted, graded reminders of lost items to passengers based on their risk level of item loss, thereby achieving accurate and effective reminders and improving the efficiency of item loss reminders.

[0005] To achieve the above objectives, according to a first aspect of this application, a method for reminding users of missing items is provided, the method comprising:

[0006] Acquire detection data collected from passengers in the vehicle;

[0007] The risk level of the passenger's items being left behind is identified based on the detection data;

[0008] Perform an item loss reminder operation on the passenger corresponding to the item loss risk level.

[0009] According to a second aspect of this application, a lost item reminder device is provided, the device comprising:

[0010] The acquisition module is used to acquire detection data collected from passengers in the vehicle;

[0011] The identification module is used to identify the risk level of the passenger's missing items based on the detection data;

[0012] The reminder module is used to perform an item omission reminder operation for the passenger corresponding to the item omission risk level.

[0013] According to a third aspect of this application, a controller is provided, including a processor and a memory, the memory storing an application program, and the processor being used to run the application program in the memory to implement the item omission reminder method provided in the embodiments of this application.

[0014] According to a fourth aspect of this application, a vehicle is provided, the vehicle including the controller provided in the third aspect of this application.

[0015] According to a fifth aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program adapted for loading by a processor to perform the steps of any of the item omission reminder methods provided in the embodiments of this application.

[0016] According to a sixth aspect of this application, a computer program product is provided, the computer program product including a computer program stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to perform the steps in the item omission reminder method provided in the embodiments of this application.

[0017] In the methods, apparatus, controllers, vehicles, media, and products for reminding passengers of lost items in this application, detection data collected from passengers in the vehicle is acquired; the risk level of passengers losing items is identified based on the detection data; and a reminder operation corresponding to the risk level of item loss is performed on the passengers. Thus, by identifying the risk level of passengers losing items based on the detection data collected from passengers in the vehicle, and performing a reminder operation corresponding to the risk level of item loss, targeted and graded reminders for lost items are implemented for passengers based on their risk level of item loss, thereby providing accurate and effective reminders and significantly improving the efficiency of item loss reminders. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram illustrating an implementation scenario of a method for reminding users of lost items provided in this application.

[0020] Figure 2 This is a flowchart illustrating a method for reminding users of lost items provided in an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of the system architecture of a method for reminding users of missing items provided in an embodiment of this application;

[0022] Figure 4This is a schematic diagram of the overall process of a method for reminding users of lost items provided in an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of the structure of the item loss reminder device provided in the embodiments of this application;

[0024] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the protection scope of this application.

[0026] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0027] This application provides a method, apparatus, controller, vehicle, medium, and product for alerting users to lost items. The controller can be an electronic device, and the lost item alert device can be integrated into the electronic device, which can be a server, a terminal, or other similar device.

[0028] The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery network (CDN) acceleration services, and big data and artificial intelligence platforms. The terminal can include, but is not limited to, mobile phones, computers, smart voice interaction devices, smart home appliances, vehicle terminals, and aircraft. The terminal and server can be directly or indirectly connected via wired or wireless communication, which is not limited herein.

[0029] The electronic device can be integrated into a vehicle, which can be a gasoline-powered vehicle, a plug-in hybrid electric vehicle, or a new energy vehicle, etc. This application does not make any specific limitations on this.

[0030] Please see Figure 1Taking the integration of a lost item reminder device into an electronic device as an example, Figure 1 This is a schematic diagram illustrating an implementation scenario of the item loss reminder method provided in this application. The electronic device can be integrated into a vehicle. The electronic device can acquire detection data collected from passengers in the vehicle; identify the risk level of item loss for passengers based on the detection data; and perform an item loss reminder operation corresponding to the risk level of item loss for passengers.

[0031] It should be noted that, Figure 1 The illustrated scenario of the missing item reminder method is merely an example. The implementation environment of the missing item reminder method described in this application is for the purpose of more clearly illustrating the technical solution of this application and does not constitute a limitation on the technical solution provided in this application. Those skilled in the art will understand that, with the evolution of missing item reminders and the emergence of new business scenarios, the technical solution provided in this application is also applicable to similar technical problems.

[0032] The solutions provided in this application are specifically illustrated through the following embodiments. It should be noted that the order of description of the following embodiments is not intended to limit the preferred order of the embodiments.

[0033] This embodiment will be described from the perspective of an item loss reminder device, which can be integrated into an electronic device.

[0034] Please see Figure 2 , Figure 2 This is a flowchart illustrating the method for reminding users of missing items provided in this application. The method includes:

[0035] Step S101: Obtain detection data collected from passengers in the vehicle.

[0036] The detection data can be data collected from passengers in the vehicle. For example, the detection data can include at least one of the visual detection data corresponding to the passenger and the pressure detection data of the region of interest corresponding to the passenger.

[0037] The visual inspection data can be visual modal data, or data detected by visual inspection equipment, such as standard cameras, event cameras, or infrared detection equipment. The region of interest (ROI) can be the area in the vehicle that the passenger needs to focus on. The pressure detection data can be data obtained through pressure sensors, and can include the pressure value experienced by the passenger's corresponding region of interest.

[0038] Optionally, the visual detection data may include at least one of a first image captured by a camera and a second image captured by an event camera.

[0039] The camera can be an in-vehicle camera, specifically a standard camera. The first image can be an image including passengers captured by the standard camera. The event camera can be a bionic vision sensor, also known as a dynamic vision sensor (DVS) or a dynamic and active-pixel vision sensor (DAVIS). The event camera outputs changes in pixel brightness. The second image can be an image captured by the event camera. Compared to the first and second images, the first image can be a static image, while the second image can be a dynamic image.

[0040] Optionally, the vehicle-mounted camera can capture images of passengers in the vehicle and operate at a low speed of less than 60 frames per second (fps), exhibiting a low dynamic range of less than 100 dB. Based on the images output by the vehicle-mounted camera, the passenger's seating position can be identified, the passenger and their surrounding region of interest can be determined, and a first image of the passenger's region of interest can be acquired. For images captured within the passenger's region of interest, high-quality lossless encoding can be performed to enhance image quality. For images captured outside the region of interest, the bitrate and image quality can be reduced to save storage space.

[0041] Optionally, the event camera can capture a second image of the passenger in the region of interest, operating at a high speed of less than 1 millisecond and possessing a high dynamic range greater than 140dB. Based on the output of the event camera, the event of interest, i.e., the second image of the passenger, can be generated. Specifically, for passenger movement, high-speed shooting and high-quality lossless encoding can be performed to enhance image quality; for passenger non-movement, the bitrate and image quality can be reduced to save storage space and improve computing speed.

[0042] Optionally, the pressure detection data can be obtained by a fiber optic pressure sensor. For example, by installing a fiber optic pressure sensor in the vehicle, the pressure detection data corresponding to the passenger can be obtained based on the fiber optic pressure sensor installed in the passenger's area of ​​interest.

[0043] In one embodiment, the fiber optic pressure sensor can be installed on the front and rear seats of the vehicle, at the bottom of the door panel storage compartment, on the vehicle floor, or at the bottom of the center console storage box or cup holder. The number and location of the pressure sensors can be adjusted according to actual needs, and this embodiment does not limit the specific installation.

[0044] Optionally, before acquiring detection data collected from passengers in the vehicle, the region of interest corresponding to the passenger can be determined. For example, images of passengers can be acquired through cameras inside the vehicle; based on the images, the passenger's seating position can be identified; and based on the seating position, the region of interest corresponding to the passenger in the vehicle can be determined.

[0045] The image can be an image containing passengers, and the seating position can be the position where the passengers are seated in the vehicle.

[0046] In one embodiment, when a passenger sits in the left rear seat of the vehicle, the area of ​​interest corresponding to the passenger may include the left rear seat of the vehicle, the door panel storage compartments around the passenger, the vehicle floor, and the area such as the storage box or cup holder on the passenger dashboard.

[0047] Step S102: Identify the risk level of passengers leaving items based on the detection data.

[0048] The item loss risk level can be defined as the level at which a passenger is at risk of losing an item. This risk level indicates the degree to which a passenger is likely to leave an item in the vehicle. The higher the level, the more likely the passenger is to leave an item behind.

[0049] There are several ways to identify the risk level of passengers leaving items based on detection data. For example, passengers can be identified based on visual detection data to obtain identification results; and the risk level of passengers leaving items can be determined based on the identification results and pressure detection data.

[0050] The identification result can be the result of identifying the risk of passengers leaving items based on visual detection data. The identification result can include item identification result and / or behavior identification result. The item identification result can be the result of identifying the risk of passengers leaving items based on a first image, and the behavior identification result can be the result of identifying the risk of passengers leaving items based on a second image.

[0051] Among them, the identification of passenger item loss risk based on visual detection data can be obtained in a variety of ways. For example, the identification result can include item identification result and / or behavior identification result. Specifically, based on the first image, it can be identified whether the passenger may have missed any items, and obtain the item identification result; and / or, based on the second image, it can be identified whether the passenger has engaged in any behavior that may have led to the loss of items, and obtain the behavior identification result.

[0052] Among them, items that may be left behind can be items that passengers are more likely to leave in the vehicle, such as mobile phones, earphones, bags, cards, keys, lipsticks, powder compacts, etc. The behaviors that lead to the loss of items can be behaviors that passengers are more likely to leave behind in the vehicle, such as answering the phone, rummaging through their bags, touching up their makeup, sleeping, etc.

[0053] Among them, based on the first image, it is possible to identify whether the passenger may have missed any items. There are multiple ways to obtain the item identification result. For example, multiple preset images of items that may have been missed can be obtained. Based on the item images and the first image, it is possible to identify whether the passenger may have missed any items and obtain the item identification result.

[0054] The item image can be an image of an item that is more likely to be missed. The item image can be stored in a first database, which can be a library of images of items that may be missed stored in the vehicle's onboard computer.

[0055] Among them, based on the item image and the first image, there are multiple ways to identify whether the passenger may have missed any items. For example, the first image can be compared with the item images stored in the first database. Through deep learning algorithms, it can autonomously identify whether there are any items in the first image that are highly likely to be missed, thereby obtaining the item recognition result.

[0056] In this process, based on the second image, it is possible to identify whether the passenger has engaged in any behavior that could lead to the loss of an item. There are several ways to obtain the behavior recognition result. For example, multiple preset event images corresponding to behaviors that could lead to the loss of an item can be obtained. Based on the event images and the second image, it is possible to identify whether the passenger has engaged in any behavior that could lead to the loss of an item, and thus obtain the behavior recognition result.

[0057] The event image can be an image corresponding to an action that may lead to the omission of items. The event image can be stored in a second database, which can be an image library of event images that may lead to the omission of items stored in the vehicle's on-board computer.

[0058] Among them, based on the event image and the second image, it is possible to identify whether the passenger has engaged in behavior that may have led to the loss of items. There are multiple ways to obtain the behavior recognition results. For example, the passenger's second image can be compared with the event images stored in the second database. In this way, deep learning algorithms can be used to autonomously identify whether the passenger has engaged in behavior that is likely to lead to the loss of items, thereby obtaining the behavior recognition results.

[0059] After obtaining the identification results, the risk level of a passenger leaving behind items can be determined based on the identification results and stress detection data. There are several ways to determine the risk level of a passenger leaving behind items based on the identification results and stress detection data. For example, initial stress detection data of the area of ​​interest before the passenger sits down can be obtained; the risk level of a passenger leaving behind items can be determined based on a comparison of the magnitude of the initial stress detection data and the identification results.

[0060] The initial pressure detection data can be the pressure value experienced by the passenger's corresponding area of ​​interest before the passenger sits down.

[0061] Optionally, the risk level of item loss may include a first risk level and a second risk level. The first risk level may indicate that the passenger has no risk of losing items, that is, the passenger is unlikely to lose items in the vehicle. The second risk level may indicate that the passenger has a risk of losing items, that is, the passenger is likely to lose items in the vehicle.

[0062] There are several ways to determine the risk level of a passenger's lost items based on the comparison between the pressure detection data and the initial pressure detection data, as well as the identification results. For example, if the pressure detection data is less than or equal to the initial pressure detection data, the risk level of the passenger's lost items is determined to be the first risk level; if the pressure detection data is greater than the initial pressure detection data, the risk level of the lost items is determined to be the second risk level based on the identification results.

[0063] If the pressure detection data is less than or equal to the initial pressure detection data, it indicates that the passenger has not placed any items near the area of ​​interest. Therefore, the passenger does not face the risk of leaving items behind, and their risk level can be determined as Level 1. If the pressure detection data is greater than the initial pressure detection data, it indicates that the passenger has placed any items near the area of ​​interest. Therefore, the passenger faces the risk of leaving items behind, and their risk level can be determined as Level 2. The passenger's risk level can be further determined based on the identification results.

[0064] Optionally, the identification result may include item identification result and behavior identification result. The second risk level may include a first sub-risk level, a second sub-risk level and a third sub-risk level. The first sub-risk level may be a low risk level, that is, the passenger is less likely to lose an item. The second sub-risk level may be a medium risk level, that is, the passenger is moderately likely to lose an item. The third sub-risk level may be a high risk level, that is, the passenger is more likely to lose an item.

[0065] Specifically, the step of determining whether the risk level of item omission is the second risk level based on the identification result if the pressure detection data is greater than the initial pressure detection data can include: if the pressure detection data is greater than the initial pressure detection data, the item identification result is negative, and the behavior identification result is negative, then the item omission risk level is determined to be the first sub-risk level; if the pressure detection data is greater than the initial pressure detection data, the item identification result is positive, and the behavior identification result is negative, then the item omission risk level is determined to be the second sub-risk level; if the pressure detection data is greater than the initial pressure detection data, the item identification result is positive, and the behavior identification result is positive, then the item omission risk level is determined to be the second sub-risk level.

[0066] For example, please refer to Table 1 below, where d1 represents the pressure detection data and d0 represents the initial pressure detection data. When the pressure detection data is less than or equal to the initial pressure detection data, and the item identification results determine that the passenger has no items that may have been left behind, and the behavior identification results determine that the passenger has no behavior that could lead to the loss of items, it can be determined that the passenger has no risk of losing items, i.e., the passenger's risk level for losing items is the first risk level. When the pressure detection data is less than or equal to the initial pressure detection data, and the item identification results determine that the passenger may have left behind items, and the behavior identification results determine that the passenger has no behavior that could lead to the loss of items, it can be determined that the passenger has no risk of losing items, i.e., the passenger's risk level for losing items is the first risk level. When the pressure detection data is less than or equal to the initial pressure detection data, and the item identification results determine that the passenger may have left behind items, and the behavior identification results determine that the passenger has behavior that could lead to the loss of items, it can be determined that the passenger has no risk of losing items, i.e., the passenger's risk level for losing items is the first risk level. If the stress detection data is greater than the initial stress detection data, and based on the item identification results it is determined that the passenger has no items that may have been left behind, and based on the behavior identification results it is determined that the passenger has no behavior that would lead to the loss of items, then the passenger can be determined to have a low risk of losing items, i.e., the passenger's risk level for losing items is level one. If the stress detection data is greater than the initial stress detection data, and based on the item identification results it is determined that the passenger has items that may have been left behind, and based on the behavior identification results it is determined that the passenger has no behavior that would lead to the loss of items, then the passenger can be determined to have a medium risk of losing items, i.e., the passenger's risk level for losing items is level two. If the stress detection data is greater than the initial stress detection data, and based on the item identification results it is determined that the passenger has items that may have been left behind, and based on the behavior identification results it is determined that the passenger has behavior that would lead to the loss of items, then the passenger can be determined to have a high risk of losing items, i.e., the passenger's risk level for losing items is level three, and so on. Therefore, based on the identification results and the relationship between the stress detection data and the initial stress detection data, the passenger's risk level for losing items can be accurately identified.

[0067] Optionally, if the pressure detection data is less than or equal to the initial pressure detection data, and the item identification results determine that the passenger does not have any items that may have been left behind, and the behavior identification results determine that the passenger has engaged in behavior that could lead to the loss of items, then the passenger can be determined to have no risk of losing items, i.e., the passenger's risk level for losing items is the first risk level.

[0068]

[0069]

[0070] Table 1

[0071] Step S103: Perform an item loss reminder operation for passengers corresponding to the item loss risk level.

[0072] The item loss reminder function can be used to remind passengers whether they have left any items behind.

[0073] There are several ways to issue a missing item reminder to a passenger based on the risk level of missing items. For example, the passenger's riding status can be detected; when the passenger's riding status meets the conditions for a missing item reminder based on the risk level of missing items, the missing item reminder operation can be performed on the passenger.

[0074] The "riding status" can refer to the passenger's vehicle status, such as "not yet arrived at the stop," "approaching the stop," "about to leave the seat," "left the seat," "doors open," "getting off the vehicle," or "vehicle about to stop." The "forgotten item reminder condition" can be the condition that triggers the reminder to the passenger for forgotten items. For example, it can be that the passenger's riding status is "approaching the stop," "about to leave the seat," or "left the seat." Specific conditions can be set according to actual circumstances, and this embodiment does not limit the specific conditions.

[0075] Optionally, different reminder conditions can be set for different risk levels of lost items. For example, for the first risk level, the reminder condition can be triggered when the passenger is about to leave their seat; for the first sub-risk level, the reminder condition can be triggered when the door is open; for the second sub-risk level, the reminder condition can be triggered when the vehicle is about to stop; and for the third sub-risk level, the reminder condition can be triggered when the passenger is about to arrive at their stop, etc.

[0076] Optionally, when the risk level of a passenger losing their belongings is the first risk level (no risk), there is no need to remind the passenger of lost items; when the risk level of a passenger losing their belongings is the first sub-risk level (low risk), a first-level warning for lost items can be activated; when the risk level of a passenger losing their belongings is the second sub-risk level (medium risk), a second-level warning for lost items can be activated; and when the risk level of a passenger losing their belongings is the third sub-risk level (high risk), a third-level warning for lost items can be activated.

[0077] Optionally, if the risk level of missing items is the first sub-risk level, the missing item reminder operation may include: playing the missing item reminder voice corresponding to the first sub-risk level.

[0078] The lost item reminder voice can be a message reminding passengers not to forget items, such as "Please check your belongings." For example, it can detect the opening status of doors around a passenger's area of ​​interest, and when a door is open, it can announce "Please check your belongings."

[0079] Optionally, if the risk level of missing items is the second or third sub-risk level, the steps for performing the missing item reminder operation corresponding to the risk level of missing items for passengers may include the following: performing a first reminder operation when the risk level of missing items is the second sub-risk level, or performing a second reminder operation when the risk level of missing items is the third sub-risk level, and detecting the vehicle locking signal; if the vehicle locking signal is detected, pushing the missing item reminder information to the terminal device corresponding to the passenger and / or driver.

[0080] The first reminder operation can be performed when the risk level of the passenger's lost item is at the second sub-risk level, and the second reminder operation can be performed when the risk level of the passenger's lost item is at the third sub-risk level. The terminal device corresponding to the passenger and / or driver can be the terminal device used by the passenger or the terminal device bound to the vehicle driver, such as a mobile phone, watch, tablet, or other electronic device. The lost item notification message can be a message indicating to the passenger that an item has been left behind.

[0081] The durations of the first and second reminder operations may differ, and both the first and second reminder operations include the target reminder behavior.

[0082] The target reminder behavior can be a reminder behavior common to both the first reminder operation and the second reminder operation.

[0083] The method of executing the target reminder behavior may include: controlling the passenger's seat to vibrate and outputting a first reminder signal; if the passenger is detected to have left the seat, detecting the first pressure detection data of the area of ​​interest; if the first pressure detection data is greater than the initial pressure detection data, controlling the vehicle to output a second reminder signal.

[0084] The first alert signal can be a notification to the passenger that a potentially forgotten item has been left behind; for example, it could be a beeping sound. The first pressure detection data can be the pressure value detected in the passenger's corresponding area of ​​interest after the passenger leaves their seat. The second alert signal can be a notification to the passenger that a potentially forgotten item has been left behind when the first pressure detection data exceeds the initial pressure detection data. For example, the second alert signal could be a flashing icon for a forgotten item on the vehicle's display screen, or the vehicle emitting a horn sound.

[0085] For example, if the risk level of a passenger leaving behind an item is the second sub-risk level, a second-level warning can be triggered when the passenger is about to arrive at the station. This will cause the seat in the passenger's area of ​​interest to vibrate and beep, which is the first reminder signal, to alert the passenger that there may be a missing item. The first reminder signal can end when d1≤d0 is detected, or when the door is manually closed, or automatically after 1 minute (the time can be set by the user). After the reminder ends, the door opening status can be continuously monitored. When the door opens and the passenger gets off the seat, the first pressure detection data d2 detected by the pressure sensor in the passenger's area of ​​interest can be detected. If d2>d0, the missing item warning can be triggered again, causing the missing item icon on the vehicle's display screen to flash and the vehicle to sound a horn. The warning ends after the door closes.

[0086] For example, if the risk level of a passenger leaving something behind is the third sub-risk level, a level three warning can be triggered when the passenger is about to arrive at their stop. This triggers the vibration of the seat in the passenger's area of ​​interest, accompanied by a beeping sound, which is the second reminder signal, to alert the passenger of a suspected lost item. The second reminder signal can end when d1 ≤ d0, when the seat is manually closed, or automatically after 2 minutes (the time can be set by the user). After the reminder ends, the door opening status can be continuously monitored. When the door opens and the passenger leaves their seat, the first pressure detection data d2 detected by the pressure sensor in the passenger's area of ​​interest can be detected. If d2 > d0, the lost item warning can be triggered again, causing the lost item icon on the vehicle's display screen to flash and the vehicle to sound its horn. The warning ends after the door closes. Then, the system can monitor whether the vehicle generates a locking signal. When the vehicle locks and generates a locking signal, a suspected lost item message (i.e., a lost item reminder) can be immediately pushed to the owner's mobile phone.

[0087] Accordingly, embodiments of this application provide an item loss detection system corresponding to the item loss reminder method. For example, please refer to... Figure 3 , Figure 3This is a schematic diagram of the system architecture of a method for reminding passengers of lost items provided in this application. The lost item detection system can be composed of an information acquisition module, an evaluation and judgment module, a central control module, and an early warning execution module. The information acquisition module can acquire static images (i.e., the first image) of the area of ​​interest in the vehicle and dynamic images (i.e., the second image) of the event of interest. Through deep learning algorithms, it determines whether there are items that are highly likely to be forgotten and behaviors that are highly likely to lead to forgetting items. Combined with the pressure value changes of the pressure sensors embedded in the vehicle, it determines the risk level of lost items for the passenger and determines the location of the lost items. It then provides graded early warnings based on the risk level of lost items, making the determination of lost item risk more accurate and convenient. Furthermore, it allows for the customization of key reminder areas and reminder cycles to avoid false alarms and frequent reminders, effectively improving the passenger's travel experience.

[0088] The information acquisition module can consist of an onboard standard camera, an onboard event camera, and a fiber optic pressure sensor. The evaluation and judgment module receives a first image of the area of ​​interest (ROI) and a second image of the event of interest. Using deep learning algorithms, it autonomously identifies whether there are potentially overlooked items or behaviors that might lead to item loss in the ROI, and determines the risk level of item loss based on pressure changes from the fiber optic pressure sensor. The central control module receives the item loss risk level from the evaluation and judgment module and controls the warning execution module to provide tiered alerts. This central control module allows for customized settings of key alert areas and alert cycles. Before or after passengers board, the operating status of each pressure sensor can be set via a remote control or the in-vehicle control panel. When items need to be temporarily stored in a specific alert area, the pressure sensor in that area can be manually turned off with a set off time to avoid false alarms and improve the passenger experience.

[0089] In one specific embodiment, please refer to Figure 4 , Figure 4This is a schematic diagram of the overall process of a method for reminding passengers of missing items provided in this application embodiment. Passengers or drivers can set or confirm the on / off status of each pressure sensor located in the vehicle through a remote control terminal. When it is necessary to enable the missing item detection function, the information acquisition module can be activated. When it is not necessary to perform missing item detection, the information acquisition module can be turned off. When the item loss detection function is activated, pressure sensors located in key areas of the vehicle record initial pressure detection data d0 when the door is detected to be open. When a passenger sits down, a standard camera installed in the vehicle captures the passenger's image. Based on the captured image, the passenger's seating position is identified, and the passenger and their surroundings are defined as the Region of Interest (ROI). Then, the vehicle-mounted standard camera acquires static images of the passenger's ROI, pressure detection data obtained from ROI pressure monitoring, and dynamic images of the passenger within the ROI. The evaluation and judgment module can then determine the level of item loss risk based on the collected detection data, classifying the passenger's item loss risk as no risk, low risk, medium risk, or high risk. Corresponding item loss warnings can then be issued. For example, a level one warning can be issued for a low-risk item loss level, a level two warning for a medium-risk item loss level, and a level three warning for a high-risk item loss level, etc.

[0090] Therefore, the item loss reminder method provided in this application embodiment can comprehensively determine the risk level of item loss from three aspects: the possibility of item loss, the behavior that leads to item loss, and changes in stress value. Compared with existing item loss reminder methods, it has higher convenience, feasibility, and accuracy. Furthermore, it can provide graded warnings for item loss risks while avoiding false alarms, taking into account both the warning effect and the driving experience, thereby improving the efficiency of item loss reminders.

[0091] As described above, this embodiment of the application acquires detection data collected from passengers in the vehicle; identifies the risk level of passengers leaving items based on the detection data; and performs item loss reminder operations corresponding to the risk level of item loss. Therefore, by identifying the risk level of passengers leaving items based on the detection data collected from passengers in the vehicle, and then performing item loss reminder operations corresponding to the risk level of item loss, it achieves targeted, graded item loss reminders for passengers based on their item loss risk level, thereby providing accurate and effective item loss reminders and significantly improving the efficiency of item loss reminders.

[0092] To facilitate better implementation of the item omission reminder method provided in this application embodiment, this application embodiment also provides an apparatus based on the above-described item omission reminder method. The meanings of the terms used are the same as in the item omission reminder method described above, and specific implementation details can be found in the description of the method embodiment.

[0093] For example, such as Figure 5 The diagram shown is a structural schematic of the item omission reminder device provided in this application embodiment. The item omission reminder device may include an acquisition module 201, an identification module 202, and a reminder module 203, as detailed below:

[0094] The acquisition module 201 is used to acquire detection data collected from passengers in the vehicle;

[0095] The identification module 202 is used to identify the risk level of passengers leaving items based on detection data;

[0096] The reminder module 203 is used to perform item loss reminder operations for passengers according to the risk level of item loss.

[0097] In one embodiment, the detection data includes at least one of visual detection data corresponding to the passenger and pressure detection data corresponding to the passenger's region of interest.

[0098] In one embodiment, the identification module 202 includes:

[0099] The identification submodule is used to identify the risk of passengers leaving items based on visual detection data and obtain the identification results.

[0100] The determination submodule is used to determine the risk level of passengers leaving items based on the identification results and pressure detection data.

[0101] In one embodiment, the visual detection data includes at least one of a first image captured by a camera and a second image captured by an event camera.

[0102] In one embodiment, the recognition result includes item recognition result and / or behavior recognition result, and the recognition submodule includes:

[0103] The first identification unit is used to identify whether the passenger may have missed any items based on the first image, and to obtain the item identification result;

[0104] And / or,

[0105] The second recognition unit is used to identify, based on the second image, whether the passenger has engaged in any behavior that would lead to the loss of an item, and to obtain the behavior recognition result.

[0106] In one embodiment, the first identification unit is configured to:

[0107] Retrieve item images of various preset items that may be missed;

[0108] Based on the item image and the first image, the system identifies whether the passenger may have missed any items, thus obtaining the item identification result.

[0109] In one embodiment, the second identification unit is used for:

[0110] Obtain event images corresponding to various preset behaviors that may lead to the omission of items;

[0111] Based on the event image and the second image, the system identifies whether the passenger engaged in any behavior that led to the loss of items, thus obtaining the behavior recognition result.

[0112] In one embodiment, determining a submodule includes:

[0113] The pressure detection unit is used to acquire initial pressure detection data of the area of ​​interest before the passenger sits down.

[0114] The level determination unit is used to determine the risk level of a passenger's lost items based on the comparison results of the pressure detection data and the initial pressure detection data, as well as the identification results.

[0115] In one embodiment, the risk level of lost items includes a first risk level and a second risk level, wherein the first risk level indicates that the passenger has no risk of losing items, and the second risk level indicates that the passenger has a risk of losing items.

[0116] Level determination unit, including:

[0117] The first-level determination subunit is used to determine the passenger's item loss risk level as the first risk level if the pressure detection data is less than or equal to the initial pressure detection data.

[0118] The second-level determination subunit is used to determine whether the risk level of item loss is the second risk level if the pressure detection data is greater than the initial pressure detection data.

[0119] In one embodiment, the identification result includes item identification result and behavior identification result; the second risk level includes a first sub-risk level, a second sub-risk level, and a third sub-risk level; and the second level determination sub-unit is used for:

[0120] If the pressure detection data is greater than the initial pressure detection data, the item identification result is negative, and the behavior identification result is negative, then the item omission risk level is determined to be the first sub-risk level.

[0121] If the pressure detection data is greater than the initial pressure detection data, the item identification result is yes, and the behavior identification result is no, then the item omission risk level is determined to be the second sub-risk level.

[0122] If the pressure detection data is greater than the initial pressure detection data, the item identification result is yes, and the behavior identification result is yes, then the item omission risk level is determined to be the second sub-risk level.

[0123] In one embodiment, the reminder module 203 includes:

[0124] The status detection submodule is used to detect the passenger's riding status;

[0125] The omission reminder submodule is used to remind passengers of missing items when their riding status meets the omission risk level corresponding to the omission reminder conditions.

[0126] In one embodiment, if the risk level of missing items is the first sub-risk level, the missing item reminder operation includes: playing the missing item reminder voice corresponding to the first sub-risk level.

[0127] In one embodiment, if the risk level of item loss is the second sub-risk level or the third sub-risk level, the reminder submodule includes one of the following:

[0128] The first alert unit is used to execute the first alert operation when the risk level of item loss is the second sub-risk level, or...

[0129] The second reminder unit is used to perform a second reminder operation when the risk level of item loss is the third sub-risk level, and to detect the vehicle locking signal generated by the vehicle.

[0130] The third reminder unit is used to push a reminder message about lost items to the terminal devices corresponding to passengers and / or drivers when a vehicle locking signal is detected.

[0131] In one embodiment, the durations of the first reminder operation and the second reminder operation are different, and both the first reminder operation and the second reminder operation include the target reminder behavior.

[0132] In one embodiment, the first reminder unit and the second reminder unit are used for:

[0133] Control the passenger's seat to vibrate and output the first alert signal;

[0134] If a passenger is detected leaving their seat, the first pressure detection data of the region of interest is detected.

[0135] If the first pressure detection data is greater than the initial pressure detection data, the vehicle will be controlled to output a second warning signal.

[0136] In one embodiment, the item loss reminder device further includes a region of interest detection module, used for:

[0137] Images of passengers are captured using cameras inside the vehicle;

[0138] Based on images, identify the passenger's seating position;

[0139] Based on seating position, determine the areas of interest for each passenger in the vehicle.

[0140] As described above, this embodiment of the application is configured with a message distribution component in the kernel. The kernel is implemented based on the first core of the target chip. The acquisition module 201 acquires detection data collected from passengers in the vehicle; the identification module 202 identifies the passenger's risk level of missing items based on the detection data; and the reminder module 203 performs an item omission reminder operation corresponding to the risk level of missing items. Thus, by identifying the passenger's risk level of missing items based on the detection data collected from passengers in the vehicle, and performing an item omission reminder operation corresponding to the risk level, targeted item omission reminders are provided to passengers based on their risk level, thereby enabling accurate and effective item omission reminders and significantly improving the efficiency of item omission reminders.

[0141] Accordingly, this application also provides a controller, including a processor and a memory. The memory stores an application program, and the processor runs the application program in the memory to implement the item omission reminder method provided in this application. This controller can be an electronic device.

[0142] Accordingly, this application also provides a vehicle, which may include the controller provided in this application.

[0143] Accordingly, embodiments of this application also provide an electronic device, such as... Figure 6 As shown, Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 300 includes a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, and a computer program stored in the memory 302 and executable on the processor. The processor 301 and the memory 302 are electrically connected. Those skilled in the art will understand that the electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0144] The processor 301 is the control center of the electronic device 300. It connects various parts of the electronic device 300 through various interfaces and lines. By running or loading software programs and / or units stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device 300 and processes data. The processor 301 may be a CPU, GPU, network processor (NP), etc., and can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0145] In this embodiment, the processor 301 in the electronic device 300 loads the instructions corresponding to the processes of one or more applications into the memory 302 according to the following steps, and the processor 301 runs the applications stored in the memory 302 to realize various functions, such as:

[0146] Acquire detection data collected from passengers in the vehicle; identify the risk level of passengers leaving behind items based on the detection data; and perform item loss reminder operations corresponding to the risk level of item loss for passengers.

[0147] Furthermore, the various functions implemented by running the application stored in memory 302 can also be found in the description of the foregoing embodiments, and will not be repeated here.

[0148] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0149] Optional, such as Figure 6 As shown, the electronic device 300 also includes: a touch display screen 303, a radio frequency circuit 304, an audio circuit 305, an input unit 306, and a power supply 307. The processor 301 is electrically connected to the touch display screen 303, the radio frequency circuit 304, the audio circuit 305, the input unit 306, and the power supply 307. Those skilled in the art will understand that... Figure 6 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0150] The touch display screen 303 can be used to display a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. The touch display screen 303 may include a display panel and a touch panel. The display panel can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the electronic device. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Optionally, the display panel can be configured using a liquid crystal display (LCD), organic light-emitting diode (OLED), or other similar technologies. The touch panel can be used to collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel), generate corresponding operation commands, and execute the corresponding program according to the operation commands. Optionally, the touch panel may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch location and the signal generated by the touch operation, transmitting the signal to the touch controller. The touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 301. It can also receive and execute commands from the processor 301. The touch panel can cover the display panel. When the touch panel detects a touch operation on or near it, it transmits the information to the processor 301 to determine the type of touch event. Subsequently, the processor 301 provides corresponding visual output on the display panel based on the type of touch event. In this embodiment, the touch panel and the display panel can be integrated into the touch display screen 303 to achieve input and output functions. However, in some embodiments, the touch panel and the touch display screen 303 can be implemented as two independent components to achieve input and output functions. That is, the touch display screen 303 can also be used as part of the input unit 306 to achieve input functions.

[0151] The radio frequency circuit 304 can be used to transmit and receive radio frequency signals to establish wireless communication with network devices or other electronic devices, and to transmit and receive signals with network devices or other electronic devices.

[0152] Audio circuitry 305 can be used to provide an audio interface between a user and an electronic device via a speaker and a microphone. Audio circuitry 305 converts received audio data into electrical signals, transmits them to the speaker, and the speaker converts them into sound signals for output. Conversely, the microphone converts collected sound signals into electrical signals, which are then received by audio circuitry 305, converted back into audio data, and then processed by processor 301 before being transmitted via radio frequency circuitry 304 to, for example, another electronic device, or output to memory 302 for further processing. Audio circuitry 305 may also include an earphone jack to facilitate communication between peripheral headphones and electronic devices.

[0153] The input unit 306 can be used to receive input target video and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0154] Power supply 307 is used to supply power to various components of electronic device 300. Optionally, power supply 307 can be logically connected to processor 301 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. Power supply 307 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0155] although Figure 6 As not shown in the diagram, the electronic device 300 may also include a camera, sensor, wireless fidelity module, Bluetooth module, etc., which will not be described in detail here.

[0156] In the above embodiments, the descriptions of each embodiment have different focuses. Parts not described in detail in a particular embodiment can be found in the relevant descriptions of other embodiments. It should be noted that the electronic device provided in this application embodiment and the method for reminding users of lost items in the above embodiments belong to the same concept. The specific implementation process is detailed in the above method embodiments and will not be repeated here.

[0157] As can be seen from the above, the electronic device provided in this application embodiment can acquire detection data collected from passengers in a vehicle; identify the risk level of passengers leaving items based on the detection data; and perform item loss reminder operations corresponding to the risk level of item loss. Thus, by identifying the risk level of passengers leaving items based on the detection data collected from passengers in the vehicle, and performing item loss reminder operations corresponding to the risk level of item loss, targeted item loss level reminders can be provided to passengers according to their item loss risk level, thereby providing accurate and effective item loss reminders and significantly improving the efficiency of item loss reminders.

[0158] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0159] Therefore, embodiments of this application provide a computer-readable storage medium, including a computer program, which, when run on an electronic device, causes the electronic device to execute any of the item omission reminder methods provided in the embodiments of this application. For example, the computer program can execute the steps of the following item omission reminder method:

[0160] Acquire detection data collected from passengers in the vehicle; identify the risk level of passengers leaving behind items based on the detection data; and perform item loss reminder operations corresponding to the risk level of item loss for passengers.

[0161] Furthermore, the detailed steps of the above method can be found in the description of the foregoing embodiments, and will not be repeated here.

[0162] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0163] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0164] Since the computer program stored in the computer-readable storage medium can execute any of the item omission reminder methods provided in the embodiments of this application, the beneficial effects that any of the item omission reminder methods provided in the embodiments of this application can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0165] According to one aspect of this application, a computer program product is also provided, comprising a computer program stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to perform the methods provided in various optional implementations of the above embodiments.

[0166] In the above embodiments of the item loss reminder device, computer-readable storage medium, controller, electronic device, vehicle, and computer program product, the descriptions of each embodiment have different focuses. Parts not described in detail in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process and beneficial effects of the item loss reminder device, computer-readable storage medium, controller, vehicle, computer program product, electronic device, and their corresponding units described above can be referred to the description of the item loss reminder method in the above embodiments, and will not be repeated here.

[0167] The foregoing has provided a detailed description of a method, apparatus, controller, vehicle, computer-readable storage medium, and computer program product for reminding users of missing items, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for reminding users of lost items, characterized in that, include: Acquire detection data collected from passengers in the vehicle. The detection data includes visual detection data corresponding to the passenger and pressure detection data of the region of interest corresponding to the passenger. The visual detection data includes a first image captured by a camera and a second image captured by an event camera. Based on the visual detection data, the risk of the passenger leaving behind items is identified, and the identification result is obtained; Based on the identification results and the pressure detection data, determine the risk level of the passenger's items being left behind; Perform the item loss reminder operation corresponding to the item loss risk level for the passenger; The identification results include item identification results and behavior identification results. The identification of the risk of item loss by the passenger based on the visual detection data, to obtain the identification results, includes: Based on the first image, identify whether the passenger may have missed any items, and obtain the item identification result; Based on the second image, it is determined whether the passenger has engaged in any behavior that would lead to the loss of an item, thus obtaining a behavior recognition result.

2. The method for reminding users of missing items according to claim 1, characterized in that, The step of identifying whether the passenger may have missed any items based on the first image, and obtaining the item identification result, includes: Retrieve item images of various preset items that may be missed; Based on the item image and the first image, it is determined whether the passenger may have missed any items, and an item identification result is obtained.

3. The method for reminding users of missing items according to claim 1, characterized in that, The step of identifying whether the passenger has engaged in any behavior that would lead to the loss of an item, based on the second image, and obtaining the behavior recognition result, includes: Obtain event images corresponding to various preset behaviors that may lead to the omission of items; Based on the event image and the second image, it is determined whether the passenger engaged in any behavior that led to the loss of an item, thus obtaining a behavior recognition result.

4. The method for reminding users of missing items according to claim 1, characterized in that, The step of determining the risk level of the passenger's lost items based on the identification results and the pressure detection data includes: Acquire initial pressure detection data of the region of interest before the passenger sits down; Based on the comparison results of the pressure detection data and the initial pressure detection data, as well as the identification results, the risk level of the passenger's lost items is determined.

5. The method for reminding users of missing items according to claim 4, characterized in that, The risk level of lost items includes a first risk level and a second risk level. The first risk level indicates that the passenger has no risk of losing items, while the second risk level indicates that the passenger has a risk of losing items. The determination of the passenger's item loss risk level based on the comparison result of the pressure detection data and the initial pressure detection data, and the identification result, includes: If the pressure detection data is less than or equal to the initial pressure detection data, then the risk level of the passenger's lost items is determined to be the first risk level. If the pressure detection data is greater than the initial pressure detection data, then the risk level of the item being missed is determined to be the second risk level based on the identification result.

6. The method for reminding users of missing items according to claim 5, characterized in that, The identification results include item identification results and behavior identification results. The second risk level includes a first sub-risk level, a second sub-risk level, and a third sub-risk level. If the stress detection data is greater than the initial stress detection data, then determining whether the item omission risk level is the second risk level based on the identification results includes: If the pressure detection data is greater than the initial pressure detection data, the item identification result is negative, and the behavior identification result is negative, then the item omission risk level is determined to be the first sub-risk level. If the pressure detection data is greater than the initial pressure detection data, the item identification result is yes, and the behavior identification result is no, then the item omission risk level is determined to be the second sub-risk level. If the pressure detection data is greater than the initial pressure detection data, the item identification result is yes, and the behavior identification result is yes, then the item omission risk level is determined to be the second sub-risk level.

7. The method for reminding users of missing items according to claim 6, characterized in that, The step of providing the passenger with an item loss reminder corresponding to the item loss risk level includes: Detect the passenger's seating status; When the passenger's riding status meets the missing item reminder conditions corresponding to the missing item risk level, the missing item reminder operation corresponding to the missing item risk level is executed on the passenger.

8. The method for reminding users of missing items according to claim 7, characterized in that, If the risk level of the missing item is the first sub-risk level, the missing item reminder operation includes: playing the missing item reminder voice corresponding to the first sub-risk level.

9. The method for reminding users of missing items according to claim 7, characterized in that, If the risk level of the missing item is the second or third sub-risk level, the step of performing the missing item reminder operation corresponding to the risk level of the missing item to the passenger includes one of the following: If the risk level of the item being missed is the second sub-risk level, execute the first reminder operation, or... If the risk level of the item being lost is the third sub-risk level, a second reminder operation is performed, and the vehicle locking signal generated by the vehicle is detected; If a vehicle lock signal is detected, a message indicating that an item has been left behind will be sent to the terminal device corresponding to the passenger and / or driver.

10. The method for reminding users of missing items according to claim 9, characterized in that, The first reminder operation and the second reminder operation have different durations, and both the first reminder operation and the second reminder operation include the target reminder behavior.

11. The method for reminding users of missing items according to claim 10, characterized in that, Execution of target reminder actions includes: Control the passenger's seat to vibrate and output a first alert signal; If the passenger is detected to have left their seat, the first pressure detection data of the region of interest is detected. If the first pressure detection data is greater than the initial pressure detection data, then the vehicle is controlled to output a second reminder signal.

12. The method for reminding users of missing items according to claim 1, characterized in that, Before acquiring the detection data collected from passengers in the vehicle, the process also includes: Images of passengers are captured using cameras inside the vehicle; Based on the image, identify the passenger's seating position; Based on the seating position, the region of interest corresponding to the passenger in the vehicle is determined.

13. A device for reminding users of lost items, characterized in that, include: The acquisition module is used to acquire detection data collected from passengers in the vehicle. The detection data includes visual detection data corresponding to the passenger and pressure detection data of the region of interest corresponding to the passenger. The visual detection data includes a first image captured by a camera and a second image captured by an event camera. The identification submodule is used to identify the risk of the passenger leaving behind items based on the visual detection data, and obtain the identification result. The determination submodule is used to determine the risk level of the passenger's lost items based on the identification results and the pressure detection data; The reminder module is used to perform an item omission reminder operation for the passenger corresponding to the item omission risk level; The identification results include item identification results and behavior identification results. The identification submodule is used to identify whether the passenger may have missed any items based on the first image, and to obtain item identification results. Based on the second image, it is used to identify whether the passenger has engaged in any behavior that may have led to the missed items, and to obtain behavior identification results.

14. A controller, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of any of the methods described in claims 1 to 12.

15. A vehicle, characterized in that, The vehicle includes the controller as described in claim 14.

16. A computer-readable storage medium, characterized in that, It includes a computer program that, when run on an electronic device, causes the electronic device to perform the steps of any of the methods described in claims 1 to 12.

17. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1 to 12.

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