False trigger prevention control system and method for b-pillar backlights

Abstract

The application discloses a kind of B column back light's anti false triggering control system and method.According to the technical scheme provided by the application, it comprises: signal acquisition module, image acquisition module, machine vision module, display control module and display module;Signal acquisition module is used to collect the position information of sensing key;Image acquisition module is used to collect the image information outside the car;Machine vision module is used to accurately screen out the passenger from image information based on machine vision;Display control module is used to control display module when the passenger is located within the preset range;Display module is used to turn on B column back light and display preset information.By the present application, the driver and passenger of the vehicle can be determined scientifically and accurately from the image information outside the vehicle using machine vision technology, and the B column back light is turned on when they approach the vehicle, effectively avoiding the situation of B column back light being turned on by mistake caused by other people, greatly reducing energy consumption and being more energy-saving and environmentally friendly.

Description

Technical Field

[0001] This invention relates to the field of intelligent human-vehicle interaction, and in particular to a control system and method for preventing accidental triggering of B-pillar backlights. Background Technology

[0002] As the automotive industry further develops towards intelligence, more and more humanized, intelligent, and personalized functions are appearing in cars. Whether it's traditional car manufacturers or emerging new energy vehicle companies, they are all focusing on applying technologies such as big data, artificial intelligence, and the Internet of Things to their current products. Based on these technologies, they aim to better meet various consumer needs, enhance the driving and riding experience, and improve the interaction between people and cars, thereby enhancing the overall user experience.

[0003] Currently, a key function for enhancing human-vehicle interaction is illuminating door lights when a passenger prepares to enter the vehicle. This feature typically involves placing a light source under the door or rearview mirror, which turns on when the passenger opens the door. However, this method is ineffective because passengers usually enter the vehicle almost instantly after the door opens, making it difficult to observe the specific content displayed by the light. Since there are many reasons for door opening, the welcome lights may be frequently activated, and if the door needs to be open for an extended period, the welcome lights may remain constantly on, resulting in energy waste and reduced light source lifespan. Furthermore, this method lacks a target selection process, leading to poor accuracy and targeting, and the displayed content is very limited. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a control system for preventing accidental triggering of B-pillar backlights and a corresponding control method for preventing accidental triggering of B-pillar backlights.

[0005] According to one aspect of the present invention, a control system for preventing accidental triggering of a B-pillar backlight is provided, comprising: a signal acquisition module, an image acquisition module, a machine vision module, a display control module, and a display module; wherein,

[0006] The signal acquisition module is used to acquire the first position information of the induction key;

[0007] The image acquisition module is used to acquire image information of the exterior of the vehicle and send the image information to the machine vision module;

[0008] The machine vision module is used to compare the received image information with the pre-stored target image within a first preset range, and combine it with the first location information of the sensing key to determine the first passenger; within the first preset range, it determines the travel route, travel speed and travel target of the person outside the vehicle based on the image information, and selects the second passenger.

[0009] The display control module is used to generate a control signal and send it to the display module when the first passenger and / or the second passenger are within a second preset range, based on the screening results for the first passenger and / or the second passenger.

[0010] The display module is used to turn on the B-pillar backlight to display preset information according to the control signal.

[0011] In the above solution, the machine vision module is further used for:

[0012] Receive image information sent by the image acquisition module; compare the pre-stored target image with the image information to select the first passenger; and / or,

[0013] Obtain the first location information of the keyless entry device and select the first passenger from the image information.

[0014] In the above solution, the machine vision module is further used for:

[0015] Extract target image features based on pre-stored target images;

[0016] Extract all features of the image to be inspected from the image information;

[0017] The similarity scores between each feature of the image to be inspected and the feature of the target image are calculated sequentially, and it is determined whether the similarity scores are greater than a preset threshold.

[0018] If the obtained similarity score is greater than the preset threshold, the recognition is successful, the person corresponding to the image information is identified as the first passenger, and the recognition stops.

[0019] If the obtained similarity score is not greater than the preset threshold, the recognition fails, and the similarity judgment is performed on the features of the next image to be detected.

[0020] In the above solution, the machine vision module is further used for:

[0021] Place the image information in the same coordinate system as the first position information of the sensor key;

[0022] Based on the first location information of the sensor key, determine the first target person corresponding to the first location information from the image information;

[0023] The first target person is identified as the first passenger.

[0024] In the above solution, the machine vision module is further used for:

[0025] Based on the image information, obtain the travel route of the first passenger and the travel routes of other people in the image information within a preset time period;

[0026] Compare the travel routes of other personnel with those of the first passenger; determine whether the travel routes of other personnel are similar to those of the first passenger.

[0027] If so, the corresponding person is determined to be the second passenger;

[0028] If not, then the corresponding person is determined not to be the second passenger.

[0029] In the above solution, the machine vision module is further used for:

[0030] Within a preset time period, the location information of the second target person and the first passenger at multiple corresponding times is extracted, and the distance between the second target person and the first passenger at each time is calculated; wherein, the second target person refers to other persons besides the first passenger.

[0031] Determine whether the distance between the second target person and the first passenger is less than the first preset distance at each time point;

[0032] If so, then the movement route of the second target person is determined to be similar to that of the first passenger.

[0033] If not, then it is determined that the travel route of the second target person is not similar to the travel route of the first passenger.

[0034] In the above solution, the machine vision module is further used for:

[0035] Based on the image information, obtain the magnitude and direction of the current movement speed of the second target person, and determine its movement target within the image range;

[0036] If the second target person's travel target is a user vehicle, then when the distance between the second target person and the user vehicle is less than the second preset distance, it is determined whether the travel speed of the second target person is less than the preset speed.

[0037] If so, the corresponding person is determined to be the second passenger;

[0038] If not, then the corresponding person is determined not to be the second passenger.

[0039] In the above solution, the display control module further includes: a voice control submodule and a remote control submodule, wherein,

[0040] The voice control submodule is used to verify identity based on preset sound information, and wake up the voice control submodule after successful verification. Then, it controls the display module according to the user's further voice content.

[0041] The remote control submodule is used to receive control signals from the smart key and / or the remote control APP to control the display module.

[0042] In the above solution, the display module is further used for:

[0043] The B-pillar backlight displays preset information via a display module.

[0044] According to another aspect of the present invention, a method for preventing accidental triggering of a B-pillar backlight is provided, comprising:

[0045] Collect the first location information of the sensor key;

[0046] It collects image information of the exterior of the car and sends the image information to the machine vision module;

[0047] Within a first preset range, the received image information is compared with the pre-stored target image, and combined with the first location information of the key to determine the first passenger; within the first preset range, the travel route, travel speed and travel target of the person outside the vehicle are determined based on the image information, and the second passenger is selected.

[0048] Based on the screening results for the first passenger and / or the second passenger, a control signal is generated and sent to the display module;

[0049] The B-pillar backlight is activated based on the control signal to display preset information.

[0050] According to the technical solution provided by the present invention, the anti-mistriggered control system for the B-pillar backlight includes: a signal acquisition module, an image acquisition module, a machine vision module, a display control module, and a display module; wherein, the signal acquisition module is used to acquire first position information of the sensing key; the image acquisition module is used to acquire image information of the exterior of the vehicle and send the image information to the machine vision module; the machine vision module is used to compare the received image information with a pre-stored target image within a first preset range, and combine it with the first position information of the sensing key to determine a first occupant; within the first preset range, it determines the travel route, travel speed, and travel target of the person outside the vehicle based on the image information, and filters out a second occupant; the display control module is used to generate a control signal and send it to the display module when the first occupant and / or the second occupant are within a second preset range, based on the filtering results of the first occupant and / or the second occupant; the display module is used to turn on the B-pillar backlight to display preset information according to the control signal. By acquiring the location of the proximity key and external image information, and based on pre-stored driver images, machine vision technology is used to filter the external image information and combine it with the proximity key's location information to more accurately identify the driver. Furthermore, after identifying the driver, machine vision technology compares the movement paths of other people in the image with the driver's path, and determines the movement targets and speeds of other people to scientifically and accurately identify the vehicle's passengers. The B-pillar backlights are only activated when the driver and passengers are close to the vehicle. Thus, by accurately filtering the driver and passengers from the surrounding image information, the backlight activation is more targeted, effectively preventing accidental activation of the B-pillar backlights when other people pass by the vehicle. Furthermore, by only activating the B-pillar backlights when the driver and passengers are very close to the vehicle, they are prevented from remaining lit for extended periods, significantly reducing energy consumption and making the system more energy-efficient and environmentally friendly. In addition, the B-pillar backlights can also be controlled via voice recognition, smart key, or an app, increasing user convenience and operational options.

[0051] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0052] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0053] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0054] Figure 1 A structural block diagram of a B-pillar backlight anti-false triggering control system according to an embodiment of the present invention is shown;

[0055] Figure 2 A flowchart illustrating a first passenger screening method according to an embodiment of the present invention is shown;

[0056] Figure 3 A flowchart illustrating a second passenger screening method according to an embodiment of the present invention is shown;

[0057] Figure 4 A flowchart illustrating a second passenger screening method according to another embodiment of the present invention is shown;

[0058] Figure 5 A structural block diagram of a B-pillar backlight anti-false triggering control system according to another embodiment of the present invention is shown;

[0059] Figure 6 A flowchart illustrating a method for preventing accidental triggering of a B-pillar backlight according to an embodiment of the present invention is shown. Detailed Implementation

[0060] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0061] Figure 1 A structural block diagram of an anti-false triggering control system for a B-pillar backlight according to an embodiment of the present invention is shown. The system includes: a signal acquisition module 101, an image acquisition module 102, a machine vision module 103, a display control module 104, and a display module 105; wherein,

[0062] The signal acquisition module 101 is used to acquire the first position information of the sensing key.

[0063] The image acquisition module 102 is used to acquire image information of the exterior of the vehicle and send the image information to the machine vision module.

[0064] The machine vision module 103 is used to compare the received image information with the pre-stored target image within a first preset range, and combine it with the first location information of the sensing key to determine the first passenger; within the first preset range, it determines the travel route, travel speed and travel target of the person outside the vehicle based on the image information, and selects the second passenger.

[0065] Specifically, it receives image information sent by the image acquisition module; compares the pre-stored target image with the image information to select the first passenger; and / or,

[0066] Obtain the first location information of the keyless entry device and select the first passenger from the image information.

[0067] Preferably, the image information is placed in the same coordinate system as the first position information of the sensor key;

[0068] Based on the first location information of the sensor key, determine the first target person corresponding to the first location information from the image information;

[0069] The first target person is identified as the first passenger.

[0070] Preferably, after placing the image information in the same coordinate system as the first location information of the sensing key, the position in the image information that is the same as the first location information is determined based on the first location information, and the corresponding first target person is found.

[0071] Preferably, the first passenger is the driver of the vehicle.

[0072] Preferably, the first preset range can be a circular range with a radius of 10 meters centered on the center of the target vehicle.

[0073] The display control module 104 is used to generate a control signal and send it to the display module 105 when the first passenger and / or the second passenger are within a second preset range, based on the screening results for the first passenger and / or the second passenger.

[0074] Preferably, the second preset range can be a circular range with a radius of 2 meters centered on the center of the target vehicle.

[0075] The display module 105 is used to turn on the B-pillar backlight to display preset information according to the control signal.

[0076] Specifically, the display module is further used for:

[0077] The B-pillar backlight displays preset information via a display module.

[0078] Preferably, the B-pillar backlight uses a display module, and the content displayed on the display module can be controlled by a separate display signal. The specific display content can be preset and controlled through various methods such as the vehicle's infotainment system and a smart terminal's app, and is not limited here.

[0079] The B-pillar backlight anti-mistriggering control system provided in this embodiment includes: a signal acquisition module, an image acquisition module, a machine vision module, a display control module, and a display module; wherein, the signal acquisition module is used to acquire first location information of the induction key; the image acquisition module is used to acquire image information of the exterior of the vehicle and send the image information to the machine vision module; the machine vision module is used to compare the received image information with a pre-stored target image within a first preset range, and combine it with the first location information of the induction key to determine a first occupant; within the first preset range, it determines the travel route, travel speed, and travel target of the person outside the vehicle based on the image information, and filters out a second occupant; the display control module is used to generate a control signal and send it to the display module when the first occupant and / or the second occupant are within a second preset range, based on the filtering results of the first occupant and / or the second occupant; the display module is used to turn on the B-pillar backlight to display preset information according to the control signal. By acquiring the location of the key fob and external image information, and based on pre-stored driver images, machine vision technology filters the external image information and combines it with the key fob's location information to more accurately identify the driver. Furthermore, after identifying the driver, machine vision technology scientifically and accurately identifies the vehicle's passengers. The B-pillar backlight is only activated when the driver and passengers are close to the vehicle. Thus, by accurately filtering the driver and passengers from the surrounding image information, the backlight activation is more targeted, effectively preventing accidental activation of the B-pillar backlight when other people pass by the vehicle. Furthermore, by only activating the B-pillar backlight when the driver and passengers are very close to the vehicle, it avoids prolonged illumination, significantly reducing energy consumption and making it more energy-efficient and environmentally friendly. By adjusting the printed cover or control display module, the specific content displayed by the B-pillar backlight can be more flexibly selected, better meeting the personalized needs of different users.

[0080] Based on machine vision module 103, there exists a method for screening first passengers, such as... Figure 2 As shown, Figure 2 A flowchart illustrating a first passenger screening method according to an embodiment of the present invention is shown;

[0081] The method includes the following steps:

[0082] Step S201: Extract target image features based on pre-stored target images.

[0083] Step S202: Extract all features of the image to be inspected from the image information.

[0084] Step S203: Calculate the similarity score between each feature of the image to be inspected and the feature of the target image in turn, and determine whether the similarity score is greater than the preset threshold.

[0085] Specifically, if yes, proceed to step S204; otherwise, proceed to step S205.

[0086] In step S204, if the obtained similarity score is greater than the preset threshold, the recognition is successful, the person corresponding to the image information is identified as the first passenger, and the recognition stops.

[0087] In step S205, if the obtained similarity score is not greater than the preset threshold, the recognition fails, and the similarity judgment is performed on the features of the next image to be detected.

[0088] Specifically, if the identification fails, return to step S203.

[0089] According to the above method, machine vision technology can be used to pre-store the facial image of the first passenger and then use facial recognition to filter and determine the first passenger from the acquired image information around the vehicle. This can greatly improve the accuracy and speed of screening the first passenger. At the same time, the above method also takes into account the situation where the first passenger does not carry a keyless entry device, that is, the purpose of accurately screening the first passenger can be achieved using only machine vision technology, thus improving the system's compatibility.

[0090] Based on machine vision module 103, there exists a second passenger screening method, such as... Figure 3 As shown, Figure 3 A flowchart illustrating a second passenger screening method according to an embodiment of the present invention is shown; the method includes the following steps:

[0091] Step S301: Based on the image information, obtain the travel route of the first passenger and the travel routes of other passengers in the image information within a preset time period.

[0092] Step S302: Compare the travel routes of other personnel with the travel route of the first passenger; determine whether the travel routes of other personnel are similar to the travel route of the first passenger.

[0093] Specifically, within a preset time period, the location information of the second target person and the first passenger at multiple corresponding times is extracted, and the distance between the second target person and the first passenger at each time is calculated; wherein, the second target person refers to other persons besides the first passenger.

[0094] Determine whether the distance between the second target person and the first passenger is less than the first preset distance at each time point;

[0095] If so, determine that the second target person's travel route is similar to the first passenger's travel route, and execute step S303;

[0096] If not, it is determined that the travel route of the second target person is not similar to the travel route of the first passenger, and step S304 is executed.

[0097] Preferably, the preset time period can be 20 seconds, and the multiple corresponding times can be 5 times; that is, the location information of 5 times is selected within 20 seconds for distance determination.

[0098] Step S303: Determine that the corresponding person is the second passenger.

[0099] Step S304: Determine that the corresponding person is not the second passenger.

[0100] Furthermore, based on the machine vision module 103, there exists another second passenger screening method, such as... Figure 4 As shown, Figure 4 A flowchart illustrating a second passenger screening method according to another embodiment of the present invention is shown; the method includes the following steps:

[0101] Step S401: Based on the image information, obtain the magnitude and direction of the current movement speed of the second target person, and determine its movement target within the image range.

[0102] Step S402: If the second target person's travel target is a user vehicle, then when the distance between the second target person and the user vehicle is less than a second preset distance, determine whether the travel speed of the second target person is less than a preset speed.

[0103] Specifically, if yes, proceed to step S403; otherwise, proceed to step S404.

[0104] Preferably, a second preset distance;

[0105] Step S403: Determine that the corresponding person is the second passenger.

[0106] Step S404: Determine that the corresponding person is not the second passenger.

[0107] Based on the two methods mentioned above, using machine vision technology, the vehicle's passengers can be quickly, scientifically, and accurately identified by comparing the travel routes of other people in the image with the driver's travel route, as well as by determining the travel targets and speeds of other people. This effectively avoids the B-pillar backlights from accidentally turning on when other people pass by the vehicle, preventing them from lighting up frequently, greatly reducing energy consumption, and making the system more energy-efficient and environmentally friendly.

[0108] Figure 5 A structural block diagram of an anti-false triggering control system for a B-pillar backlight according to another embodiment of the present invention is shown, as follows: Figure 5 As shown, the system includes: a signal acquisition module 501, an image acquisition module 502, a machine vision module 503, a display control module 504, and a display module 505; wherein, the display control module 504 further includes:

[0109] Voice control submodule 506 and remote control submodule 507, wherein,

[0110] The voice control submodule 506 is used to verify identity based on preset sound information, and wake up the voice control submodule after successful verification, and then control the display module according to further voice content from the user.

[0111] The remote control submodule 507 is used to receive control signals from the smart key and / or the remote control APP to control the display module.

[0112] Specifically, the functions implemented by the signal acquisition module 501, image acquisition module 502, machine vision module 503, display control module 504, and display module 505 in this system, as well as their interrelationships, are as shown in the above embodiment and will not be repeated here.

[0113] According to the above system, the B-pillar backlight can be controlled via voice recognition, smart key, or APP, which increases user convenience and the choice of operation methods.

[0114] Figure 6 A flowchart illustrating a method for preventing accidental triggering of a B-pillar backlight according to an embodiment of the present invention is shown; as follows: Figure 6 As shown, the method includes the following steps:

[0115] Step S601: Collect the first location information of the sensor key.

[0116] Step S602: Acquire image information of the exterior of the vehicle and send the image information to the machine vision module.

[0117] In step S603, within the first preset range, the received image information is compared with the pre-stored target image, and combined with the first location information of the sensor key, the first passenger is determined; within the first preset range, the travel route, travel speed and travel target of the person outside the vehicle are determined according to the image information, and the second passenger is selected.

[0118] Specifically, it receives image information sent by the image acquisition module; compares the pre-stored target image with the image information to select the first passenger; and / or,

[0119] Obtain the first location information of the keyless entry device and select the first passenger from the image information.

[0120] Preferably, the image information is placed in the same coordinate system as the first position information of the sensor key;

[0121] Based on the first location information of the sensor key, determine the first target person corresponding to the first location information from the image information;

[0122] The first target person is identified as the first passenger.

[0123] Specifically, target image features are extracted based on pre-stored target images;

[0124] Extract all features of the image to be inspected from the image information;

[0125] The similarity scores between each feature of the image to be inspected and the feature of the target image are calculated sequentially, and it is determined whether the similarity scores are greater than a preset threshold.

[0126] If the obtained similarity score is greater than the preset threshold, the recognition is successful, the person corresponding to the image information is identified as the first passenger, and the recognition stops.

[0127] If the obtained similarity score is not greater than the preset threshold, the recognition fails, and the similarity judgment is performed on the features of the next image to be detected.

[0128] Specifically, based on the image information, the travel route of the first passenger and the travel routes of other people in the image information within a preset time period are obtained;

[0129] Compare the travel routes of other personnel with those of the first passenger; determine whether the travel routes of other personnel are similar to those of the first passenger.

[0130] If so, the corresponding person is determined to be the second passenger;

[0131] If not, then the corresponding person is determined not to be the second passenger.

[0132] Preferably, within a preset time period, the location information of the second target person and the first passenger at multiple corresponding times is extracted, and the distance between the second target person and the first passenger at each time is calculated; wherein, the second target person refers to persons other than the first passenger;

[0133] Determine whether the distance between the second target person and the first passenger is less than the first preset distance at each time point;

[0134] If so, then the movement route of the second target person is determined to be similar to that of the first passenger.

[0135] If not, then it is determined that the travel route of the second target person is not similar to the travel route of the first passenger.

[0136] Specifically, based on the image information, the magnitude and direction of the second target person's current movement speed are obtained to determine their movement target within the image range;

[0137] If the second target person's travel target is a user vehicle, then when the distance between the second target person and the user vehicle is less than the second preset distance, it is determined whether the travel speed of the second target person is less than the preset speed.

[0138] If so, the corresponding person is determined to be the second passenger;

[0139] If not, then the corresponding person is determined not to be the second passenger.

[0140] Step S604: Based on the screening results for the first passenger and / or the second passenger, generate a control signal and send it to the display module.

[0141] Specifically, the system verifies identity based on preset voice information and wakes up the voice control submodule after successful verification. Then, it controls the display module according to the user's further voice commands.

[0142] Specifically, it receives control signals from smart keys and / or remote control apps to control the display module.

[0143] Step S605: Turn on the B-pillar backlight to display preset information according to the control signal.

[0144] Specifically, the B-pillar backlight displays preset information via a display module.

[0145] According to the above-mentioned anti-mistriggered control method for the B-pillar backlight, the following steps can be taken: first position information of the induction key is collected; image information of the exterior of the vehicle is collected and sent to the machine vision module; within a first preset range, the received image information is compared with a pre-stored target image, and combined with the first position information of the induction key, the first passenger is determined; within the first preset range, the travel route, travel speed, and travel target of the person outside the vehicle are determined based on the image information, and the second passenger is selected; based on the selection results for the first passenger and / or the second passenger, a control signal is generated and sent to the display module; and the B-pillar backlight is turned on to display preset information according to the control signal. By acquiring the location of the proximity key and external image information, and based on pre-stored driver images, machine vision technology is used to filter the external image information and combine it with the proximity key's location information to more accurately identify the driver. Furthermore, after identifying the driver, machine vision technology compares the movement paths of other people in the image with the driver's path, and determines the movement targets and speeds of other people to scientifically and accurately identify the vehicle's passengers. The B-pillar backlights are only activated when the driver and passengers are close to the vehicle. Thus, by accurately filtering the driver and passengers from the surrounding image information, the backlight activation is more targeted, effectively preventing accidental activation of the B-pillar backlights when other people pass by the vehicle. Furthermore, by only activating the B-pillar backlights when the driver and passengers are very close to the vehicle, they are prevented from remaining illuminated for extended periods, significantly reducing energy consumption and making the system more energy-efficient and environmentally friendly. In addition, the B-pillar backlights can also be controlled via voice recognition, smart key, or an app, increasing user convenience and operational options.

[0146] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0147] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0148] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0149] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0150] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0151] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0152] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A control system for preventing accidental triggering of B-pillar backlights, comprising: The system includes a signal acquisition module, an image acquisition module, a machine vision module, a display control module, and a display module; among which, The signal acquisition module is used to acquire the first position information of the induction key; The image acquisition module is used to acquire image information of the exterior of the vehicle and send the image information to the machine vision module; The machine vision module is used to compare the received image information with the pre-stored target image within a first preset range, and combine it with the first location information of the sensing key to determine the first passenger, wherein the first passenger is the driver of the car; after determining the driver, within the first preset range, the module determines the travel route, travel speed and travel target of the person outside the car based on the image information, and filters out the second passenger, wherein the second passenger is the passenger of the car; the first preset range is a circular range with a radius of 10 meters centered on the center of the target vehicle; The display control module is used to generate a control signal and send it to the display module when the first passenger and the second passenger are within a second preset range, based on the screening results for the first passenger and the second passenger; the second preset range is a circular range with a radius of 2 meters centered on the center of the target vehicle. The display module is used to turn on the B-pillar backlight to display preset information according to the control signal.

2. The system according to claim 1, characterized in that, The machine vision module is further used for: Receive image information sent by the image acquisition module; compare the pre-stored target image with the image information to select the first passenger; and / or, Obtain the first location information of the keyless entry device and select the first passenger from the image information.

3. The system according to claim 1, characterized in that, The machine vision module is further used for: Extract target image features based on pre-stored target images; Extract all features of the image to be inspected from the image information; The similarity scores between each feature of the image to be inspected and the feature of the target image are calculated sequentially, and it is determined whether the similarity scores are greater than a preset threshold. If the obtained similarity score is greater than the preset threshold, the recognition is successful, the person corresponding to the image information is identified as the first passenger, and the recognition stops. If the obtained similarity score is not greater than the preset threshold, the recognition fails, and the similarity judgment is performed on the features of the next image to be detected.

4. The system according to claim 1 or 2, characterized in that, The machine vision module is further used for: Place the image information in the same coordinate system as the first position information of the sensor key; Based on the first location information of the sensor key, determine the first target person corresponding to the first location information from the image information; The first target person is identified as the first passenger.

5. The system according to claim 1, characterized in that, The machine vision module is further used for: Based on the image information, obtain the travel route of the first passenger and the travel routes of other people in the image information within a preset time period; Compare the travel routes of other personnel with those of the first passenger; determine whether the travel routes of other personnel are similar to those of the first passenger. If so, the corresponding person is determined to be the second passenger; If not, then the corresponding person is determined not to be the second passenger.

6. The system according to claim 1, characterized in that, The machine vision module is further used for: Within a preset time period, the location information of the second target person and the first passenger at multiple corresponding times is extracted, and the distance between the second target person and the first passenger at each time is calculated; wherein, the second target person refers to other persons besides the first passenger. Determine whether the distance between the second target person and the first passenger is less than the first preset distance at each time point; If so, then the movement route of the second target person is determined to be similar to that of the first passenger. If not, then it is determined that the travel route of the second target person is not similar to the travel route of the first passenger.

7. The system according to claim 1, characterized in that, The machine vision module is further used for: Based on the image information, obtain the magnitude and direction of the current movement speed of the second target person, and determine its movement target within the image range; If the second target person's travel target is a user vehicle, then when the distance between the second target person and the user vehicle is less than the second preset distance, it is determined whether the travel speed of the second target person is less than the preset speed. If so, the corresponding person is determined to be the second passenger; If not, then the corresponding person is determined not to be the second passenger.

8. The system according to claim 1, characterized in that, The display control module further includes: a voice control submodule and a remote control submodule, wherein, The voice control submodule is used to verify identity based on preset sound information, and wake up the voice control submodule after successful verification. Then, it controls the display module according to the user's further voice content. The remote control submodule is used to receive control signals from the smart key and / or the remote control APP to control the display module.

9. The system according to claim 1, characterized in that, The display module is further used for: The B-pillar backlight displays preset information via a display module.

10. A method for preventing accidental triggering of a B-pillar backlight, comprising: Collect the first location information of the sensor key; It collects image information of the exterior of the car and sends the image information to the machine vision module; Within a first preset range, the received image information is compared with a pre-stored target image, and combined with the first location information of the key fob, to determine the first passenger, wherein the first passenger is the driver of the car; after determining the driver, within the first preset range, the travel route, travel speed and travel target of the person outside the car are determined based on the image information, and the second passenger is selected, wherein the second passenger is the passenger of the car; the first preset range is a circular range with a radius of 10 meters centered on the center of the target vehicle; Based on the screening results for the first and second passengers, when the first and second passengers are within a second preset range, a control signal is generated and sent to the display module; the second preset range is a circular area with a radius of 2 meters centered on the center of the target vehicle. The B-pillar backlight is activated based on the control signal to display preset information.

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