CN114475502A - Method and device for protecting getting-off safety of passengers - Google Patents
Method and device for protecting getting-off safety of passengers Download PDFInfo
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- CN114475502A CN114475502A CN202210299006.8A CN202210299006A CN114475502A CN 114475502 A CN114475502 A CN 114475502A CN 202210299006 A CN202210299006 A CN 202210299006A CN 114475502 A CN114475502 A CN 114475502A
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- vehicle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
- B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
Abstract
The application provides a passenger getting-off safety protection method and a passenger getting-off safety protection device, wherein the passenger getting-off safety protection device comprises: the detection device is used for detecting whether a passenger touches the door handle or not; the acquisition device is used for acquiring the information of a moving target running behind the vehicle; and the control device is used for controlling the acquisition device to acquire moving target information of the vehicle driving behind when the detection device detects that the passenger touches the door handle, determining the danger of the moving target according to the DNN classification model, and controlling the door handle to be locked when the moving target is judged to have high danger. The safety of passengers when getting off the vehicle is judged based on the collected moving target running behind the vehicle through the DNN classification model, and the door handle is controlled to be locked when the high risk is judged, so that the safety of the passengers when getting off the vehicle is improved.
Description
Technical Field
One or more embodiments of the present disclosure relate to the field of automotive technologies, and in particular, to a method and a device for protecting a passenger from getting off a vehicle.
Background
With the development of economy, people often adopt to take a bus for going out, but when getting off the vehicle, high danger often appears.
Especially, when a passenger gets off the vehicle, especially a rear passenger cannot accurately observe whether a vehicle, a pedestrian or a non-motor vehicle is approaching behind the passenger, and therefore, the passenger, the vehicle and an object approaching the vehicle behind the passenger are potentially dangerous. At present, the safety of getting off is only limited to whether the vehicle is parked on the ground or not, and the safety protection force on the person to get off is relatively small.
At present, a method for ensuring the getting-off safety of passengers mainly adopts the steps that a camera device and a radar device are arranged below a vehicle door, collected data are compared with pre-stored safe ground image sample data for characteristics, and if the comparison result shows that the data are not suitable for getting-off, a buzzer reminds a user that the data are not suitable for getting-off. The scheme can only carry out safety prejudgment on the condition of a static road surface below the vehicle, and cannot carry out prejudgment on unsafe factors behind the vehicle.
Disclosure of Invention
In view of the above, one or more embodiments of the present disclosure are directed to a method and a device for protecting passengers from getting off, so as to improve the safety of passengers getting off.
In a first aspect, a safety protection device for a passenger to get off is provided, where the safety protection device for a passenger to get off includes:
the detection device is used for detecting whether a passenger touches the door handle or not;
the acquisition device is used for acquiring the information of a moving target running behind the vehicle;
and the control device is used for controlling the acquisition device to acquire moving target information of the vehicle driving behind when the detection device detects that a passenger touches the door handle, determining the danger of the moving target according to the DNN classification model, and controlling the door handle to be locked when the moving target is judged to have high danger. The safety of passengers when getting off the vehicle is judged based on the collected moving target running behind the vehicle through the DNN classification model, and the door handle is controlled to be locked when the high risk is judged, so that the safety of the passengers when getting off the vehicle is improved.
In a specific embodiment, the collection device comprises:
the camera device is arranged on the rear windshield of the vehicle and is used for shooting an image of a moving target behind the vehicle;
the radar device is arranged on a rear bumper of the vehicle and is used for collecting motion data of a moving target behind the vehicle.
In a specific possible embodiment, the control device is further configured to identify the position and the type of the object potentially threatening the passenger around the vehicle in the moving object information collected by the collecting device based on an object detection model of R-CNN.
In a specific possible embodiment, the control means is further adapted to predict future motion behavior of the object potentially threatening the passenger based on the LSTM target tracking algorithm.
In a specific possible embodiment, the control device is further specifically configured to determine a risk of the potentially passenger-threatening object according to a DNN classification model based on the prediction of the future motion behavior of the potentially passenger-threatening object, and to control the door handle to lock when it is determined that there is a high risk.
In a specific embodiment, the method further comprises: an alarm device;
the control device is also used for controlling the alarm device to send out a first alarm when the door handle is controlled to be locked.
In a specific embodiment, the method comprises the following steps:
the control device is also used for controlling the alarm device to give out a second alarm without locking the door handle when the moving object is judged to have low danger.
In a second aspect, a method for protecting getting-off safety of passengers is provided, which comprises the following steps: detecting whether a passenger touches the door handle or not;
when the detection device detects that a passenger touches the door handle, the moving target information of the vehicle driving behind is collected;
based on the collected moving target information of the vehicle driving behind, determining the danger of the moving target according to a DNN classification model;
and controlling the door handle to be locked when the moving target is judged to have high danger.
According to the technical scheme, the safety of the passengers when getting off the vehicle is judged through the DNN classification model based on the collected moving target running behind the vehicle, and the door handle is controlled to be locked when the high risk is judged, so that the safety of the passengers when getting off the vehicle is improved.
In a specific possible implementation, the collecting the moving object information of the vehicle driving behind is specifically:
shooting an image of a moving object behind the vehicle through a camera device;
collecting motion data of the vehicle rear moving object by a radar device
In a specific possible implementation, the step of determining the risk of the moving object according to the DNN classification model based on collecting information of the moving object driven by the vehicle is specifically as follows:
identifying the position and the type of an object which potentially threatens passengers and is arranged around the vehicle in the moving target information collected by the collecting device based on a target detection model of R-CNN;
predicting future motion behavior of the object potentially threatening the passenger based on an LSTM target tracking algorithm;
determining a risk of the potentially passenger-threatening object according to a DNN classification model based on the prediction of future motion behavior of the potentially passenger-threatening object.
In a specific possible embodiment, the method further comprises:
and when the door handle is controlled to be locked, the alarm device is controlled to send out a first alarm.
In a specific possible embodiment, the method further comprises:
and when the moving target is determined to have low danger, controlling the alarm device to send out a second alarm without locking the door handle.
In a third aspect, an automobile is provided, which comprises an automobile body and the passenger getting-off safety protection device arranged in the automobile body. According to the technical scheme, the safety of the passengers when getting off the vehicle is judged through the DNN classification model based on the collected moving target running behind the vehicle, and the door handle is controlled to be locked when the high risk is judged, so that the safety of the passengers when getting off the vehicle is improved.
In a fourth aspect, an electronic device is provided, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method for performing the second aspect and any one of the possible designs of the second aspect when executing the program.
In a fifth aspect, a non-transitory computer-readable storage medium is provided, which stores computer instructions for causing the computer to perform the second aspect and any one of the possible design methods of the second aspect.
In a sixth aspect, there is also provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any one of the possible designs of the second aspect and the second aspect of the present application.
In addition, for technical effects brought by any one of the possible design manners in the fourth aspect to the sixth aspect, reference may be made to effects brought by different design manners in the method portion, and details are not described herein again.
Drawings
In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only one or more embodiments of the present specification, and that other drawings may be obtained by those skilled in the art without inventive effort from these drawings.
Fig. 1 is a block diagram illustrating a passenger getting-off safety protection device according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a method for protecting a passenger from getting off in accordance with an embodiment of the present application;
fig. 3 is a block diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.
It is to be noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present specification should have the ordinary meaning as understood by those of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in one or more embodiments of the specification is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
The technical carrier involved in payment in the embodiments of the present specification may include Near Field Communication (NFC), WIFI, 3G/4G/5G, POS machine card swiping technology, two-dimensional code scanning technology, barcode scanning technology, bluetooth, infrared, Short Message Service (SMS), Multimedia Message (MMS), and the like, for example.
In order to facilitate understanding of the passenger getting-off safety protection device provided by the embodiment of the application, an application scenario of the passenger getting-off safety protection device is firstly explained, and the passenger getting-off safety protection device provided by the embodiment of the application is used for protecting a passenger from being collided by a bicycle, a pedestrian or an automobile around the vehicle when the passenger gets off the vehicle. As the traffic becomes more and more busy, vehicles and pedestrians on the road become more and more, which inevitably causes the safety of passengers when getting off the vehicle. For the person who sits in the driving seat or the passenger seat, the situation can be observed through the rearview mirror of the vehicle, but for the person who sits in the rear row, when getting off the vehicle, the person does not have too many means to observe, and only can open the door to observe, which inevitably causes risks. Therefore, the present invention provides a passenger getting-off safety protection device and a protection method, which will be described below with reference to the specific drawings and embodiments.
Referring first to fig. 1, fig. 1 illustrates a passenger getting-off safety protection device according to an embodiment of the present application. The passenger getting-off safety protection device is a passenger getting-off reminding and protecting device based on image recognition, and relates to the fields of mobile internet and artificial intelligence. According to functions, the system can be divided into three parts of perception, decision and execution; it includes according to structure division: detection device 20, collection device 30, control device 10 and door handle lock. The detecting device 20 and the collecting device 30 are sensing parts, and the detecting device 20 is used for detecting whether a passenger touches the door handle 40 and taking the signal as a signal whether the whole device needs to be started; the acquisition device 30 is used for acquiring the information of a moving target running behind the vehicle and using the signal to judge whether an original signal of danger exists; and the control device 10 is used as a decision part for controlling the acquisition device 30 to acquire moving object information of the vehicle driving after the vehicle when the detection device 20 detects that the passenger touches the door handle 40, determining the danger of the moving object according to the DNN classification model, and controlling the door handle 40 to be locked when the moving object is judged to have high danger. The door lock serves as an executing portion for executing a corresponding command according to the determination result of the control device 10. The command is specifically: when high danger is judged, the door handle lock executes a locking command; when low risk or no risk is determined, the door handle lock executes a command not to lock.
With continued reference to FIG. 1, the detection device 20 is disposed on the door handle 40 and may be a different type of sensor, such as a sensor that senses that the door handle 40 is being groomed, or a sensor that senses a touch by a user's hand. For example, the detecting device 20 may be a pressure sensor, a capacitance sensor, or other sensors capable of sensing the touch of the hand on the wrench.
The acquisition device 30 specifically includes a camera device 31 and a radar device 32, wherein the camera device 31 is used for acquiring a video of a moving target around the vehicle; the radar device 32 is used to collect motion data of a moving object behind the vehicle. To detect the distance of the moving object from the current vehicle and the approaching speed. The moving object refers to an object such as a vehicle or a person traveling around the vehicle.
When the image pickup device 31 is specifically provided, the image pickup device 31 is located on the rear windshield of the vehicle with its angle of view directed toward the outside of the vehicle. For example, the camera device 31 may be fixed to the rear windshield of the vehicle by adhesion. Of course, the present invention may be provided at various positions such as the rear portion of the vehicle, a rear bumper, and the like, in addition to the rear windshield.
When the radar device 32 is specifically provided, the radar device 32 is provided on a rear bumper of the vehicle, and a scanning area thereof is located in an area of the vehicle near a rear door. In particular fixing, the radar device 32 may be fixed to the rear bumper by bolts or screws.
The control device 10 is a decision-making part of the whole device, and can be a central control computer of an automobile, or a common control device 10 such as a separately arranged PLC, a single chip microcomputer and the like.
Specifically, when the pickup device 30 and the door handle lock are controlled, the control device 10 first receives a detection signal from the detection device 20, and when the detection device 20 detects that the user is acting on the door handle 40, the control device 10 controls the pickup device 30 to start pickup of information on a moving object around the vehicle. And determining the risk of the moving object according to the DNN classification model. If the high risk is judged, controlling the door handle lock to be locked; when low risk or no risk is determined, the door handle lock is controlled not to be locked.
When the control device 10 specifically controls the acquisition device 30 to acquire the information of the moving target, the camera device 31 is firstly controlled to acquire the image of the moving target around the vehicle, the control device 10 performs image recognition and detection on the acquired image, and when the moving target is recognized and detected to be close to the vehicle, the radar device 32 is controlled to detect the distance between the moving target and the current vehicle and the approaching speed, and risk assessment is performed on the image recognition result and the radar detection result. The two data acquisition results are comprehensively considered, and the getting-off safety of passengers is divided into three levels, namely safety, low risk and high risk.
When image recognition and detection are specifically performed, the control device 10 includes an image recognition system, and the intelligent image recognition system can perform a large amount of simulation training on historical images by means of machine learning according to images shot by the camera device 31, preliminarily judge whether dangerous objects are approaching from the rear, and output recognition results when the dangerous objects are not limited to moving pedestrians, vehicles and non-motor vehicles.
In a specific training, the images acquired by the imaging device 31 may be manually labeled to obtain a training sample. And obtaining a model causing danger to passengers to get off the vehicle through the machine exercise of the answer quantity.
The position and type of objects that potentially pose a threat to passengers around the vehicle in the moving object information collected by the collection device 30 are first identified by training the R-CNN-based object detection model. And predicting the future motion behavior of the object potentially threatening the passenger by training an LSTM-based target tracking algorithm.
When the control device 10 specifically determines a danger, the control device 10 identifies the position and type of an object potentially threatening the passenger around the vehicle in the moving object information acquired by the acquisition device 30 through a trained object detection model based on R-CNN, and thus identifies the position and type of an object potentially threatening the passenger, such as a pedestrian and a vehicle, around the vehicle in the present situation. And predicting the future motion behavior of the object potentially threatening the passenger through a trained LSTM-based target tracking algorithm, thereby confirming the dynamic environment around the vehicle.
The control device 10 is further specifically adapted to determine the risk of an object potentially threatening the passenger from the DNN classification model based on predicting future motion behavior of the object potentially threatening the passenger. That is, based on data collected by the radar device 32 and an identification result of the intelligent image identification system as decision characteristics, the current environment risk of getting off passengers is predicted through the DNN model classification model, and the environment risk level is divided into safety, low risk and high risk.
The control device 10 is based on the result obtained by training the cloud server, and the cloud server reports a large amount of image recognition results and detection data of the radar device 32, so that the model for machine learning training through artificial intelligence is more accurate in decision making.
The execution part can also comprise an alarm device besides the door handle lock; the alarm device can be a light alarm device, or a sound and light alarm device, etc.
The control device is also used for controlling the alarm device to give out a first alarm when the door handle 40 is controlled to be locked. And controlling the alarm device to give a second alarm without locking the door handle 40 when it is determined that there is a low risk of the moving object.
For example, when the passenger touches the door handle 40, if the getting-off safety level is low risk, the control device 10 sends a voice reminding instruction to the alarm, and the alarm gives a second alarm, such as "there is an unsafe object approaching behind, please open the door carefully"; if the exit security level is high risk, the control device 10 sends a command for prohibiting opening the door to the vehicle, the vehicle door controller executes a door locking action to lock the door handle 40, and simultaneously plays a second alarm, such as voice playing "there is a dangerous object approaching behind, please get off the vehicle later". Thereby achieving the purpose of safety reminding and protection when the passenger gets off the vehicle.
As can be seen from the above description, the present application provides a passenger getting-off protection device based on image recognition. The system comprises three components, namely a sensing part based on an in-vehicle rear camera device 31 and a vehicle rear radar device 32; a decision part composed of an image recognition system, big data and artificial intelligence; and an execution part composed based on the vehicle controller. When a passenger stops touching the door handle 40, the rear camera device 31 in the vehicle collects images, the radar detects the distance between a dynamic object and the current vehicle and the approaching speed, and the intelligent image recognition system and the big data evaluate the collected data to decide whether safe getting-off is available at present. Thereby improving the safety of passengers when getting off the bus.
As shown in fig. 2, in order to facilitate understanding of the device for ensuring the safety of passengers getting off according to the embodiment of the present application, the present application further provides a method for ensuring the safety of passengers getting off, which includes the following steps:
step 001: detecting whether a passenger touches the door handle or not;
in particular, the passenger is checked by means of a detection device provided on the door handle, which may be a sensor of different types, such as a sensor sensing the movement of the door handle or a sensor sensing the touch of the user's hand. For example, the detection device may be a pressure sensor or a capacitance sensor, which may sense that the hand touches the wrench.
Step 002: when the detection device detects that a passenger touches the door handle, the moving target information of the vehicle driving behind is collected;
specifically, an image of a moving object behind the vehicle is shot through a camera device; and collecting the motion data of the moving target behind the vehicle through a radar device. The camera device is used for acquiring videos of moving objects around the vehicle; the radar device is used for collecting motion data of a moving object behind the vehicle. To detect the distance of the moving object from the current vehicle and the approaching speed. The moving object refers to an object such as a vehicle or a person traveling around the vehicle.
Step 003: based on the collected moving target information of the vehicle driving behind, determining the danger of the moving target according to the DNN classification model;
specifically, the position and the type of an object which potentially threatens passengers around the vehicle in the moving target information collected by the collecting device are identified based on an R-CNN target detection model;
predicting future movement behavior of an object potentially threatening a passenger based on an LSTM target tracking algorithm;
based on predicting future motion behavior of an object potentially threatening the passenger, the risk of the object potentially threatening the passenger is determined according to the DNN classification model. The detailed description may refer to the related description in fig. 1.
Step 004: and when the moving object is judged to have high danger, controlling the door handle to be locked.
Specifically, when the door handle is controlled to be locked, the alarm device is controlled to send out a first alarm. When the moving object is judged to have low danger, the alarm device is controlled to give out a second alarm, and the door handle is not locked
According to the technical scheme, the safety of the passengers when getting off the vehicle is judged through the DNN classification model based on the collected moving target running behind the vehicle, and the door handle is controlled to be locked when the high risk is judged, so that the safety of the passengers when getting off the vehicle is improved.
The embodiment of the application also provides an automobile which comprises an automobile body and any one of the passenger getting-off safety protection devices arranged in the automobile body. In the technical scheme, the corresponding equipment registration module, the operation search module and the first calling module are constructed aiming at different chips, so that when a program is developed, the equipment can be controlled only by calling the function corresponding to each equipment, and a software engineer only needs to call the corresponding function when developing, does not need to care about specific chip types, and reduces the design, implementation and maintenance cost of complex driving.
The present application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements a method for implementing the second aspect and any one of the possible designs of the second aspect.
Embodiments of the present application also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the second aspect and any one of the possible design methods of the second aspect.
Embodiments of the present application also provide a computer program product, which includes instructions that, when executed on a computer, cause the computer to perform the method according to the second aspect of the present application and any one of the possible designs of the second aspect.
It should be noted that the method of one or more embodiments of the present disclosure may be performed by a single device, such as a computer or server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the devices may perform only one or more steps of the method of one or more embodiments of the present disclosure, and the devices may interact with each other to complete the method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the modules may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.
The apparatus of the foregoing embodiment is used to implement the corresponding method in the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Fig. 3 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.
The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the spirit of the present disclosure, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present description as described above, which are not provided in detail for the sake of brevity.
In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures, for simplicity of illustration and discussion, and so as not to obscure one or more embodiments of the disclosure. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the understanding of one or more embodiments of the present description, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the one or more embodiments of the present description are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the disclosure, it should be apparent to one skilled in the art that one or more embodiments of the disclosure can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
It is intended that the one or more embodiments of the present specification embrace all such alternatives, modifications and variations as fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of one or more embodiments of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (15)
1. A safety protection device for getting off a passenger is characterized by comprising:
the detection device is used for detecting whether a passenger touches the door handle or not;
the acquisition device is used for acquiring the information of a moving target running behind the vehicle;
and the control device is used for controlling the acquisition device to acquire moving target information of the vehicle driving behind when the detection device detects that a passenger touches the door handle, determining the danger of the moving target according to the DNN classification model, and controlling the door handle to be locked when the moving target is judged to have high danger.
2. A vehicle occupant get-off safety protection device according to claim 1, wherein said collection means comprises:
the camera device is arranged on the rear windshield of the vehicle and is used for shooting an image of a moving target behind the vehicle;
the radar device is arranged on a rear bumper of the vehicle and is used for collecting motion data of a moving target behind the vehicle.
3. A passenger disembarkation safety arrangement according to claim 2, wherein the control device is further configured to identify the location and type of objects potentially threatening passengers around the vehicle in the moving object information collected by the collecting device based on an object detection model of R-CNN.
4. A vehicle occupant disembarking safety arrangement according to claim 3, wherein said control means is further adapted to predict future movement behavior of said object potentially threatening the occupant based on an LSTM target tracking algorithm.
5. A vehicle occupant egress safety protection arrangement according to claim 4, wherein said control means is further specifically configured to determine a risk of said potentially passenger-threatening object according to a DNN classification model based on said predicting future motion behavior of said potentially passenger-threatening object, and to control said door handle to be locked when it is determined that there is a high risk.
6. A vehicle occupant get-off safety protection device according to any one of claims 1 to 5, further comprising: an alarm device;
the control device is also used for controlling the alarm device to send out a first alarm when the door handle is controlled to be locked.
7. A vehicle occupant get-off safety protection device according to claim 6, comprising:
the control device is also used for controlling the alarm device to give out a second alarm without locking the door handle when the moving object is judged to have low danger.
8. A passenger getting-off safety protection method is characterized by comprising the following steps:
detecting whether a passenger touches the door handle or not;
when the detection device detects that a passenger touches the door handle, the moving target information of the vehicle driving behind is collected;
based on the collected moving target information of the vehicle driving behind, determining the danger of the moving target according to a DNN classification model;
and controlling the door handle to be locked when the moving target is judged to have high danger.
9. A method of providing occupant drop safety protection as claimed in claim 8,
the method for acquiring the moving target information of the vehicle running behind specifically comprises the following steps:
shooting an image of a moving object behind the vehicle through a camera device;
and collecting the motion data of the moving target behind the vehicle through a radar device.
10. A passenger get-off safety protection method according to claim 9, wherein the step of determining the risk of the moving object based on the collected information of the moving object after the vehicle travels and according to the DNN classification model specifically comprises:
identifying the position and the type of an object which potentially threatens passengers and is arranged around the vehicle in the moving target information collected by the collecting device based on a target detection model of R-CNN;
predicting future motion behavior of the object potentially threatening the passenger based on an LSTM target tracking algorithm;
determining a risk of the potentially passenger-threatening object according to a DNN classification model based on the prediction of future motion behavior of the potentially passenger-threatening object.
11. A method of providing ride safety protection for an occupant of a vehicle as claimed in claim 10, further comprising:
and when the door handle is controlled to be locked, the alarm device is controlled to send out a first alarm.
12. A method of providing ride safety protection for an occupant of a vehicle as recited in claim 11, further comprising:
and when the moving target is determined to have low danger, controlling the alarm device to send out a second alarm without locking the door handle.
13. An automobile, characterized by comprising an automobile body and the passenger getting-off safety protection device according to any one of claims 1 to 7 arranged in the automobile body.
14. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of providing occupant exit safety protection as claimed in any one of claims 8 to 12 when executing the program.
15. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the occupant egress safety protection method according to any one of claims 8 to 12.
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| CN202210299006.8A CN114475502A (en) | 2022-03-24 | 2022-03-24 | Method and device for protecting getting-off safety of passengers |
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| CN202210299006.8A CN114475502A (en) | 2022-03-24 | 2022-03-24 | Method and device for protecting getting-off safety of passengers |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115631553A (en) * | 2022-10-11 | 2023-01-20 | 中国第一汽车股份有限公司 | Vehicle unlocking method, vehicle unlocking device and vehicle |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105329167A (en) * | 2015-12-11 | 2016-02-17 | 安徽工程大学 | Vehicle door opening early warning system and safety protection method thereof |
| JP2018205909A (en) * | 2017-05-31 | 2018-12-27 | 本田技研工業株式会社 | Processing device, vehicle, processing method, and program |
| CA3067573A1 (en) * | 2019-01-14 | 2020-07-14 | Harbin Engineering University | Target tracking systems and methods for uuv |
| WO2021179340A1 (en) * | 2020-03-12 | 2021-09-16 | 博睿泰克科技（宁波）有限公司 | Vehicle driving-based danger early-warning method and system, and storage medium |
| CN113997864A (en) * | 2021-12-06 | 2022-02-01 | 中南大学 | Automobile getting-off collision-prevention early warning and intervention system and method |
-
2022
- 2022-03-24 CN CN202210299006.8A patent/CN114475502A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105329167A (en) * | 2015-12-11 | 2016-02-17 | 安徽工程大学 | Vehicle door opening early warning system and safety protection method thereof |
| JP2018205909A (en) * | 2017-05-31 | 2018-12-27 | 本田技研工業株式会社 | Processing device, vehicle, processing method, and program |
| CA3067573A1 (en) * | 2019-01-14 | 2020-07-14 | Harbin Engineering University | Target tracking systems and methods for uuv |
| WO2021179340A1 (en) * | 2020-03-12 | 2021-09-16 | 博睿泰克科技（宁波）有限公司 | Vehicle driving-based danger early-warning method and system, and storage medium |
| CN113997864A (en) * | 2021-12-06 | 2022-02-01 | 中南大学 | Automobile getting-off collision-prevention early warning and intervention system and method |
Non-Patent Citations (2)
| Title |
|---|
| 何福贵: "《Python深度学习：逻辑、算法与编程实战》", 30 September 2020, 机械工业出版社, pages: 146 - 149 * |
| 国网江苏省电力有限公司、东南大学: "Python深度学习：逻辑、算法与编程实战", 东南大学出版社, pages: 194 - 197 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115631553A (en) * | 2022-10-11 | 2023-01-20 | 中国第一汽车股份有限公司 | Vehicle unlocking method, vehicle unlocking device and vehicle |
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