CN118311562A - Passenger vehicle door opening monitoring system and method - Google Patents
Passenger vehicle door opening monitoring system and method Download PDFInfo
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- CN118311562A CN118311562A CN202410738042.9A CN202410738042A CN118311562A CN 118311562 A CN118311562 A CN 118311562A CN 202410738042 A CN202410738042 A CN 202410738042A CN 118311562 A CN118311562 A CN 118311562A
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Abstract
The invention provides a passenger vehicle door opening monitoring system and a method, wherein the system comprises the following steps: the device comprises a millimeter wave radar module, an infrared human body sensor module and a control module; when the approaching distance is smaller than or equal to a preset distance threshold value, controlling the infrared human body sensor module to detect whether the approaching object is a living being or not; when the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened; a door opening collision probability map is also constructed; when the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; determining door opening collision probability corresponding to the vehicle position from the collision probability map; determining radar detection frequency corresponding to door opening collision probability from a preset radar detection frequency library; the millimeter wave radar module is controlled to detect the approaching distance of the approaching object behind the vehicle tail at the radar detection frequency. The data processing load of the system is reduced, the influence of bad weather on mobile biological detection is reduced, and the applicability of the system is greatly improved.
Description
Technical Field
The invention relates to the technical field of automobile safety control, in particular to a passenger vehicle door opening monitoring system and method.
Background
Currently, for avoiding an impact accident caused by opening a vehicle door, the current solutions mainly include two types: the first type is to detect a rear object by using a camera and a millimeter wave radar, and when the distance from the moving object to the vehicle body is detected to be smaller than a set threshold value, the result is prompted to personnel in the vehicle through a display or a voice prompt device, and the personnel in the vehicle operate to prevent collision. The other is an ultrasonic sensor combination scheme, wherein a plurality of ultrasonic sensors are used for detecting a rear object, judging the position of the object, and pre-warning the opening of the vehicle door according to the distance.
However, for the scheme that the former camera is matched with the millimeter wave radar, image data signals acquired by the camera are required to be processed, on one hand, an algorithm is required to be constructed to identify objects, so that a software part is more complex, and the data load of a vehicle ECU is increased; on the other hand, the camera recognition effect is greatly affected in the environments such as night, rainy days, snowy days and the like. With the latter ultrasonic sensor scheme, although the cost is low, the recognition and detection efficiency of the moving object is low, and it is impossible to recognize the moving organism behind at the first time and prevent the door from being opened.
Secondly, the two schemes are used for controlling the detection hardware to continuously work, however, the probability of occurrence of collision between pedestrians and vehicles when the doors are opened is also different due to different factors such as traffic flow of different streets, and if the detection hardware is controlled to continuously monitor, the service life of the detection hardware can be reduced, and the power consumption can be increased.
Thus, a solution is needed.
Disclosure of Invention
The invention aims to provide a passenger vehicle door opening monitoring system, which adopts a solution of matching a millimeter wave radar with an infrared human body sensor, so that the complex problem of large data image processing can be solved, the data processing load of the system can be reduced, the influence of bad weather on mobile biological detection can be reduced, and the efficient detection can be realized with low cost, and the door opening can be prevented from collision accidents; and a door opening collision probability map is introduced, so that the door opening collision probability is rapidly determined, the radar detection frequency corresponding to the door opening collision probability is determined, and the millimeter wave radar module is controlled to detect the approaching distance of the approaching object behind the vehicle tail at the radar detection frequency, so that the applicability of the system is greatly improved.
The embodiment of the invention provides a passenger vehicle door opening monitoring system, which comprises:
At least one millimeter wave radar module arranged at the tail of the passenger vehicle;
at least one infrared human body sensor module arranged at the rearview mirror of the passenger vehicle;
the control module is connected with the millimeter wave radar module and the infrared human body sensor module and is used for comprising:
Controlling the millimeter wave radar module to detect the approaching distance of an approaching object behind the vehicle tail;
when the approaching distance is smaller than or equal to a preset distance threshold value, controlling the infrared human body sensor module to detect whether the approaching object is a living organism or not;
When the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened;
the control module is further configured to include:
constructing a door opening collision probability map;
when the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; the target state includes: the speed of the vehicle is zero and the passengers do not get off the vehicle;
determining door opening collision probability corresponding to the vehicle position from a collision probability map;
determining radar detection frequency corresponding to the door opening collision probability from a preset radar detection frequency library;
and controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the tail at the radar detection frequency.
Preferably, the control module constructs a door opening collision probability map, including:
acquiring a plurality of door opening collision events from a big data platform;
acquiring a plurality of occurrence positions of each door opening collision event;
calling a preset urban traffic map;
Determining a plurality of first roadside parking positions corresponding to each incident position from the urban traffic map;
giving a first target probability preset for each first roadside parking position;
determining a plurality of second roadside parking locations other than the first roadside parking location from the urban traffic map;
Traversing the second roadside parking position in sequence;
Determining whether the first roadside parking location exists on the traversed street of the second roadside parking location from the urban traffic map;
When present, assigning the first target probability to the traversed second roadside parking location; when the first road side parking position and the second road side parking position are not found, respectively acquiring first position environment information of the traversed second road side parking position and second position environment information of the traversed second road side parking position from the urban traffic map;
Calculating the maximum similarity between the first position environment information and the second position environment information;
Determining a second target probability corresponding to the maximum similarity from a preset probability library;
assigning the second target probability to the traversed second roadside parking location;
And taking the urban traffic map endowed with the first target probability of the first roadside parking position and the second target probability of the second roadside parking position as a door opening collision probability map.
Preferably, the control module obtains a plurality of door opening collision events from the big data platform, including:
acquiring a guarantee value of each event element of the door opening collision event of the big data platform for trusted guarantee;
and when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, acquiring the door-opening collision event.
Preferably, the control module acquires a plurality of door opening collision events from the big data platform, and the method further comprises:
When at least one guarantee value of the credible guarantee of each event element of the door opening collision event is smaller than a guarantee threshold value, acquiring a generation scene and a generation source of the door opening collision event;
acquiring a generation type of a door opening collision event generated by a generation source in a generation scene;
When the generation type of the door opening collision event generated by the generation source in the generation scene is active generation, traversing each event element in the door opening collision event in sequence;
each time of traversing, determining a scene association relation and an element extraction strategy corresponding to the element type of the traversed event element from a scene association relation library; the element extraction rule includes: extracting execution rules and execution priorities corresponding to the groups one by one;
Sequentially executing corresponding extraction execution rules in other scenes with scene association relations with the generated scenes according to the execution priority from large to small;
When the replacement event element is extracted, stopping executing the extraction execution rule, and replacing the traversed event element in the door opening collision event with the replacement event element;
After each event element in the traversing door-opening collision event is finished, acquiring a door-opening collision event in which the event element is replaced by a replacement event element;
when the generation type of the door opening collision event generated by the generation source in the generation scene is passive generation, acquiring multi-mode information which is newly generated by the generation source in the generation scene and related to the door opening collision event;
constructing an information description vector of the multi-mode information;
Determining a quasi-acquired value corresponding to the information description vector from a quasi-acquired value library;
And acquiring a door opening collision event when the quasi-acquisition value is greater than or equal to the quasi-acquisition value threshold.
Preferably, the control module controls the millimeter wave radar module to detect the approaching distance of the approaching object behind the vehicle tail, including:
After the passenger vehicle parks, the passenger prepares to get off; at this time, the vehicle speed sensor detects that the vehicle speed of the passenger vehicle is 0;
the passengers prepare to get on the bus; at this time, the lock state identifier detects that the lock is in the unlocked state.
Preferably, the distance threshold includes: 5 meters.
Preferably, the control module is further configured to control the opening of the door when the occupant opens the door twice in succession.
The method for monitoring the opening of the door of the passenger vehicle provided by the embodiment of the invention comprises the following steps:
controlling a millimeter wave radar module arranged at the tail of the passenger vehicle to detect the approaching distance of an approaching object behind the tail;
when the approaching distance is smaller than or equal to a preset distance threshold value, an infrared human body sensor module arranged at a rearview mirror of the passenger vehicle detects whether the approaching object is a living organism or not;
When the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened;
the method further comprises the steps of:
constructing a door opening collision probability map;
when the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; the target state includes: the speed of the vehicle is zero and the passengers do not get off the vehicle;
determining door opening collision probability corresponding to the vehicle position from a collision probability map;
determining radar detection frequency corresponding to the door opening collision probability from a preset radar detection frequency library;
starting the millimeter wave radar module;
and controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the tail at the radar detection frequency.
Preferably, the constructing the door opening collision probability map includes:
acquiring a plurality of door opening collision events from a big data platform;
acquiring a plurality of occurrence positions of each door opening collision event;
calling a preset urban traffic map;
Determining a plurality of first roadside parking positions corresponding to each incident position from the urban traffic map;
giving a first target probability preset for each first roadside parking position;
determining a plurality of second roadside parking locations other than the first roadside parking location from the urban traffic map;
Traversing the second roadside parking position in sequence;
Determining whether the first roadside parking location exists on the traversed street of the second roadside parking location from the urban traffic map;
When present, assigning the first target probability to the traversed second roadside parking location; when the first road side parking position and the second road side parking position are not found, respectively acquiring first position environment information of the traversed second road side parking position and second position environment information of the traversed second road side parking position from the urban traffic map;
Calculating the maximum similarity between the first position environment information and the second position environment information;
Determining a second target probability corresponding to the maximum similarity from a preset probability library;
assigning the second target probability to the traversed second roadside parking location;
And taking the urban traffic map endowed with the first target probability of the first roadside parking position and the second target probability of the second roadside parking position as a door opening collision probability map.
Preferably, the acquiring a plurality of door opening collision events from the big data platform includes:
acquiring a guarantee value of each event element of the door opening collision event of the big data platform for trusted guarantee;
and when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, acquiring the door-opening collision event.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of the installation positions of millimeter wave radar and infrared human body sensors in an embodiment of the invention;
Fig. 2 is an electrical schematic diagram of a passenger vehicle door opening monitoring system according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a passenger vehicle door opening monitoring system, as shown in fig. 1, comprising:
At least one millimeter wave radar module arranged at the tail of the passenger vehicle;
at least one infrared human body sensor module arranged at the rearview mirror of the passenger vehicle;
the control module is connected with the millimeter wave radar module and the infrared human body sensor module and is used for comprising:
Controlling the millimeter wave radar module to detect the approaching distance of an approaching object behind the vehicle tail;
when the approaching distance is smaller than or equal to a preset distance threshold value, controlling the infrared human body sensor module to detect whether the approaching object is a living organism or not;
When the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened;
the control module is further configured to include:
Constructing a door opening collision probability map; the door opening collision probability map is provided with door opening collision probabilities corresponding to different road side parking positions in the city; the door opening collision probability is the probability that the vehicle door is stopped and opened to collide with pedestrians, vehicles coming from the vehicle and the like;
When the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; the target state includes: the speed of the vehicle is zero and the passengers do not get off the vehicle; the preset duration may be, for example: 3 minutes; when the passenger vehicle is kept in the target state for a period longer than the preset period, the passenger vehicle is stopped, but passengers are not taken off, for example: driver/occupant in car, etc.;
determining door opening collision probability corresponding to the vehicle position from a collision probability map;
determining radar detection frequency corresponding to the door opening collision probability from a preset radar detection frequency library; the radar detection frequency library has radar detection frequencies corresponding to different door opening collision probabilities, and the higher the door opening collision probability is, the more intensive monitoring is needed, and the higher the radar detection frequency is;
and controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the tail at the radar detection frequency.
In the concrete implementation, a millimeter wave radar is arranged at the tail part of the vehicle body, and a first millimeter wave radar is arranged at the left rear edge of the vehicle body; the second millimeter wave radar is arranged at the right rear edge of the vehicle body; millimeter wave radar is used to measure the condition of approaching a target at the rear and detect the distance of a moving object from a door. The infrared human body sensor is arranged below the automobile rearview mirror, the first infrared human body sensor is arranged below the automobile body left rearview mirror, the second infrared human body sensor is arranged below the automobile body right rearview mirror, the infrared human body sensor is used for judging whether a moving object approaching the automobile door is biological or not, and the installation position is shown in fig. 1. In fig. 1, a reference numeral 1 is an infrared human body sensor installation position, and a reference numeral 2 is a millimeter wave radar installation position.
Door opening is divided into two states: the state 1 is that after the automobile is stopped, the automobile speed is zero, and passengers open the automobile door to get off; the state 2 is that no person is in the car, and an outside person needs to open the car door to get on the car.
The state 1 is that a vehicle speed sensor (the vehicle is provided with a self belt and is arranged on a wheel hub) detects that the vehicle speed is 0; the state 2 is that a lock state identifier (the automobile is provided with the lock and is installed on the lock) detects that the lock is in an open state, and when at least one state is activated, the function of the door opening monitoring system is activated. The millimeter wave radar is used for detecting whether a moving object reaches a set threshold value of the controller, the returned signal is sent to the processor for signal processing, the distance between a target object to be detected and a vehicle door is obtained through the time difference between a signal transmitted by the ultrasonic radar and a signal received by the ultrasonic radar and the sound wave speed, when the distance reaches the set threshold value (the safety threshold value set by the control system is 5 meters), the controller processes the signal received by the infrared human body sensor, and if the target object is a living being, the control processor controls the vehicle lock control switch to lock the vehicle lock and give out an alarm. If the door is to be opened, the person needs to unlock the door twice continuously manually to open the door. Fig. 2 is an electrical schematic diagram of a passenger vehicle door opening monitoring system according to an embodiment of the invention.
The millimeter wave radar is adopted to cooperate with the infrared human body sensor, so that the complex problem of large data image processing can be solved, the data processing load of the system is reduced, the influence of severe weather on mobile biological detection can be reduced, and the efficient detection and the prevention of the door opening to prevent collision accidents can be realized at low cost. The scheme of adopting millimeter wave radar to cooperate with infrared human body sensor detects outside road conditions to open the door in the twinkling of an eye to the car, when probably taking place the collision accident with outside pedestrian or cyclist, restriction open the door or warning open the door. Has certain effect on preventing and reducing traffic accidents caused by sudden door opening.
Controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the vehicle tail at the radar detection frequency; a passenger vehicle may have a special usage scenario: the driver stops the car at the roadside and the driver/driver stops the car at the roadside, and then gets off the car, and the passengers are left in the car, at the moment, the passengers possibly get off the car at any time, the millimeter wave radar module is generally controlled to continuously monitor, but the operation is unreasonable, the factors such as traffic flow of different streets are different, the probability of occurrence of collision between the door and pedestrians and the coming car is also different, and if the millimeter wave radar module is controlled to continuously monitor, the service life of the millimeter wave radar module is possibly reduced, and the power consumption is increased; the embodiment of the invention can solve the problem, introduces a door opening collision probability map, and rapidly determines the door opening collision probability, thereby determining the radar detection frequency corresponding to the door opening collision probability, controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the vehicle tail by the radar detection frequency, and greatly improving the applicability of the system.
In one embodiment, the control module constructs a door opening collision probability map comprising:
Acquiring a plurality of door opening collision events from a big data platform; the big data platform is a big data information platform; the door opening collision event is a door opening and killing event of news report and shared by drivers/masses;
acquiring a plurality of occurrence positions of each door opening collision event;
calling a preset urban traffic map;
Determining a plurality of first roadside parking positions corresponding to each incident position from the urban traffic map;
Giving a first target probability preset for each first roadside parking position; the first target probability may be, for example: 70% of the total weight of the steel sheet; the first road side parking position historically has an over-door collision event, and the first target probability is directly given;
determining a plurality of second roadside parking locations other than the first roadside parking location from the urban traffic map;
Traversing the second roadside parking position in sequence;
Determining whether the first roadside parking location exists on the traversed street of the second roadside parking location from the urban traffic map;
When present, assigning the first target probability to the traversed second roadside parking location; the first roadside parking position exists on the same street as the second roadside parking position, and the first target probability is directly given to the second roadside parking position;
When the first road side parking position and the second road side parking position are not found, respectively acquiring first position environment information of the traversed second road side parking position and second position environment information of the traversed second road side parking position from the urban traffic map; the first location context information includes: the street daily average traffic flow, the lane width, the number of residents nearby the street and the like of the street where the second roadside parking position is located; the second location context information includes: the first road side parking position is located on the street, such as the average daily traffic flow, the lane width, the number of residents nearby the street and the like;
Calculating the maximum similarity between the first position environment information and the second position environment information; the similarity calculation is in the prior art category and will not be described in detail;
Determining a second target probability corresponding to the maximum similarity from a preset probability library; the probability library has second target probabilities corresponding to different similarities, and the greater the similarity is, the greater the probability of a door opening collision event representing the first road side parking position sent at the second road side parking position is, the greater the corresponding second target probability is;
assigning the second target probability to the traversed second roadside parking location;
And taking the urban traffic map endowed with the first target probability of the first roadside parking position and the second target probability of the second roadside parking position as a door opening collision probability map.
When the door opening collision probability map is constructed, the probability that the vehicle door is opened by parking at each roadside parking position in the city and the collision between the vehicle door and pedestrians, vehicles and the like is reasonably determined, so that the applicability of the system is further improved, and meanwhile, the system is more intelligent. In addition, the door opening collision probability map is built on line, related hardware equipment is not required to be arranged in the passenger vehicle, and convenience is improved.
In one embodiment, the control module obtains a plurality of door opening crash events from a big data platform, including:
Acquiring a guarantee value of each event element of the door opening collision event of the big data platform for trusted guarantee; the event elements include: time of occurrence, place of occurrence, type of occurrence, etc. of the door opening collision event; when a big data platform provides a door opening collision event, each event element is subjected to trusted guarantee, a guarantee value is set, and the higher the guarantee value is, the higher the guarantee degree is;
And when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, acquiring the door-opening collision event. The vouching threshold may be, for example: 75; when the guarantee value is larger than or equal to the guarantee threshold, the guarantee degree of the big data platform for carrying out the credible guarantee on the event elements is larger, and the corresponding event elements are credible; and when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, the door-opening collision event is completely credible and is acquired.
In the application, the event quality of the door opening collision event directly determines the construction quality of the door opening collision probability map, and if the event quality of the door opening collision event is lower, the determination of the first target probability and the second target probability is influenced, so that the determination error is caused, and the accuracy of the door opening collision probability map for determining the collision probability is seriously reduced; secondly, big data technology is becoming popular, but the quality of data provided by big data technology is uneven, and a solution is needed. According to the embodiment of the application, the guarantee value of each event element of the large data platform opposite-door collision event is obtained, and when the guarantee value of each event element of the large data platform opposite-door collision event is larger than or equal to the guarantee threshold, the door-door collision event is obtained, so that the quality and accuracy of the door-door collision event are improved, and the applicability of the large data technology is improved.
In one embodiment, the control module obtains a plurality of door opening collision events from the big data platform, and further comprises:
When at least one guarantee value of the credible guarantee of each event element of the door opening collision event is smaller than a guarantee threshold value, acquiring a generation scene and a generation source of the door opening collision event; when at least one guarantee value of the trusted guarantee of each event element of the door-opening collision event is smaller than a guarantee threshold value, the door-opening collision event is indicated to be possibly unreliable; the generation scenario may be: the vehicle friends exchange forum, news platform, etc., and correspondingly, the generation sources can be: owner users, news reporters, etc.;
Acquiring a generation type of a door opening collision event generated by a generation source in a generation scene; the generation types are divided into active generation and passive generation, wherein the active generation is such as an event that a vehicle owner user shares the position of the city where the vehicle owner user is about to open a door and encounters a sudden coming vehicle at the rear, and the passive generation is such as an event that a vehicle manufacturer obtains a driver monitored by a vehicle machine to open a door and encounters a coming vehicle at the rear;
When the generation type of the door opening collision event generated by the generation source in the generation scene is active generation, traversing each event element in the door opening collision event in sequence;
Each time of traversing, determining a scene association relation and an element extraction strategy corresponding to the element type of the traversed event element from a scene association relation library; the element extraction rule includes: extracting execution rules and execution priorities corresponding to the groups one by one; the element types include: time, place, type, etc.; when the door opening collision event is not credible, the event element of the door opening collision event needs to be replaced; introducing scene association relations and element extraction strategies corresponding to different element types, and extracting the replacement event elements of the replacement event elements from other scenes with the scene association relations between the generated scenes based on the element extraction strategies, wherein the replacement event elements comprise: the element type is an event position, the scene association relationship is a scene which is generated after the scene is generated and is shared by the scene which is used as a generation source (after a car owner user shares an event of sudden coming in the rear of the car owner user when the car owner is about to open a car door at which position of a city, the event is negotiated in a later sharing post), and the element extraction strategy comprises a plurality of groups of extraction execution rules and execution priorities which are in one-to-one correspondence, for example: the extraction execution rule is an occurrence position issued by an extraction source, and the corresponding execution priority is 3, for example: the extraction execution rule is the incident position of the comment of the extraction commentator, and the corresponding execution priority is 2;
Sequentially executing corresponding extraction execution rules in other scenes with scene association relations with the generated scenes according to the execution priority from large to small;
When the replacement event element is extracted, stopping executing the extraction execution rule, and replacing the traversed event element in the door opening collision event with the replacement event element; when the replacement event element is extracted, execution of the extraction execution rule is stopped, for example: after the fact that the owner user shares the incident position of the incident of the sudden coming vehicle behind the owner user at the position of the city about to come into the vehicle door in the vehicle friend forum is extracted, stopping executing the extraction execution rule;
After each event element in the traversing door-opening collision event is finished, acquiring a door-opening collision event in which the event element is replaced by a replacement event element;
when the generation type of the door opening collision event generated by the generation source in the generation scene is passive generation, acquiring multi-mode information which is newly generated by the generation source in the generation scene and related to the door opening collision event; the multimodal information includes: generating a number of door opening collision events historically provided by the source, generating authentication information of the source, and the like;
constructing an information description vector of the multi-mode information;
Determining a quasi-acquired value corresponding to the information description vector from a quasi-acquired value library; the quasi-acquired value library has quasi-acquired values corresponding to different information description vectors, the higher the credibility of the multi-mode information representation generation source is, the larger the quasi-acquired value corresponding to the constructed information description vector is, for example: the more the number of door opening collision events provided by the source historically and the more comprehensive the authentication information of the source is generated, the higher the credibility of the source is, and the larger the quasi-acquisition value corresponding to the information description vector is;
And acquiring a door opening collision event when the quasi-acquisition value is greater than or equal to the quasi-acquisition value threshold. The quasi-acquisition value threshold may be, for example: 80; and acquiring the door opening collision event when the quasi-acquisition value is greater than or equal to the quasi-acquisition value threshold value.
When a plurality of door opening collision events are acquired from a big data platform, firstly determining the guarantee condition of the door opening collision event of the big data platform, determining whether the door opening collision event needs to be subjected to event element replacement/source generation trusted verification based on the guarantee condition, reducing the resource occupation of a system, improving the event acquisition efficiency, and secondly, when the door opening collision event needs to be subjected to event element replacement/source generation trusted verification, respectively carrying out event element replacement/source generation trusted verification according to different generation types of the door opening collision event generated by the source generation scene, thereby improving the accuracy of event acquisition; and secondly, introducing a scene association relation corresponding to the element type and an element extraction strategy, so that the efficiency of determining the element of the replacement event is improved.
In one embodiment, the control module controlling the timing of the millimeter wave radar module to detect the approach distance of the approaching object behind the vehicle tail includes:
After the passenger vehicle parks, the passenger prepares to get off; at this time, the vehicle speed sensor detects that the vehicle speed of the passenger vehicle is 0;
the passengers prepare to get on the bus; at this time, the lock state identifier detects that the lock is in the unlocked state.
This embodiment corresponds to the two states of door opening described above.
In one embodiment, the control module is further configured to control the opening of the door when the occupant opens the door twice in succession.
When the occupant opens the door twice in succession, the door may be opened for it.
The embodiment of the invention provides a method for monitoring the opening of a door of a passenger vehicle, which comprises the following steps:
controlling a millimeter wave radar module arranged at the tail of the passenger vehicle to detect the approaching distance of an approaching object behind the tail;
when the approaching distance is smaller than or equal to a preset distance threshold value, an infrared human body sensor module arranged at a rearview mirror of the passenger vehicle detects whether the approaching object is a living organism or not;
When the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened;
the method further comprises the steps of:
constructing a door opening collision probability map;
when the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; the target state includes: the speed of the vehicle is zero and the passengers do not get off the vehicle;
determining door opening collision probability corresponding to the vehicle position from a collision probability map;
determining radar detection frequency corresponding to the door opening collision probability from a preset radar detection frequency library;
starting the millimeter wave radar module;
and controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the tail at the radar detection frequency.
The constructing a door opening collision probability map includes:
acquiring a plurality of door opening collision events from a big data platform;
acquiring a plurality of occurrence positions of each door opening collision event;
calling a preset urban traffic map;
Determining a plurality of first roadside parking positions corresponding to each incident position from the urban traffic map;
giving a first target probability preset for each first roadside parking position;
determining a plurality of second roadside parking locations other than the first roadside parking location from the urban traffic map;
Traversing the second roadside parking position in sequence;
Determining whether the first roadside parking location exists on the traversed street of the second roadside parking location from the urban traffic map;
When present, assigning the first target probability to the traversed second roadside parking location; when the first road side parking position and the second road side parking position are not found, respectively acquiring first position environment information of the traversed second road side parking position and second position environment information of the traversed second road side parking position from the urban traffic map;
Calculating the maximum similarity between the first position environment information and the second position environment information;
Determining a second target probability corresponding to the maximum similarity from a preset probability library;
assigning the second target probability to the traversed second roadside parking location;
And taking the urban traffic map endowed with the first target probability of the first roadside parking position and the second target probability of the second roadside parking position as a door opening collision probability map.
The acquiring a plurality of door opening collision events from the big data platform comprises the following steps:
acquiring a guarantee value of each event element of the door opening collision event of the big data platform for trusted guarantee;
and when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, acquiring the door-opening collision event.
Acquiring a plurality of door opening collision events from the big data platform, and further comprising:
When at least one guarantee value of the credible guarantee of each event element of the door opening collision event is smaller than a guarantee threshold value, acquiring a generation scene and a generation source of the door opening collision event;
acquiring a generation type of a door opening collision event generated by a generation source in a generation scene;
When the generation type of the door opening collision event generated by the generation source in the generation scene is active generation, traversing each event element in the door opening collision event in sequence;
each time of traversing, determining a scene association relation and an element extraction strategy corresponding to the element type of the traversed event element from a scene association relation library; the element extraction rule includes: extracting execution rules and execution priorities corresponding to the groups one by one;
Sequentially executing corresponding extraction execution rules in other scenes with scene association relations with the generated scenes according to the execution priority from large to small;
When the replacement event element is extracted, stopping executing the extraction execution rule, and replacing the traversed event element in the door opening collision event with the replacement event element;
After each event element in the traversing door-opening collision event is finished, acquiring a door-opening collision event in which the event element is replaced by a replacement event element;
when the generation type of the door opening collision event generated by the generation source in the generation scene is passive generation, acquiring multi-mode information which is newly generated by the generation source in the generation scene and related to the door opening collision event;
constructing an information description vector of the multi-mode information;
Determining a quasi-acquired value corresponding to the information description vector from a quasi-acquired value library;
And acquiring a door opening collision event when the quasi-acquisition value is greater than or equal to the quasi-acquisition value threshold.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A passenger vehicle door opening monitoring system, comprising:
At least one millimeter wave radar module arranged at the tail of the passenger vehicle;
at least one infrared human body sensor module arranged at the rearview mirror of the passenger vehicle;
the control module is connected with the millimeter wave radar module and the infrared human body sensor module and is used for comprising:
Controlling the millimeter wave radar module to detect the approaching distance of an approaching object behind the vehicle tail;
when the approaching distance is smaller than or equal to a preset distance threshold value, controlling the infrared human body sensor module to detect whether the approaching object is a living organism or not;
When the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened;
the control module is further configured to include:
constructing a door opening collision probability map;
when the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; the target state includes: the speed of the vehicle is zero and the passengers do not get off the vehicle;
determining door opening collision probability corresponding to the vehicle position from a collision probability map;
determining radar detection frequency corresponding to the door opening collision probability from a preset radar detection frequency library;
and controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the tail at the radar detection frequency.
2. The passenger vehicle door opening monitoring system of claim 1, wherein the control module constructs a door opening collision probability map comprising:
acquiring a plurality of door opening collision events from a big data platform;
acquiring a plurality of occurrence positions of each door opening collision event;
calling a preset urban traffic map;
Determining a plurality of first roadside parking positions corresponding to each incident position from the urban traffic map;
giving a first target probability preset for each first roadside parking position;
determining a plurality of second roadside parking locations other than the first roadside parking location from the urban traffic map;
Traversing the second roadside parking position in sequence;
Determining whether the first roadside parking location exists on the traversed street of the second roadside parking location from the urban traffic map;
When present, assigning the first target probability to the traversed second roadside parking location; when the first road side parking position and the second road side parking position are not found, respectively acquiring first position environment information of the traversed second road side parking position and second position environment information of the traversed second road side parking position from the urban traffic map;
Calculating the maximum similarity between the first position environment information and the second position environment information;
Determining a second target probability corresponding to the maximum similarity from a preset probability library;
assigning the second target probability to the traversed second roadside parking location;
And taking the urban traffic map endowed with the first target probability of the first roadside parking position and the second target probability of the second roadside parking position as a door opening collision probability map.
3. The passenger vehicle door opening monitoring system of claim 2, wherein the control module obtains a plurality of door opening crash events from a big data platform, comprising:
acquiring a guarantee value of each event element of the door opening collision event of the big data platform for trusted guarantee;
and when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, acquiring the door-opening collision event.
4. The passenger vehicle door opening monitoring system of claim 3, wherein the control module obtains a plurality of door opening crash events from a big data platform, further comprising:
When at least one guarantee value of the credible guarantee of each event element of the door opening collision event is smaller than a guarantee threshold value, acquiring a generation scene and a generation source of the door opening collision event;
acquiring a generation type of a door opening collision event generated by a generation source in a generation scene;
When the generation type of the door opening collision event generated by the generation source in the generation scene is active generation, traversing each event element in the door opening collision event in sequence;
each time of traversing, determining a scene association relation and an element extraction strategy corresponding to the element type of the traversed event element from a scene association relation library; the element extraction rule includes: extracting execution rules and execution priorities corresponding to the groups one by one;
Sequentially executing corresponding extraction execution rules in other scenes with scene association relations with the generated scenes according to the execution priority from large to small;
When the replacement event element is extracted, stopping executing the extraction execution rule, and replacing the traversed event element in the door opening collision event with the replacement event element;
After each event element in the traversing door-opening collision event is finished, acquiring a door-opening collision event in which the event element is replaced by a replacement event element;
when the generation type of the door opening collision event generated by the generation source in the generation scene is passive generation, acquiring multi-mode information which is newly generated by the generation source in the generation scene and related to the door opening collision event;
constructing an information description vector of the multi-mode information;
Determining a quasi-acquired value corresponding to the information description vector from a quasi-acquired value library;
And acquiring a door opening collision event when the quasi-acquisition value is greater than or equal to the quasi-acquisition value threshold.
5. The passenger vehicle door opening monitoring system of claim 1, wherein the control module controlling the timing of the millimeter wave radar module to detect the approach distance of the approaching object behind the vehicle tail comprises:
After the passenger vehicle parks, the passenger prepares to get off; at this time, the vehicle speed sensor detects that the vehicle speed of the passenger vehicle is 0;
the passengers prepare to get on the bus; at this time, the lock state identifier detects that the lock is in the unlocked state.
6. A passenger vehicle door opening monitoring system as set forth in claim 1, wherein the distance threshold comprises: 5 meters.
7. A passenger vehicle door opening monitoring system as set forth in claim 1 wherein the control module is further configured to control door opening when the passenger opens the door twice in succession.
8. A passenger vehicle door opening monitoring method, comprising:
controlling a millimeter wave radar module arranged at the tail of the passenger vehicle to detect the approaching distance of an approaching object behind the tail;
when the approaching distance is smaller than or equal to a preset distance threshold value, an infrared human body sensor module arranged at a rearview mirror of the passenger vehicle detects whether the approaching object is a living organism or not;
When the vehicle door is biological, controlling the door of the passenger vehicle to be forbidden to be opened;
the method further comprises the steps of:
constructing a door opening collision probability map;
when the passenger vehicle is kept in a target state for a period longer than a preset period, acquiring the vehicle position of the passenger vehicle; the target state includes: the speed of the vehicle is zero and the passengers do not get off the vehicle;
determining door opening collision probability corresponding to the vehicle position from a collision probability map;
determining radar detection frequency corresponding to the door opening collision probability from a preset radar detection frequency library;
starting the millimeter wave radar module;
and controlling the millimeter wave radar module to detect the approaching distance of the approaching object behind the tail at the radar detection frequency.
9. The passenger vehicle door opening monitoring method according to claim 8, wherein the constructing the door opening collision probability map includes:
acquiring a plurality of door opening collision events from a big data platform;
acquiring a plurality of occurrence positions of each door opening collision event;
calling a preset urban traffic map;
Determining a plurality of first roadside parking positions corresponding to each incident position from the urban traffic map;
giving a first target probability preset for each first roadside parking position;
determining a plurality of second roadside parking locations other than the first roadside parking location from the urban traffic map;
Traversing the second roadside parking position in sequence;
Determining whether the first roadside parking location exists on the traversed street of the second roadside parking location from the urban traffic map;
When present, assigning the first target probability to the traversed second roadside parking location; when the first road side parking position and the second road side parking position are not found, respectively acquiring first position environment information of the traversed second road side parking position and second position environment information of the traversed second road side parking position from the urban traffic map;
Calculating the maximum similarity between the first position environment information and the second position environment information;
Determining a second target probability corresponding to the maximum similarity from a preset probability library;
assigning the second target probability to the traversed second roadside parking location;
And taking the urban traffic map endowed with the first target probability of the first roadside parking position and the second target probability of the second roadside parking position as a door opening collision probability map.
10. The passenger vehicle door opening monitoring method of claim 9, wherein the acquiring a plurality of door opening collision events from the big data platform comprises:
acquiring a guarantee value of each event element of the door opening collision event of the big data platform for trusted guarantee;
and when the guarantee value of the credible guarantee of each event element of the door-opening collision event by the big data platform is larger than or equal to the guarantee threshold value, acquiring the door-opening collision event.
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