Disclosure of Invention
The invention mainly aims to provide a blind area early warning method, device, equipment and storage medium, and aims to solve the technical problem that the blind area early warning in the prior art is inaccurate.
In order to achieve the above purpose, the present invention provides a dead zone early warning method, which comprises the following steps:
acquiring current steering wheel rotation angle data and a current risk threshold value;
inputting the current steering wheel angle data into a preset steering model to obtain a current risk value;
and when the current risk value is greater than or equal to the current risk threshold value, carrying out blind zone early warning.
Optionally, the inputting the current steering wheel angle data into a preset steering model to obtain a current risk value includes:
Inputting the current steering wheel angle data to a preset steering model to obtain the current total number of lane changing and the current total number of lane changing without lighting;
and calculating a current risk value according to the current lane change total times and the current non-lighting lane change total times.
Optionally, when the current risk value is greater than or equal to the current risk threshold, performing blind zone early warning includes:
when the current risk value is greater than or equal to the current risk threshold value, acquiring a first alarm time when the current vehicle is changed;
calculating collision time according to the current risk value and the first alarm time;
And carrying out blind area early warning according to the collision time.
Optionally, the performing the dead zone early warning according to the collision time includes:
Detecting whether a vehicle is in line or not;
and when the vehicle is in line pressing, carrying out primary early warning according to the collision time.
Optionally, after the first-stage early warning is performed according to the collision time when the vehicle is in the line pressing state, the method further includes:
detecting the state information of a steering lamp of a vehicle;
When the steering lamp state information indicates that the steering lamp is not turned on, comparing the first alarm time with the collision time;
And when the first alarm time is smaller than the collision time, upgrading the first-stage early warning to the second-stage early warning, and carrying out the second-stage early warning.
Optionally, before the current steering wheel angle data is input into the preset steering model to obtain the current risk value, the method further includes:
Collecting historical lane change occurrence time data, historical lane change total frequency data and historical non-lighting lane change total frequency data of a user;
recording historical steering wheel steering data of a user during lane changing;
establishing corresponding relations among steering wheel steering, total lane changing times and total lane changing times under different lane changing occurrence times according to the historical lane changing occurrence time data, the historical lane changing total times data, the historical non-lighting lane changing total times data and the historical steering wheel steering data;
And establishing a preset steering model according to the corresponding relation.
Optionally, acquiring the current risk threshold includes:
acquiring the type of the road where the vehicle is currently located;
And matching the corresponding risk threshold according to the road type to obtain the current risk threshold.
In addition, in order to achieve the above object, the present invention further provides a blind area early warning device, including:
the acquisition module is used for acquiring current steering wheel rotation angle data and a current risk threshold value;
the input module is used for inputting the current steering wheel angle data into a preset steering model to obtain a current risk value;
and the early warning module is used for carrying out blind zone early warning when the current risk value is greater than or equal to the current risk threshold value.
In addition, in order to achieve the aim, the invention also provides blind area early warning equipment, which comprises a memory, a processor and a blind area early warning program which is stored in the memory and can run on the processor, wherein the blind area early warning program is configured to achieve the steps of the blind area early warning method.
In addition, in order to achieve the above object, the present invention also proposes a storage medium on which a dead zone early-warning program is stored, which when executed by a processor, implements the steps of the dead zone early-warning method as described above.
According to the invention, the current steering wheel angle data and the current risk threshold value are obtained, the current steering wheel angle data is input into the preset steering model to obtain the current risk value, and when the current risk value is greater than or equal to the current risk threshold value, the blind zone early warning is carried out, so that the accurate current risk value can be obtained quickly according to the preset steering model, the blind zone early warning is accurately carried out according to the current risk value, and the early warning accuracy and applicability are improved.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a dead zone early warning device of a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the blind spot warning apparatus may include a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the configuration shown in FIG. 1 is not limiting of the blind spot warning apparatus and may include more or fewer components than shown, or certain components may be combined, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a blind spot warning program may be included in the memory 1005 as one type of storage medium.
In the blind area early warning device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server, the user interface 1003 is mainly used for data interaction with a user, and the processor 1001 and the memory 1005 in the blind area early warning device can be arranged in the blind area early warning device, and the blind area early warning device calls a blind area early warning program stored in the memory 1005 through the processor 1001 and executes the blind area early warning method provided by the embodiment of the invention.
The embodiment of the invention provides a blind area early warning method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the blind area early warning method.
In this embodiment, the blind area early warning method includes the following steps:
And S10, acquiring current steering wheel rotation angle data and a current risk threshold value.
It should be noted that, the execution body of the embodiment is a blind area early warning device, and may be other devices that can implement the same or similar functions, which is not limited in this embodiment, and the blind area early warning device is described as an example in this embodiment.
In specific implementation, the common logic of blind area monitoring and parallel line assistance is that a vehicle exists in a blind area or a vehicle which is in rapid approaching at the rear side of the blind area, and primary alarm is carried out. And the driver changes the lane when giving a primary alarm, and then gives a secondary alarm. It is generally determined that the driver's lane change intention is based on a state change of a turn signal or a turn switch. However, when some drivers change lanes, the blind area monitoring alarm is insufficient because the steering lamp is not turned on. The application provides a blind area early warning method for solving the problems, which firstly learns the habit of turning light when a user changes lanes, and upgrades the alarm level of blind area monitoring alarm when judging that the user changes lanes and does not turn the steering light and the blind area monitoring function alarms, so that the warning function of the function is more effective.
It will be appreciated that steering wheel angle is typically measured to understand the degree of deflection of the front wheels of the vehicle during cornering and to determine whether the vehicle requires tire adjustment or positioning. Current steering wheel angle data may be measured by mounting an angle sensor on the steering wheel. The current steering wheel angle data can also be detected by four-wheel positioning equipment, in particular to the position and angle of each wheel can be accurately measured by installing a sensor and a camera on the wheel.
The current risk threshold can be set according to the road types, different road types are matched with corresponding risk thresholds, and the relationship between the road types and the risk thresholds can be established in advance, so that the current risk threshold is obtained.
Further, the step of obtaining the current risk threshold value comprises the steps of obtaining the road type where the vehicle is currently located, and obtaining the current risk threshold value according to the corresponding risk threshold value matched by the road type.
In a specific implementation, the road type where the vehicle is located can be recorded through map positioning, such as a rural small road, an urban road, a high-speed overhead road and the like, or whether the current road has lane lines, the number of lanes and the like can be recorded through a front-view camera to distinguish the road types.
In a specific implementation, a relationship between a road type and a risk threshold value can be established in advance, for example, a road type sample is collected in advance, and different risk threshold values are set according to different road type samples, so that a mapping relationship between the road type and the risk threshold value is established through the road type sample and different risk threshold values, and after the current road type is obtained, the current risk threshold value can be obtained according to the mapping relationship between the road type and the risk threshold value and the current road type.
It should be appreciated that the corresponding risk threshold S1 may be matched according to road type, resulting in a current risk threshold S1.
And S20, inputting the current steering wheel angle data into a preset steering model to obtain a current risk value.
It should be noted that, the preset steering model is a model established by user lane changing data collected in advance and steering wheel angles during lane changing, the preset steering model can output corresponding steering wheel angles according to the input lane changing data, and the preset steering model can also output corresponding lane changing data according to the input steering wheel angles.
In specific implementation, the corresponding lane change data can be obtained by inputting the current steering wheel angle data into a preset steering model, and the current risk value is calculated according to the lane change data. The current risk value characterizes the risk at the current lane change.
And step S30, performing blind zone early warning when the current risk value is greater than or equal to the current risk threshold value.
It should be noted that, whether early warning needs to be performed or not can be determined by comparing the current risk value with the current risk threshold, for example, if the current risk value is smaller than the current risk threshold, the current lane change is free of risk and does not perform early warning, and if the current risk value is greater than or equal to the current risk threshold, the current lane change is at risk, and then blind zone early warning needs to be performed.
According to the embodiment, the current steering wheel angle data and the current risk threshold value are obtained, the current steering wheel angle data are input into the preset steering model to obtain the current risk value, and when the current risk value is greater than or equal to the current risk threshold value, blind zone early warning is conducted, and an accurate current risk value can be obtained quickly according to the preset steering model, so that blind zone early warning is conducted accurately according to the current risk value, and early warning accuracy and applicability are improved.
Referring to fig. 3, fig. 3 is a flow chart of a second embodiment of the blind zone early warning method according to the present invention.
Based on the above first embodiment, the step S20 of the blind area early warning method of this embodiment includes:
Step 201, inputting the current steering wheel angle data to a preset steering model to obtain the current total lane change times and the current total lane change times without lighting.
It should be noted that, the current steering wheel angle data is input to the preset steering model, so as to obtain the current lane change data corresponding to the current steering wheel angle data.
In a specific implementation, the lane change data includes the current lane change total times m1 of the user and the current non-lighting lane change total times n1 of the user.
In a specific implementation, a variable pass threshold S2 may be set, and the current total number of passes m1 is compared with the variable pass threshold S2, if the current total number of passes m1 is smaller than the variable pass threshold S2, the variable pass is insufficient to cause danger, and early warning is not needed, statistics is continued until the current total number of passes m1 is greater than or equal to the variable pass threshold S2.
And S202, calculating a current risk value according to the current lane change total times and the current non-lighting lane change total times.
In a specific implementation, when the current total number of lane changes m1 is greater than or equal to the lane change threshold S2, the current risk value p1 may be calculated, where the current risk value p1=the current total number of lane changes/the current total number of no-light lane changes=m1/n1×100%.
After the current risk value p1 is calculated, the current risk value p1 can be compared with the current risk threshold value S1, so as to determine whether blind zone early warning is needed.
In a specific implementation, before the blind area early warning, in order to improve the efficiency of acquiring the lane change data, a preset steering model may be further established in advance, and before step S20, the method further includes:
Collecting historical lane change occurrence time data, historical lane change total frequency data and historical non-lighting lane change total frequency data of a user;
recording historical steering wheel steering data of a user during lane changing;
establishing corresponding relations among steering wheel steering, total lane changing times and total lane changing times under different lane changing occurrence times according to the historical lane changing occurrence time data, the historical lane changing total times data, the historical non-lighting lane changing total times data and the historical steering wheel steering data;
And establishing a preset steering model according to the corresponding relation.
It should be understood that the historical lane change occurrence time data may be counted when the user performs lane change, the historical lane change total number data and the historical non-lighting lane change total number data may be used to determine whether the lane change occurs in the vehicle through the camera, and may be used to determine whether the lane change of the user is a user operation through an operation state of an ALC (Automatic Level Control, automatic horizontal control) system of the vehicle. ALC is a vehicle equipped function, and is mainly used for automatically adjusting the suspension system of the vehicle to maintain the horizontal state of the vehicle body, and provide better driving comfort and stability. This technique can be used to adjust the stiffness or height of the suspension system to accommodate different road conditions and driving conditions. Sometimes also referred to as an adaptive suspension system.
If the automatic driving function operates the lane change, the lane change number is not counted, if the automatic driving function operates the lane change, the time of the lane change is recorded, the total number of lane changes m1 of the user is increased by 1, and if the user does not turn on a turn signal lane change, the total number of lane changes n1 of the user is increased by 1, so that the historical lane change total number data and the historical non-turn signal total number data are counted.
In a specific implementation, the historical steering wheel steering data of a user in lane change is recorded, and the time of the vehicle in line pressing is recorded.
After the historical steering wheel steering data is obtained, a steering wheel angle curve can be drawn, the steering wheel angle curve is drawn according to the data such as steering wheel angle, vehicle starting steering time, vehicle line pressing time and the like, as shown in fig. 4, fig. 4 is a schematic diagram of the steering wheel angle curve, the abscissa is time, the ordinate is steering wheel angle, the figure comprises the starting steering time, the vehicle line pressing time, the corresponding relation among steering wheel steering, total lane changing times and total number of times of turning without lamps under different lane changing occurrence time can be obtained through the drawn steering wheel angle curve, and therefore a preset steering model is established according to the corresponding relation, and the time t1 from starting steering to vehicle line pressing under different conditions of a driver is recorded. And cleaning recorded data before a certain time period, such as data before 3 months, so as to obtain lane change data of different lane classifications and steering wheel angles, and thus establishing a preset steering model.
In a specific implementation, the preset steering model may be multiple models, multiple steering models may be built according to the habit of the driver, and the time t1 from the start of steering to the line pressing of the vehicle for the user under different steering models is calculated and counted.
Through learning the steering habit of the user, the user steering model is customized, and when the lane change possibly has risks, the alarm level is improved, and a better warning effect is achieved.
According to the method, the device and the system, the current steering wheel angle data are input into the preset steering model to obtain the current lane change total times and the current lane change total times without lighting, the current risk value is calculated according to the current lane change total times and the current lane change total times without lighting, the current lane change total times and the current lane change total times without lighting corresponding to the current steering wheel angle data can be obtained according to the preset steering model, and the accuracy of blind zone early warning is improved.
Referring to fig. 5, fig. 5 is a flowchart illustrating a third embodiment of the blind area early warning method according to the present invention.
Based on the above first embodiment, the step S30 of the blind area early warning method of this embodiment includes:
Step 301, when the current risk value is greater than or equal to the current risk threshold value, acquiring a first alarm time when the current vehicle is changed.
When the current risk value is greater than or equal to the current risk threshold value, the system generates collision time data t2, wherein the collision time data is calculated from the current risk value and the first alarm time when the normal LCA (LANE CHANGE ASSIST, lane change auxiliary system) alarms. A lane change assist system is a vehicle safety assist technique that aims to assist a driver in performing an operation more safely when a lane is changed. Systems of different vehicle manufacturers may vary, but typically include the functionality that a lane change assist system is typically equipped with a blind zone monitoring function, with sensors monitoring blind zones on both sides of the vehicle, and when other vehicles enter the blind zone, the system provides a warning, typically by audible or visual cues. Lane keeping assistance some systems also include a lane keeping assistance function that can detect whether the vehicle is traveling in a lane and provide a warning or take corrective action, such as a slight direction adjustment, when signs of departure from the lane are found. Active lane change assistance some advanced systems have active lane change assistance capability that enables automatic lane changes. The driver only needs to turn on the steering lamp, and the system can automatically detect the safe time and conduct lane change. Visual or audible warning-the system typically passes the warning on the dashboard when a potential hazard is detected or action is required by the driver.
In an implementation, the first alarm time t3 when the current vehicle is changed normally can be obtained. When the vehicle is changed normally, if an obstacle exists around the vehicle, the LCA can perform early warning, and early warning time during early warning can be recorded, namely, first warning time t3.
And step S302, calculating collision time according to the current risk value and the first alarm time.
In a specific implementation, the collision time t2 may be calculated according to the present risk value p1 and the first alarm time t 3. Time of collision t 2=t3×p1.
And step S303, carrying out blind area early warning according to the collision time.
It can be understood that the dead zone early warning can be performed through the calculated collision time, for example, early warning display is performed according to the collision time, and the user is prompted to pay attention to avoiding.
The dead zone early warning method comprises the steps of detecting whether a vehicle is in line or not, and carrying out primary early warning according to the collision time when the vehicle is in line.
It should be noted that, whether the vehicle is pressed line can be judged through the camera, and the surrounding environment data of the vehicle is collected through the camera arranged around the vehicle, so that the lane lines around the vehicle are collected, and whether the vehicle is pressed line is determined. If the camera fails or no lane lines and no lane line damage occurs, the moment of the vehicle after the vehicle starts turning t1 is used as the line pressing judgment, and the first-level early warning can be carried out according to the collision time from the start of line pressing of the vehicle to the success of line changing.
In a specific implementation, if the user does not turn the turn signal light during lane change, the pre-warning needs to be updated, and after step S303, the method further includes:
detecting the state information of a steering lamp of a vehicle;
When the steering lamp state information indicates that the steering lamp is not turned on, comparing the first alarm time with the collision time;
And when the first alarm time is smaller than the collision time, upgrading the first-stage early warning to the second-stage early warning, and carrying out the second-stage early warning.
It should be appreciated that the turn signal status information of the vehicle may be detected by sensors, and whether the vehicle turns on the turn signal typically requires the use of sensors, software or hardware devices, or information that relies on the vehicle network and signals. Some common methods are vehicle network signaling, typically using a Control Area Network (CAN) or other vehicle network to communicate information. The turn signal status may be detected by reading a corresponding signal in the vehicle network. A specialized vehicle diagnostic tool or device may be used to obtain this information. Turn signal switch sensor the turn signal switch of the vehicle is controlled by a sensor, and by detecting the switch state it can be determined whether the turn signal is on. This sensor is typically located near the steering wheel or in a position associated with the steering column. Camera and computer vision some advanced driving assistance systems or autopilot techniques use camera and computer vision to detect the environment surrounding the vehicle, including the status of the turn signal lights. By analyzing the images or videos captured by the camera, the light state of the vehicle can be identified. Photoresistor sensor-in some vehicles, the turn signal lamp on state can be detected by the photoresistor sensor whether the vehicle lamp is lighted. Such sensors are typically located near the vehicle dashboard or light fixture. Wireless communication some vehicles use wireless communication to transmit vehicle status information, including turn signal status. This may be accomplished by the vehicle sending a signal to surrounding vehicles or infrastructure, or by internet of vehicles communication between vehicles.
The turn signal status information may include left turn signal status information and right turn signal status information, which may be turn signal on or turn signal not on.
In a specific implementation, when the status information of the turn signal lamp is that the turn signal lamp is not turned on, the first alarm time is compared with the collision time t2, so as to determine whether the early warning upgrading is required.
In the implementation, when the first alarm time is smaller than the collision time, the first early warning is updated to the second early warning, so that the second early warning is performed.
According to the embodiment, when the current risk value is larger than or equal to the current risk threshold value, the first alarm time when the current vehicle is changed is obtained, the collision time is calculated according to the current risk value and the first alarm time, the blind zone early warning is conducted according to the collision time, the collision time is calculated according to the calculated current risk value, and therefore the blind zone early warning can be conducted according to the collision time rapidly.
Referring to fig. 6, fig. 6 is a block diagram illustrating a first embodiment of a blind zone early warning device according to the present invention.
As shown in fig. 6, the blind area early warning device provided by the embodiment of the invention includes:
The acquiring module 10 is configured to acquire current steering wheel angle data and a current risk threshold.
And the input module 20 is used for inputting the current steering wheel angle data into a preset steering model to obtain a current risk value.
And the early warning module 30 is used for carrying out blind zone early warning when the current risk value is greater than or equal to the current risk threshold value.
According to the embodiment, the current steering wheel angle data and the current risk threshold value are obtained, the current steering wheel angle data are input into the preset steering model to obtain the current risk value, and when the current risk value is greater than or equal to the current risk threshold value, blind zone early warning is conducted, and an accurate current risk value can be obtained quickly according to the preset steering model, so that blind zone early warning is conducted accurately according to the current risk value, and early warning accuracy and applicability are improved.
In an embodiment, the input module 20 is further configured to input the current steering wheel angle data to a preset steering model, obtain a current total number of lane changes and a current total number of lane changes without lighting, and calculate a current risk value according to the current total number of lane changes and the current total number of lane changes without lighting.
In an embodiment, the early warning module 30 is further configured to obtain a first warning time when the current risk value is greater than or equal to the current risk threshold, calculate a collision time according to the current risk value and the first warning time, and perform blind zone early warning according to the collision time.
In an embodiment, the early warning module 30 is further configured to detect whether the vehicle is in a line, and perform a first-level early warning according to the collision time when the vehicle is in the line.
In an embodiment, the early warning module 30 is further configured to detect a status information of a turn signal of the vehicle, compare the first warning time with the collision time when the status information of the turn signal is that the turn signal is not turned on, upgrade the first warning to the second warning when the first warning time is less than the collision time, and perform the second warning.
In an embodiment, the input module 20 is further configured to collect historical lane change occurrence time data, historical lane change total times data, and historical non-lighting lane change total times data of the user, record historical steering wheel steering data of the user during lane change, establish a corresponding relationship between steering wheel steering, lane change total times, and non-lighting lane change total times at different lane change occurrence times according to the historical lane change occurrence time data, the historical lane change total times data, the historical non-lighting lane change total times data, and the historical steering wheel steering data, and establish a preset steering model according to the corresponding relationship.
In an embodiment, the obtaining module 10 is further configured to obtain a current road type of the vehicle, and obtain a current risk threshold according to the matching of the road type with a corresponding risk threshold.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium is stored with a dead zone early warning program, and the dead zone early warning program realizes the steps of the dead zone early warning method when being executed by a processor.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details which are not described in detail in the present embodiment can refer to the blind area early warning method provided in any embodiment of the present invention, and are not described herein.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.