CN115447599A - Automatic early warning method, automatic early warning device, automatic early warning equipment and computer readable storage medium for vehicle steering - Google Patents
Automatic early warning method, automatic early warning device, automatic early warning equipment and computer readable storage medium for vehicle steering Download PDFInfo
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Abstract
The invention relates to a vehicle steering automatic early warning method, an automatic early warning device, automatic early warning equipment and a computer readable storage medium. The automatic early warning method for vehicle steering comprises the steps of acquiring surrounding environment data of a vehicle and the speed of the vehicle in real time; s1, predicting steering probability; s2, judging whether steering is performed or not; and S3, triggering steering early warning. The invention provides an automatic early warning method, an automatic early warning device, automatic early warning equipment and a computer readable storage medium for vehicle steering, which can judge whether a vehicle is steered and trigger steering early warning according to the judgment result so as to assist a driver to steer safely.
Description
Technical Field
The invention relates to the technical field of automatic driving of vehicles, in particular to an automatic early warning method, an automatic early warning device, automatic early warning equipment and a computer readable storage medium for vehicle steering.
Background
In the current technical scheme of vehicle steering early warning, the following two situations exist:
(1) The trigger mechanism to the vehicle turn to the early warning highly relies on the vehicle indicator signal, however in the actual driving process, many car owners do not have good habit of turning to the indicator in advance, there are many circumstances that do not turn to the indicator but turn to even, if the car owner does not turn to the indicator in advance, but turns to the indicator midway, then can lead to all ring edge borders early warning to remind the function to trigger late, there is great driving safety risk, and if the car owner does not turn to the indicator, then directly do not trigger the early warning and remind the function, this kind of circumstances is more dangerous. Therefore, the automatic early warning scheme for the vehicle steering cannot depend too much on the turn signal of the vehicle.
(2) The driver needs to manually switch the large screen display to observe the blind area picture around the vehicle body, however, in the actual driving process, especially in the steering process, the driver needs to rotate the steering wheel and observe the road environment, at this moment, more attention is not paid to manually switching the display button, a series of actions of finding the button and pressing the button are easy to disperse the attention of the driver, so how to obtain the vehicle state judged in advance, the automatic steering early warning is realized, and the blind area detection result is displayed in a proper mode, so that the solution for assisting the driver in safely steering becomes a problem to be solved urgently.
Disclosure of Invention
In view of the above problems in the prior art, the present invention provides an automatic early warning method, an automatic early warning device, an automatic early warning apparatus, and a computer-readable storage medium for determining whether a vehicle is turning and triggering early warning of turning according to the determination result, so as to assist a driver in steering safely.
Specifically, the invention provides an automatic early warning method for vehicle steering, which comprises the following steps: acquiring surrounding environment data of the vehicle and the speed of the vehicle in real time;
s1, predicting the steering probability based onRespectively calculating first parameters V for representing average speed difference of adjacent lanes by using vehicle surrounding environment data and vehicle speed _neighbour (t c ) And a second parameter Signal (t) for characterizing the passive steering tendency c ) And a third parameter P for characterizing the active steering tendency _action (t c ) For the first parameter V _neighbour (t c ) Second parameter Signal (t) c ) And a third parameter P _action (t c ) After normalization processing, weights of the first to third parameters are configured, and the steering probability P (t) of the vehicle is calculated c )：
P(t c )＝m 1 ×V _neighbour (t c )+m 2 ×Signal(t c )+m 3 ×P _action (t c )；
Wherein, t c Representing the current time, m1, m2 and m3 are weight coefficients;
s2, judging whether the steering is performed or not, judging whether the steering probability of the self-vehicle reaches a set threshold value or not, and if so, turning to the step S3;
and S3, triggering a steering early warning, judging whether the distance from the vehicle to the intersection meets a preset condition, and if so, triggering the steering early warning.
According to an embodiment of the present invention, if it is determined that the vehicle passes through the current intersection, the steps S1 to S3 are updated until the vehicle passes through the next intersection.
According to one embodiment of the invention, the vehicle surrounding environment data at least comprises a lane where the vehicle is located, a guide mark of the vehicle lane, and vehicle speed of an adjacent lane;
then in the step S1, a first parameter V for representing the average speed difference of the adjacent lanes is calculated based on the vehicle speed of the adjacent lane and the vehicle speed of the vehicle _neighbour (t c ) (ii) a Calculating a second parameter Signal (t) for representing the passive steering trend based on the guide mark and the staying time of the lane after the guide mark is obtained c ) (ii) a Calculating a third parameter P for representing the active steering trend based on the lane change state of the vehicle _action (t c )。
According toIn one embodiment of the invention, the first parameter V _neighbour (t c ) The calculation formula of (2) is as follows:
f(Δv)＝sigmoid(V avg (t)-V HV )；
V avg represents from t 0 To t c Average vehicle speed, V, of vehicles in adjacent lanes at all times HV Indicates the speed of the vehicle, k _i Is a coefficient, t 0 The time when the vehicle enters the lane after passing through the last intersection is shown, and n represents the number of lanes of the adjacent lane.
According to one embodiment of the invention, the second parameter Signal (t) c ) For indicating that the vehicle is at t l After the guide mark k is detected at the moment, at t c The accumulated value of the duration time of the current lane of the self-vehicle staying at the current lane at any moment is calculated according to the following formula:
wherein, t l And a is a parameter, and a is more than or equal to 0 and less than or equal to 1.
According to an embodiment of the invention, the third parameter P _action (t c ) For indicating a slave t 0 To t c The calculation formula of the accumulated numerical value of the behavior action of the self-turning trend at all times is as follows:
according to one embodiment of the invention, the vehicle surrounding environment data is acquired through a vehicle-mounted looking-around detection system.
According to one embodiment of the invention m2 is larger than m1, m3.
According to an embodiment of the present invention, in step S3, the preset condition is a distance from the vehicle to the intersection
If the distance is less than the set distance or the time T from the vehicle to the intersection is less than the set time, triggering a steering early warning; wherein, the first and the second end of the pipe are connected with each other,
，V HV indicating the speed of the vehicle.
According to one embodiment of the invention, the steering early warning is triggered in step S3 to display steering blind area early warning information;
and/or synchronously triggering the automobile data recorder to record all-round image data.
The invention also provides a vehicle steering automatic early warning device, which is used for realizing the vehicle steering automatic early warning method and comprises the following steps:
an acquisition unit configured to acquire the vehicle surrounding environment data and a vehicle speed of a vehicle;
a prediction unit for calculating a first parameter V for representing the average speed difference of adjacent lanes based on the vehicle surrounding environment data and the vehicle speed _neighbour (t c ) And a second parameter Signal (t) for characterizing the passive steering tendency c ) A third parameter P for characterizing the active steering trend _action (t c ) For the first parameter V _neighbour (t c ) Second parameter Signal (t) c ) And a third parameter P _action (t c ) After normalization processing, weights of the first to third parameters are configured, and the steering probability P (t) of the vehicle is calculated c )：
P(t c )＝m 1 ×V _neighbour (t c )+m 2 ×Signal(t c )+m 3 ×P _action (t c )；
Wherein, t c Representing the current time, and m1, m2 and m3 are weight coefficients;
a judging unit for judging whether the steering probability of the vehicle reaches a set threshold value;
and the triggering unit is used for judging whether the distance from the vehicle to the intersection meets a preset condition or not, and if so, triggering the steering early warning.
The invention also provides a vehicle steering automatic early warning device which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of any one of the vehicle steering automatic early warning methods when executing the computer program.
The invention also provides a computer readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the vehicle steering automatic warning method according to any one of the preceding claims.
According to the automatic early warning method, the automatic early warning device, the automatic early warning equipment and the computer readable storage medium for vehicle steering, the steering probability is predicted by acquiring the surrounding environment data of the vehicle and the vehicle speed of the vehicle in real time, whether the vehicle is steered or not is judged based on the steering probability, and the steering early warning is triggered according to the judgment result, so that the safe steering of a driver is assisted.
It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed.
Drawings
The accompanying drawings, which are included to provide a further explanation of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a block flow diagram illustrating a method for automatic early warning of vehicle steering according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an automatic early warning device for vehicle steering according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It should be apparent that the described embodiments are only a few embodiments of the present application, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the application, its application, or uses. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as exemplary only and not as limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
In the description of the present application, it is to be understood that the orientation or positional relationship indicated by the directional terms such as "front, rear, upper, lower, left, right", "lateral, vertical, horizontal" and "top, bottom", etc., are generally based on the orientation or positional relationship shown in the drawings, and are used for convenience of description and simplicity of description only, and in the case of not making a reverse description, these directional terms do not indicate and imply that the device or element being referred to must have a particular orientation or be constructed and operated in a particular orientation, and therefore, should not be considered as limiting the scope of the present application; the terms "inner and outer" refer to the inner and outer relative to the profile of the respective component itself.
It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, so that the scope of the present application is not to be construed as being limited. Further, although the terms used in the present application are selected from publicly known and used terms, some of the terms mentioned in the specification of the present application may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Further, it is required that the present application is understood not only by the actual terms used but also by the meaning of each term lying within.
Fig. 1 is a block flow diagram illustrating a method for automatic early warning of vehicle steering according to an embodiment of the present invention. As shown in the figure, the invention provides an automatic early warning method for vehicle steering, which comprises the following steps: acquiring surrounding environment data of a vehicle and a vehicle speed of the vehicle in real time, wherein the vehicle speed of the vehicle can be generally acquired through an Electronic Control Unit (ECU);
s1, predicting the steering probability, and respectively calculating a first parameter V for representing the average speed difference of adjacent lanes based on the surrounding environment data of the vehicle and the speed of the vehicle _neighbour (t c ) And a second parameter Signal (t) for characterizing the passive steering trend c ) And a third parameter P for characterizing the active steering tendency _action (t c ) For the first parameter V _neighbour (t c ) Second parameter Signal (t) c ) And a third parameter P _action (t c ) After normalization processing, weights of the first to third parameters are configured, and the steering probability P (t) of the vehicle is calculated c )：
P(t c )＝m 1 ×V _neighbour (t c )+m 2 ×Signal(t c )+m 3 ×P _action (t c )；
Wherein, t c Representing the current time, m1, m2 and m3 are weight coefficients; in this step, a first parameter V _neighbour (t c ) And a second parameter Signal (t) c ) And a third parameter P _action (t c ) Respectively, are used for representing different steering possibilities, and the steering probability of the vehicle is calculated through weighting.
S2, judging whether the steering is performed or not, judging whether the steering probability of the self vehicle reaches a set threshold or not, and if so, turning to a step S3;
and S3, triggering a steering early warning, judging whether the distance from the vehicle to the intersection meets a preset condition, and if so, triggering the steering early warning.
According to the automatic early warning method for vehicle steering, the first to third parameters for representing the average speed difference, the passive steering trend and the active steering trend of adjacent lanes are obtained through the surrounding environment data of the vehicle and the speed of the vehicle, the steering probability is calculated in a weighting mode based on the first to third parameters, and the active steering early warning function is automatically achieved based on the judgment of the steering probability. Compared with the prior art, do not rely on the indicator signal and automatic triggering early warning is reminded before the vehicle turns to, reduce the danger that the vehicle turns to the in-process and probably exist, and then promote vehicle safety and turn to.
Preferably, if it is determined that the vehicle enters the next lane through the current intersection, the steps S1 to S3 are updated until the vehicle passes the next intersection. The automatic early warning method for vehicle steering is carried out based on time dimension, a time window is refreshed after a vehicle enters the next intersection, and steering probability prediction based on the next time window is started. Therefore, the time window is continuously updated during the driving process of the vehicle, and the acquired surrounding environment data of the vehicle and the speed of the vehicle are updated and analyzed on each road section, so that the probability value of the vehicle about to turn at the intersection is predicted.
Preferably, the environmental data around the vehicle at least comprises a lane where the vehicle is located, a guide mark of the vehicle lane of the vehicle, and the vehicle speed of the adjacent lane;
in step S1, a first parameter V for representing the average speed difference of the adjacent lanes is calculated based on the vehicle speed of the adjacent lanes and the vehicle speed of the vehicle _neighbour (t c ) (ii) a Calculating a second parameter Signal (t) for representing the passive steering trend based on the guide mark and the stay time of the lane after the guide mark is obtained c ) (ii) a Calculating a third parameter P for representing active steering trend based on lane change state of the vehicle _action (t c )。
Preferably, the first parameter V _neighbour (t c ) The calculation formula of (2) is as follows:
f(Δv)＝sigmoid(V avg (t)-V HV )；
V avg represents from t 0 To t c Average vehicle speed, V, of vehicles in adjacent lanes at all times HV Indicates the speed of the vehicle, k _i Is a coefficient, t 0 The time when the vehicle enters the lane after passing through the last intersection is shown, and n represents the number of lanes of the adjacent lane. First parameter V _neighbour (t c ) Represents from t 0 To t c Average speed V of vehicles in adjacent lanes of the lane where the self-vehicle is located at any moment avg With speed V of the vehicle HV If there are two adjacent lanes, the positive correlation function of the difference in time is accumulated. Coefficient k _i Whether the adjacent lane is a left lane or a right lane. If the adjacent lane is the left lane, the coefficient k _i Can be set to 0.7 if the adjacent lane is the right vehicleTime of flight, coefficient k _i May be set to 0.3.
Preferably, the second parameter Signal (t) c ) For indicating that the vehicle is at t l After the guide mark k is detected at the moment, at t c The accumulated value of the duration of the time that the vehicle stays in the current lane at all times. It is easy to understand that the longer the time that the vehicle stays in the current lane, the more likely the vehicle is to make the driving direction selection according to the guide mark k of the current lane. Second parameter Signal (t) c ) The calculation formula of (c) is:
wherein, t l And a is a parameter, and a is more than or equal to 0 and less than or equal to 1. The value of the parameter a may be set to 0.2.
Preferably, the third parameter P _action (t c ) For indicating a slave t 0 To t c And (4) the accumulated value of the steering trend behavior action of the self-vehicle at all times. The steering tendency behavior action here includes that the vehicle continuously changes lanes towards the edge lanes of the road or continuously changes lanes towards the middle lanes of the road, and the possibility of subsequent steering of the vehicle is indicated by means of cumulative calculation of the steering tendency behavior action. Third parameter P _action (t c ) The calculation formula of (c) is:
Preferably, the vehicle surrounding environment data is acquired through a vehicle-mounted looking-around detection system. The vehicle-mounted all-round looking detection system comprises a plurality of all-round looking cameras arranged on a vehicle, and all-round looking image data around the vehicle can be acquired through the all-round looking cameras. The method comprises the steps of converting an image into an IPM image by carrying out distortion correction and perspective transformation on all-around image data, extracting image characteristics by utilizing a convolutional neural network, and identifying road information, wherein the road information comprises a vehicle travelable area, surrounding traffic participants, lane lines, lane guide marks, traffic lights and the like. Acquiring a lane where the self-vehicle is located based on the road line; acquiring information such as the speed, the vehicle type, the distance and the like of adjacent lanes and adjacent lane vehicles on the basis of lane lines and traffic participants; recognizing guidance categories including turning, turning around, straight going or turning based on the lane guidance marks, wherein the turning includes left turning, right turning, left turning + right turning, confluence and the like, and the turning includes straight going + right turning, straight going + left turning, straight going + turning around and the like; the distance from the vehicle to the intersection is obtained based on the vehicle feasible region and the traffic signal. By way of example and not limitation, part of the vehicle surrounding environment data may also be acquired through a laser radar, a millimeter wave radar or an infrared camera provided on the vehicle. For example, laser radar or millimeter wave radar can be used to obtain the average vehicle speed of the adjacent lanes, and an infrared camera can be used to obtain the lane guide mark.
Preferably, the value of the weighting factor m2 is greater than the values of m1, m3. Giving a second parameter Signal (t) c ) A relatively large weight value is used to represent the second parameter Signal (t) c ) The steering probability calculation will be affected more. More preferably, the sum of the weight coefficients m1, m2 and m3 is 1.
Preferably, the threshold is set to 0.85 in step S2. When the result of the turn probability calculation reaches or exceeds 0.85, the process proceeds to step S3.
Preferably, in step S3, the preset condition is the distance from the vehicle to the intersection
If the distance is less than the set distance or the time T from the vehicle to the intersection is less than the set time, triggering a steering early warning; wherein the content of the first and second substances,
V HV indicating the speed of the vehicle. Setting the distance to be 2m and the time to be 3s, and triggering the steering early warning if the calculation result meets one of the two conditions.
Preferably, the steering warning is triggered in the step S3 to display steering blind area warning information; and/or synchronously triggering the automobile data recorder to record all-round-looking image data. The steering blind area early warning information can be displayed on a screen of the vehicle or projected onto a front windshield of the vehicle.
Fig. 2 is a schematic structural diagram of an automatic early warning device for vehicle steering according to an embodiment of the present invention. As shown in the figure, the invention also provides an automatic early warning device 200 for vehicle steering. The automatic early warning device 200 for vehicle steering is used for realizing the automatic early warning method for vehicle steering, and mainly comprises an acquisition unit 201, a prediction unit 202, a judgment unit 203 and a trigger unit 204.
The acquiring unit 201 is used for acquiring the vehicle surrounding environment data and the vehicle speed;
the prediction unit 202 calculates a first parameter V for representing the average speed difference of adjacent lanes based on the vehicle surrounding environment data and the vehicle speed _neighbour (t c ) And a second parameter Signal (t) for characterizing the passive steering trend c ) A third parameter P for characterizing the active steering tendency _action (t c ) For the first parameter V _neighbour (t c ) Second parameter Signal (t) c ) And a third parameter P _action (t c ) After normalization processing, weights of the first to third parameters are configured, and the steering probability P (t) of the vehicle is calculated c )：
P(t c )＝m 1 ×V _neighbour (t c )+m 2 ×Signal(t c )+m 3 ×P _action (t c )；
Wherein, t c Representing the current time, and m1, m2 and m3 are weight coefficients;
the judging unit 203 is used for judging whether the steering probability of the vehicle reaches a set threshold value;
the triggering unit 204 is configured to determine whether a distance from the vehicle to the intersection meets a preset condition, and if so, trigger a steering early warning.
The invention also provides a vehicle steering automatic early warning device which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of any one of the vehicle steering automatic early warning methods when executing the computer program.
The invention also provides a computer readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of any of the aforementioned vehicle steering automatic warning methods.
The specific implementation manners and technical effects of the automatic vehicle steering early warning device, the automatic vehicle steering early warning apparatus, and the computer-readable storage medium can be referred to the embodiments of the automatic vehicle steering early warning method provided by the present invention, and are not described herein again.
The invention provides an automatic early warning method, an automatic early warning device, automatic early warning equipment and a computer readable storage medium for vehicle steering, which have the following advantages:
(1) The steering early warning mechanism which highly depends on the information of the vehicle steering lamps in the prior art is solved, the surrounding environment data of the vehicle and the speed of the vehicle are obtained in advance, the active steering early warning function is realized, the steering early warning is triggered, and the safe steering is improved.
(2) The operation that the blind area situation is observed by manually switching large-screen display in the prior art is solved, and more autonomous and more automatic vehicle steering blind area early warning is realized.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative logical modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
It will be apparent to those skilled in the art that various modifications and variations can be made to the above-described exemplary embodiments of the present invention without departing from the spirit and scope of the invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.
Claims (12)
1. An automatic early warning method for vehicle steering comprises the following steps: acquiring surrounding environment data of the vehicle and the speed of the vehicle in real time;
s1, predicting the steering probability, and respectively calculating a first parameter V for representing the average speed difference of adjacent lanes based on the surrounding environment data of the vehicle and the speed of the vehicle _neighbour (t c ) And a second parameter Signal (t) for characterizing the passive steering tendency c ) And a third parameter P for characterizing the active steering tendency _action (t c ) For the first parameter V _neighbour (t c ) Second parameter Signal (t) c ) And a third parameter P _action (t c ) After normalization processing, weights of the first to third parameters are configured, and the steering probability P (t) of the vehicle is calculated c )：
P(t c )＝m 1 ×V _neighbour (t c )+m 2 ×Signal(t c )+m 3 ×P _action (t c )；
Wherein, t c Representing the current time, m1, m2 and m3 are weight coefficients;
s2, judging whether the steering is performed or not, judging whether the steering probability of the self vehicle reaches a set threshold or not, and if so, turning to a step S3;
and S3, triggering a steering early warning, judging whether the distance from the vehicle to the intersection meets a preset condition, and if so, triggering the steering early warning.
2. The automatic early warning method for vehicle turning according to claim 1, wherein if the vehicle is judged to pass through the current intersection, the steps S1 to S3 are updated until the vehicle passes through the next intersection.
3. The vehicle steering automatic early warning method according to claim 1, wherein the vehicle surrounding environment data at least comprises a lane where the vehicle is located, a guide mark of the vehicle lane, and vehicle speeds of adjacent lanes;
then in the step S1, a first parameter V for representing the average speed difference of the adjacent lanes is calculated based on the vehicle speed of the adjacent lane and the vehicle speed of the vehicle _neighbour (t c ) (ii) a Calculating a second parameter Signal (t) for representing the passive steering trend based on the guide mark and the staying time of the lane after the guide mark is obtained c ) (ii) a Calculating a third parameter P for representing active steering trend based on lane change state of the vehicle _action (t c )。
4. The automatic early warning method for vehicle steering as claimed in claim 3, characterized in thatCharacterized by a first parameter V _neighbour (t c ) The calculation formula of (c) is:
f(Δv)＝sigmoid(V avg (t)-V HV )；
V avg represents from t 0 To t c Average vehicle speed, V, of adjacent lanes at time HV Indicates the speed of the vehicle, k _i Is a coefficient, t 0 The time when the vehicle enters the lane after passing through the last intersection is shown, and n represents the number of lanes of the adjacent lane.
5. The automatic early warning method for vehicle steering according to claim 3, wherein the second parameter Signal (t) c ) For indicating that the vehicle is at t l After the guide mark k is detected at the moment, at t c The accumulated value of the duration of the current lane in which the vehicle stays at the current lane at any moment is calculated according to the following formula:
wherein, t l And a is a parameter, and a is more than or equal to 0 and less than or equal to 1.
6. The vehicle steering automatic warning method according to claim 3, wherein the third parameter P _action (t c ) For indicating a slave t 0 To t c The calculation formula of the accumulated value of the behavior motion of the self-turning trend at the moment is as follows:
7. The vehicle steering automatic early warning method according to claim 1, wherein the vehicle surrounding environment data is acquired by a vehicle-mounted looking-around detection system.
8. The automatic early warning method for vehicle turning according to claim 1, wherein in step S3, the preset condition is a distance from the vehicle to the intersection
If the distance is less than the set distance or the time T from the vehicle to the intersection is less than the set time, triggering a steering early warning; wherein the content of the first and second substances,
V HV indicating the speed of the vehicle.
9. The vehicle steering automatic early warning method according to claim 1, wherein the steering early warning is triggered in step S3 to display steering blind area early warning information;
and/or synchronously triggering the automobile data recorder to record all-round-looking image data.
10. An automatic early warning device for vehicle steering, which is used for realizing the automatic early warning method for vehicle steering according to claim 1, and is characterized by comprising the following steps:
the acquisition unit is used for acquiring the surrounding environment data of the vehicle and the speed of the vehicle;
a prediction unit for calculating a first parameter V for representing the average speed difference of adjacent lanes based on the vehicle surrounding environment data and the vehicle speed _neighbour (t c ) And a second parameter Signal (t) for characterizing the passive steering tendency c ) A third parameter P for characterizing the active steering tendency _action (t c ) For the first parameter V _neighbour (t c ) And a second parameter Signal (t) c ) And a third parameter P _action (t c ) After normalization processing, weights of the first to third parameters are configured, and the steering probability P (t) of the vehicle is calculated c )：
P(t c )＝m 1 ×V _neighbour (t c )+m 2 ×Signal(t c )+m 3 ×P _action (t c )；
Wherein, t c Representing the current time, m1, m2 and m3 are weight coefficients;
a judgment unit for judging whether the steering probability of the vehicle reaches a set threshold value;
and the triggering unit is used for judging whether the distance from the vehicle to the intersection meets a preset condition or not, and if so, triggering the steering early warning.
11. A vehicle steering automatic early warning apparatus comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor when executing the computer program implements the steps of the vehicle steering automatic early warning method according to any one of claims 1 to 9.
12. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of a method for automatic warning of steering of a vehicle according to any one of claims 1 to 9.
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