CN115223147B - False touch prevention method and device for commercial vehicle anti-collision system and storage medium - Google Patents
False touch prevention method and device for commercial vehicle anti-collision system and storage medium Download PDFInfo
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Abstract
The invention relates to the field of false touch prevention of an anti-collision system of a commercial vehicle, and discloses a false touch prevention method, equipment and a storage medium of the anti-collision system of the commercial vehicle. The method comprises the following steps: acquiring information of a current driving scene in real time in the driving process of a commercial vehicle, and extracting scene characteristics of each scene segment from the information of the current driving scene; determining the probability of avoiding false touch of scene feature classification of each scene segment by adopting a deep learning model; and counting the classification results of the scene segments in real time, and determining a false touch prevention strategy according to the statistical results. The anti-collision system is used for avoiding the mistaken touch of the anti-collision system and ensuring the driving safety.
Description
Technical Field
The invention relates to the field of running safety of commercial vehicles, in particular to a method, equipment and a storage medium for preventing false touch of an anti-collision system of a commercial vehicle.
Background
The anti-collision system is widely applied in the field of commercial vehicles. For the commercial vehicle, the anti-collision system can improve the driving safety.
Existing collision avoidance systems preset a series of rules to perform emergency braking or steering operations when a hazard is predicted. However, due to the defects of the anti-collision system and the complex and variable running environment of the vehicle, especially in the scenes of curves, overtaking, entering bends, exiting bends and the like, the anti-collision system is also triggered when no danger actually exists, and the false touch occurs. The wrong touch not only influences the driving experience, but also brings potential safety hazards.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method, equipment and a storage medium for preventing false touch of an anti-collision system of a commercial vehicle, so that the false touch of the anti-collision system is avoided, and the driving safety is ensured.
The embodiment of the invention provides a method for preventing mistaken touch of an anti-collision system of a commercial vehicle, which comprises the following steps:
acquiring information of a current driving scene in real time in the driving process of a commercial vehicle, and extracting scene characteristics of each scene segment from the information of the current driving scene;
determining the probability of avoiding false touch for the scene feature classification of each scene segment by adopting a deep learning model; the deep learning model is obtained by training scene features of each scene segment of an anti-collision system false touch scene and avoidance false touch labels;
and counting the classification results of the scene segments in real time, and determining a false touch prevention strategy according to the statistical results.
An embodiment of the present invention provides an electronic device, including:
a processor and a memory;
the processor is used for executing the steps of the false touch prevention method of the collision prevention system of the commercial vehicle according to any embodiment by calling the program or the instruction stored in the memory.
The embodiment of the invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a program or an instruction, and the program or the instruction enables a computer to execute the steps of the false touch prevention method of the commercial vehicle anti-collision system in any embodiment.
The embodiment of the invention has the following technical effects:
by training a deep learning model in advance, the probability that each scene segment is classified as avoiding false touch is accurately identified by adopting a deep learning algorithm; the dynamic change condition of a continuous scene is described by counting the classification results of a plurality of scene segments in real time, so that the matching degree of the current driving scene and the false touch scene can be accurately described; furthermore, due to the integral statistical mode, whether the current driving scene is the false touch scene or not can be judged in advance, a prospective false touch prevention strategy can be provided, and prevention control is achieved before the anti-collision system is triggered.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a false touch prevention method of an anti-collision system of a commercial vehicle according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a straight lane entering a curve, which is provided by an embodiment of the present invention, and the host vehicle easily recognizes vehicles on adjacent lanes as pre-collision vehicles, thereby causing a false touch of the collision avoidance system;
FIG. 3 is a schematic diagram of a stationary vehicle beside a overtaking road of the vehicle provided by the embodiment of the invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for preventing the false touch of the anti-collision system of the commercial vehicle, which is provided by the embodiment of the invention, is mainly suitable for controlling the anti-collision system on the commercial vehicle. The false touch prevention method of the anti-collision system of the commercial vehicle is executed by the electronic equipment, and the electronic equipment is integrated with the anti-collision system at the same time or is communicated with the equipment integrated with the anti-collision system.
Fig. 1 is a flowchart of a false touch prevention method for an anti-collision system of a commercial vehicle according to an embodiment of the present invention, which specifically includes:
s110, acquiring information of a current driving scene in real time in the driving process of the commercial vehicle, and extracting scene features of each scene segment from the information of the current driving scene.
Optionally, a visual sensor (such as a camera and a radar) and a vehicle body sensor are mounted on the commercial vehicle, the visual sensor is used for collecting surrounding environment information, and the vehicle body sensor is used for collecting driving data of the commercial vehicle, such as vehicle speed and direction.
The information of the current driving scene is collected at a fixed collection frequency, and the information of the driving scenes at a plurality of continuous moments is collected into a scene segment. For example, every 0.1s, a set of driving scene information is collected, and then 5 sets of driving scene information of 0.5s in succession are formed into a scene segment.
And identifying each scene segment through a point cloud identification algorithm, an image identification algorithm and the like to obtain scene characteristics including the relative motion relation and the driving state of the commercial vehicle and the objects outside the vehicle. For example, the relative movement distance between the commercial vehicle and the pedestrian, the relative movement speed, the average driving speed, the steering angle and the like.
S120, determining the probability of classifying the scene features of each scene segment into avoidance of false touches by adopting a deep learning model; the deep learning model is obtained by training scene features of each scene segment of an anti-collision system false touch scene and avoidance false touch labels.
The method provided by the embodiment needs to train the deep learning model in advance, does not limit the structure of the deep learning model, and can classify the scene features.
The method comprises the steps that the scene characteristics and the avoidance mistaken touch labels of one scene segment of a scene are taken as a training sample by the anti-collision system, the scene characteristics and the avoidance mistaken touch labels of one scene segment of a non-mistaken touch scene of the anti-collision system are taken as a training sample, and the deep learning model is trained. The anti-collision system mistaken touch scene is a scene where the anti-collision system is triggered under a safe condition, and the anti-collision system non-mistaken touch scene is a scene where the anti-collision system is triggered under a dangerous condition.
After the model is trained, each scene segment is input into the deep learning model, and the type (including avoiding false touch and not avoiding false touch) of the scene segment and the probability of the corresponding type are output. The probability represents the degree to which the scene segment belongs to the type, and also represents the matching degree of the scene segment with the scene segment in the anti-collision system false touch scene.
S130, counting the classification results of the scene segments in real time, and determining a false touch prevention strategy according to the counting results.
Optionally, the scene segments are collected in real-time, so that the probabilities are obtained by real-time classification. And accumulating the probability of each scene segment obtained along with the time, and determining the false touch prevention strategy according to the accumulation result in real time.
Preferably, the corresponding set score is determined according to the probability of avoiding false touch of the current scene segment classification. For example, the probability is set to 0 at 50% or less, 1 at 50% to 80% and 2 at 80% or more. Therefore, the matching degree of different scene segments and the scene segments in the false touch scene of the anti-collision system can be obviously distinguished. And then accumulating the set scores of the scene segments, and determining a false touch prevention strategy corresponding to a threshold value according to whether the accumulated scores reach the threshold value.
The accumulated scores depict the matching degree of the dynamic change condition of the continuous scene and the dynamic change condition of the scene segment in the scene touched by the anti-collision system by mistake, and the characteristics of the dynamic driving scene are consistent, so that the anti-collision system is independent of the scene at a certain moment, and whether the current driving scene needs to be triggered or not can be accurately judged.
The threshold value in this application is at least one. For example, 20, when the accumulated score reaches 20, the current driving scene is considered to be easy to be touched by mistake, and the anti-collision system is restrained.
For more refined control, the anti-false touch strategy comprises an anti-collision strategy inhibition and an anti-collision system trigger condition improvement; and increasing that the threshold corresponding to the trigger condition of the anti-collision system is lower than the threshold corresponding to the anti-collision inhibition strategy. For example, when the cumulative score reaches 15, the probability of a false touch is considered to be high, and the triggering condition of the collision avoidance system is increased, such as the lateral distance for triggering braking is decreased. When the accumulated score reaches 20, the probability of false touch is considered to be extremely high, and the anti-collision strategy is directly inhibited.
In some scenes, if the commercial vehicle runs in a dangerous scene for a long time, the probability that the scene features of the scene segments are classified as avoiding false touch is low. However, the accumulation over time also leads to a larger statistical result, which may lead to a suppression when the collision avoidance system should be triggered. To avoid such a situation, when the classification results of a plurality of scene segments are counted in real time, if the probabilities of a continuously set number (e.g., 10) of scene segments are all lower than a set value (e.g., 20%), the current statistical result is cleared, and the statistics is started from the classification result of the current scene segment again.
In the embodiment, the deep learning model is trained in advance, so that the probability that each scene segment is classified as avoiding false touch is accurately identified by adopting a deep learning algorithm; the dynamic change condition of a continuous scene is described by counting the classification results of a plurality of scene segments in real time, so that the matching degree of the current driving scene and the false touch scene can be accurately described; furthermore, due to the integral statistical mode, whether the current driving scene is the false touch scene or not can be judged in advance, a prospective false touch prevention strategy can be provided, and prevention control is achieved before the anti-collision system is triggered. Moreover, the staged false touch prevention strategy realizes prospective control while realizing fine control, and the driving experience is better.
The application effect of the embodiment of the invention mainly depends on the recognition effect of the deep learning model, and a good training sample plays an important role. The process of obtaining training samples of the deep learning model is described in detail below.
Optionally, before collecting information of a current driving scene in the driving process of the commercial vehicle, the method further includes: acquiring information of multiple anti-collision system false touch scene segments, and constructing a false touch scene library according to the information of the anti-collision system false touch scene segments; and extracting scene features of each scene segment from the false touch scene library.
Firstly, obtaining the information of the scene segment touched by the anti-collision system by mistake according to road analysis. Fig. 2 is a schematic diagram of a straight road going into a curve, which is provided by an embodiment of the present invention, and the host vehicle easily recognizes vehicles on adjacent lanes as pre-collision vehicles, so as to cause a false touch of the anti-collision system. Fig. 3 is a schematic diagram of a stationary vehicle beside a overtaking road of a vehicle according to an embodiment of the present invention. The host vehicle easily recognizes a stationary vehicle as a pre-crash vehicle to cause a false touch of the collision avoidance system. The driving scene segment similar to that shown in fig. 2 and 3 is known as a false touch scene segment by performing road analysis.
Then, in the driving process of the commercial vehicle, the information of the scene fragments touched by the anti-collision system in a wrong way is collected through the vehicle-mounted vision sensor and the vehicle body sensor, so that the scene library touched by the mistake can be continuously added aiming at the condition of the mistaken touch in the driving process, the scene library touched by the mistake which is continuously expanded is further used for dealing with the complex and changeable environment, and a data basis is provided for obtaining the real-time scene fragments for avoiding the probability of the mistaken touch in the follow-up process.
In the embodiment, at the initial stage of establishing the false touch scene library, a basis can be provided for avoiding common easy-false-touch scenes; through continuous expansion in the later period, the limitation of simply establishing rules in a complex and changeable driving environment can be broken through.
Preferably, the scene segment touched by the anti-collision system by mistake includes a segment with a set time length before the anti-collision system touched by mistake and a segment when the anti-collision system touched by mistake. The set time period can be determined by an actual false touch prevention effect test, and is 3s for example. The segment when the anti-collision system is touched by mistake is from the moment of being touched by mistake to the moment of quitting the anti-collision system. Assuming that the anti-collision system exits when triggering k +3s at the moment k, the segments when preventing false touch comprise k-3 to ks and k to k +3s.
When the false touch scene is fully utilized, especially the scene before the false touch possibly occurs, namely the false touch scene library is constructed through the continuous forward-looking scene, so that the matching between the current driving scene and the forward-looking scene is identified through the deep learning model, and the forward-looking false touch prevention strategy is provided conveniently.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 4, the electronic device 400 includes one or more processors 401 and memory 402.
The processor 401 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 400 to perform desired functions.
In one example, the electronic device 400 may further include: an input device 403 and an output device 404, which are interconnected by a bus system and/or other form of connection mechanism (not shown). The input device 403 may include, for example, a keyboard, a mouse, and the like. The output device 404 can output various information to the outside, including warning prompt information, braking force, and the like. The output devices 404 may include, for example, a display, speakers, a printer, and a communication network and its connected remote output devices, among others.
Of course, for simplicity, only some of the components of the electronic device 400 relevant to the present invention are shown in fig. 4, omitting components such as buses, input/output interfaces, and the like. In addition, electronic device 400 may include any other suitable components depending on the particular application.
In addition to the above method and apparatus, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, cause the processor to execute the steps of the false touch prevention method of the collision avoidance system for a commercial vehicle provided by any embodiment of the present invention.
The computer program product may write program code for carrying out operations for embodiments of the present invention in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, an embodiment of the present invention may also be a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the processor may execute the steps of the false touch prevention method of the collision avoidance system for a commercial vehicle according to any embodiment of the present invention.
The computer readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present application. As used in the specification and claims of this application, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus 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, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, or apparatus that comprises the element.
It is also noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," "outer," and the like are used herein to denote an orientation or positional relationship, as illustrated in the accompanying drawings, for convenience in describing the present invention and to simplify the description, but are not intended to denote or imply that the referenced device or element must have a particular orientation, be constructed in a particular orientation, and be operated in a particular orientation, and thus should not be construed as limiting the present invention. Unless expressly stated or limited otherwise, the terms "mounted," "connected," "coupled," and the like are to be construed broadly and encompass, for example, both fixed and removable coupling or integral coupling; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for preventing false touch of a commercial vehicle anti-collision system is characterized by comprising the following steps:
acquiring information of a current driving scene in real time in the driving process of a commercial vehicle, and extracting scene characteristics of each scene segment from the information of the current driving scene;
determining the probability of avoiding false touch of scene feature classification of each scene segment by adopting a deep learning model; the deep learning model is obtained by training scene features of each scene segment of an anti-collision system false touch scene and avoidance false touch labels;
and counting the classification results of the scene segments in real time, and determining a false touch prevention strategy according to the statistical results.
2. The false touch prevention method for the collision avoidance system of the commercial vehicle according to claim 1, wherein before collecting information of a current driving scene during driving of the commercial vehicle, the method further comprises:
acquiring information of multiple anti-collision system false touch scene segments, and constructing a false touch scene library according to the information of the anti-collision system false touch scene segments;
and extracting scene features of each scene segment from the false touch scene library.
3. The method for preventing false touch of the collision avoidance system of the commercial vehicle according to claim 2, wherein the obtaining information of the multiple collision avoidance system false touch scene segments comprises:
obtaining the information of the scene fragments mistakenly touched by the anti-collision system according to road analysis;
in the driving process of the commercial vehicle, the information of the scene fragments touched by the anti-collision system in a wrong way is acquired through the vehicle-mounted vision sensor and the vehicle body sensor.
4. The false touch prevention method for the collision avoidance system of the commercial vehicle according to claim 3, wherein the false touch scene segment of the collision avoidance system comprises a segment with a set time length before the false touch of the collision avoidance system and a segment when the false touch of the collision avoidance system occurs.
5. The false touch prevention method of the collision avoidance system of the commercial vehicle according to any one of claims 1 to 4, wherein the scene characteristics comprise relative motion relationship and driving state of the commercial vehicle and the vehicle-mounted object.
6. The false touch prevention method of the commercial vehicle collision avoidance system according to claim 1, wherein the counting classification results of a plurality of scene segments in real time and determining a false touch prevention strategy according to the counting results comprises:
determining a corresponding set score according to the probability of avoiding false touch of the current scene segment classification;
accumulating the set scores of the scene segments, and determining the false touch prevention strategy corresponding to the threshold value according to whether the accumulated scores reach the threshold value.
7. The false touch prevention method for the collision avoidance system of the commercial vehicle according to claim 6, wherein the false touch prevention strategy comprises suppressing the collision avoidance strategy and raising a trigger condition of the collision avoidance system;
and the threshold value corresponding to the trigger condition for improving the anti-collision system is lower than the threshold value corresponding to the anti-collision inhibition strategy.
8. The false touch prevention method for the collision avoidance system of the commercial vehicle according to claim 1, wherein the real-time statistics of the classification results of the plurality of scene segments comprises:
when the classification results of a plurality of scene segments are counted in real time, if the probabilities of a continuously set number of scene segments are all lower than a set value, the current counting result is cleared, and counting is started from the classification result of the current scene segment again.
9. An electronic device, characterized in that the electronic device comprises:
a processor and a memory;
the processor is used for executing the steps of the false touch prevention method of the collision avoidance system of the commercial vehicle according to any one of claims 1 to 8 by calling the program or the instructions stored in the memory.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a program or instructions for causing a computer to execute the steps of the false touch prevention method of the collision avoidance system for commercial vehicles according to any one of claims 1 to 8.
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| WO2022021910A1 (en) * | 2020-07-25 | 2022-02-03 | 华为技术有限公司 | Vehicle collision detection method and apparatus, and computer-readable storage medium |
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| US9626867B2 (en) * | 2012-07-18 | 2017-04-18 | Ford Global Technologies, Llc | False warning suppression in a collision avoidance system |
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| CN110371025A (en) * | 2019-08-09 | 2019-10-25 | 爱驰汽车有限公司 | Method, system, equipment and the storage medium of the preposition collision detection for operating condition of overtaking other vehicles |
| CN111401414A (en) * | 2020-02-29 | 2020-07-10 | 同济大学 | A Dangerous Scene Extraction and Classification Method Based on Natural Driving Data |
| WO2022021910A1 (en) * | 2020-07-25 | 2022-02-03 | 华为技术有限公司 | Vehicle collision detection method and apparatus, and computer-readable storage medium |
| CN113788016A (en) * | 2021-08-31 | 2021-12-14 | 厦门理工学院 | Automatic emergency braking control method, system, server and storage medium for preventing false triggering |
| CN115056768A (en) * | 2022-04-26 | 2022-09-16 | 一汽奔腾轿车有限公司 | Control method, system, equipment and storage medium for preventing front collision and early warning and misinformation |
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