CN112180927B - Automatic driving time domain construction method, device, storage medium and device - Google Patents
Automatic driving time domain construction method, device, storage medium and device Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0055—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot with safety arrangements
- G05D1/0061—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot with safety arrangements for transition from automatic pilot to manual pilot and vice versa
Abstract
The invention discloses an automatic driving time domain construction method, equipment, a storage medium and a device, wherein when a target vehicle is detected to exit an automatic driving mode, a qualitative judgment result is obtained from driving information collected at present through a preset qualitative judgment model, a critical parameter set is determined from driving environment information through a preset quantitative judgment model, a corresponding critical value set is obtained, a parameter value set of each critical parameter in a preset time period is obtained, a quantitative judgment result is obtained, and an automatic driving time domain is constructed according to the qualitative judgment result and the quantitative judgment result. In the prior art, no clear automatic driving time domain construction method exists, but the automatic driving time domain is constructed according to the obtained qualitative judgment result and quantitative judgment result by obtaining the qualitative judgment result and the quantitative judgment result.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to an automatic driving time domain construction method, automatic driving time domain construction equipment, an automatic driving time domain storage medium and an automatic driving time domain device.
Background
At present, a great deal of manpower and material resources are invested at home and abroad to develop an automatic driving automobile. At the beginning of the function definition and system development of the automatic driving system, the operation range of the automatic driving vehicle needs to be defined, namely, the automatic driving vehicle runs in the range, the system is activated, and the system fails beyond the range.
There is no specific method for constructing an ODD in an automatic driving time domain in the prior art at home and abroad, and the existing ODD description is mostly embodied in a 'qualitative' level, for example, an automatic driving system is suitable for an expressway, daytime, rainy day and the like, but there is no description of a 'quantitative' level, such as the gradient of the expressway, a specific value of road curvature, illumination values at daytime and night, a specific value of rainfall and the like.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide an automatic driving time domain construction method, equipment, a storage medium and a device, and aims to solve the technical problem of the automatic driving time domain construction process in the prior art.
In order to achieve the above object, the present invention provides an automatic driving time domain construction method, which includes the steps of:
when the target vehicle is detected to exit the automatic driving mode, acquiring a qualitative judgment result from the currently acquired driving information through a preset qualitative judgment model;
determining a critical parameter set from the driving environment information through a preset quantitative judgment model, and acquiring a critical value set corresponding to the critical parameter set;
acquiring a parameter value set of each critical parameter in the critical parameter set within a preset time period, and acquiring a quantitative judgment result according to the critical value set and the parameter value set;
and constructing an automatic driving time domain according to the qualitative judgment result and the quantitative judgment result.
Preferably, before the step of obtaining the qualitative determination result from the currently acquired driving information through the preset qualitative determination model when it is detected that the target vehicle exits the automatic driving mode, the method further includes:
acquiring a sample library of qualitative judgment elements and an initial qualitative judgment model;
and constructing an initial element set of the element model according to the sample library, and constructing a preset qualitative judgment model according to the initial element set and the initial qualitative judgment model.
Preferably, when it is detected that the target vehicle exits the automatic driving mode, the step of obtaining the qualitative judgment result from the currently acquired driving information through the preset qualitative judgment model includes:
acquiring characteristic element information from the driving information;
and inputting the characteristic element information into the preset qualitative judgment model, and comparing the characteristic element information with the initial element set to obtain a qualitative judgment result.
Preferably, the step of determining a critical parameter set from the driving environment information through a preset quantity judgment model and acquiring a critical value set corresponding to the critical parameter set includes:
determining a changing environment element from the driving environment information;
obtaining a critical parameter set in the variable environment elements according to the preset quantity judgment model and the variable environment elements;
and acquiring a parameter value set of the critical parameter set as a critical value set.
Preferably, the step of obtaining the critical parameter set in the variable environment element according to the preset quantity judgment model and the variable environment element includes:
traversing different environment elements in the changed environment elements to obtain the current changed environment elements;
judging the current change environment elements according to the preset quantity judgment model to obtain a judgment result;
and obtaining critical parameters according to the judgment result, returning to the step of traversing the change environment elements, and obtaining a critical parameter set when the traversal is finished.
Preferably, the step of obtaining a parameter value set of each critical parameter in the critical parameter set within a preset time period and obtaining a quantitative determination result according to the critical value set and the parameter value set includes:
acquiring a parameter value set of a critical parameter set in a preset time period;
screening the parameter value set through the critical value set to obtain a threshold value of the critical parameter set;
and obtaining a quantitative judgment result according to the critical parameter set and the threshold value.
Preferably, the step of screening the parameter value set through the threshold value set to obtain the threshold value of the threshold parameter set includes:
selecting a corresponding parameter critical value from the critical value set according to the parameter value set;
and screening the parameter value set through the parameter critical value to obtain a threshold value of the critical parameter set.
In addition, to achieve the above object, the present invention further provides an automatic driving time domain constructing apparatus, which includes a memory, a processor, and an automatic driving time domain constructing program stored in the memory and executable on the processor, wherein the automatic driving time domain constructing program is configured to implement the steps of the automatic driving time domain constructing method as described above.
In addition, to achieve the above object, the present invention further provides a storage medium having an automatic driving time domain constructing program stored thereon, which when executed by a processor, implements the steps of the automatic driving time domain constructing method as described above.
In addition, in order to achieve the above object, the present invention further provides an automatic driving time domain constructing apparatus, including: the device comprises a qualitative result acquisition module, a critical value acquisition module, a quantitative result acquisition module and a time domain construction module;
the qualitative result acquisition module is used for acquiring a qualitative judgment result from the currently acquired driving information through a preset qualitative judgment model when the target vehicle is detected to exit the automatic driving mode;
the critical value set acquisition module is used for determining a critical parameter set from the driving environment information through a preset quantity judgment model and acquiring a critical value set corresponding to the critical parameter set;
the quantitative result obtaining module is used for obtaining a parameter value set of each critical parameter in the critical parameter set in a preset time period, and obtaining a quantitative judgment result according to the critical value set and the parameter value set;
and the time domain construction module is used for constructing an automatic driving time domain construction according to the qualitative judgment result and the quantitative judgment result.
The invention provides a method, equipment, a storage medium and a device for constructing an automatic driving time domain, which are used for firstly obtaining a qualitative judgment result from currently collected driving information through a preset qualitative judgment model when a target vehicle is detected to exit an automatic driving mode, secondly determining a critical parameter set from driving environment information through a preset quantitative judgment model, combining and obtaining a corresponding critical value set, obtaining a parameter value set of each critical parameter in a preset time period, obtaining a quantitative judgment result, and constructing the automatic driving time domain according to the qualitative judgment result and the quantitative judgment result. In the prior art, no clear automatic driving time domain construction method exists, and the automatic driving time domain is constructed according to the obtained qualitative judgment result and quantitative judgment result by obtaining the qualitative judgment result and the quantitative judgment result.
Drawings
FIG. 1 is a schematic structural diagram of an automatic driving time domain construction device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of an automatic driving time domain construction method according to the present invention;
FIG. 3 is a flowchart illustrating a second embodiment of the automatic driving time domain constructing method according to the present invention;
FIG. 4 is a flowchart illustrating a third embodiment of the automatic driving time domain constructing method according to the present invention;
fig. 5 is a block diagram illustrating a first embodiment of an automatic driving time domain constructing apparatus according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an automatic driving time domain construction device of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the automatic driving time domain constructing apparatus may include: a processor 1001, such as a central processing unit, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a display screen, and the optional user interface 1003 may further include a standard wired interface, a wireless interface, and the wired interface for the user interface 1003 may be a USB interface in the present invention. The network interface 1004 may optionally include a standard wired interface, a wireless interface. The memory 1005 may be a high speed random access memory or a stable memory such as a disk memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the automated driving horizon construction apparatus and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in FIG. 1, memory 1005, identified as one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and an autopilot time domain building program.
In the automatic driving time domain constructing apparatus shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting user equipment; the automatic driving time domain constructing device calls the automatic driving time domain constructing program stored in the memory 1005 through the processor 1001, and executes the automatic driving time domain constructing method provided by the embodiment of the invention.
Based on the hardware structure, the embodiment of the automatic driving time domain construction method is provided.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the automatic driving time domain construction method of the present invention, and proposes the first embodiment of the automatic driving time domain construction method of the present invention.
In a first embodiment, the automatic driving time domain construction method includes the steps of:
step S10: and when the target vehicle is detected to exit the automatic driving mode, acquiring a qualitative judgment result from the currently acquired driving information through a preset qualitative judgment model.
It should be understood that the execution subject of the present embodiment may be an automatic driving time domain construction system, which includes a driving information acquisition device, a vehicle state detection device, and an automatic driving time domain construction device; the driving information acquisition device can be a visual sensor, a camera, a GPS antenna, a high-precision inertial navigation device and the like and is used for acquiring the driving information of the vehicle; the vehicle state detection device can be a camera, a velometer and other devices and is used for detecting whether the vehicle exits the automatic driving mode in real time; and the automatic driving time domain constructing device is used for constructing an automatic driving operation time domain.
It should be noted that the predetermined qualitative determination model is a model that is set in advance and is used for determining the influence of the element property on the automatic driving mode. The currently collected driving information refers to driving information collected by the automatic driving time domain construction system when the vehicle exits the automatic driving mode, and the driving information is specific to the nature of the element. The qualitative judgment result is a judgment result that the nature of the judgment element influences the exit of the driving mode, for example, when the automatic driving mode exits, if an obstacle exists in the current driving information and is located in the middle of a front road, the obstacle influences the automatic driving mode, so that the vehicle exits the automatic driving mode, and the obstacle is the qualitative element influencing automatic driving.
It can be understood that, when the automatic driving time domain building system detects that the automatic driving mode exits, the current driving information is acquired through the sensor, the preset qualitative judgment model judges the environmental elements in the current driving information through the qualitative elements in the model to obtain the qualitative judgment result of the environmental elements influencing the automatic driving mode in the current driving information, for example, the qualitative elements in the current driving information can be judged one by one, the automatic driving mode is simulated through the preset qualitative judgment model, the qualitative elements are added into the current driving state one by one, whether the automatic driving mode after the qualitative elements are added exits is detected, and then the qualitative judgment result of each qualitative element is judged.
Step S20: and determining a critical parameter set from the driving environment information through a preset quantity judgment model, and acquiring a critical value set corresponding to the critical parameter set.
The preset quantity judgment model is a model in which the magnitude of the judgment element set in advance affects the automatic driving mode. The critical parameter set is a set of quantitative factors, which are factors that the magnitude of the current factor will have an impact on the autonomous driving mode. The critical value is the magnitude of the current element which affects the automatic driving mode, and the critical value set is the critical value set formed by the critical values of all the current elements.
It can be understood that the quantitative element set in the current driving information is obtained as the critical parameter set by comparing the quantitative element set in the preset quantitative model with the elements in the current driving information. And simulating an automatic driving mode scene through a preset quantitative model, determining critical values of the critical parameters one by one when the automatic driving mode exits, and acquiring a critical value set.
Step S30: and acquiring a parameter value set of each critical parameter in the critical parameter set in a preset time period, and acquiring a quantitative judgment result according to the critical value set and the parameter value set.
It should be noted that the preset time period is a time preset for determining the influence of the magnitude of the quantitative element on the automatic driving state, and the magnitude of the quantitative element in the preset time period changes linearly with time, for example, when the influence of rainfall on the automatic driving mode is measured, the rainfall gradually increases linearly from small to large in a certain time period, so as to determine the influence of the magnitude of the rainfall on the automatic driving mode. The parameter value set is a set of qualitative element value changes in a preset time period, and in a specific implementation process, in order to avoid influence caused by measurement errors, the parameter value changes need to exceed a critical value.
It can be understood that the automatic driving time domain construction system detects the change of each critical parameter in a preset time period through a sensor, and records the result of the change set of the element quantity values, namely the parameter value set of the critical parameter. Screening the parameter value set according to the critical value of the element, obtaining the threshold value of the parameter which does not affect the automatic driving mode in the element parameter value set, as the quantitative judgment result of the element, screening the parameter value set of all the elements in turn, obtaining the parameter threshold value of all the elements as the quantitative judgment result, for example, when determining the influence of the illumination intensity on the automatic driving mode, the illumination intensity is gradually decreased from the standard light intensity until the light intensity gradually approaches zero within a certain time period, and the low light intensity threshold value for exiting the automatic driving mode is obtained, screening the changed light intensity through the weak light intensity critical value, selecting the threshold value from the weak light intensity critical value to the standard light intensity as the weak light threshold value, then obtaining the strong light threshold value in the same way, and acquiring a light intensity threshold value according to the weak light threshold value and the strong light threshold value, and taking the light intensity threshold value as a quantitative judgment result of the light intensity element.
Step S40: and constructing an automatic driving time domain according to the qualitative judgment result and the quantitative judgment result.
The automatic driving time zone is a time zone in which the change of the qualitative or quantitative element in the vehicle-lane does not affect the exit of the automatic driving mode in the automatic driving mode state of the vehicle.
It can be understood that a qualitative factor threshold value which does not cause exit influence on the automatic driving mode can be obtained according to the qualitative judgment result; and obtaining a quantitative element value set which does not cause exit influence on the automatic driving mode according to the quantitative judgment result. And constructing an automatic driving time domain of the qualitative and quantitative elements according to the threshold value of the qualitative element and the magnitude set of the quantitative element.
In a first embodiment, an automatic driving time domain construction method is provided, which includes obtaining a qualitative judgment result from currently acquired driving information through a preset qualitative judgment model when it is detected that a target vehicle exits an automatic driving mode, determining a critical parameter set from driving environment information through a preset quantitative judgment model, combining the critical parameter set to obtain a corresponding critical value set, obtaining a parameter value set of each critical parameter in a preset time period, obtaining a quantitative judgment result, and constructing an automatic driving time domain according to the qualitative judgment result and the quantitative judgment result. In the prior art, there is no clear automatic driving time domain construction method, but in the present embodiment, an automatic driving time domain is constructed by obtaining a qualitative judgment result and a quantitative judgment result and according to the obtained qualitative judgment result and the quantitative judgment result.
Referring to fig. 3, fig. 3 is a schematic flow chart of a second embodiment of the automatic driving time domain construction method of the present invention, and the second embodiment of the automatic driving time domain construction method of the present invention is proposed based on the first embodiment shown in fig. 2.
In the second embodiment, before the step S10, the method further includes:
step S101': and acquiring a sample library of qualitative judgment elements and an initial qualitative judgment model.
The sample library of qualitative determination elements is a collection of qualitative elements, and the automated driving pattern can be simulated based on the elements in the collection. The initial qualitative judgment model is an unadjusted qualitative judgment model, and qualitative factors cannot be judged without any qualitative factor set in the model.
It is understood that the sample library for obtaining the qualitative judgment elements may be obtained through an actual driving scene, and may be obtained for the qualitative elements that are not determined in different scenes, for example, a rockfall or other obstacles that are likely to appear on a road and a prompt mark for paying attention to the rockfall may be obtained on a rockfall road segment.
Step S102': and constructing an initial element set of the element model according to the sample library, and constructing a preset qualitative judgment model according to the initial element set and the initial qualitative judgment model.
The initial element set is a set having elements of the simulated automatic driving mode, and the set includes various elements that affect exit from the walk-through driving mode.
It can be understood that the preset qualitative judgment mode can be constructed according to the initial element set and the initial qualitative judgment model, so that the initial judgment mode can complete the simulation of the automatic driving state, namely the preset qualitative judgment model.
Accordingly, step S10 includes:
step S101: and acquiring characteristic element information from the driving information.
It should be noted that the driving information is the driving information collected by the sensor of the automatic driving time domain construction system when the vehicle exits the automatic driving state. The characteristic element information is information having qualitative elements and can affect exit from the automatic driving mode.
It should be noted that the sensor of the automatic driving time domain construction system collects driving information in real time, and collects current driving information when the automatic driving mode exits. And identifying the characteristic elements in the driving information to acquire the characteristic element information in the driving information.
Step S102: and inputting the characteristic element information into the preset qualitative judgment model, and comparing the characteristic element information with the initial element set to obtain a qualitative judgment result.
The method includes inputting feature element information into a preset qualitative judgment model, comparing and judging the input feature element information one by one, building an automatic driving mode of a judgment condition of current feature information by using the preset qualitative judgment model, judging the current feature element, then reselecting the current feature until all feature elements are selected, and acquiring qualitative elements which do not influence the current automatic driving mode as qualitative judgment results.
In a second embodiment, an automatic driving time domain construction method is provided, wherein when it is detected that a target vehicle exits an automatic driving mode, a qualitative judgment result is obtained from driving information currently acquired through a preset qualitative judgment model, a critical parameter set is determined and a corresponding critical value set is obtained from driving environment information through a preset quantitative judgment model, a parameter value set of each critical parameter in a preset time period is obtained, a quantitative judgment result is obtained, and an automatic driving time domain is constructed according to the qualitative judgment result and the quantitative judgment result. In the prior art, there is no clear automatic driving time domain construction method, but in the present embodiment, an automatic driving time domain is constructed by obtaining a qualitative judgment result and a quantitative judgment result and according to the obtained qualitative judgment result and the quantitative judgment result.
Referring to fig. 4, fig. 4 is a flowchart illustrating a third embodiment of the automatic driving time domain building method according to the present invention, and the third embodiment of the automatic driving time domain building method according to the present invention is proposed based on the first embodiment illustrated in fig. 2.
In the third embodiment, the step S20 includes:
step S201: determining a changing environment element from the driving environment information.
It should be noted that the automatic driving time domain construction system monitors driving environment information in real time during the automatic driving process. The variable environmental element is an environmental element in which the magnitude of the element varies during automatic driving, for example, a road has an uphill section during driving, and the gradient of each uphill is different, i.e., a varying gradient.
It is understood that in the driving environment information, the changed environmental elements can be obtained by recording the environmental elements for different time periods. In the embodiment, the road gradient information is measured by high-precision inertial navigation, and other devices or methods can be adopted without specific requirements.
Step S2021: and traversing different environment elements in the changed environment elements to obtain the current changed environment elements.
It should be noted that traversal is a process of selecting elements in the current set without putting back. Each traversal to one element in the current set ends the convenience process when all elements are traversed. The current change environment element is one change environment element in the change environment element set.
It is understood that the following steps are performed by traversing different ones of the varying environment elements, selecting one of the varying environment elements from the set of varying environment elements.
Step S2022: and judging the current change environment element according to the preset quantity judgment model to obtain a judgment result.
It should be noted that, when the preset quantity judgment model judges the changing environmental elements, it is necessary to judge the influence of other changing environmental elements on the current changing environmental elements, and the preset quantity judgment model performs standardized setting on other environmental elements, or may perform normal state setting, and no specific requirement is made here. The preset amount judgment model can judge only one changed environmental element at a time. The judgment result is the judgment result of whether the current change environment element has exit influence on the automatic driving mode.
It can be understood that the preset quantitative determination model limits other environmental elements, simulates an automatic driving mode, and acquires a quantitative result of a current changing environment as a determination result under the condition that the current environmental element is linearly changed.
Step S2023: and obtaining critical parameters according to the judgment result, returning to the step of traversing the change environment elements, and obtaining a critical parameter set when the traversal is finished.
It should be noted that the critical parameter is a critical parameter of the current changing environmental element of the above steps. The critical parameter set is a set of critical parameters of all the elements of the varying environment.
It can be understood that after the critical parameter of the current variable environment element is acquired, the critical parameter of another variable environment element needs to be acquired, and then the step of traversing the variable environment element needs to be returned, the current variable environment element is traversed again, and when the traversal is finished, the critical parameter set of the variable environment element is acquired.
Step S203: and acquiring a parameter value set of the critical parameter set as a critical value set.
It should be noted that the threshold value set is a set of intra-threshold parameter values of the changed environmental elements. And determining a parameter value set of the critical parameters according to a specific implementation condition, wherein for example, the road curvature change has a certain range value, the change value at the corner is large, the change value of the common road surface is small, and all the changed values need to be acquired to be used as the curvature change value set.
Accordingly, the step S30 includes:
step S301: and acquiring a parameter value set of the critical parameter set in a preset time period.
It should be noted that, in a period of time before the automatic driving mode exits, the current variable environmental factor affecting the automatic driving mode exits does not cause the automatic driving mode to exit, and in order to avoid a large amount of data processing, the variable value of the current variable environmental factor in a period of time before and after the automatic driving mode exits needs to be obtained for processing.
Step S3021: and selecting corresponding parameter critical values from the critical value set according to the parameter value set.
It can be understood that, the above steps obtain the parameter value set and the threshold value set, select the threshold value corresponding to the current variable environment information parameter value from the threshold value set through the current variable environment information, and make one-to-one correspondence between the parameter value sets of all variable environment elements and their corresponding threshold values.
Step S3022: and screening the parameter value set through the parameter critical value to obtain a threshold value of the critical parameter set.
It should be noted that the threshold of the critical parameter set is a threshold at which the current changing environment information does not cause the automatic driving mode to exit.
It can be understood that the parameter value set is screened according to the parameter critical value of the current change environment element influencing exit of the automatic driving mode, the threshold value of the parameter value which does not cause exit of the automatic driving mode is obtained, and the threshold value of the parameter value which causes exit of the automatic driving mode is excluded.
Step S303: and obtaining a quantitative judgment result according to the critical parameter set and the threshold value.
The threshold value is a set of parameter value thresholds, which are threshold values of parameter values corresponding to respective critical parameters, and the critical parameter set is a set of quantitative environmental elements affecting the automatic driving mode.
It is understood that, when obtaining a quantitative environmental element affecting the automated driving mode and a threshold value of the quantitative environmental element, the quantitative determination result of the quantitative environmental element on the automated driving mode may be determined, and all the quantitative environmental elements and the threshold value may be determined to obtain the quantitative determination result which is the determination result of all the quantitative elements.
In a third embodiment, an automatic driving time domain construction method is provided, wherein when it is detected that a target vehicle exits an automatic driving mode, a qualitative judgment result is obtained from currently acquired driving information through a preset qualitative judgment model, then a critical parameter set is determined from driving environment information through a preset quantitative judgment model, a corresponding critical value set is obtained, a parameter value set of each critical parameter in a preset time period is obtained, a quantitative judgment result is obtained, and an automatic driving time domain is constructed according to the qualitative judgment result and the quantitative judgment result. In the prior art, there is no clear automatic driving time domain construction method, but in the present embodiment, an automatic driving time domain is constructed by obtaining a qualitative judgment result and a quantitative judgment result and according to the obtained qualitative judgment result and the quantitative judgment result.
In addition, an embodiment of the present invention further provides a storage medium, where an automatic driving time domain constructing program is stored on the storage medium, and when executed by a processor, the automatic driving time domain constructing program implements the steps of the automatic driving time domain constructing method described above.
In addition, referring to fig. 5, an embodiment of the present invention further provides an automatic driving time domain constructing apparatus, where the apparatus includes: a qualitative result obtaining module 10, a critical value obtaining module 20, a quantitative result obtaining module 30 and a time domain constructing module 40.
The qualitative result obtaining module 10 is configured to obtain a qualitative determination result from currently acquired driving information through a preset qualitative determination model when it is detected that the target vehicle exits the automatic driving mode;
the critical value set obtaining module 20 is configured to determine a critical parameter set from the driving environment information through a preset quantity judgment model, and obtain a critical value set corresponding to the critical parameter set;
the quantitative result obtaining module 30 is configured to obtain a parameter value set of each critical parameter in the critical parameter set in a preset time period, and obtain a quantitative determination result according to the critical value set and the parameter value set;
and the time domain construction module 40 is configured to construct an automatic driving time domain construction according to the qualitative judgment result and the quantitative judgment result.
In this embodiment, a qualitative determination result affecting the automatic driving mode is obtained by the qualitative result obtaining module 10, then the critical value set obtaining module 20 obtains a quantitative critical parameter and a critical value set, then the quantitative result obtaining module 30 obtains a quantitative determination result affecting the automatic driving mode, and finally the time domain constructing module 40 constructs the automatic driving time domain according to the qualitative determination result and the quantitative determination result. In the prior art, there is no clear automatic driving time domain construction method, but in the present embodiment, an automatic driving time domain is constructed by obtaining a qualitative judgment result and a quantitative judgment result and according to the obtained qualitative judgment result and the quantitative judgment result.
Other embodiments or specific implementation manners of the automatic driving time domain constructing device of the present invention may refer to the above method embodiments, and are not described herein again.
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 an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order, but rather the words first, second, third, etc. are to be interpreted as names.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g., a Read Only Memory (ROM)/Random Access Memory (RAM), a magnetic disk, an optical disk), and includes several instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. An automatic driving time domain construction method is characterized by comprising the following steps:
when the target vehicle is detected to exit the automatic driving mode, acquiring a qualitative judgment result from the currently acquired driving information through a preset qualitative judgment model;
determining a critical parameter set from the driving information through a preset quantity judgment model, and acquiring a critical value set corresponding to the critical parameter set, wherein the critical parameter set is a set of elements of which the element quantity values influence an automatic driving mode;
acquiring a parameter value set of each critical parameter in the critical parameter set within a preset time period, and acquiring a quantitative judgment result according to the critical value set and the parameter value set;
constructing an automatic driving time domain according to the qualitative judgment result and the quantitative judgment result;
the step of acquiring the qualitative judgment result from the currently acquired driving information through the preset qualitative judgment model comprises the following steps of:
acquiring characteristic element information from the driving information;
and inputting the characteristic element information into the preset qualitative judgment model, and comparing all current characteristics in the characteristic element information with the initial element set one by one to obtain a qualitative judgment result.
2. The method of claim 1, wherein the step of obtaining a qualitative determination result from the currently collected driving information through a preset qualitative determination model upon detecting that the target vehicle exits the autonomous driving mode further comprises:
acquiring a sample library of qualitative judgment elements and an initial qualitative judgment model;
and constructing an initial element set of the element model according to the sample library, and constructing a preset qualitative judgment model according to the initial element set and the initial qualitative judgment model.
3. The method of claim 1, wherein the step of determining a critical parameter set from the driving information through a predetermined quantitative determination model and obtaining a critical parameter set corresponding to the critical parameter set comprises:
determining a changing environmental element from the driving information;
obtaining a critical parameter set in the variable environment elements according to the preset quantity judgment model and the variable environment elements;
and acquiring a parameter value set of the critical parameter set as a critical value set.
4. The method of claim 3, wherein the step of obtaining the set of critical parameters in the variable environment element from the predetermined quantity judgment model and the variable environment element comprises:
traversing different environment elements in the changed environment elements to obtain the current changed environment elements;
judging the current change environment elements according to the preset quantity judgment model to obtain a judgment result;
and obtaining critical parameters according to the judgment result, returning to the step of traversing the change environment elements, and obtaining a critical parameter set when the traversal is finished.
5. The method of claim 4, wherein the step of obtaining a parameter value set of each critical parameter in the critical parameter set within a preset time period and obtaining a quantitative determination result according to the critical value set and the parameter value set comprises:
acquiring a parameter value set of a critical parameter set in a preset time period;
screening the parameter value set through the critical value set to obtain a threshold value of the critical parameter set;
and obtaining a quantitative judgment result according to the critical parameter set and the threshold value.
6. The method of claim 5, wherein the step of filtering the set of parameter values through the set of critical values to obtain threshold values for the set of critical parameters comprises:
selecting a corresponding parameter critical value from the critical value set according to the parameter value set;
and screening the parameter value set through the parameter critical value to obtain a threshold value of the critical parameter set.
7. An apparatus, characterized in that the apparatus comprises: a memory, a processor, and an autopilot time domain construction program stored on the memory and executable on the processor, the autopilot time domain construction program when executed by the processor implementing the steps of the autopilot time domain construction method of any one of claims 1 to 6.
8. A storage medium having stored thereon an autopilot time domain construction program which, when executed by a processor, implements the steps of the autopilot time domain construction method according to one of claims 1 to 6.
9. An autonomous driving horizon constructing apparatus, the apparatus comprising: the device comprises a qualitative result acquisition module, a critical value acquisition module, a quantitative result acquisition module and a time domain construction module;
the qualitative result acquisition module is used for acquiring a qualitative judgment result from the currently acquired driving information through a preset qualitative judgment model when the target vehicle is detected to exit the automatic driving mode;
the critical value obtaining module is used for determining a critical parameter set from the driving information through a preset quantity judging model and obtaining a critical value set corresponding to the critical parameter set, wherein the critical parameter set is a set of elements of which the element quantity value influences an automatic driving mode;
the quantitative result obtaining module is used for obtaining a parameter value set of each critical parameter in the critical parameter set in a preset time period, and obtaining a quantitative judgment result according to the critical value set and the parameter value set;
the time domain construction module is used for constructing an automatic driving time domain construction according to the qualitative judgment result and the quantitative judgment result;
the qualitative result acquisition module is also used for acquiring characteristic element information from the driving information; and inputting the characteristic element information into the preset qualitative judgment model, and comparing all current characteristics in the characteristic element information with the initial element set one by one to obtain a qualitative judgment result.
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