CN113401132A - Driving model updating method and device and electronic equipment - Google Patents
Driving model updating method and device and electronic equipment Download PDFInfo
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- CN113401132A CN113401132A CN202110868169.9A CN202110868169A CN113401132A CN 113401132 A CN113401132 A CN 113401132A CN 202110868169 A CN202110868169 A CN 202110868169A CN 113401132 A CN113401132 A CN 113401132A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0019—Control system elements or transfer functions
- B60W2050/0028—Mathematical models, e.g. for simulation
- B60W2050/0031—Mathematical model of the vehicle
Abstract
The invention discloses a driving model updating method, a driving model updating device and electronic equipment, and relates to the technical field of automatic driving, wherein the driving model updating method comprises the following steps: determining a driving track of the automatic driving vehicle according to the driving destination of the user; generating a to-be-driven area of the automatic driving vehicle according to the driving track; when the area to be driven contains an unfamiliar area, acquiring environmental data of the unfamiliar area to train a driving model; and performing driving control on the automatic driving vehicle by using the driving model obtained by training. Whether the area to be driven of the automatically driven vehicle contains an unfamiliar area or not is judged, the environment data of the unfamiliar area is obtained in time to train a driving model under the condition that the area contains the unfamiliar area, the driving model obtained after the new environment data is used for training is used for driving and controlling the automatically driven vehicle, and the driving safety of the automatically driven vehicle in the unfamiliar environment is guaranteed.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a driving model updating method and device and electronic equipment.
Background
Autopilot is a high-level complex systematic project composed of multiple sensors and subsystems, such as laser radar, millimeter wave radar, camera, global positioning system, inertial measurement unit, etc. The key technology of automatic driving is perception, decision and control. The perception model is used for perceiving environmental information in the driving process of the vehicle, the decision model is mainly used for calculating behaviors of the vehicle and the like according to the perceived environmental information and the high-precision map, and the control model is used for executing electronic control operation on vehicle components according to decision results.
Because the driving models such as the perception model integrated in the automatic driving vehicle are mostly obtained by training the acquired environmental data based on history, when the automatic driving vehicle drives to a strange environment, the existing perception model is possibly not suitable, so that the output result of the perception model influences the driving safety of the automatic driving vehicle. Therefore, a new driving model updating method is urgently needed to be provided to update the perception model in time so as to ensure the driving safety of the vehicle.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect that the existing driving model is always used for vehicle driving control of the existing automatic driving vehicle, which affects the vehicle driving safety, so as to provide a driving model updating method, device and electronic equipment.
According to a first aspect, an embodiment of the present invention discloses a driving model updating method, including: determining a driving track of the automatic driving vehicle according to the driving destination of the user; generating a to-be-driven area of the automatic driving vehicle according to the driving track; when the area to be driven contains an unfamiliar area, acquiring environmental data of the unfamiliar area to train a driving model; and performing driving control on the automatic driving vehicle by using the driving model obtained by training.
Optionally, the method further comprises: comparing the area to be driven with a historical driving area of the automatic driving vehicle; and taking the area to be driven which is not contained in the history driving area as a strange area.
Optionally, obtaining environmental data of the unfamiliar area to train a driving model, including: determining a target database for storing corresponding position environment data according to the geographical position information of the unfamiliar area; acquiring environmental data within the historical duration of a target from a target database; and training the driving model by using the environmental data in the target historical duration.
Optionally, the method further comprises: acquiring the current position and the running speed of the automatic driving vehicle; determining a distance of the current location from the unfamiliar area; and calling processors with different processing capabilities to train the driving model according to the distance and the driving speed.
Optionally, the method further comprises: determining the time length required by the training of the driving model; when the required training time is longer than the preset time, the running speed of the automatic driving vehicle is adjusted according to the required training time, so that the driving model training is completed before the automatic driving vehicle runs to the unfamiliar area, wherein the preset time is determined according to the distance between the current vehicle and the unfamiliar area and the current running speed of the vehicle.
According to a second aspect, an embodiment of the present invention further discloses a driving model updating apparatus, including: the automatic driving vehicle control system comprises a first determining module, a second determining module and a control module, wherein the first determining module is used for determining a driving track of the automatic driving vehicle according to a driving destination of a user; the generating module is used for generating a to-be-driven area of the automatic driving vehicle according to the driving track; the first acquisition module is used for acquiring environment data of an unfamiliar area to train a driving model when the area to be driven contains the unfamiliar area; and the control module is used for carrying out driving control on the automatic driving vehicle by utilizing the driving model obtained by training.
Optionally, the apparatus further comprises: the second acquisition module is used for acquiring the current position and the running speed of the automatic driving vehicle; the second determination module is used for determining the distance between the current position and the unfamiliar area; and the calling module is used for calling processors with different processing capabilities to train the driving model according to the distance and the driving speed.
Optionally, the apparatus further comprises: the third determining module is used for determining the time length required by the training of the driving model; and the adjusting module is used for adjusting the running speed of the automatic driving vehicle according to the time length required by training when the time length required by training is greater than the preset time length, so that the driving model training is completed before the automatic driving vehicle runs to the unfamiliar area, wherein the preset time length is determined according to the distance between the current vehicle and the unfamiliar area and the current running speed of the vehicle.
According to a third aspect, an embodiment of the present invention further discloses an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the driving model updating method according to the first aspect or any one of the alternative embodiments of the first aspect.
According to a fourth aspect, the present invention further discloses a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the driving model updating method according to the first aspect or any one of the optional embodiments of the first aspect.
The technical scheme of the invention has the following advantages:
the driving model updating method/device provided by the invention determines the driving track of the automatic driving vehicle according to the driving destination of the user, generates the area to be driven of the automatic driving vehicle according to the driving track, acquires the environmental data of the unfamiliar area to train the driving model when the area to be driven contains the unfamiliar area, and performs driving control on the automatic driving vehicle by using the driving model obtained by training. By implementing the method and the device, whether the area to be driven of the automatic driving vehicle contains the strange area or not is judged, the environment data of the strange area is timely acquired under the condition that the area contains the strange area to train the driving model, the driving model obtained after the model is trained by using the new environment data is used for driving and controlling the automatic driving vehicle, and the driving safety of the automatic driving vehicle in the strange environment is ensured.
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 specific example of a driving model updating method in the embodiment of the invention;
fig. 2 is a schematic block diagram of a specific example of a driving model updating apparatus in the embodiment of the invention;
fig. 3 is a diagram of a specific example of an electronic device in an embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present 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.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment of the invention discloses a driving model updating method which can be applied to a vehicle end or a server end, and as shown in figure 1, the method comprises the following steps:
For example, the user's driving destination may be obtained by inputting the driving destination through a keyboard of an interactive module in the vehicle or by voice. The embodiment of the application does not limit the obtaining mode of the driving destination of the user, and a person skilled in the art can determine the obtaining mode according to actual needs. The running track of the automatic driving vehicle can be determined in a mode that after the running destination of the user is obtained, the running track from the current position to the destination is generated for the user by the aid of the positioned current position of the automatic driving vehicle and a pre-integrated high-precision map.
And 102, generating a to-be-driven area of the automatic driving vehicle according to the driving track. And determining the area where the automatic driving vehicle is going to pass from the high-precision map according to the vehicle running track, and taking the area of the pass as the area to be driven of the automatic driving vehicle.
For example, whether the area to be traveled includes an unfamiliar area or not may be determined, in a specific manner, a historical travel area corresponding to a historical travel track of the vehicle is obtained by taking an administrative district/county as a dividing unit, the area to be traveled of the vehicle is compared with the historical travel area of the vehicle, a non-overlapping area is found, and when the non-overlapping area is a complete administrative district/county, the administrative district/county is taken as an unfamiliar area.
The environment data may include, but is not limited to, types of obstacles, road signs, marking lines, and the like, and the above environment data in one administrative district/county is generally the same, so that the strange area division may be performed in units of one administrative district/county, and when the area to be driven of the vehicle includes one administrative district/county as a strange area, in order to ensure the safety of automatic driving of the vehicle, the environment data in the area is acquired and the driving model for controlling the driving of the vehicle is trained by using the acquired environment data in the strange area. The present embodiment does not limit the type of the driving model, and any model for controlling the vehicle running, which is trained using the vehicle historical running data, may be used as the driving model in the present embodiment.
As an optional embodiment of the present invention, the method further comprises: comparing the area to be driven with a historical driving area of the automatic driving vehicle; and taking the area to be driven which is not contained in the history driving area as a strange area. The driving model used for controlling the vehicle to run in the area to be driven is obtained by training according to the environment data of the actual area to be driven, and all the non-coincident areas are directly used as the strange areas compared with a mode of determining the strange areas by presetting the divided areas, so that the safety of automatic driving of the vehicle according to the driving model is ensured.
The method for acquiring the environmental data of the unfamiliar area may be that a data acquisition instruction is sent to data acquisition equipment at the position of the unfamiliar area, so that the corresponding data acquisition equipment feeds back the acquired data in real time according to the data acquisition instruction, and the data analysis processing is performed on the fed-back data to obtain the environmental data of the unfamiliar area.
As an optional embodiment of the present invention, acquiring the environmental data of the unfamiliar area to train the driving model may further include: determining a target database for storing corresponding position environment data according to the geographical position information of the unfamiliar area; acquiring environmental data within the historical duration of a target from a target database; and training the driving model by using the environmental data in the target historical duration.
For example, the environmental data of different areas may be obtained by analyzing images collected by image collecting devices such as cameras installed on roadsides, such as obtaining images collected by cameras installed on roadsides, analyzing data such as whether there are obstacles on a driving road of a vehicle and the types of the obstacles, and storing the analyzed data in a corresponding database. Determining a target database for storing environment data of an unfamiliar area according to the geographical location information of the unfamiliar area, acquiring the environment data of a target historical time (such as a last month or only a week) from the target database, and training the driving model by using the environment data in the target historical time. Compared with the method for acquiring the training data in real time, the method for acquiring the environmental data for training the driving model from the database saves data transmission time and improves the efficiency of model training.
And 104, performing driving control on the automatic driving vehicle by using the driving model obtained by training.
The driving model updating method provided by the invention comprises the steps of determining the driving track of the automatic driving vehicle according to the driving destination of a user, generating a region to be driven of the automatic driving vehicle according to the driving track, acquiring environmental data of an unfamiliar region to train the driving model when the region to be driven contains the unfamiliar region, and performing driving control on the automatic driving vehicle by using the driving model obtained through training. By implementing the method and the device, whether the area to be driven of the automatic driving vehicle contains a strange area or not is judged, the environment data of the strange area is obtained in time to train the driving model under the condition that the area contains the strange area, the driving model obtained after the new environment data is used for driving control over the automatic driving vehicle, and the driving safety of the automatic driving vehicle under the strange environment is ensured.
As an optional embodiment of the present invention, the method further comprises: acquiring the current position and the running speed of the automatic driving vehicle; determining a distance of the current location from the unfamiliar area; and calling processors with different processing capabilities to train the driving model according to the distance and the driving speed.
For example, the current position of the autonomous vehicle may be obtained from a positioning module installed on the autonomous vehicle, the driving speed may be determined according to a driving mode set by the autonomous vehicle, and different driving models correspond to different driving speeds or the driving speed of the vehicle may be directly obtained from a speed sensor of the vehicle. The current vehicle position and the running speed are not limited in the embodiment of the application, and can be determined by a person skilled in the art according to actual needs.
And determining the distance between the current position and the unfamiliar area according to the acquired current position of the automatic driving vehicle, and obtaining the time when the vehicle reaches the unfamiliar area according to the distance and the driving speed of the vehicle. Because the updating training of the model requires time, in order to finish the model training before the vehicle reaches the unfamiliar area, processors with different processing capacities can be selected to respond to the training operation of the driving model according to the time of the vehicle reaching the unfamiliar area, and the shorter the time of the vehicle reaching the unfamiliar area is, the stronger the processing capacity of the used processor is, so that the training operation of the driving model can be finished in time. The type of the processor is not limited in the embodiments of the present application, and a person skilled in the art may select a corresponding type of processor according to actual use requirements.
As an optional embodiment of the present invention, the method further comprises: determining the time length required by the training of the driving model; when the required training time is longer than the preset time, the running speed of the automatic driving vehicle is adjusted according to the required training time, so that the driving model training is completed before the automatic driving vehicle runs to the unfamiliar area, wherein the preset time is determined according to the distance between the current vehicle and the unfamiliar area and the current running speed of the vehicle.
For example, the duration required by the training of the driving model may be determined according to the duration of the training of the historical model, and in order to further ensure the reliable training of the driving model, the duration required by the training of the driving model is preferably set as the maximum duration required by the training of the model. When the time length required by the model training is longer than the time length required by the vehicle to reach the unfamiliar area, the driving speed of the current vehicle is reduced, so that the driving model training is completed before the automatically driven vehicle drives to the unfamiliar area, and the updated driving model can be used for driving control when the vehicle enters the unfamiliar area, so that the driving safety of the vehicle in the unfamiliar area is improved.
The embodiment of the invention also discloses a driving model updating device, as shown in fig. 2, the device comprises:
a first determination module 201, configured to determine a driving track of the autonomous vehicle according to a driving destination of the user;
the generating module 202 is configured to generate a to-be-driven area of the autonomous vehicle according to the driving track;
the first obtaining module 203 is used for obtaining environment data of an unfamiliar area to train a driving model when the area to be driven contains the unfamiliar area;
and the control module 204 is used for performing driving control on the automatic driving vehicle by using the trained driving model.
The driving model updating device provided by the invention determines the driving track of the automatic driving vehicle according to the driving destination of the user, generates the area to be driven of the automatic driving vehicle according to the driving track, acquires the environmental data of the unfamiliar area to train the driving model when the area to be driven contains the unfamiliar area, and performs driving control on the automatic driving vehicle by using the driving model obtained by training. By implementing the method and the device, whether the area to be driven of the automatic driving vehicle contains a strange area or not is judged, the environment data of the strange area is obtained in time to train the driving model under the condition that the area contains the strange area, the driving model obtained after the new environment data is used for driving control over the automatic driving vehicle, and the driving safety of the automatic driving vehicle under the strange environment is ensured.
As an optional embodiment of the present invention, the apparatus further comprises: the comparison module is used for comparing the area to be driven with the historical driving area of the automatic driving vehicle; and the judging module is used for taking the area to be driven which is not contained in the historical driving area as a strange area.
As an optional embodiment of the present invention, the first obtaining module includes: the determining submodule is used for determining a target database for storing corresponding position environment data according to the geographical position information of the unfamiliar area; the acquisition submodule is used for acquiring environmental data in the target historical duration from the target database; and the training submodule is used for training the driving model by utilizing the environmental data in the target historical duration.
As an optional embodiment of the present invention, the apparatus further comprises: the second acquisition module is used for acquiring the current position and the running speed of the automatic driving vehicle; the second determination module is used for determining the distance between the current position and the unfamiliar area; and the calling module is used for calling processors with different processing capabilities to train the driving model according to the distance and the driving speed.
As an optional embodiment of the present invention, the apparatus further comprises: the third determining module is used for determining the time length required by the training of the driving model; and the adjusting module is used for adjusting the running speed of the automatic driving vehicle according to the time length required by training when the time length required by training is greater than the preset time length, so that the driving model training is completed before the automatic driving vehicle runs to the unfamiliar area, wherein the preset time length is determined according to the distance between the current vehicle and the unfamiliar area and the current running speed of the vehicle.
An embodiment of the present invention further provides an electronic device, as shown in fig. 3, the electronic device may include a processor 401 and a memory 402, where the processor 401 and the memory 402 may be connected by a bus or in another manner, and fig. 3 takes the connection by the bus as an example.
The memory 402, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the driving model updating method in the embodiment of the present invention. The processor 401 executes various functional applications and data processing of the processor by running non-transitory software programs, instructions and modules stored in the memory 402, that is, implements the driving model updating method in the above method embodiment.
The memory 402 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor 401, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 402 may optionally include memory located remotely from processor 401, which may be connected to processor 401 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 402 and, when executed by the processor 401, perform a driving model update method as in the embodiment shown in fig. 1.
The details of the electronic device may be understood with reference to the corresponding related description and effects in the embodiment shown in fig. 1, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. A driving model updating method, characterized by comprising:
determining a driving track of the automatic driving vehicle according to the driving destination of the user;
generating a to-be-driven area of the automatic driving vehicle according to the driving track;
when the area to be driven contains an unfamiliar area, acquiring environmental data of the unfamiliar area to train a driving model;
and performing driving control on the automatic driving vehicle by using the driving model obtained by training.
2. The method of claim 1, further comprising:
comparing the area to be driven with a historical driving area of the automatic driving vehicle;
and taking the area to be driven which is not contained in the history driving area as a strange area.
3. The method of claim 1, wherein obtaining environmental data of the unfamiliar area trains a driving model, comprising:
determining a target database for storing corresponding position environment data according to the geographical position information of the unfamiliar area;
acquiring environmental data within the historical duration of a target from a target database;
and training the driving model by using the environmental data in the target historical duration.
4. The method according to any one of claims 1-3, further comprising:
acquiring the current position and the running speed of the automatic driving vehicle;
determining a distance of the current location from the unfamiliar area;
and calling processors with different processing capabilities to train the driving model according to the distance and the driving speed.
5. The method of claim 4, further comprising:
determining the time length required by the training of the driving model;
when the required training time is longer than the preset time, the running speed of the automatic driving vehicle is adjusted according to the required training time, so that the driving model training is completed before the automatic driving vehicle runs to the unfamiliar area, wherein the preset time is determined according to the distance between the current vehicle and the unfamiliar area and the current running speed of the vehicle.
6. A driving model updating apparatus characterized by comprising:
the automatic driving vehicle control system comprises a first determining module, a second determining module and a control module, wherein the first determining module is used for determining a driving track of the automatic driving vehicle according to a driving destination of a user;
the generating module is used for generating a to-be-driven area of the automatic driving vehicle according to the driving track;
the first acquisition module is used for acquiring environment data of an unfamiliar area to train a driving model when the area to be driven contains the unfamiliar area;
and the control module is used for carrying out driving control on the automatic driving vehicle by utilizing the driving model obtained by training.
7. The apparatus of claim 6, further comprising:
the second acquisition module is used for acquiring the current position and the running speed of the automatic driving vehicle;
the second determination module is used for determining the distance between the current position and the unfamiliar area;
and the calling module is used for calling processors with different processing capabilities to train the driving model according to the distance and the driving speed.
8. The apparatus of claim 7, further comprising:
the third determining module is used for determining the time length required by the training of the driving model;
and the adjusting module is used for adjusting the running speed of the automatic driving vehicle according to the time length required by training when the time length required by training is greater than the preset time length, so that the driving model training is completed before the automatic driving vehicle runs to the unfamiliar area, wherein the preset time length is determined according to the distance between the current vehicle and the unfamiliar area and the current running speed of the vehicle.
9. An electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the driving model updating method according to any one of claims 1-5.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the driving model updating method according to any one of claims 1 to 5.
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