CN116136409A - Driving control method, driving control system, driving control device and computer readable storage medium - Google Patents
Driving control method, driving control system, driving control device and computer readable storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of automatic driving, in particular to a driving control method, a driving control system, a driving control device and a computer readable storage medium, and aims to solve the problem of how to effectively realize the combination between manual driving and automatic driving in real time. Therefore, the method and the device can acquire the standard-precision map matching path based on the path planning request, further acquire the high-precision map matching road section included in the standard-precision map matching path, and then determine the driving mode of the vehicle based on the high-precision map matching condition of the vehicle along the current road section where the standard-precision map matching path is located. The method can realize real-time determination of which road sections can be navigated by using the high-precision map and which road sections can be navigated by using the standard-precision map, so that the vehicle can realize more effective switching between manual driving and automatic driving, the requirement of effective combination between manual driving and automatic driving is met, and the effectiveness of automatic driving is greatly improved.
Description
Technical Field
The invention relates to the technical field of automatic driving, and particularly provides a driving control method, a driving control system, a driving control device and a computer readable storage medium.
Background
The manual driving is to use the standard-definition map for navigation, and the standard-definition map is simpler and has less information. With the development of electric vehicles, automatic driving is made possible, and high-precision maps are required for automatic driving as support. The existing high-precision map does not cover all roads, so when the paths between the starting point and the end point of the vehicle are not all high-precision maps, how to realize the effective combination of manual driving and automatic driving, and how to acquire a more real-time effective high-precision map navigation path when automatic driving is applied are problems to be solved in the field.
Disclosure of Invention
The present invention has been made to overcome the above drawbacks, and provides a solution or at least partially solves the problem of how to more effectively achieve a combination of manual driving and automatic driving in real time.
In a first aspect, the present invention provides a driving control method, the method comprising:
acquiring a map matching path corresponding to the path planning request;
acquiring a high-precision map matching road section included in the standard-precision map matching path;
and determining a corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path.
In one technical scheme of the driving control method, the obtaining the high-precision map matching road section included in the standard-precision map matching path includes:
acquiring high-precision map data corresponding to the standard-precision map matching path from a high-precision map database;
and carrying out lane-level matching on the high-precision map data and the standard-precision map matching path according to preset automatic driving ODD information and lane information data contained in the high-precision map data, and obtaining a planned lane of the high-precision map matching road section.
In one technical scheme of the driving control method, the performing lane-level matching on the high-precision map data and the standard-precision map matching path according to the preset automatic driving ODD information and the lane information data included in the high-precision map data to obtain a planned lane of the high-precision map matching road section includes:
applying a pre-trained high-precision map matching model to match the lane information data with the standard-precision map matching path to obtain a matching result;
and acquiring a planning lane of the high-precision map matched road section according to the matching result, the lane information data and the automatic driving ODD information.
In one aspect of the above driving control method, the method further includes:
acquiring a standard-definition map data sample and a high-definition map data sample;
extracting features of the standard-precision map data sample and the high-precision map data sample; the characteristics extracted from the high-precision map data sample comprise lane information data;
and performing machine learning model training on the high-precision map matching model according to the extracted features to obtain a trained high-precision map matching model.
In one technical scheme of the driving control method, the determining the corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path includes:
and judging the current road section as the high-precision map matching road section, determining a driving mode as an automatic driving mode and enabling the vehicle to run according to the planned lane.
In one technical scheme of the driving control method, the determining the corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path includes:
and judging the current road section as a road section which is not matched with the high-precision map, and determining the driving mode as a manual driving mode.
In one aspect of the above driving control method, the method further includes:
the determined driving mode is presented for selection.
In one technical scheme of the driving control method, the obtaining the map matching path corresponding to the path planning request includes:
responding to a path calculation request initiated by a user, and generating a plurality of path planning requests;
aiming at each path planning request, acquiring a map matching path corresponding to the path planning request;
the obtaining the high-precision map matching road section included in the standard-precision map matching path includes:
aiming at each standard-definition map matching path, acquiring a high-definition map matching road section included in the standard-definition map matching path;
displaying a plurality of standard-definition map matching paths and high-definition map matching road sections corresponding to each standard-definition map matching path so that a user selects from the plurality of standard-definition map matching paths; wherein,,
determining a corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path corresponding to the selection result; and/or the number of the groups of groups,
the method further comprises the steps of:
when a recalculation request exists, acquiring the latest high-precision map matching road section according to the recalculation request;
and carrying out driving control according to the latest high-precision map matching road section.
In one technical scheme of the driving control method, the obtaining the map matching path corresponding to the path planning request includes:
acquiring starting point and end point information according to the path planning request;
and planning a standard-definition map path according to the starting point and the end point information so as to obtain the standard-definition map matching path.
In one technical scheme of the driving control method, the step of obtaining the high-precision map matching road section included in the standard-precision map matching path is executed by a cloud server.
In one technical scheme of the driving control method, the cloud server obtains a corresponding high-precision map database according to a vehicle-end high-precision map engine version included in the path planning request.
In a second aspect, a control device is provided, which comprises at least one processor and at least one storage device, said storage device being adapted to store a plurality of program codes, said program codes being adapted to be loaded and executed by said processor to perform the driving control method according to any one of the above-mentioned driving control methods.
In a third aspect, there is provided a computer readable storage medium having stored therein a plurality of program codes adapted to be loaded and executed by a processor to perform the driving control method according to any one of the above-described driving control methods.
In a fourth aspect, a driving control system is provided, which comprises a control device as described in the control device claim.
The technical scheme provided by the invention has at least one or more of the following beneficial effects:
in the technical scheme of implementing the invention, the standard-definition map matching path can be obtained based on the path planning request, the high-definition map matching road sections included in the standard-definition map matching path are further obtained, and then the driving mode of the vehicle is determined based on the high-definition map matching condition of the vehicle along the current road section where the standard-definition map matching path is located. Through the configuration mode, the high-precision map matching road sections contained in the standard-precision map matching path can be obtained on the basis of the path, the real-time determination of which road sections can be navigated by using the high-precision map and which road sections can be navigated by using the standard-precision map can be realized, so that the vehicle can realize more effective switching between manual driving and automatic driving, the requirement of effective combination between manual driving and automatic driving is met, and the effectiveness of automatic driving is greatly improved.
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The present disclosure will become more readily understood with reference to the accompanying drawings. As will be readily appreciated by those skilled in the art: the drawings are for illustrative purposes only and are not intended to limit the scope of the present invention. Wherein:
FIG. 1 is a flow chart of the main steps of a driving control method according to one embodiment of the present invention;
fig. 2 is a schematic diagram of the principal constituent structure of a drive control system according to an embodiment of the present invention;
FIG. 3 is a flow chart of main steps of a driving control method according to an embodiment of the present invention;
fig. 4 is a flowchart of main steps of acquiring a high-precision map matching road section included in a standard-precision map matching path according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the main component framework of model training and map matching by a high-precision map-matching model according to one implementation of an embodiment of the present invention;
FIG. 6 is a flow chart of the main steps of driving control based on a road calculation request according to an implementation of an embodiment of the invention;
fig. 7 is a schematic diagram of a map-matching path and a high-precision map-matching road section according to an example of an embodiment of the present invention.
Detailed Description
Some embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
In the description of the present invention, a "module," "processor" may include hardware, software, or a combination of both. A module may comprise hardware circuitry, various suitable sensors, communication ports, memory, or software components, such as program code, or a combination of software and hardware. The processor may be a central processor, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and/or signal processing functions. The processor may be implemented in software, hardware, or a combination of both. Non-transitory computer readable storage media include any suitable medium that can store program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, and the like. The term "a and/or B" means all possible combinations of a and B, such as a alone, B alone or a and B. The term "at least one A or B" or "at least one of A and B" has a meaning similar to "A and/or B" and may include A alone, B alone or A and B. The singular forms "a", "an" and "the" include plural referents.
Referring to fig. 1, fig. 1 is a schematic flow chart of main steps of a driving control method according to an embodiment of the present invention. As shown in fig. 1, the driving control method in the embodiment of the present invention mainly includes the following steps S101 to S103.
Step S101: and acquiring a map matching path corresponding to the path planning request.
In this embodiment, after the path planning request is acquired, the standard deviation map matching path corresponding to the path planning request may be acquired.
In one embodiment, the path planning request may be a request initiated by the vehicle to the vehicle end mark precise map navigation module. The path planning request may include start point and end point information. And planning the map path according to the start point and the end point information, so as to obtain a map matching path.
In one embodiment, the standard-definition map can be acquired through the vehicle-end standard-definition map navigation module, the vehicle-end matching module is applied, and the acquired standard-definition map is applied to obtain a matched standard-definition map matching path.
Step S102: and obtaining a high-precision map matching road section included in the standard-precision map matching path.
In the present embodiment, since not all the maps have high-precision map coverage, the high-precision map segments included on the standard-precision map matching path may be acquired based on the standard-precision map matching path. That is, it is determined which road segments are covered by the high-precision map to obtain corresponding high-precision map-matched road segments.
In one embodiment, step S102 may further include the following steps S1021 and S1022:
step S1021: and acquiring high-precision map data corresponding to the standard-precision map matching path from the high-precision map database.
In this embodiment, high-precision map data corresponding to the standard-precision map matching path may be acquired from a preset high-precision map database.
In one embodiment, the corresponding high-precision map database may be obtained according to a vehicle-end high-precision map engine version included in the path planning request. That is, the high-precision map database may include high-precision map data of different versions, so that in the process of obtaining the high-precision map matching road section, the high-precision map matching road section can be obtained based on the standard-precision map matching path without depending on a specific manufacturer even if the vehicle end is provided with high-precision map engines of different versions.
Step S1022: and carrying out lane-level matching on the high-precision map data and the standard-precision map matching path according to the preset automatic driving ODD information and the lane information data contained in the high-precision map data, and obtaining a planned lane of the high-precision map matching road section.
In the present embodiment, step S1022 may further include the following steps S10221 and S10222:
step S10221: and matching the lane information data with the standard-definition map matching path by using a pre-trained high-definition map matching model to obtain a matching result.
In this embodiment, a pre-trained high-precision map matching model may be applied to match the lane information data included in the high-precision map data with the standard-definition map matching path, thereby obtaining a plurality of matching results. In the process of matching by applying the high-precision map matching model, a plurality of matched lane information can exist for the same road section on the standard-definition map path, and lane information with different matching scores can also exist for different road sections. The matching result can be determined according to the matching score, namely, the lane information with low matching score is filtered out through the matching score, and the lane information with high matching score (such as higher than a preset threshold) is reserved. The lane information data may include information such as an attribute, a position sequence point, and a width of the lane.
In one embodiment, training of the high-precision map matching model may be performed according to the following steps S201 to S203.
Step S201: and obtaining a standard-definition map data sample and a high-definition map data sample.
Step S202: extracting features of the standard-definition map data sample and the high-definition map data sample; wherein, the characteristics extracted by the high-precision map data sample comprise lane information data.
Step S203: and performing machine learning model training on the high-precision map matching model according to the extracted features to obtain a trained high-precision map matching model.
In this embodiment, features of the standard-definition map data sample and the high-definition map data sample may be prepared, and the samples may be put into a machine learning model for training, thereby obtaining a trained high-definition map matching model.
Step S10222: and acquiring a planned lane of the high-precision map matched road section according to the matching result, the lane information data and the automatic driving ODD (Operational Design Domain, operation design domain) information.
In the present embodiment, the planned lane of the high-precision matching road section may be acquired based on the matching result, the lane information data, and the ODD information of the automatic driving. That is, the planned lane that the vehicle already included in the high-precision map matching section is traveling when performing automatic driving is returned to the user as the optimal lane navigation result, and the real-time effectiveness of performing automatic driving by applying the planned lane can be ensured. Where ODD information refers to operating conditions of the autopilot system including, but not limited to, environmental, geographic, and time constraints, and/or the presence or absence of certain traffic or road features, etc.
In one embodiment, when the planned lane of the high-precision map matching road section is obtained, the most suitable planned lane can be selected according to the information such as the start point, the end point and the like, the lane information data and the ODD information included in the path planning request. For example, the similarity, the road attribute matching degree, the matching length and other information among the paths can be comprehensively scored according to the matching result, so that the score of each lane is obtained, and the planned lane is finally determined. Wherein the comprehensive scoring may be performed by means of weighting.
Step S103: and determining a corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path.
In this embodiment, the driving mode corresponding to the vehicle may be determined according to the current road section where the vehicle travels along the map-based matching path. And whether the manual driving mode or the automatic driving mode is used can be determined according to whether the planning lanes corresponding to the high-precision map matched road sections exist in the current road section, so that the seamless combination of the manual driving and the automatic driving is realized.
In one embodiment, step S103 may further include the following step S1031.
Step S1031: and judging the current road section as a high-precision map matching road section, determining the driving mode as an automatic driving mode and enabling the vehicle to run according to the planned lane.
In the present embodiment, when it is determined that the current link is a high-definition map link, the automatic driving mode may be used so that the vehicle travels in the planned lane.
In one embodiment, step S103 may further include the following step S1032.
Step S1032: and judging that the road section is not matched with the high-precision map, and determining that the driving mode is a manual driving mode.
In the present embodiment, if the current link is not a high-precision map link, the manual driving mode may be applied.
Referring to fig. 7, fig. 7 is a schematic diagram of a map matching path and a high-precision map matching road section according to an example of the embodiment of the present invention. As shown in fig. 7, the standard-definition map matching path from the a-land to the B-land is a high-definition map matching path obtained by matching the line segments corresponding to CD and EF. In the process of traveling from the site A to the site B, on paths except for the CD and EF sections, a manual driving mode can be used for traveling along the map-matching path; in the CD and EF sections, an automatic driving mode can be used for driving along a planned lane corresponding to the high-precision map matching road section, so that effective switching between manual driving and automatic driving can be realized, and automatic driving of lane-level navigation can be realized in an area covered by the high-precision map.
In one embodiment, the autopilot mode and the manual drive mode may be presented for selection by the user. Such as on a vehicle for selection by a user.
Based on the steps S101-S103, the embodiment of the present invention can obtain the standard-definition map matching path based on the path planning request, further obtain the high-definition map matching road section included in the standard-definition map matching path, and then determine the driving mode of the vehicle based on the high-definition map matching condition of the vehicle along the current road section where the standard-definition map matching path is located. Through the configuration mode, the high-precision map matching road sections contained in the standard-precision map matching path can be obtained on the basis of the path, real-time determination of which road sections can be navigated by using the high-precision map and which road sections can be navigated by using the standard-precision map can be realized, so that a vehicle can be effectively switched between manual driving and automatic driving, the requirement of effective combination between manual driving and automatic driving is met, and the effectiveness of automatic driving is greatly improved.
In one implementation of the embodiment of the present invention, step S101 may include step S1011 and step S1012:
step S1011: a plurality of path planning requests are generated in response to a user initiated path computation request.
Step S1012: and acquiring a map matching path corresponding to the path planning request for each path planning request.
In this embodiment, when a user initiates a route calculation request, a plurality of route planning requests may be generated based on the route calculation request. If the user initiates a road calculation request from the place A to the place B, a plurality of path planning requests, such as a path planning request with the shortest running time from the place A to the place B, a path planning request with the least traffic lights from the place A to the place B, a path planning request with the largest coverage of a high-precision map from the place A to the place B, and the like, can be generated based on the road calculation request. And then based on each path planning request, obtaining a corresponding standard-definition map matching path.
In the present embodiment, step S102 may further include the following steps S1023 and S1024:
step S1023: and aiming at each standard-definition map matching path, acquiring a high-definition map matching road section included in the standard-definition map matching path.
Step S1024: and displaying the plurality of standard-definition map matching paths and the high-definition map matching road sections corresponding to each standard-definition map matching path, so that a user selects from the plurality of standard-definition map matching paths, and determining a corresponding driving mode according to the high-definition map matching condition of the current road section where the vehicle runs along the standard-definition map matching path corresponding to the selection result.
In this embodiment, each standard-definition map matching path and the high-definition map matching road section included in the standard-definition map matching path may be displayed, so as to facilitate selection by the user. If the user can select a shorter map matching path based on own preference; or selecting a map matching path with longer matching road section of the matched high-precision map, etc. The high-precision map matching road sections can be lane-level or road-level. When the user selects to finish, the corresponding driving model can be determined based on the high-precision map matching condition of the current road section where the standard-precision map matching path selected by the user runs, so as to realize driving control of the vehicle.
In one embodiment, the recalculation request may occur when a scene such as an abrupt environmental change occurs. When there is a recalculation request, the latest high-precision map matching section may be acquired according to the recalculation request, so that driving control is performed according to the latest high-precision map matching section.
In one embodiment, in order to achieve the requirements of saving the vehicle-end resources, such as the storage resources, the computing resources, and the electric quantity resources of the vehicle end, the step S102 may be deployed on a cloud server, where a high-precision map database may be disposed on the cloud server.
In one embodiment, reference may be made to fig. 2, and fig. 2 is a schematic diagram of the main constituent structure of a driving control system according to an embodiment of the present invention. As shown in fig. 2, the driving control system may include two parts, a vehicle end and a cloud end. The vehicle-end standard-definition map navigation module generates a standard-definition map path (standard-definition map matching path) based on the path planning request, and the vehicle-end matching module sends a matching request to the cloud based on the standard-definition map path and the vehicle-end high-definition map engine version. After receiving the matching request, the cloud matching service module sends the request to the cloud matching module; the cloud matching module gives a high-precision path (a high-precision map matching road section) based on a cloud high-precision map database; and returning the obtained high-precision path to the vehicle end so that the vehicle end calls a map engine to perform manual driving or automatic driving switching according to a returned result.
In one embodiment, referring to fig. 3, fig. 3 is a schematic flow chart of main steps of a driving control method according to an embodiment of the present invention. In the present embodiment, the driving control method may include the following steps S301 to S308.
Step S301: and acquiring path starting point and end point information based on the path planning request.
Step S302: planning a standard-definition map path to obtain a standard-definition map matching path
Step S303: and (5) vehicle end matching, and initiating a matching request to the cloud end.
Step S304: judging whether cloud end results exist or not; if yes, go to step S305; if not, go to step S308.
Step S305: and (5) processing a user. The user may select the presented driving model according to the need.
Step S306: and calling a high-precision map engine.
Step S307: and judging and switching between manual driving and automatic driving in real time.
Step S308: an error is returned.
In one embodiment, referring to fig. 4, fig. 4 is a schematic flow chart of main steps of obtaining a high-precision map matching road section included in a target-precision map matching path according to an embodiment of the present invention. As shown in fig. 4, acquiring the high-precision map-matching road section included in the standard-precision map-matching path may include the following steps S401 to S406.
Step S401: the matching service parses the request and looks up the corresponding map version.
Step S402: and acquiring real-time ODD information.
Step S403: and acquiring high-precision map data.
Step S404: lane level matching and path planning.
Step S405: and (5) matching and post-processing.
Step S406: and returning a matching result.
In one embodiment, reference may be made to fig. 5, and fig. 5 is a schematic diagram of a main component framework of model training and map matching by using a high-precision map matching model according to an embodiment of the present invention. As shown in fig. 5, the model training and map matching performed by the high-precision map matching model can be divided into a training phase and an online phase. And in the training stage, performing feature preparation on an SD road data offline sample (standard-definition map data sample) and an HD lane data offline sample (high-definition map data sample), and performing machine model training to obtain a training result model (a trained high-definition map matching model). In the online stage, when an online request arrives, data analysis is carried out, the obtained SD online road data (standard-definition map matching path) is put into a trained model, matching scoring is carried out on the SD online road data (standard-definition map matching path) and the SD online road data and the lane information data in an HD map database (high-definition map database), then the SD online road data enter a path planning and scoring module, and an optimal lane navigation result (a planned lane of a high-definition map matching road section) is obtained by considering ODD information to a user.
In one embodiment, referring to fig. 6, fig. 6 is a schematic flow chart of main steps of driving control based on a road calculation request according to an embodiment of the present invention. As shown in fig. 6, performing driving control based on the road calculation request may include the following steps S501 to S508.
Step S501: the user initiates a calculation request.
Step S502: and (5) processing by a cloud matching algorithm.
Step S503: and processing and visualizing cloud matching results.
Step S504: the user selects the most appropriate path.
Step S505: auxiliary driving (automatic driving) is started.
Step S506: judging whether a recalculation road is needed in the auxiliary driving process; if yes, jump to step S507; if not, go to step S508.
Step S507: and (5) processing by a cloud matching algorithm.
Step S508: the vehicle end uses the latest matching result.
It should be noted that, although the foregoing embodiments describe the steps in a specific order, it will be understood by those skilled in the art that, in order to achieve the effects of the present invention, the steps are not necessarily performed in such an order, and may be performed simultaneously (in parallel) or in other orders, and these variations are within the scope of the present invention.
It should be noted that, the data (including, but not limited to, data for analysis, stored data, displayed data, vehicle usage data, data collected by the vehicle, etc.) according to the embodiments of the present disclosure are all data fully authorized by each party. The data acquisition, collection and other actions involved in the embodiments of the present disclosure are performed after user and object authorization or after full authorization by each party.
It will be appreciated by those skilled in the art that the present invention may implement all or part of the above-described methods according to the above-described embodiments, or may be implemented by means of a computer program for instructing relevant hardware, where the computer program may be stored in a computer readable storage medium, and where the computer program may implement the steps of the above-described embodiments of the method when executed by a processor. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable storage medium may include: any entity or device, medium, usb disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier wave signals, telecommunications signals, software distribution media, and the like capable of carrying the computer program code. It should be noted that the computer readable storage medium may include content that is subject to appropriate increases and decreases as required by jurisdictions and by jurisdictions in which such computer readable storage medium does not include electrical carrier signals and telecommunications signals.
Further, the invention also provides a control device. In one control device embodiment according to the present invention, the control device includes a processor and a storage device, the storage device may be configured to store a program for executing the driving control method of the above-described method embodiment, and the processor may be configured to execute the program in the storage device, including, but not limited to, the program for executing the driving control method of the above-described method embodiment. For convenience of explanation, only those portions of the embodiments of the present invention that are relevant to the embodiments of the present invention are shown, and specific technical details are not disclosed, please refer to the method portions of the embodiments of the present invention.
The control device in the embodiment of the invention can be a control device formed by various electronic devices. In some possible embodiments, the control device may include a plurality of memory devices and a plurality of processors. And the program for executing the driving control method of the above-described method embodiment may be divided into a plurality of sub-programs, each of which may be loaded and executed by the processor to perform the different steps of the driving control method of the above-described method embodiment, respectively. Specifically, each of the subroutines may be stored in different storage devices, respectively, and each of the processors may be configured to execute the programs in one or more storage devices to collectively implement the driving control method of the above-described method embodiment, that is, each of the processors executes different steps of the driving control method of the above-described method embodiment, respectively, to collectively implement the driving control method of the above-described method embodiment.
The plurality of processors may be processors disposed on the same device, and for example, the control means may be a high-performance device composed of a plurality of processors, and the plurality of processors may be processors disposed on the high-performance device. In addition, the plurality of processors may be processors disposed on different devices, for example, the control apparatus may be a server cluster, and the plurality of processors may be processors on different servers in the server cluster.
Further, the invention also provides a computer readable storage medium. In one embodiment of the computer-readable storage medium according to the present invention, the computer-readable storage medium may be configured to store a program for executing the driving control method of the above-described method embodiment, which may be loaded and executed by a processor to implement the above-described driving control method. For convenience of explanation, only those portions of the embodiments of the present invention that are relevant to the embodiments of the present invention are shown, and specific technical details are not disclosed, please refer to the method portions of the embodiments of the present invention. The computer readable storage medium may be a storage device including various electronic devices, and optionally, the computer readable storage medium in the embodiments of the present invention is a non-transitory computer readable storage medium.
Further, the invention also provides a driving control system. In one driving control system embodiment according to the invention, the driving control system may comprise a control device of the control device embodiment.
In one embodiment, the driving control system may comprise a vehicle.
In one embodiment, a driving control system may include a vehicle and a cloud server.
Further, it should be understood that, since the respective modules are merely set to illustrate the functional units of the apparatus of the present invention, the physical devices corresponding to the modules may be the processor itself, or a part of software in the processor, a part of hardware, or a part of a combination of software and hardware. Accordingly, the number of individual modules in the figures is merely illustrative.
Those skilled in the art will appreciate that the various modules in the apparatus may be adaptively split or combined. Such splitting or combining of specific modules does not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solution after splitting or combining falls within the protection scope of the present invention.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will fall within the scope of the present invention.
Claims (14)
1. A driving control method, characterized in that the method comprises:
acquiring a map matching path corresponding to the path planning request;
acquiring a high-precision map matching road section included in the standard-precision map matching path;
and determining a corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path.
2. The method of claim 1, wherein the obtaining the high-precision map matching road segment included in the standard-precision map matching path comprises:
acquiring high-precision map data corresponding to the standard-precision map matching path from a high-precision map database;
and carrying out lane-level matching on the high-precision map data and the standard-precision map matching path according to preset automatic driving ODD information and lane information data contained in the high-precision map data, and obtaining a planned lane of the high-precision map matching road section.
3. The method according to claim 2, wherein the step of performing lane-level matching on the high-precision map data and the standard-precision map matching path according to the preset automatic driving ODD information and the lane information data included in the high-precision map data to obtain the planned lane of the high-precision map matching road section includes:
applying a pre-trained high-precision map matching model to match the lane information data with the standard-precision map matching path to obtain a matching result;
and acquiring a planning lane of the high-precision map matched road section according to the matching result, the lane information data and the automatic driving ODD information.
4. A method according to claim 3, characterized in that the method further comprises:
acquiring a standard-definition map data sample and a high-definition map data sample;
extracting features of the standard-precision map data sample and the high-precision map data sample; the characteristics extracted from the high-precision map data sample comprise lane information data;
and performing machine learning model training on the high-precision map matching model according to the extracted features to obtain a trained high-precision map matching model.
5. The method of claim 2, wherein the determining the corresponding driving mode according to the high-precision map matching condition of the current road section along which the vehicle is traveling along the standard-precision map matching path comprises:
and judging the current road section as the high-precision map matching road section, determining a driving mode as an automatic driving mode and enabling the vehicle to run according to the planned lane.
6. The method of claim 1, wherein the determining the corresponding driving mode according to the high-precision map matching condition of the current road section along which the vehicle is traveling along the standard-precision map matching path comprises:
and judging that the current road section is not the high-precision map matching road section, and determining that the driving mode is a manual driving mode.
7. The method according to claim 5 or 6, characterized in that the method further comprises:
the determined driving mode is presented for selection.
8. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the obtaining the map matching path corresponding to the path planning request comprises the following steps:
responding to a path calculation request initiated by a user, and generating a plurality of path planning requests;
aiming at each path planning request, acquiring a map matching path corresponding to the path planning request;
the obtaining the high-precision map matching road section included in the standard-precision map matching path includes:
aiming at each standard-definition map matching path, acquiring a high-definition map matching road section included in the standard-definition map matching path;
displaying a plurality of standard-definition map matching paths and high-definition map matching road sections corresponding to each standard-definition map matching path so that a user selects from the plurality of standard-definition map matching paths; wherein,,
determining a corresponding driving mode according to the high-precision map matching condition of the current road section where the vehicle runs along the standard-precision map matching path corresponding to the selection result; and/or the number of the groups of groups,
the method further comprises the steps of:
when a recalculation request exists, acquiring the latest high-precision map matching road section according to the recalculation request;
and carrying out driving control according to the latest high-precision map matching road section.
9. The method according to claim 1 or 8, wherein the obtaining a standard deviation map matching path corresponding to the path planning request comprises:
acquiring starting point and end point information according to the path planning request;
and planning a standard-definition map path according to the starting point and the end point information so as to obtain the standard-definition map matching path.
10. The method according to any one of claims 2-4, wherein the step of obtaining the high-precision map matching road segments comprised by the standard-precision map matching path is performed by a cloud server.
11. The method of claim 10, wherein the cloud server obtains a corresponding high-precision map database according to a vehicle-end high-precision map engine version included in the path planning request.
12. A control device comprising at least one processor and at least one storage device, the storage device being adapted to store a plurality of program codes, characterized in that the program codes are adapted to be loaded and executed by the processor to perform the driving control method of any one of claims 1 to 11.
13. A computer readable storage medium, in which a plurality of program codes are stored, characterized in that the program codes are adapted to be loaded and executed by a processor to perform the driving control method according to any one of claims 1 to 11.
14. A driving control system, characterized in that the system comprises the control device of claim 12.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105675000A (en) * | 2016-01-15 | 2016-06-15 | 武汉光庭信息技术股份有限公司 | Lane-level path planning method and system based on high precision map |
| CN109215487A (en) * | 2018-08-24 | 2019-01-15 | 宽凳（北京）科技有限公司 | A kind of high-precision cartography method based on deep learning |
| CN110304066A (en) * | 2019-07-22 | 2019-10-08 | 爱驰汽车有限公司 | Routing method, system, equipment and storage medium under automatic driving mode |
| CN110530393A (en) * | 2019-10-08 | 2019-12-03 | 北京邮电大学 | Lane grade paths planning method, device, electronic equipment and readable storage medium storing program for executing |
| CN112504286A (en) * | 2020-11-14 | 2021-03-16 | 武汉中海庭数据技术有限公司 | Path planning method and system based on guideline layer, server and medium |
| CN113701776A (en) * | 2021-08-27 | 2021-11-26 | 中国第一汽车股份有限公司 | Automatic driving guiding system and method |
| CN113804204A (en) * | 2021-10-28 | 2021-12-17 | 中国第一汽车股份有限公司 | Driving method and device applied to vehicle, electronic equipment and storage medium |
| CN114187412A (en) * | 2021-11-11 | 2022-03-15 | 北京百度网讯科技有限公司 | High-precision map generation method and device, electronic equipment and storage medium |
| CN114659529A (en) * | 2022-03-03 | 2022-06-24 | 江铃汽车股份有限公司 | High-precision map system of high-level automatic driving vehicle |
| CN114689069A (en) * | 2022-02-14 | 2022-07-01 | 北京百度网讯科技有限公司 | Navigation route processing method and device of automatic driving equipment and electronic equipment |
| CN114689061A (en) * | 2022-02-14 | 2022-07-01 | 北京百度网讯科技有限公司 | Navigation route processing method and device of automatic driving equipment and electronic equipment |
| CN114771534A (en) * | 2022-05-20 | 2022-07-22 | 阿波罗智能技术(北京)有限公司 | Control method, training method, vehicle, device, and medium for automatically driving vehicle |
-
2023
- 2023-04-18 CN CN202310412783.3A patent/CN116136409A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105675000A (en) * | 2016-01-15 | 2016-06-15 | 武汉光庭信息技术股份有限公司 | Lane-level path planning method and system based on high precision map |
| CN109215487A (en) * | 2018-08-24 | 2019-01-15 | 宽凳（北京）科技有限公司 | A kind of high-precision cartography method based on deep learning |
| CN110304066A (en) * | 2019-07-22 | 2019-10-08 | 爱驰汽车有限公司 | Routing method, system, equipment and storage medium under automatic driving mode |
| CN110530393A (en) * | 2019-10-08 | 2019-12-03 | 北京邮电大学 | Lane grade paths planning method, device, electronic equipment and readable storage medium storing program for executing |
| CN112504286A (en) * | 2020-11-14 | 2021-03-16 | 武汉中海庭数据技术有限公司 | Path planning method and system based on guideline layer, server and medium |
| CN113701776A (en) * | 2021-08-27 | 2021-11-26 | 中国第一汽车股份有限公司 | Automatic driving guiding system and method |
| CN113804204A (en) * | 2021-10-28 | 2021-12-17 | 中国第一汽车股份有限公司 | Driving method and device applied to vehicle, electronic equipment and storage medium |
| CN114187412A (en) * | 2021-11-11 | 2022-03-15 | 北京百度网讯科技有限公司 | High-precision map generation method and device, electronic equipment and storage medium |
| CN114689069A (en) * | 2022-02-14 | 2022-07-01 | 北京百度网讯科技有限公司 | Navigation route processing method and device of automatic driving equipment and electronic equipment |
| CN114689061A (en) * | 2022-02-14 | 2022-07-01 | 北京百度网讯科技有限公司 | Navigation route processing method and device of automatic driving equipment and electronic equipment |
| CN114659529A (en) * | 2022-03-03 | 2022-06-24 | 江铃汽车股份有限公司 | High-precision map system of high-level automatic driving vehicle |
| CN114771534A (en) * | 2022-05-20 | 2022-07-22 | 阿波罗智能技术(北京)有限公司 | Control method, training method, vehicle, device, and medium for automatically driving vehicle |
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