CN111024084A - Automatic driving method, device, equipment and storage medium for automatic driving vehicle - Google Patents
Automatic driving method, device, equipment and storage medium for automatic driving vehicle Download PDFInfo
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- CN111024084A CN111024084A CN201911303347.2A CN201911303347A CN111024084A CN 111024084 A CN111024084 A CN 111024084A CN 201911303347 A CN201911303347 A CN 201911303347A CN 111024084 A CN111024084 A CN 111024084A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
Abstract
The invention discloses an automatic driving method, device, equipment and storage medium for an automatic driving vehicle. The automatic driving method of the automatic driving vehicle comprises the following steps: acquiring vehicle position information and destination position information of an autonomous vehicle; determining at least one planned path according to the vehicle position information and the destination position information; according to a preset positioning precision situation map, screening a target planning path meeting a preset automatic driving precision requirement from at least one planning path so as to enable an automatic driving vehicle to automatically drive according to the target planning path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information. According to the embodiment of the invention, the driving efficiency of automatic driving can be improved, and the user experience is further improved.
Description
Technical Field
The invention belongs to the technical field of automatic driving, and particularly relates to an automatic driving method and device for an automatic driving vehicle, electronic equipment and a computer storage medium.
Background
Currently, a planned route may be determined according to the position of the autonomous vehicle and the position of the destination before the autonomous vehicle is autonomously driven. The position of the automatic driving vehicle can be determined through satellite positioning, and a planning path which can be passed can be determined according to the connectivity of roads or lanes in a map.
However, for autonomous vehicles, planning a path to only meet passable is not practical. If the positioning condition of a certain road section in the planned path is poor, the positioning precision requirement of automatic driving is not met, and no additional reference data exists, the automatic driving vehicle cannot continue to drive when the automatic driving vehicle drives to the position, so that the driving efficiency and the user experience of automatic driving are greatly reduced.
For example, the positioning accuracy of a tunnel in a planned path is poor, and the positioning accuracy requirement of automatic driving is not met, and an automatic driving vehicle cannot continue to drive when driving to the tunnel, so that the driving efficiency of automatic driving and the user experience are greatly reduced.
Therefore, how to improve the driving efficiency of the automatic driving and further improve the user experience is a technical problem that needs to be solved urgently by those skilled in the art.
Disclosure of Invention
The embodiment of the invention provides an automatic driving method and device for an automatic driving vehicle, electronic equipment and a computer storage medium, which can improve the driving efficiency of automatic driving and further improve the user experience.
In a first aspect, there is provided an autonomous driving method of an autonomous vehicle, the method comprising:
acquiring vehicle position information and destination position information of an autonomous vehicle;
determining at least one planned path according to the vehicle position information and the destination position information;
according to a preset positioning precision situation map, screening a target planning path meeting a preset automatic driving precision requirement from at least one planning path so as to enable an automatic driving vehicle to automatically drive according to the target planning path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information.
Optionally, the generating of the preset positioning accuracy situation map includes:
acquiring first position information of a sample automatic driving vehicle sent by a satellite and a first positioning quality factor corresponding to the first position information;
and generating a preset positioning precision situation map based on the first position information and the first positioning quality factor.
Optionally, generating a preset positioning accuracy situation map based on the first location information and the first positioning quality factor, including:
determining error data of the first position information based on a preset accurate position;
based on the error data, correcting the first position information and the first positioning quality factor, and determining second position information of the sample autonomous vehicle and a second positioning quality factor corresponding to the second position information;
and generating a preset positioning precision situation map based on the second position information and the second positioning quality factor, so that a more accurate preset positioning precision situation map can be generated.
Optionally, generating a preset positioning accuracy situation map based on the second location information and the second positioning quality factor, including:
determining the position information of the target feature point in the preset large and small area based on the second position information and the preset high-precision map;
determining relative position information of the sample automatic driving vehicle relative to the target characteristic point;
determining third position information of the sample autonomous vehicle based on the position information and the relative position information of the target feature point;
determining a third positioning quality factor corresponding to the third location information;
and generating a preset positioning precision situation map based on the third position information and the third positioning quality factor, so that a more accurate preset positioning precision situation map can be generated.
Optionally, generating a preset positioning accuracy situation map based on the third location information and the third positioning quality factor, including:
determining fourth position information of the sample autonomous vehicle and a fourth positioning quality factor corresponding to the fourth position information based on the second position information, the second positioning quality factor, the third position information and the third positioning quality factor;
and generating a preset positioning precision situation map based on the fourth position information and the fourth positioning quality factor, so that a more accurate preset positioning precision situation map can be generated.
Optionally, the generating of the preset positioning accuracy situation map includes:
acquiring road condition information of a road where a plurality of sample automatic driving vehicles are located;
and generating a preset positioning precision situation map based on the sample vehicle position information, the sample positioning quality factor and the road condition information, so that a more accurate preset positioning precision situation map can be generated.
Optionally, obtaining the traffic information of the road on which the multiple sample autonomous vehicles are located includes:
the method comprises the steps of obtaining environment information and/or road traffic state information of a road where a plurality of sample automatic driving vehicles are located, taking the environment information and/or the road traffic state information as the road traffic information, and generating a more accurate preset positioning precision situation map.
In a second aspect, there is provided an autonomous driving apparatus of an autonomous vehicle, the apparatus comprising:
a position information acquisition module for acquiring vehicle position information and destination position information of the autonomous vehicle;
the planned path determining module is used for determining at least one planned path according to the vehicle position information and the destination position information;
the target planning path determining module is used for screening a target planning path meeting the preset automatic driving precision requirement from at least one planning path according to a preset positioning precision situation map so as to enable the automatic driving vehicle to automatically drive according to the target planning path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information.
Optionally, the target planning path determining module includes:
the positioning quality factor acquisition submodule is used for acquiring first position information of the sample automatic driving vehicle sent by the satellite and a first positioning quality factor corresponding to the first position information;
and the preset positioning precision situation map generating submodule is used for generating a preset positioning precision situation map based on the first position information and the first positioning quality factor.
Optionally, the preset positioning accuracy situation map generation sub-module includes:
an error data determination unit for determining error data of the first position information based on a preset accurate position;
a position information and positioning quality factor determination unit for correcting the first position information and the first positioning quality factor based on the error data, and determining second position information of the sample autonomous driving vehicle and a second positioning quality factor corresponding to the second position information;
and the preset positioning precision situation map generating unit is used for generating a preset positioning precision situation map based on the second position information and the second positioning quality factor.
Optionally, the preset positioning accuracy situation map generating unit includes:
the position information determining subunit is used for determining the position information of the target feature point in the preset large and small area based on the second position information and the preset high-precision map;
the relative position information determining subunit is used for determining the relative position information of the sample automatic driving vehicle relative to the target characteristic point;
a third position information determination subunit for determining third position information of the sample autonomous vehicle based on the position information and the relative position information of the target feature point;
a third positioning quality factor determining subunit, configured to determine a third positioning quality factor corresponding to the third location information;
and the preset positioning precision situation map generating subunit is used for generating a preset positioning precision situation map based on the third position information and the third positioning quality factor.
Optionally, the preset positioning accuracy situation map generating subunit includes:
the position information and positioning quality factor determining secondary subunit is used for determining fourth position information of the sample automatic driving vehicle and a fourth positioning quality factor corresponding to the fourth position information based on the second position information, the second positioning quality factor, the third position information and the third positioning quality factor;
and the second-level subunit is used for generating a preset positioning precision situation map based on the fourth position information and the fourth positioning quality factor.
Optionally, the target planning path determining module includes:
the road condition information acquisition sub-module is used for acquiring the road condition information of the road where the plurality of sample automatic driving vehicles are located;
and the preset positioning precision situation map generation submodule is used for generating a preset positioning precision situation map based on the sample vehicle position information, the sample positioning quality factor and the road condition information.
Optionally, the traffic information obtaining sub-module includes:
and the road condition information acquisition unit is used for acquiring environment information and/or road traffic state information of a road where the plurality of sample automatic driving vehicles are located, and taking the environment information and/or the road traffic state information as the road condition information.
In a third aspect, an electronic device is provided, the device comprising:
a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements the autonomous driving method of the autonomous vehicle of the first aspect.
In a fourth aspect, there is provided a computer storage medium having computer program instructions stored thereon that, when executed by a processor, implement the autopilot method of an autopilot vehicle of the first aspect.
According to the automatic driving method and device for the automatic driving vehicle, the electronic equipment and the computer storage medium, the driving efficiency of automatic driving can be improved, and further user experience is improved. According to the automatic driving method of the automatic driving vehicle, a target planning path meeting the requirement of the preset automatic driving precision is screened from at least one planning path according to a preset positioning precision situation map. The preset positioning precision situation map is generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information, so that the automatic driving vehicles automatically drive according to a target planning path, the driving efficiency of automatic driving can be improved, and further the user experience is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of an autonomous driving method for an autonomous vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an automated driving process provided by one embodiment of the present invention;
fig. 3 is a schematic structural diagram of a vehicle-end device according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a sensor assembly according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an autopilot device for an autopilot vehicle according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Currently, a planned route may be determined according to the position of the autonomous vehicle and the position of the destination before the autonomous vehicle is autonomously driven. The position of the automatic driving vehicle can be determined through satellite positioning, and a planning path which can be passed can be determined according to the connectivity of roads or lanes in a map.
However, for autonomous vehicles, planning a path to only meet passable is not practical. If the positioning condition of a certain road section in the planned path is poor, the positioning precision requirement of automatic driving is not met, and no additional reference data exists, the automatic driving vehicle cannot continue to drive when the automatic driving vehicle drives to the position, so that the driving efficiency and the user experience of automatic driving are greatly reduced.
In order to solve the prior art problems, embodiments of the present invention provide an automatic driving method and apparatus for an automatic driving vehicle, an electronic device, and a computer storage medium. First, an automated driving method of an automated driving vehicle according to an embodiment of the present invention will be described. Fig. 1 is a schematic flow chart of an automatic driving method for an automatic driving vehicle according to an embodiment of the present invention. As shown in fig. 1, the automatic driving method of the automatic driving vehicle includes:
s101, vehicle position information and destination position information of the automatic driving vehicle are obtained.
The vehicle position information of the autonomous vehicle may be obtained by one or more of positioning manners such as satellite positioning, reference base station positioning, sensor positioning, and the like, and is not particularly limited. The destination location information can be obtained by recognizing the characters input by the user or by recognizing the voice of the user.
And S102, determining at least one planned path according to the vehicle position information and the destination position information.
After the vehicle position information and the destination position information are obtained, at least one planned route can be determined according to the vehicle position information and the destination position information, and the planned routes can generally guarantee that the vehicle can pass from the current vehicle position to the destination.
S103, screening a target planned path meeting the preset automatic driving precision requirement from at least one planned path according to a preset positioning precision situation map so as to enable the automatic driving vehicle to automatically drive according to the target planned path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information.
Although it is determined in step S102 that planned routes that can be generally guaranteed to be passable from the current vehicle position to the destination are generally guaranteed, any planned route is often composed of links with different positioning accuracy. The positioning accuracy of the road sections can be obtained from a preset positioning accuracy situation map, the preset positioning accuracy situation map reflects the positioning accuracy of the road section by using the position accuracy of each sample vehicle position information on the road section, and if the positioning accuracy of the road section does not meet the preset automatic driving accuracy requirement, one or more planned paths where the road section is located cannot be used as target planned paths.
In one embodiment, if the target planned path cannot be screened out according to the current preset automatic driving precision requirement, the current preset automatic driving precision requirement can be adaptively reduced, and the screening of the target planned path is performed again. The preset autopilot accuracy requirement generally corresponds to an autopilot automation level, and the higher the preset autopilot accuracy requirement, the higher the autopilot automation level correspondingly. In one embodiment, some poorly positioned road segments cannot be avoided, and the driving decision system may reduce the level of automated driving automation. For example, from L4 to L3, and prompts the driver for intervention opportunities.
In one embodiment, the autonomous driving vehicle may pre-store the preset positioning accuracy map in the vehicle-side device, and may dynamically call the pre-stored preset positioning accuracy map for positioning and autonomous driving decision making in the absence of a communication signal. In another embodiment, the preset positioning accuracy situation map may be stored in the cloud platform, and the cloud platform determines the target planning path after querying the preset positioning accuracy situation map, and issues the target planning path to the autonomous vehicle.
The preset positioning precision situation map is generated based on the sample vehicle position information of the automatic driving vehicles and the sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information, so that the automatic driving vehicles can automatically drive according to the target planning path, the driving efficiency and the safety of automatic driving can be improved, and further the user experience is improved.
In one embodiment, the generating of the preset positioning accuracy situation map generally includes: acquiring first position information of a sample automatic driving vehicle sent by a satellite and a first positioning quality factor corresponding to the first position information; and generating a preset positioning precision situation map based on the first position information and the first positioning quality factor.
In this embodiment, the first position information and the first positioning quality factor are obtained through Satellite positioning, and specifically, the first position information and the first positioning quality factor may be obtained through a Global Navigation Satellite System (GNSS). The Global NAVIGATION satellite system includes a Global Positioning System (GPS) in the united states, a Global NAVIGATION satellite system (Global NAVIGATION SATELLITE SYSTEM, GLONASS) in russia, a galileo satellite positioning system in europe, and a beidou satellite system in china. They can provide positioning, navigation and time service for various users all day around the world. However, these satellite-based positioning systems all have a certain degree of accuracy error, such as a satellite clock error, an ephemeris error, an ionosphere error, a troposphere error, etc., which causes an accuracy error in the acquired first position information and the first positioning quality factor, so that the accuracy of the preset positioning accuracy situation map generated based on the first position information and the first positioning quality factor is still deficient.
For example, after the end-of-vehicle device of the autonomous vehicle is started, the first position information is obtained by the GNSS device, and the accuracy range is usually 1-10 meters. Meanwhile, the GNSS device may calculate a first positioning quality factor of the first location information. Typically, the scale is measured in 10 points, with 1 point being the lowest and 10 points being the highest. A score of 1 indicates an accuracy of over 10 meters, and a score of 10 indicates an accuracy of around 1 meter.
To generate a more accurate preset positioning accuracy situation map, in one embodiment, the generating a preset positioning accuracy situation map based on the first location information and the first positioning quality factor generally includes: determining error data of the first position information based on a preset accurate position; based on the error data, correcting the first position information and the first positioning quality factor, and determining second position information of the sample autonomous vehicle and a second positioning quality factor corresponding to the second position information; and generating a preset positioning precision situation map based on the second position information and the second positioning quality factor.
In order to eliminate the precision error of satellite positioning, a reference base station can be introduced, and the error data of the first position information can be determined by using the precise position of the reference base station. The reference base station may be uniformly distributed within a certain range by a Real-time kinematic (RTK) technique or a Precision Point Positioning (PPP) technique. Illustratively, the vehicle communication equipment sends the first position information to the reference base station through the network, the reference base station calculates error data of the first position information according to the accurate position of the reference base station, and transmits the error data back to the vehicle communication equipment, and the vehicle communication equipment corrects the first position information and the first positioning quality factor based on the error data to obtain more accurate second position information and a second positioning quality factor. Based on the second position information and the second positioning quality factor, a more accurate preset positioning precision situation map can be generated.
In one embodiment, the process of performing automatic driving according to the preset positioning accuracy situation map is as shown in fig. 2, where an automatic driving vehicle obtains a rough position by satellite positioning, then uses a reference base station to calculate an accurate position, then plans some traversable paths, then obtains the positioning accuracy of the paths from the preset positioning accuracy situation map, and determines a driving decision for changing the paths according to the positioning accuracy.
However, even if the reference base station is introduced to determine the error data of the first position information, since the determination of the error data is affected by the surrounding environment and the communication network where the reference base station is located, for example, in some specific occasions (underground tunnels, underground parking lots, bridges, high-rise dense areas, etc.), when satellite signals and network signals are blocked or obstructed, the error data obtained through the reference base station is relatively large, and in some cases, the error data cannot be obtained, and at this time, the positioning accuracy of the autonomous vehicle cannot meet the requirement of autonomous driving at all.
In order to eliminate the influence of adverse surrounding environment on the reference base station, an Inertial Measurement Unit (IMU), a visual camera, a millimeter wave radar, a laser radar and the like can be introduced to observe the surrounding environment of the automatic driving vehicle in real time to obtain the relative positioning of the automatic driving vehicle, the satellite rough positioning and the relative positioning of the automatic driving vehicle are fused, and a high-precision map is combined to obtain a positioning result with higher precision.
To generate a more accurate preset positioning accuracy situation map, in one embodiment, the generating a preset positioning accuracy situation map based on the second location information and the second positioning quality factor generally includes: determining the position information of the target feature point in the preset large and small area based on the second position information and the preset high-precision map; determining relative position information of the sample automatic driving vehicle relative to the target characteristic point;
determining third position information of the sample autonomous vehicle based on the position information and the relative position information of the target feature point; determining a third positioning quality factor corresponding to the third location information; and generating a preset positioning precision situation map based on the third position information and the third positioning quality factor.
The target feature point may be a lane line, a stop line, a lamp post, a traffic light, a zebra crossing, or the like, and is located in a preset size area corresponding to the second position information, and the preset size area may be set by a person skilled in the art. In one embodiment, the relative position of the autonomous vehicle from the target feature point can be obtained through camera recognition, detection by a laser radar and a millimeter wave radar, and calculation by an IMU component, that is, the relative position information of the autonomous vehicle relative to the target feature point is obtained. After the relative position information is acquired, third position information of the autonomous vehicle may be determined based on the position information of the target feature point and the relative position information, wherein the position information of the target feature point may be determined by a high-precision map. In one embodiment, a third positioning quality factor corresponding to the third position information may be calculated by fusion according to the recognition accuracy of each sensor in different environments. After the third position information and the third positioning quality factor are obtained, a more accurate preset positioning precision situation map can be generated based on the third position information and the third positioning quality factor.
To generate a more accurate preset positioning accuracy situation map, in one embodiment, the generating a preset positioning accuracy situation map based on the third location information and the third positioning quality factor generally includes: determining fourth position information of the sample autonomous vehicle and a fourth positioning quality factor corresponding to the fourth position information based on the second position information, the second positioning quality factor, the third position information and the third positioning quality factor; and generating a preset positioning precision situation map based on the fourth position information and the fourth positioning quality factor.
In one embodiment, the second position information and the third position information are fused, and the fourth position information and the fourth positioning quality factor can be calculated by taking the positioning quality factors corresponding to the respective position information as reference objects. After the fourth position information and the fourth positioning quality factor are obtained, a more accurate preset positioning precision situation map can be generated based on the fourth position information and the fourth positioning quality factor.
To generate a more accurate preset positioning accuracy situation map, in one embodiment, the generation of the preset positioning accuracy situation map generally includes: acquiring road condition information of a road where a plurality of sample automatic driving vehicles are located; and generating a preset positioning precision situation map based on the sample vehicle position information, the sample positioning quality factor and the road condition information.
In one embodiment, environmental information and/or road traffic status information of a road on which a plurality of sample autonomous vehicles are located may be obtained, and the environmental information and/or the road traffic status information may be used as the road traffic information. The environment information may include environmental data such as rainfall, light intensity, visibility, weather conditions, and the like, and may be acquired by an environment sensor; the road traffic state information may reflect the congestion state of the road. In one embodiment, the planned path corresponding to the positioning quality factor with a large difference with the environmental information can be screened out, and therefore reliability is improved.
In one embodiment, a more accurate preset positioning accuracy situation map can be generated based on a large number of samples of the first to fourth position information of the autonomous driving vehicle at different moments and the corresponding first to fourth positioning quality factors and environment information. For example, the positioning situation data record table corresponding to the preset positioning accuracy situation map is shown in table 1:
TABLE 1
In one embodiment, the end-of-vehicle devices of the autonomous vehicle may be used to collect sensor-sensed ambient data, send and receive positioning accuracy data for roads and lanes, and may also be used to sense the environment surrounding the autonomous vehicle and develop environmental data and relative positioning data.
For example, as shown in fig. 3, the vehicle-end device may be composed of the following 4 parts:
a communication component: the method is used for exchanging data with a preset positioning precision situation map and a reference base station, and uploading and downloading related information.
A sensor assembly: the sensor is used for sensing external environment and comprises but is not limited to a laser radar, a visual camera, a millimeter wave radar, a rainfall sensor, a visibility sensor, a light sensor, an IMU component and the like. For example, as shown in FIG. 4, the sensor assembly includes an environmental sensing component, a lidar, a millimeter wave radar, a vision camera, and an IMU assembly.
A high-precision map component: the method is used for storing geographic information and mainly comprises a high-precision map and a feature positioning map.
A GNSS component: for receiving satellite positioning information.
In one embodiment, the accuracy of the location of the current position of the autonomous vehicle may be used to dynamically adapt the reference utilization for the fusion calculation. For example, in the case of good light, the scale factor of the visual camera is increased, and in rainy days, the scale factor of the millimeter wave radar is increased.
In one embodiment, the positioning quality factor can adopt different fusion positioning parameters according to the high, medium and low grade models of the vehicle-end equipment. For example, the scale factor of a high-grade vehicle-end device is increased, and the scale factor of a low-grade vehicle-end device is decreased.
The following describes an automatic driving apparatus, an electronic device, and a computer storage medium for an automatic driving vehicle according to embodiments of the present invention, and the automatic driving apparatus, the electronic device, and the computer storage medium for an automatic driving vehicle described below and the automatic driving method for an automatic driving vehicle described above may be referred to in correspondence with each other. Fig. 5 is a schematic structural diagram of an autopilot device of an autopilot vehicle according to an embodiment of the present invention, and as shown in fig. 5, the autopilot device of the autopilot vehicle includes:
a position information acquisition module 501 for acquiring vehicle position information and destination position information of an autonomous vehicle;
a planned path determination module 502 for determining at least one planned path according to the vehicle location information and the destination location information;
a target planned path determining module 503, configured to screen, according to a preset positioning accuracy situation map, a target planned path that meets a preset automatic driving accuracy requirement from at least one planned path, so that an automatic driving vehicle automatically drives according to the target planned path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information.
Optionally, the target planning path determining module 503 includes:
the positioning quality factor acquisition submodule is used for acquiring first position information of the sample automatic driving vehicle sent by the satellite and a first positioning quality factor corresponding to the first position information;
and the preset positioning precision situation map generating submodule is used for generating a preset positioning precision situation map based on the first position information and the first positioning quality factor.
Optionally, the preset positioning accuracy situation map generation sub-module includes:
an error data determination unit for determining error data of the first position information based on a preset accurate position;
a position information and positioning quality factor determination unit for correcting the first position information and the first positioning quality factor based on the error data, and determining second position information of the sample autonomous driving vehicle and a second positioning quality factor corresponding to the second position information;
and the preset positioning precision situation map generating unit is used for generating a preset positioning precision situation map based on the second position information and the second positioning quality factor.
Optionally, the preset positioning accuracy situation map generating unit includes:
the position information determining subunit is used for determining the position information of the target feature point in the preset large and small area based on the second position information and the preset high-precision map;
the relative position information determining subunit is used for determining the relative position information of the sample automatic driving vehicle relative to the target characteristic point;
a third position information determination subunit for determining third position information of the sample autonomous vehicle based on the position information and the relative position information of the target feature point;
a third positioning quality factor determining subunit, configured to determine a third positioning quality factor corresponding to the third location information;
and the preset positioning precision situation map generating subunit is used for generating a preset positioning precision situation map based on the third position information and the third positioning quality factor.
Optionally, the preset positioning accuracy situation map generating subunit includes:
the position information and positioning quality factor determining secondary subunit is used for determining fourth position information of the sample automatic driving vehicle and a fourth positioning quality factor corresponding to the fourth position information based on the second position information, the second positioning quality factor, the third position information and the third positioning quality factor;
and the second-level subunit is used for generating a preset positioning precision situation map based on the fourth position information and the fourth positioning quality factor.
Optionally, the target planning path determining module 503 includes:
the road condition information acquisition sub-module is used for acquiring the road condition information of the road where the plurality of sample automatic driving vehicles are located;
and the preset positioning precision situation map generation submodule is used for generating a preset positioning precision situation map based on the sample vehicle position information, the sample positioning quality factor and the road condition information.
Optionally, the traffic information obtaining sub-module includes:
and the road condition information acquisition unit is used for acquiring environment information and/or road traffic state information of a road where the plurality of sample automatic driving vehicles are located, and taking the environment information and/or the road traffic state information as the road condition information.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
The electronic device may include a processor 601 and a memory 602 storing computer program instructions.
In particular, processor 601 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits that may be configured to implement an embodiment of the present invention.
The processor 601 implements an autonomous driving method of an autonomous vehicle in any of the above embodiments by reading and executing computer program instructions stored in the memory 602.
In one example, the electronic device may also include a communication interface 603 and a bus 610. As shown in fig. 6, the processor 601, the memory 602, and the communication interface 603 are connected via a bus 610 to complete communication therebetween.
The communication interface 603 is mainly used for implementing communication between modules, apparatuses, units and/or devices in the embodiments of the present invention.
In addition, in combination with the automatic driving method of the automatic driving vehicle in the above embodiments, embodiments of the present invention may be implemented by providing a computer storage medium. The computer storage medium having computer program instructions stored thereon; the computer program instructions, when executed by the processor, implement the autopilot method of an autonomous vehicle in the embodiment shown in fig. 1.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
As described above, only the specific embodiments of the present invention are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present invention, and these modifications or substitutions should be covered within the scope of the present invention.
Claims (10)
1. An autonomous driving method of an autonomous vehicle, comprising:
acquiring vehicle position information and destination position information of an autonomous vehicle;
determining at least one planned path according to the vehicle position information and the destination position information;
according to a preset positioning precision situation map, screening a target planning path meeting a preset automatic driving precision requirement from the at least one planning path so as to enable the automatic driving vehicle to automatically drive according to the target planning path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information.
2. The autonomous driving method of an autonomous vehicle according to claim 1, characterized in that the generation of the preset positioning accuracy situational map comprises:
acquiring first position information of the sample automatic driving vehicle sent by a satellite and a first positioning quality factor corresponding to the first position information;
and generating the preset positioning precision situation map based on the first position information and the first positioning quality factor.
3. The autonomous driving method of an autonomous vehicle according to claim 2, characterized in that said generating the preset positioning accuracy situational map based on the first location information and the first positioning quality factor comprises:
determining error data of the first position information based on a preset accurate position;
based on the error data, correcting the first position information and the first positioning quality factor, and determining second position information of the sample autonomous vehicle and a second positioning quality factor corresponding to the second position information;
and generating the preset positioning precision situation map based on the second position information and the second positioning quality factor.
4. The autonomous driving method of an autonomous vehicle according to claim 3, wherein said generating the preset positioning accuracy situational map based on the second location information and the second positioning quality factor comprises:
determining the position information of the target feature point in a preset large and small area based on the second position information and a preset high-precision map;
determining relative position information of the sample autonomous vehicle relative to the target feature point;
determining third position information of the sample autonomous vehicle based on the position information of the target feature point and the relative position information;
determining a third positioning quality factor corresponding to the third location information;
and generating the preset positioning precision situation map based on the third position information and the third positioning quality factor.
5. The autonomous driving method of an autonomous vehicle according to claim 4, characterized in that said generating the preset positioning accuracy situational map based on the third position information and the third positioning quality factor comprises:
determining fourth position information of the sample autonomous vehicle and a fourth positioning quality factor corresponding to the fourth position information based on the second position information, the second positioning quality factor, the third position information, and the third positioning quality factor;
and generating the preset positioning precision situation map based on the fourth position information and the fourth positioning quality factor.
6. The automated driving method of an autonomous vehicle according to any of claims 1 to 5, characterized in that the generation of the preset positioning accuracy map comprises:
acquiring road condition information of a road where a plurality of sample automatic driving vehicles are located;
and generating the preset positioning precision situation map based on the sample vehicle position information, the sample positioning quality factor and the road condition information.
7. The method of claim 6, wherein the obtaining the traffic information of the road on which the sample autonomous vehicles are located comprises:
and acquiring environment information and/or road traffic state information of a road where a plurality of sample automatic driving vehicles are located, and taking the environment information and/or the road traffic state information as the road condition information.
8. An autopilot device for an autopilot vehicle, comprising:
a position information acquisition module for acquiring vehicle position information and destination position information of the autonomous vehicle;
the planned path determining module is used for determining at least one planned path according to the vehicle position information and the destination position information;
the target planning path determining module is used for screening a target planning path meeting the preset automatic driving precision requirement from the at least one planning path according to a preset positioning precision situation map so as to enable the automatic driving vehicle to automatically drive according to the target planning path; the preset positioning precision situation map is a situation map generated based on sample vehicle position information of a plurality of sample automatic driving vehicles and sample positioning quality factors corresponding to the sample vehicle position information, and the sample positioning quality factors represent the position precision of the corresponding sample vehicle position information.
9. An electronic device, characterized in that the device comprises: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements an autonomous driving method of an autonomous vehicle as claimed in any of claims 1-7.
10. A computer storage medium having computer program instructions stored thereon that, when executed by a processor, implement an autonomous driving method of an autonomous vehicle as claimed in any of claims 1-7.
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