CN111623789A - Automatic driving method and device for vehicle - Google Patents
Automatic driving method and device for vehicle Download PDFInfo
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- CN111623789A CN111623789A CN202010448143.4A CN202010448143A CN111623789A CN 111623789 A CN111623789 A CN 111623789A CN 202010448143 A CN202010448143 A CN 202010448143A CN 111623789 A CN111623789 A CN 111623789A
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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
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
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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
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3626—Details of the output of route guidance instructions
- G01C21/3641—Personalized guidance, e.g. limited guidance on previously travelled routes
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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
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3626—Details of the output of route guidance instructions
- G01C21/3647—Guidance involving output of stored or live camera images or video streams
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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
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3667—Display of a road map
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2556/00—Input parameters relating to data
- B60W2556/40—High definition maps
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Abstract
The invention provides an automatic driving method and device of a vehicle, wherein the method comprises the following steps: generating a navigation route according to the destination position and the starting position of the vehicle; when the vehicle is controlled to run according to the navigation route, reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period; calculating the driving distance of the vehicle in the next period according to the real-time speed, and determining a navigation road section in the navigation route according to the real-time position and the driving distance; and acquiring high-precision map data containing the navigation road section, and controlling the vehicle to run according to the high-precision map data. Therefore, the technical problem that in the prior art, the vehicle autonomous navigation has high requirements on vehicle configuration due to overlarge data volume and calculated amount is solved.
Description
Technical Field
The invention relates to the technical field of automatic driving automobiles, in particular to an automatic driving method and device of a vehicle.
Background
With the emergence and rapid growth of autonomous vehicles, the requirements of autonomous vehicles on navigation technology are higher and higher, and the traditional centralized cloud computing processing mode cannot meet the development speed of autonomous vehicles, so that a method for independently completing navigation by autonomous vehicles with low data and calculation amount is urgently needed to be designed.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the first objective of the present invention is to provide an automatic driving method for a vehicle, so as to achieve the effects of getting rid of cloud computing and completing navigation independently for the automatic driving vehicle.
A second object of the invention is to propose an automatic driving device of a vehicle.
A third object of the invention is to propose a computer device.
A fourth object of the invention is to propose a non-transitory computer-readable storage medium.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides an automatic driving method for a vehicle, including: generating a navigation route according to the destination position and the starting position of the vehicle; when the vehicle is controlled to run according to the navigation route, reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period; calculating the driving distance of the vehicle in the next period according to the real-time speed, and determining a navigation road section in the navigation route according to the real-time position and the driving distance; and acquiring high-precision map data containing the navigation road section, and controlling the vehicle to run according to the high-precision map data.
In order to achieve the above object, an embodiment of a second aspect of the present invention provides an automatic driving apparatus for a vehicle, including: the generating module is used for generating a navigation route according to the destination position and the starting position of the vehicle; the reading module is used for reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period when the vehicle is controlled to run according to the navigation route; the determining module is used for calculating the driving distance of the vehicle in the next period according to the real-time vehicle speed and determining a navigation road section in the navigation route according to the real-time position and the driving distance; and the control module is used for acquiring high-precision map data containing the navigation road section and controlling the vehicle to run according to the high-precision map data.
To achieve the above object, a third embodiment of the present invention provides a computer device, including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to implement the method of autonomous driving of a vehicle as described in the preceding method embodiments.
In order to achieve the above object, a fourth aspect embodiment of the present invention proposes a non-transitory computer-readable storage medium, in which instructions that, when executed by a computer device processor, enable a computer device to perform an autonomous driving method of a vehicle.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
generating a navigation route according to the destination position and the starting position of the vehicle; when the vehicle is controlled to run according to the navigation route, reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period; calculating the driving distance of the vehicle in the next period according to the real-time speed, and determining a navigation road section in the navigation route according to the real-time position and the driving distance; and acquiring high-precision map data containing the navigation road section, and controlling the vehicle to run according to the high-precision map data. Therefore, the technical problem that in the prior art, the vehicle autonomous navigation has high requirements on vehicle configuration due to overlarge data volume and calculated amount is solved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flow chart of an automatic driving method for a vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for calculating a distance traveled by a vehicle in a next cycle based on a real-time vehicle speed;
FIG. 3 is a flow chart illustrating a method for obtaining high-precision map data including navigation links
FIG. 4 is a flowchart of a method for extracting high accuracy map data within a predetermined distance range from a navigation segment from candidate high accuracy map data; and
fig. 5 is a schematic structural diagram of an automatic driving apparatus of a vehicle according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
An automatic driving method and apparatus of a vehicle according to an embodiment of the present invention will be described with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of an automatic driving method of a vehicle according to an embodiment of the present invention.
In view of the technical problems mentioned in the above technical background, an embodiment of the present invention provides an automatic driving method for a vehicle, so as to achieve the effects of enabling the automatic driving vehicle to get rid of cloud computing and independently completing navigation, as shown in fig. 1, the method includes the following steps:
specifically, a destination position and a starting point position provided by the user are acquired, and a navigation route is generated according to the position information. Wherein the user can input the locations of the destination and the starting point into the vehicle through a voice recognition system of the vehicle or a related input device; or the vehicle can obtain the starting position and the destination position by using a method of sending navigation information to the vehicle by using a terminal device or a server bound with the vehicle; of course, the third-party service platform may also generate a destination location and a starting location after receiving the travel order of the customer, so as to control the vehicle to meet the travel demand of the customer. In addition, the navigation route generated by using the destination position and the starting position of the vehicle can be one or more, if the navigation route is multiple, the multiple navigation routes are displayed for the user to select, and the navigation route selected by the user is used as the final navigation route. Meanwhile, in order to reduce unnecessary calculation, a navigation route may be generated using a destination position and a start position on a general map first.
the preset period may be understood as a time period of a specified length, or may be understood as a specified driving distance, such as 5 seconds or 500 meters. The length of the preset period may be fixed or may be changed according to a specific environment, for example, in an environment with simple road conditions, the preset period may be set a little longer; in an environment with complex road conditions, the setting of the preset period can be shorter, so that the change of the environment can be detected more accurately and timely.
Specifically, in the process of normal automatic driving of the vehicle according to the navigation route, the real-time position and the real-time speed of the vehicle are acquired by using a preset position acquisition module and a speed sensor according to a specified periodic rule. The method for obtaining the real-time position and the real-time speed of the vehicle may be a method for applying to the vehicle controller, and the vehicle controller recovers the real-time position and the real-time speed, so as to obtain the real-time position and the real-time speed of the vehicle. The position acquisition module can be a GPS module or a Beidou positioning module of the vehicle, and also can be a position detection module and the like specially arranged at a specified position, and the module firstly acquires data after the vehicle is powered on so as to ensure that the position information can be normally received, otherwise, the vehicle is forbidden to enter an automatic driving mode.
It should be noted that the time for acquiring the real-time position and the real-time vehicle speed is different according to different scenes:
in some possible examples, the real-time position and real-time vehicle speed acquisition time may be at the beginning of the cycle.
In other possible examples, the real-time position and real-time vehicle speed may be collected at half the time or distance traveled during the cycle.
In still other possible examples, the acquisition times for the real-time location and the real-time vehicle speed may be separated, the real-time location being when half the distance is traveled during the present cycle, and the real-time vehicle speed may use the average vehicle speed during the first half of the present cycle.
In still other possible examples, the high-accuracy map obtained by the vehicle may range well beyond the distance traveled in the present cycle, and the real-time location and real-time vehicle speed may be obtained at the end of the present cycle.
103, calculating the driving distance of the vehicle in the next period according to the real-time speed, and determining a navigation road section in the navigation route according to the real-time position and the driving distance;
the navigation section may be understood as a navigation route or a part of the navigation route, and the navigation section may include a section intersecting with a circle within a range of the circle whose radius is a driving distance in the following cycle with a real-time position of the vehicle as a center.
Specifically, the driving distance of the vehicle in the next period is calculated by using the obtained real-time vehicle speed and the time length of the preset period, and then the navigation road section in the navigation route is determined according to the driving distance and the real-time position of the vehicle in the next period and the generated navigation route.
It should be noted that, in different application scenarios, the running distance of the vehicle in the next period is calculated according to the real-time vehicle speed, and the following example illustrates the following:
example one:
in the present example, as shown in fig. 2, the generation of the travel distance in the next cycle requires the reference of the signal control parameter and the road environment parameter of the navigation section.
wherein the preset period is a period of designated time.
Specifically, the time length of the preset period is obtained by inquiring the preset period information, and the current real-time speed of the vehicle is obtained through analysis and calculation after data are collected through a vehicle speed sensor. And calculating a product value of the time length of the preset period and the current real-time speed of the vehicle, and taking the product value as the reference driving distance. And then, acquiring the real-time position of the vehicle through a position acquisition module, marking a circular range by taking the real-time position of the vehicle as the center and the reference driving distance as the radius, and determining the part of the navigation route, which is overlapped with the circular range, as a reference navigation road section.
And 203, acquiring a signal control parameter and a road environment parameter of the reference navigation section, adjusting the reference navigation section according to the signal control parameter and the road environment parameter, and generating the driving distance in the next period.
The signal control parameters can be understood as traffic control signals such as the number of intersections and other types of intersections of the reference navigation road section, the number of traffic lights, the duration of green lights, the duration of a cycle period and the like. The road environment parameters can be understood as the number and length of bridges, tunnels, schools, shopping malls, ascending and descending slopes with a specified gradient and the like in the reference navigation road sections, and can also include the specific conditions of traffic flow, weather, speed limit signs and the like of each reference navigation road section. The information control parameters and the road environment parameters influence the time of the automatic driving vehicle passing through the relevant road sections to a certain extent, and a degree table of influence of different information control parameters and road environment parameters obtained through a large amount of experimental data on the driving distance is stored in advance on the vehicle (the data of the table can be normalized data, and the data size is between 0 and 100 percent). In addition, the method for acquiring the signal control parameters and the road environment parameters of the navigation road section can be that the signal control parameters and the road environment parameters returned by the designated server are received by the data downloading unit after the data uploading unit of the vehicle applies for the designated server.
Specifically, the vehicle applies for the information control parameter and the road environment parameter of the reference road section from the designated server through the data uploading and downloading unit, so that the information control parameter and the road environment parameter of the fed-back reference road section are obtained, then the influence degree table of different information control parameters and road environment parameters on the reference driving distance obtained through a large amount of experimental data is inquired, the influence degree value of the information control parameters and the road environment parameters on the reference driving distance is obtained, and the product value of the influence degree value and the reference driving distance is used as the driving distance in the next period.
Example two:
in this example, the driving distance in each next cycle may be a distance that is fixed by the system according to the road condition of the navigation section. For example, in a navigation section of a full-course expressway, the travel distance in the next cycle is 50km, in a navigation section including town streets and not including country streets, the travel distance in the next cycle is 10km, in a navigation section including country streets, and the travel distance in the next cycle is 15 km.
Example three:
in this example, the travel distance in each next cycle may be set according to the average speed of the vehicle in the present cycle, and if the average speed in the present cycle is 50km/h, the travel distance in the next cycle is 50 km; if the average speed of the period is 100km/h, the driving distance in the next period is 100 km;
and 104, acquiring high-precision map data containing the navigation road section, and controlling the vehicle to run according to the high-precision map data.
The high-precision map data can be separately stored in a designated area after being cut, so that small-amount and multi-time transmission of the high-precision map data is realized.
Specifically, according to the determined navigation section, high-precision map data of each block containing the navigation section are obtained, and the vehicle is controlled to run according to the navigation section according to the high-precision map data containing the navigation section.
It should be understood that, in different application scenarios, the manner of acquiring the high-precision map data including the navigation links is different, and the following example illustrates the following:
example one:
in the present example, as shown in fig. 3, the autonomous vehicle obtains high-precision map data from the edge cloud device.
the preset distance range from the real-time position may be understood as a range of a circle covered by taking the real-time position as a center and the preset distance as a radius. The preset distance may be determined based on the travel distance in the next cycle, or may be a fixed value, or may be related to the average travel speed of the vehicle in the cycle. Meanwhile, the edge cloud equipment can be understood as a type of equipment which is arranged at a specified position and used for receiving and uploading a high-precision map within a preset distance range from the edge cloud equipment, the stored high-precision map can be issued to a specified vehicle, and high-precision map data stored by adjacent edge cloud equipment can have a superposition part, so that the vehicle can be ensured to have at least two edge clouds capable of providing high-precision map data of the current position at any place. The candidate edge cloud devices may be understood as all edge cloud devices within a preset distance range of the vehicle.
Specifically, a preset distance range is determined according to the real-time position and the preset distance, and all edge cloud devices within the preset distance range are determined as candidate edge cloud devices.
specifically, the vehicle directly applies for the candidate edge cloud equipment to obtain high-precision map data stored on the candidate edge cloud equipment, the edge cloud equipment issues the high-precision map data stored in the edge cloud equipment to a vehicle data downloading unit, and the vehicle obtains the candidate high-precision map data stored in the candidate edge cloud equipment.
And 303, extracting high-precision map data within a preset distance range from the navigation road section from the candidate high-precision map data.
The preset distance may be understood as a preset distance value. It should be noted that the preset distance is different from the preset distance range mentioned above in determining whether the edge cloud device is a candidate edge cloud device.
Specifically, high-precision map data within a preset distance range from the navigation section is extracted from the obtained multiple candidate high-precision maps. In addition, optionally, after high-precision map data containing the navigation road section is acquired, historical high-precision map data acquired in a historical period can be deleted; the user can also be reminded whether to save the high-precision map data of the navigation road section through a vehicle screen or other output devices to be used as the common navigation road section.
Example two:
in this example, after the high-precision map data is requested from the edge cloud device a plurality of times, no reply is obtained.
Specifically, if the vehicle does not receive a reply from the candidate edge cloud device after sending the request to the candidate edge cloud device for three times, the vehicle needs to apply for candidate high-precision map data on the candidate edge cloud device to the designated server, and then obtains the high-precision map data within the preset distance range from the candidate high-precision map.
Example three:
in this example as well, after requesting high-precision map data from the edge cloud device multiple times, no reply is obtained.
Specifically, if the vehicle does not receive a reply from the candidate edge cloud device after sending the request to the candidate edge cloud device for three times, the vehicle may apply for the candidate high-precision map data on the candidate edge cloud device to other surrounding vehicles equipped with the navigation function of the present invention, and further obtain the high-precision map data within the preset distance range from the navigation section from the candidate high-precision map.
It is to be understood that, after the navigation route is generated according to the destination position and the starting position of the vehicle, the obtaining of the high-precision map data of the navigation section of the vehicle in the first period can also be included.
Specifically, after the navigation route is generated, high-precision map data of the navigation section of the specified distance range is obtained for use in the first cycle. The specified distance range may be 10km or 15km, etc.
In summary, according to the automatic driving method of the vehicle of the embodiment of the present disclosure, a navigation route is generated according to the destination position and the starting position of the vehicle; when the vehicle is controlled to run according to the navigation route, reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period; calculating the driving distance of the vehicle in the next period according to the real-time speed, and determining a navigation road section in the navigation route according to the real-time position and the driving distance; and acquiring high-precision map data containing the navigation road section, and controlling the vehicle to run according to the high-precision map data. Therefore, the technical problem that in the prior art, due to the fact that data volume and calculation amount are too large, navigation of the automatic driving vehicle excessively depends on cloud computing, and autonomous navigation cannot be achieved independently is solved.
Based on the above embodiment, in different application scenarios, there are different methods for extracting high-precision map data within a preset distance range from a navigation section from candidate high-precision map data, and the following description is given with reference to an example:
example one:
in the present example, as shown in fig. 4, high-precision map data covering a preset distance range of a navigation section is found among a plurality of candidate high-precision maps.
specifically, after candidate high-precision map data in a plurality of candidate edge clouds are obtained, the candidate high-precision map data are used for matching with a navigation road section, whether a single candidate high-precision map data can completely contain the navigation road section or not is determined, if the single candidate high-precision map data exists, the single candidate high-precision map data is determined to be first target high-precision map data, and then high-precision map data within a preset distance range from the navigation road section are extracted from the first target high-precision map data.
and 405, combining the plurality of second target high-precision map data to generate third target high-precision map data, and extracting the high-precision map data within a preset distance range from the navigation road section from the third target high-precision map data.
Specifically, if there is no first target high-precision map data in which a single candidate high-precision map data can completely contain a navigation link, determining all second target high-precision map data containing a part of the navigation link, merging the plurality of second target high-precision map data to generate a third target high-precision map data, and extracting high-precision map data within a preset distance range from the navigation link from the third target high-precision map data.
Example two:
the vehicle can send range information of a preset distance away from the navigation road section of the next period to the peripheral edge cloud equipment, after the edge cloud equipment receives the range information, the edge cloud equipment judges whether the high-precision map data stored in the edge cloud equipment contains part or all of the range information, if so, the part or all of the high-precision map data containing the range information is fed back to the vehicle, and if not, an instruction which is not contained is replied. After the vehicle receives part or all of the high-precision map data containing the preset distance range of the next periodic distance navigation section, all the high-precision map data are combined to obtain a high-precision map within the preset distance range of the next periodic distance navigation section.
In conclusion, the methods for extracting the high-precision map data within the preset distance range from the navigation section from the candidate high-precision map data are various and have strong operability.
In order to realize the embodiment, the invention also provides an automatic driving device of the vehicle.
Fig. 5 is a schematic structural diagram of an automatic driving apparatus of a vehicle according to an embodiment of the present invention.
As shown in fig. 5, the automatic driving apparatus of a vehicle includes: a generating module 501, a reading module 502, a determining module 503 and a control module 504.
A generating module 501, configured to generate a navigation route according to a destination location and a starting location of a vehicle;
the reading module 502 is used for reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period when the vehicle is controlled to run according to the navigation route;
the determining module 503 is configured to calculate a driving distance of the vehicle in a next period according to the real-time vehicle speed, and determine a navigation road segment in the navigation route according to the real-time position and the driving distance;
and the control module 504 is used for acquiring high-precision map data containing the navigation road section and controlling the vehicle to run according to the high-precision map data.
In an embodiment of the present application, the control module 504 is specifically configured to: the method for acquiring high-precision map data containing a navigation road section and controlling a vehicle to run according to the high-precision map data comprises the following steps:
the control module 504 determines a preset distance range according to the real-time position and the preset distance, and determines all the edge cloud devices within the preset distance range as candidate edge cloud devices.
The vehicle control module 504 obtains high-precision map data stored on the candidate edge cloud devices by directly applying for the candidate edge cloud devices, the edge cloud devices issue the high-precision map data stored in the edge cloud devices to the vehicle data downloading unit, and the vehicle control module 504 obtains the candidate high-precision map data stored in the candidate edge cloud devices.
Among the obtained multiple candidate high-precision maps, the control module 504 extracts high-precision map data within a preset distance range from the navigation section. In addition, optionally, the control module 504 may further delete historical high-precision map data acquired in a historical period after acquiring high-precision map data including a navigation road segment; the control module 504 may also remind the user through a vehicle screen or other output device whether the high-precision map data of the navigation segment needs to be saved as a commonly used navigation segment.
It should be noted that the foregoing explanation of the embodiment of the automatic driving method for a vehicle is also applicable to the automatic driving device for a vehicle of this embodiment, and is not repeated here.
In summary, according to the automatic driving apparatus for a vehicle in the embodiment of the present disclosure, the generating module generates the navigation route according to the destination location and the starting location of the vehicle; the reading module reads the real-time position and the real-time speed of the vehicle in the current period according to a preset period when the vehicle is controlled to run according to the navigation route; the determining module calculates the driving distance of the vehicle in the next period according to the real-time speed, and determines a navigation road section in the navigation route according to the real-time position and the driving distance; the control module acquires high-precision map data containing a navigation road section and controls the vehicle to run according to the high-precision map data. Therefore, the technical problem that in the prior art, the vehicle autonomous navigation has high requirements on vehicle configuration due to overlarge data volume and calculated amount is solved.
In order to implement the foregoing embodiment, the present invention further provides a computer device, including: a processor, and a memory for storing processor-executable instructions.
Wherein the processor is configured to implement the method of autonomous driving of a vehicle as described above.
To achieve the above embodiments, the present invention also proposes a non-transitory computer-readable storage medium, in which instructions, when executed by a computer device processor, enable a computer device to perform an automatic driving method of a vehicle.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A method of automatic driving of a vehicle, comprising the steps of:
generating a navigation route according to the destination position and the starting position of the vehicle;
when the vehicle is controlled to run according to the navigation route, reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period;
calculating the driving distance of the vehicle in the next period according to the real-time vehicle speed, and determining a navigation road section in the navigation route according to the real-time position and the driving distance;
and acquiring high-precision map data containing the navigation road section, and controlling the vehicle to run according to the high-precision map data.
2. The method of claim 1, wherein the obtaining high-precision map data containing the navigation segment comprises:
determining a plurality of candidate edge cloud devices within a preset distance range from the real-time position;
acquiring candidate high-precision map data stored in the plurality of candidate edge cloud devices;
and extracting the high-precision map data within a preset distance range from the navigation road section from the candidate high-precision map data.
3. The method according to claim 2, wherein the extracting the high-precision map data within a preset distance range from the navigation section from the candidate high-precision map data includes:
obtaining candidate high-precision map data stored by each candidate edge cloud device in the plurality of candidate edge cloud devices;
judging whether first target high-precision map data containing all navigation road sections exist in the candidate high-precision map data stored by each candidate edge cloud device;
if the first target high-precision map data exists, extracting the high-precision map data within a preset distance range from the navigation road section from the first target high-precision map data;
if the candidate high-precision map data does not exist, acquiring a plurality of second target high-precision map data of the navigation road section contained in the candidate high-precision map data;
and merging the plurality of second target high-precision map data to generate third target high-precision map data, and extracting the high-precision map data within a preset distance range from the navigation road section from the third target high-precision map data.
4. The method of claim 1, wherein after the obtaining high-precision map data containing the navigation segment, further comprising:
and deleting the historical high-precision map data acquired in the historical period.
5. The method of claim 1, wherein said calculating a distance traveled by said vehicle during a next cycle based on said real-time vehicle speed comprises:
calculating a product value of the preset period and the real-time vehicle speed to obtain a reference driving distance;
determining a reference navigation road section in the navigation route according to the real-time position and the reference driving distance;
and acquiring a signal control parameter and a road environment parameter of the reference navigation section, adjusting the reference navigation section according to the signal control parameter and the road environment parameter, and generating the driving distance in the next period.
6. An automatic driving apparatus of a vehicle, characterized by comprising:
the generating module is used for generating a navigation route according to the destination position and the starting position of the vehicle;
the reading module is used for reading the real-time position and the real-time speed of the vehicle in the current period according to a preset period when the vehicle is controlled to run according to the navigation route;
the determining module is used for calculating the driving distance of the vehicle in the next period according to the real-time vehicle speed and determining a navigation road section in the navigation route according to the real-time position and the driving distance;
and the control module is used for acquiring high-precision map data containing the navigation road section and controlling the vehicle to run according to the high-precision map data.
7. The apparatus of claim 6, wherein the control module is specifically configured to:
determining a plurality of candidate edge cloud devices within a preset distance range from the real-time position;
acquiring candidate high-precision map data stored in the plurality of candidate edge cloud devices;
and extracting the high-precision map data within a preset distance range from the navigation road section from the candidate high-precision map data.
8. The apparatus of claim 6, wherein the control module is specifically configured to:
and deleting the historical high-precision map data acquired in the historical period.
9. Computer arrangement, characterized in that it comprises a memory, a processor and a computer program stored on said memory and executable on said processor, when executing said computer program, implementing an automatic driving method of a vehicle according to any of claims 1-5.
10. A non-transitory computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements an autonomous driving method of a vehicle according to any of claims 1-5.
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