CN112960000A - High-precision map updating method and device, electronic equipment and storage medium - Google Patents
High-precision map updating method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of unmanned vehicles, automatic driving and unmanned driving, and provides a high-precision map updating method, device, electronic equipment and storage medium for an unmanned vehicle, which can acquire images acquired by the unmanned vehicle in real time in the driving process; if the comparison result of the image and the historical image in the high-precision map is that the change of the map elements exceeds the range of a preset threshold value, automatically updating the high-precision map by the image corresponding to the map elements; if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle to continue to automatically drive and acquire images in real time; or if the driving road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle to drive and acquiring the image in real time, continuously comparing the acquired image with the historical image in the high-precision map, and judging whether the high-precision map is updated or not. Therefore, the utilization rate and the operation efficiency of the unmanned vehicle can be improved, and the accuracy of high-precision map updating is improved.
Description
Technical Field
The disclosure relates to the technical field of unmanned vehicles, automatic driving and unmanned driving, in particular to a high-precision map updating method and device for the unmanned vehicles, electronic equipment and a storage medium.
Background
The updating of the current front-loading map is generally that a driver manually downloads the latest map at a certain time, or a system pushes the latest map of the whole province or city to update at a certain time.
The traditional technology has the following technical problems:
the current map updating method of the prior device leads to poor map updating real-time performance, the map cannot be updated in time during the driving process of a vehicle, and the road condition can be judged by a driver according to the actual condition. When the vehicle is driven automatically without the operation of a driver, if the map is not updated in time, the judgment of the vehicle-mounted computer is influenced, and the driving safety is easily caused.
The unmanned driving integrates a plurality of technologies such as automatic control, a system structure, artificial intelligence, visual calculation and the like, and is a product of high development of computer science, mode recognition and intelligent control technologies. The unmanned automobile senses the road environment through the vehicle-mounted sensing system according to the high-precision map, automatically plans the driving route and controls the automobile to reach a preset target, and therefore the development of the unmanned technology is related to the accuracy of the high-precision map.
For the initial collection, a person is required to remotely control the vehicle by using a remote controller on site to collect data or a remote driving system is used to collect data, so that the labor cost is increased, and the safety problem can be caused if the data is collected on a public road. Furthermore, with the rapid development of urban traffic, municipal construction or road maintenance are frequently used, and the map is not updated timely, which also affects the judgment of the vehicle-mounted terminal and easily causes traffic safety. When data acquisition is carried out by utilizing unmanned vehicle automatic driving, the existing unmanned vehicle cannot automatically sense and judge the environmental change, the problem occurs in the automatic driving under the unknown condition, the danger is also improved, and the automatic driving of the automatic driving vehicle is required to be degraded to driving assistance or manual take over, so that the automatic driving realization degree of the automatic driving vehicle is low.
Disclosure of Invention
In order to solve the technical problems, the present disclosure provides a high-precision map updating method and apparatus for an unmanned vehicle, an electronic device, and a storage medium, which can detect a change in a field environment in real time by using an autonomous driving of the unmanned vehicle and automatically trigger an update of a high-precision map, thereby improving a utilization rate and an operating efficiency of the unmanned vehicle, and improving an accuracy of the update of the high-precision map.
In one aspect, the present disclosure provides a high-precision map updating method for an unmanned vehicle, including:
the unmanned vehicle pulls a local high-precision map and runs in an automatic driving mode according to the high-precision map;
acquiring an image acquired by the unmanned vehicle in real time in the driving process;
comparing the image with the historical image in the high-precision map to generate a comparison result;
if the comparison result shows that the map element change on the driving road exceeds the range of a preset threshold value, automatically updating the high-precision map by the image corresponding to the map element;
if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle to continue to drive in the automatic driving mode and acquiring images in real time; and if the driving road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle to drive and acquiring images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether to update the high-precision map.
Preferably, the map elements include at least: road lane lines, traffic lights, flow guide belts, pedestrian crossing lines, stop lines, guardrails, kerbs, light poles, sewer openings, building signs and overpasses,
the map element change exceeding a preset threshold range includes:
at least one of the aforementioned road lane lines, traffic lights, flow guide belts, pedestrian crossing lines, stop lines, guardrails, curbs, light poles, sewer openings, building signs and overpasses is changed.
Preferably, the case where the aforementioned automatic driving condition is not satisfied includes at least one of:
the map elements cannot be identified under the current light condition;
the current weather conditions cannot identify roads;
the unmanned vehicle cannot automatically identify and plan a driving route under the condition of complicated current roads.
Preferably, before the step of the unmanned vehicle pulling the local high-precision map, the high-precision map updating method further includes:
receiving remote control, and acquiring images in real time during the driving process of the unmanned vehicle along the road; and
and manufacturing the high-precision map according to the acquired image.
Preferably, if the driving road in the updated high-precision map does not satisfy the automatic driving condition, the step of remotely controlling the unmanned vehicle to drive and acquiring the image in real time comprises:
if the updated running road in the high-precision map does not meet the automatic driving condition, sending an inquiry request to a server for inquiring whether the server is switched from automatic driving to remote control driving;
and after receiving a response of switching to remote control driving, receiving remote control of the server, and enabling the unmanned vehicle to run and acquire images in real time.
Preferably, after the comparison result is generated, the high-precision map updating method further includes:
and if the comparison result shows that the change of the map elements on the driving road does not exceed the range of the preset threshold value, automatically storing the images into the image set corresponding to the map elements in the high-precision map.
Preferably, the step of remotely controlling the unmanned vehicle to travel and acquiring an image in real time if the travel road in the updated high-precision map does not satisfy the automatic driving condition further includes:
and if the unmanned vehicle determines that the automatic driving condition is met again in the process of remote control driving, switching back to automatic driving.
In another aspect, the present disclosure provides a high-precision map updating apparatus for an unmanned vehicle, the high-precision map updating apparatus including an acquisition module installed on the unmanned vehicle, wherein the high-precision map updating apparatus is configured to execute the high-precision map updating method.
Preferably, the aforementioned acquisition module comprises: the system comprises a binocular camera, a laser radar, a global positioning system and an inertia measurement unit;
or, the aforementioned acquisition module includes: monocular cameras, lidar, global positioning systems, and inertial measurement units.
In another aspect, the present disclosure also provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor,
the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the high-precision map updating method.
Yet another aspect the present disclosure also provides a non-transitory computer readable storage medium storing computer instructions for causing the aforementioned computer to execute the aforementioned high precision map updating method.
The beneficial effects of this disclosure are: according to the high-precision map updating method and device for the unmanned vehicle, the electronic equipment and the storage medium, an automatic driving function of the unmanned vehicle can be used for carrying an (image) acquisition module, a local high-precision map is pulled by the unmanned vehicle, and the image is acquired in real time according to the fact that the unmanned vehicle runs in an automatic driving mode; comparing the real-time collected images with historical images in a high-precision map, and using the generated comparison result to judge the change of map elements in the driving road; if the comparison result shows that the map element change on the driving road exceeds the range of the preset threshold value, the high-precision map is automatically updated by the image corresponding to the map element, so that the utilization rate and the operation efficiency of the unmanned vehicle are improved, and the updating accuracy of the high-precision map is improved; if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle to continue to drive in the automatic driving mode and acquiring images in real time; and if the driving road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle to drive and acquiring images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether to update the high-precision map. Therefore, flexible switching between automatic driving and remote driving is achieved, and the operation efficiency and safety of the unmanned vehicle are further improved.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of the embodiments of the present disclosure with reference to the accompanying drawings.
FIG. 1 shows a schematic diagram of a prior art remote controlled drive with an unmanned vehicle;
fig. 2 is a schematic structural diagram of a high-precision map updating device for an unmanned vehicle according to a first embodiment of the disclosure;
fig. 3 is a schematic flow chart illustrating a high-precision map updating method for an unmanned vehicle according to a second embodiment of the present disclosure;
fig. 4 is a schematic flow chart of a high-precision map updating method for an unmanned vehicle according to a third embodiment of the present disclosure;
fig. 5 is a schematic flow chart illustrating a high-precision map updating method for an unmanned vehicle according to a fourth embodiment of the present disclosure;
fig. 6 shows a schematic flow chart of a high-precision map updating method for an unmanned vehicle according to a fifth embodiment of the present disclosure;
fig. 7 shows a schematic flow chart of a high-precision map updating method for an unmanned vehicle according to a sixth embodiment of the present disclosure;
fig. 8 is a schematic flow chart illustrating a high-precision map updating method for an unmanned vehicle according to a seventh embodiment of the present disclosure;
fig. 9 shows a schematic structural diagram of a server according to an eighth embodiment of the present disclosure.
Detailed Description
To facilitate an understanding of the present disclosure, the present disclosure will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present disclosure are set forth in the accompanying drawings. However, the present disclosure may be embodied in different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used in the description of the disclosure herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure.
According to the related art, referring to fig. 1, in the prior art, the remote driving of the unmanned vehicle can share the dynamic state of the unmanned vehicle 10 to the cloud through a server 20 by using a GPS module and a signal transmission module mounted on the unmanned vehicle 10, so as to share information of other remote terminals 30 (which may be mobile device terminals, vehicle-mounted terminals, data processing consoles, etc.), and when the driving environment of the unmanned vehicle 10 is complex and automatic driving cannot be directly completed according to navigation of a high-precision map, the signal transmission of the remote terminal 30 is required, the server 20 is used for signal transfer, and remote control driving of the unmanned vehicle 10 is completed based on an image acquired by the unmanned vehicle 10 in real time.
The high-precision map is the basis for realizing automatic driving, and along with the development of the automatic driving technology, the high-precision map technology is also rapidly developed. Compared with the traditional high-precision map, the high-precision map has richer and more detailed information such as roads and traffic signs, and can reflect the real condition of the roads more accurately. Compared with the traditional high-precision map, the high-precision map has more layers and more fine layer content, and for example, map elements contained in the high-precision map can be as follows: lane lines, roadside landmarks, guard rails, overhead objects, sewer ports and the like have huge data volume due to the rich information content of high-precision maps. For example, the position or the attribute of a traffic board in a city is changed, for example, a square traffic board is originally arranged at the position A and used for indicating the speed limit of 40km/h, and then the square traffic board is changed into a hexagonal traffic board and used for indicating the speed limit of 60 km/h; in order to ensure the safe driving of the automatic driving automobile, the high-precision map not only covers the map information accurately and comprehensively, but also ensures that the later data can be updated quickly and accurately.
When data acquisition is carried out by utilizing unmanned vehicle automatic driving, the existing unmanned vehicle cannot automatically sense and judge the environmental change, the problem occurs in the automatic driving under the unknown condition, the danger can be improved along with the problem, and the automatic driving of the automatic driving vehicle is required to be degraded to driving assistance or manual take-over, so that the realization degree of the automatic driving vehicle is low.
Based on this, the high-precision map updating method and device for the unmanned vehicle, the electronic device and the storage medium provided by the embodiment of the disclosure can not only improve the utilization rate and the operation efficiency of the unmanned vehicle and improve the accuracy of high-precision map updating, but also realize flexible switching between automatic driving and remote driving so as to further improve the operation efficiency and the safety of the unmanned vehicle, thereby reducing the loss and the cost.
[ term interpretation ]
And (3) target detection algorithm: the image is divided according to the grid window according to the identification result, then the image blocks of each grid window are subjected to threshold value removal to remove the target window with low possibility, and then NMS removes the redundant window, a plurality of elements (objects) are identified for the image blocks of the rest grids by utilizing a feature comparison algorithm, and the coordinate information of different elements (objects) is positioned based on the static reference coordinate. The target detection algorithm is common in the process of collecting environment data by the unmanned vehicle, and the high-precision map is manufactured and/or updated according to the comparison result of the image data containing map elements in the driving road and the historical image data in the high-precision map by the unmanned vehicle in the embodiment of the disclosure.
Point cloud matching algorithm: the point cloud matching algorithm is used for matching two frames of point cloud data so as to obtain pose difference before and after a sensor (laser radar or camera), namely mileage data. In the embodiment of the present disclosure, point cloud data (based on image data including one or several map elements at a certain position) of a current laser frame is converted into a reference frame coordinate system (based on the same geographic position or image data including the same map elements in a high-precision map), iterative calculation of a conversion matrix is used to determine whether information of each map element and each corresponding map element changes, and updating of the high-precision map is completed according to the change.
Map elements:
corresponding to the recognition and classification results of various object types in the image frame of the high-precision map, the map elements contained in the high-precision map can be: lane lines, traffic lights, guard rails, street lamp posts, building signs and the like.
The present disclosure is described in detail below with reference to the accompanying drawings.
The first embodiment is as follows:
fig. 2 shows a schematic structural diagram of a high-precision map updating device for an unmanned vehicle according to a first embodiment of the present disclosure.
Referring to fig. 2, in a high-precision map updating apparatus 100 for an unmanned vehicle according to a first embodiment of the present disclosure, the high-precision map updating apparatus 100 includes an acquisition module 110 installed on the unmanned vehicle 10, and is capable of pulling a local high-precision map, enabling the unmanned vehicle 10 to run in an automatic driving mode according to the high-precision map, and controlling the unmanned vehicle 10 to perform commercial operation during running, and detecting and updating map information on an operation route maintained in the high-precision map. The acquisition module 110 is configured to acquire image data acquired by the unmanned vehicle 10 in real time during the driving process according to the high-precision map, and the high-precision map updating apparatus 100 compares the acquired image data with historical image data in the high-precision map, and determines whether the change of the map elements on the driving road exceeds a preset threshold range according to the comparison result, so as to determine whether to update the high-precision map according to the image data of the map elements.
In this embodiment, the high-precision map updating apparatus 100 may process the image data acquired by the acquisition module 110, detect the image recognition information and the posture information of one map element in the acquired image data based on a target detection algorithm and a point cloud matching algorithm, and determine whether the image recognition information and the posture information of the same map element on the high-precision map are the same.
Optionally, the map elements at least comprise: road lane line, traffic lights, water conservancy diversion area, pedestrian crossing line, stop line, guardrail, curb, light pole, offal road junction, building sign and overpass to, the change of aforementioned map element can include beyond the preset threshold value scope:
at least one of the aforementioned road lane lines, traffic lights, flow guide belts, pedestrian crossing lines, stop lines, guardrails, curbs, light poles, sewer openings, building signs and overpasses is changed.
In this embodiment, the high-precision map updating apparatus 100 may further return the captured image data (image identification information and posture information of the same map element) to a server to automatically update the high-precision map with an image corresponding to the map element when the comparison result indicates that the change of the map element on the traveling road is beyond a preset threshold range, that is, when the image identification information and posture information of one map element in the captured image data are not identical to the history image identification information and posture information of the same map element on the high-precision map, or when the comparison result indicates that the change of the map element on the traveling road is not beyond the preset threshold range, that is, when the image identification information and posture information of one map element in the captured image data are identical to the history image identification information and posture information of the same map element on the high-precision map, and storing the acquired image data into a historical image data set corresponding to the map elements so as to increase a feature library corresponding to each map element in the high-precision map and improve the accuracy of data updating and monitoring.
In this embodiment, the problem that the image data of a certain map element acquired by the acquisition module 110 has an error is avoided. The high-precision map updating device 100 stores a preset number, and when it is determined that the image data of the map element changes according to the above process, if the number of the changed image data of the map element is greater than the preset number, that is, the image data of the map element is different from the preset data of the map element in the high-precision map, the changed image data of the map element is reported to the server, and it is determined that the image data of the map element in the high-precision map needs to be updated, the preset image data of the map element in the high-precision map is replaced with the image data acquired this time.
And if the map element does not exist in the high-precision map, the map element is a newly added object in the high-precision map, and the image data of the map element is added into the high-precision map. Specifically, the manner of adding the image data of the map element in the high-precision map may be the same as the manner of replacing the image data of the map element in the high-precision map described above.
It is conceivable that, if the high-precision map updating apparatus 100 acquires a map element that is not already stored in the map among the plurality of map elements, it is determined that the already stored map element in the high-precision map is deleted, and the preset image data of the already stored map element in the high-precision map may be deleted.
In this embodiment, after the preset data of the map elements in the high-precision map is updated, the high-precision map may be updated. In particular, map elements may be added, deleted or modified in the map.
Optionally, the acquisition module 110 includes: a binocular camera, a laser radar, a Global Positioning System (GPS for short), an Inertial measurement unit (IMU for short), and a synchronous control System. These devices are mounted inside the unmanned vehicle 10 or on the roof deck; alternatively, the aforementioned acquisition module 110 includes: monocular cameras, lidar, global positioning system GPS, and Inertial Measurement Units (IMU).
The binocular camera (or the monocular camera) is used for acquiring images of map elements on the road; the laser radar is used for collecting original point cloud data; the GPS is used to measure the position of the unmanned vehicle 10 at various times; the IMU is used for measuring the attitude of the unmanned vehicle 10 at each moment; the synchronous control system is used for aligning the data acquired or measured by the components by taking time as a basis.
In practical applications, the camera may be mounted on the roof or front area of the unmanned vehicle 10 to capture image data (attitude information of each map element and its corresponding image data) on the road on which the vehicle is traveling. For example, a camera is installed on the roof of the unmanned vehicle 10, and during the driving process of the unmanned vehicle 10, image data corresponding to each map element on the vehicle advancing road can be collected, and the attitude information corresponding to each map element can be determined through a laser radar.
In this embodiment, the high-precision map updating apparatus 100 may acquire image data of a map element through a binocular camera, or may acquire point cloud data corresponding to the image data of the map element on a driving road through a laser radar, to obtain a point cloud data set, and record an acquisition time of the image and an acquisition time of the point cloud data set during the process of acquiring the image and the point cloud data set. And finally, obtaining the recognition matching result of the homonymous feature points by using a stereo intersection technology, and determining the posture information and the image information of the map element according to the geographic coordinates of the homonymous feature points. The laser point cloud data refers to a set of vectors in a three-dimensional coordinate system, and the point cloud data set is a set formed by laser point cloud data with the same acquisition time. Because the laser point cloud data has the characteristics of high precision, small influence caused by measuring distance and the like, the accuracy of determining the spatial position and the posture information of the map element by combining the laser point cloud data is higher.
In the present embodiment, the high-accuracy map updating apparatus 100 may further determine whether the current travel road satisfies the automatic driving condition based on the updated high-accuracy map, wherein the case where it is determined that the unmanned vehicle 10 does not satisfy the automatic driving condition includes at least one of:
the aforementioned image data indicates that a road on the aforementioned high-precision map does not exist;
the aforementioned image data indicates that the road on the aforementioned high-precision map is closed;
the aforementioned image data indicates that the aforementioned road on the high-precision map is damaged;
the image data indicates that an obstacle is present on the road on the high-precision map, and the remaining width blocked by the obstacle is not enough for the unmanned vehicle 10 to pass through;
the map elements cannot be identified under the current light condition;
the current weather conditions cannot identify roads;
the unmanned vehicle 10 cannot automatically recognize a planned driving route due to the complicated current road conditions.
Optionally, if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle 10 to continue to drive in the automatic driving mode and acquire the image in real time; and if the running road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle 10 to run and acquiring images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether to update the high-precision map.
Optionally, in this embodiment, the high-precision map updating apparatus 100 may further request remote control driving from a server when the driving road in the updated high-precision map does not satisfy the automatic driving condition of the unmanned vehicle 10, and after receiving a response to switch to the remote control driving, control driving of the unmanned vehicle 10 with a remote terminal, and repeatedly acquire images; and then, whether the high-precision map is updated or not is judged according to comparison between the image and the historical image in the high-precision map, so that flexible switching between automatic driving and remote driving is realized, and the operating efficiency and the safety of the unmanned vehicle 10 are improved.
Optionally, in this embodiment, the high-precision map updating apparatus 100 may further maintain the automatic driving of the unmanned vehicle 10 based on the high-precision map data when the repeatedly acquired image data meets the automatic driving condition of the unmanned vehicle 10, so as to further realize flexible switching between the automatic driving and the remote driving, so as to improve the operation efficiency and the safety of the unmanned vehicle 10.
In this embodiment, the high-precision map updating apparatus 100 may further receive remote control, so that the unmanned vehicle 10 acquires image data in real time during the driving process along the road, reports the image data to the server, manufactures a high-precision map by using the acquired image data, carries an operation route on which an acquisition module periodically reciprocates by using an automatic driving function of the high-precision map, and automatically triggers updating of the high-precision map by detecting a change in a field environment in real time, so that the high-precision map may be manufactured/updated by using the remotely driven unmanned vehicle 10 according to the environment data acquired during the driving process, and then is imported onto the unmanned vehicle 10, thereby improving the utilization rate and the operation efficiency of the unmanned vehicle 10.
Example two:
fig. 3 shows a flow chart of a high-precision map updating method for an unmanned vehicle according to a second embodiment of the present disclosure.
Referring to fig. 3, a high-precision map updating method for an unmanned vehicle according to a second embodiment of the present disclosure includes:
the unmanned vehicle pulls a local high-precision map and runs in an automatic driving mode according to the high-precision map;
acquiring an image acquired in real time in the driving process of the unmanned vehicle;
comparing the image with the historical image in the high-precision map to generate a comparison result;
if the comparison result shows that the map element change on the driving road exceeds the range of a preset threshold value, automatically updating the high-precision map by the image corresponding to the map element;
if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle to continue to drive in the automatic driving mode and acquiring images in real time; and if the driving road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle to drive and acquiring images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether to update the high-precision map.
With reference to the description of the first embodiment, in the second embodiment, the unmanned vehicle 10 may pull a local high-precision map, and enable the unmanned vehicle 10 to run in an automatic driving mode according to the high-precision map, the unmanned vehicle 10 may perform commercial operation during running, perform real-time detection and update on map information on an operation route maintained in the high-precision map, the unmanned vehicle 10 may acquire image data in real time through a camera during running, and determine, based on a target detection algorithm and a point cloud matching algorithm, attitude information of a map element on the high-precision map corresponding to the acquired image data, and determine whether the acquired image data is identical to historical image identification information and attitude information of the same map element on the high-precision map or not, in combination with laser radar and the like acquisition of laser point cloud data corresponding to each map element. And when the comparison result shows that the map element change on the driving road exceeds the range of a preset threshold value, the acquired image data (the image identification information and the posture information of the same map element) are transmitted back to a server, and the high-precision map is automatically updated by the image corresponding to the map element; or when the comparison result shows that the change of the map elements on the driving road does not exceed the range of the preset threshold value, the acquired image data is stored in the historical image data set corresponding to the map elements so as to increase the feature library of the corresponding map elements in the high-precision map and improve the accuracy of data updating.
In this embodiment, the high-precision map updating apparatus 100 may further determine whether the current driving road meets the automatic driving condition based on the updated high-precision map, and if the driving road in the updated high-precision map meets the automatic driving condition, enable the unmanned vehicle 10 to continue the automatic driving and acquire an image in real time; and if the running road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the driving unmanned vehicle 10 to acquire images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether to update the high-precision map.
In the present embodiment, the problem of error in the image data of a certain map element acquired by the acquisition module 110 is avoided. The high-precision map updating device 100 stores a preset number, and when it is determined that the image data of the map element changes according to the above process, if the number of the changed image data of the map element is greater than the preset number, that is, the image data of the map element is different from the preset data of the map element in the high-precision map, the changed image data of the map element is reported to the server, and it is determined that the image data of the map element in the high-precision map needs to be updated, the preset data of the map element in the high-precision map is replaced with the image data acquired this time.
And if the map element does not exist in the high-precision map, the map element is a newly added object in the high-precision map, and the image data of the map element is added into the high-precision map. Specifically, the manner of adding the image data of the map element in the high-precision map may be the same as the manner of replacing the image data of the map element in the high-precision map described above.
It is conceivable that, if the high-precision map updating apparatus 100 acquires a map element that is not already stored in the map among the plurality of map elements, it is determined that the already stored map element in the high-precision map is deleted, and the preset data of the deleted already stored map element in the high-precision map may be deleted.
In this embodiment, after the preset data of the map elements in the high-precision map is updated, the high-precision map may be updated. In particular, map elements may be added, deleted or modified in the map.
Based on the present embodiment, when it is determined based on the updated high-precision map that the acquired image data satisfies the automatic driving condition of the unmanned vehicle 10, the automatic driving of the unmanned vehicle 10 is maintained based on the high-precision map data, or when the acquired image data does not satisfy the automatic driving condition of the unmanned vehicle 10, the driving of the unmanned vehicle 10 is controlled by a remote terminal, the image data is continuously acquired in real time, and the comparison between the image and the historical image in the high-precision map is repeatedly performed to determine whether to update the high-precision map, thereby realizing the flexible switching between the automatic driving and the remote driving to improve the operation efficiency and the safety of the unmanned vehicle 10, or when the acquired image data satisfies the automatic driving condition of the unmanned vehicle 10, the automatic driving of the unmanned vehicle 10 is continuously maintained, and the labor cost can be saved to a certain extent, the work efficiency is improved, and the safety of the unmanned vehicle 10 in operation is improved.
Example three:
fig. 4 shows a flow chart of a high-precision map updating method for an unmanned vehicle according to a third embodiment of the present disclosure.
The third embodiment of the present disclosure correspondingly provides a high-precision map updating method for an unmanned vehicle, as shown in fig. 4.
Specifically, the high-precision map updating method for the unmanned vehicle provided by the third embodiment basically adopts the same steps as those of the second embodiment.
The difference lies in that: when the driving road in the updated high-precision map does not satisfy the automatic driving condition of the unmanned vehicle 10, the remote control driving is requested to the server, and after the response of switching to the remote control driving is received, the driving of the unmanned vehicle 10 is controlled by the remote terminal, the images are repeatedly collected, the collected images are continuously compared with the historical images in the high-precision map, and whether the high-precision map is updated or not is judged.
In the embodiment, when the unmanned vehicle 10 judges that the driving road in the updated high-precision map does not satisfy the automatic driving condition of the unmanned vehicle 10 based on the updated high-precision map, an inquiry request is actively sent to the server to inquire whether the server switches from automatic driving to remote control driving, so as to reduce the data operation process, avoid the waste of storage resources, and save time cost, the acquisition mode of the subsequent image data of the unmanned vehicle 10 is determined through active inquiry and quick judgment of remote control personnel, after the current road information does not satisfy the automatic driving condition of the unmanned vehicle 10 according to the image data, a remote control instruction is sent, and then the unmanned vehicle receives the response of switching to the remote control driving through the server 20, receives the remote control of the server 20, so as to improve the accuracy of data monitoring, the flexible switching between automatic driving and remote driving is realized, the working efficiency of high-precision map updating is further improved, and meanwhile the running safety of the unmanned vehicle 10 is improved.
Example four:
fig. 5 shows a flowchart of a high-precision map updating method for an unmanned vehicle according to a fourth embodiment of the present disclosure.
The fourth embodiment of the present disclosure correspondingly provides a high-precision map updating method for an unmanned vehicle, as shown in fig. 5.
Specifically, the high-precision map updating method for the unmanned vehicle provided by the fourth embodiment basically adopts the same steps as those of the previous embodiment.
The difference lies in that: before the step of pulling the local high-precision map by the unmanned vehicle, the unmanned vehicle 10 receives remote control, collects image data in the process of driving along a road, reports the image data to a server, and utilizes the collected image data to manufacture the high-precision map.
Based on the embodiment, the unmanned vehicle 10 acquires image data in real time in the process of running along a road by receiving remote control, reports the image data to the server, manufactures a high-precision map by using the acquired image data, carries an operation route on the high-precision map by using an automatic driving function of the unmanned vehicle, and carries an acquisition module to periodically and repeatedly run on the high-precision map, detects the change of a field environment in real time and automatically triggers the update of the high-precision map, so that the high-precision map can be manufactured/updated by using the remotely driven unmanned vehicle 10 according to the acquired environment data in the running process, and then is guided to the unmanned vehicle 10 or the unmanned vehicle 10 actively pulls the high-precision map to carry out commercial operation, thereby improving the utilization rate and the operation efficiency of the unmanned vehicle 10.
Example five:
fig. 6 shows a schematic flow chart of a high-precision map updating method for an unmanned vehicle according to a fifth embodiment of the present disclosure.
The fifth embodiment of the present disclosure correspondingly provides a high-precision map updating method for an unmanned vehicle, as shown in fig. 6.
Specifically, the high-precision map updating method for the unmanned vehicle provided by the fifth embodiment basically adopts the same steps as those of the fourth embodiment.
The difference lies in that: and if the running road in the updated high-precision map does not meet the automatic driving condition, directly receiving the image acquired in real time by remotely controlling and driving the unmanned vehicle 10, continuously comparing the image acquired in real time with the historical image in the high-precision map, and judging whether to update the high-precision map. Thereby realizing the flexible switching between the automatic driving and the remote driving so as to improve the operation efficiency and the safety of the unmanned vehicle 10.
Example six:
fig. 7 shows a flowchart of a high-precision map updating method for an unmanned vehicle according to a sixth embodiment of the present disclosure.
Fig. 7 shows a high-precision map updating method for an unmanned vehicle according to a sixth embodiment of the present disclosure.
Specifically, the high-precision map updating method for the unmanned vehicle provided by the sixth embodiment basically adopts the same steps as those of the first embodiment.
The difference lies in that: if the driving road in the updated high-precision map does not meet the automatic driving condition, under the condition that the unmanned vehicle is remotely controlled to drive and the images are collected in real time, if the automatic driving condition is determined to be met again in the process of remote control driving, the automatic driving mode is switched back, the images collected in real time are continuously compared with the historical images in the high-precision map, and whether the high-precision map is updated or not is judged.
Based on the embodiment, after the automatic driving condition is determined to be met again in the process of remote control driving, the automatic driving mode is switched back to the automatic driving mode for image data acquisition, so that flexible switching between automatic driving and remote driving can be further realized, the operation efficiency and the safety of the unmanned vehicle 10 are improved, the labor cost can be saved to a certain extent, the working efficiency is improved, and the operation safety of the unmanned vehicle 10 is improved.
Example seven:
fig. 8 shows a flow chart of a high-precision map updating method for an unmanned vehicle according to a seventh embodiment of the present disclosure.
A seventh embodiment of the present disclosure correspondingly provides a high-precision map updating method for an unmanned vehicle, as shown in fig. 8.
Specifically, the seventh embodiment provides a high-precision map updating method for an unmanned vehicle, which basically adopts the same steps as those in the sixth embodiment.
The difference lies in that: if the driving road in the updated high-precision map does not meet the automatic driving condition, requesting remote control driving from a server, and controlling the unmanned vehicle to drive and acquiring an image in real time by a remote terminal after receiving a response of switching to the remote control driving; and if the automatic driving condition is determined to be met again in the process of remote control driving, switching back to the automatic driving mode, acquiring images in real time, continuously comparing the images acquired in real time with historical images in the high-precision map, and judging whether to update the high-precision map.
Based on the embodiment, when the driving environment in the updated high-precision map does not meet the automatic driving condition, the server is actively sent with an inquiry request to inquire whether the server is switched from the automatic driving to the remote control driving, so as to reduce the data operation process and avoid the waste of storage resources, and also save time cost, the acquisition mode of the subsequent image data of the unmanned vehicle 10 is decided through the active inquiry and the rapid judgment of remote control personnel, after the current road information is judged to not meet the automatic driving condition of the unmanned vehicle 10 according to the image data, a remote control instruction is sent, after the unmanned vehicle receives the response of switching to the remote control driving through the server 20, the remote control of the server 20 is received, and then the automatic driving mode is switched back and the image is acquired in real time under the condition that the automatic driving condition is determined to be met again in the process of the remote control driving, therefore, the work efficiency of high-precision map updating is further improved, the flexible switching between automatic driving and remote driving is realized, the running safety of the unmanned vehicle 10 is further improved, the flexible operation in the high-precision map updating process is facilitated, and the accuracy is improved.
It should be noted that the foregoing embodiments are merely exemplary and are not intended to limit the present invention, and other alternative embodiments may be substituted by other means which are easily conceivable based on the present disclosure, and the embodiments may be combined with each other for understanding that various steps may be added, deleted and substituted in combination with specific embodiments, and are not limited herein.
Example eight:
fig. 9 shows a schematic structural diagram of a server according to an eighth embodiment of the present disclosure.
Referring to fig. 9, the present disclosure also presents a block diagram of an exemplary server suitable for use in implementing embodiments of the present disclosure. It should be understood that the server shown in fig. 9 is only an example, and should not bring any limitation to the function and the scope of the application of the embodiments of the present disclosure.
As shown in fig. 9, the server 200 is in the form of a general purpose computing device. The components of server 200 may include, but are not limited to: one or more processors or processing units 210, a memory 220, and a bus 201 that couples the various system components (including the memory 220 and the processing unit 210).
The system memory 220 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)221 and/or cache memory 222. The server 200 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 223 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 9, often referred to as a "hard drive"). Although not shown in FIG. 9, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 201 by one or more data media interfaces. Memory 220 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the disclosure.
Program/utility 224 having a set (at least one) of program modules 2241 may be stored, for example, in memory 220, such program modules 2241 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination of which may comprise an implementation of a network environment. Program modules 2241 generally perform the functions and/or methods of the embodiments described in the embodiments of the present disclosure.
Optionally, the server 200 may also be communicatively connected to a display 300, the display 300 may be used for displaying the captured image data, the comparison result of the map elements, and the like, for example, and the display 300 may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some embodiments, the display 300 may also be a touch screen.
Optionally, the server 200 may also communicate with one or more devices that enable a user to interact with the server 200, and/or with any devices (e.g., network cards, modems, etc.) that enable the server 200 to communicate with one or more other computing devices. Such communication may be through input/output (I/O) interfaces 230. Also, server 200 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via network adapter 240. As shown, network adapter 240 communicates with the other modules of server 200 via bus 201. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the server 200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 210 executes various functional applications and data processing by executing programs stored in the system memory 220, for example, implementing a high-precision map updating method for an unmanned vehicle provided in the first embodiment of the present disclosure.
Example nine
Ninth embodiment of the present disclosure further provides a computer-readable storage medium, on which a computer program (or referred to as computer-executable instructions) is stored, where the computer program is used, when executed by a processor, to perform a high-precision map updating method for an unmanned vehicle, which is provided in the various embodiments of the present disclosure, and taking the second embodiment as an example, the high-precision map updating method may include:
the unmanned vehicle pulls a local high-precision map, and runs in an automatic driving mode according to the high-precision map, and the unmanned vehicle carries out commercial operation in the running process;
acquiring an image acquired in real time by an unmanned vehicle in the process of driving according to a high-precision map;
comparing the image with the historical image in the high-precision map to generate a comparison result;
if the comparison result shows that the map element change on the driving road exceeds the range of a preset threshold value, automatically updating the high-precision map by the image corresponding to the map element;
if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle to continue automatic driving and collecting images in real time; and if the driving road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle to drive and acquiring images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether to update the high-precision map.
The computer storage media of the disclosed embodiments may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It should be noted that in the description of the present disclosure, it is to be understood that the terms "upper", "lower", "inner", and the like, indicate orientation or positional relationship, are only for convenience in describing the present disclosure and simplifying the description, but do not indicate or imply that the referenced components or elements must have a particular orientation, be constructed and operated in a particular orientation, and therefore should not be construed as limiting the present disclosure.
Further, in this document, the contained terms "include", "contain" or any other variation thereof are intended to cover a non-exclusive inclusion, so that a process, a method, an article or an apparatus including a series of elements includes not only those elements but also other elements not explicitly listed or inherent to such process, method, article or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Finally, it should be noted that: it should be understood that the above examples are only for clearly illustrating the present disclosure, and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications of the invention as herein taught are within the scope of the present disclosure.
Claims (10)
1. A high-precision map updating method for an unmanned vehicle, the method comprising:
the unmanned vehicle pulls a local high-precision map and runs in an automatic driving mode according to the high-precision map;
acquiring an image acquired by the unmanned vehicle in real time in the driving process;
comparing the image with a historical image in the high-precision map to generate a comparison result;
if the comparison result is that the change of the map elements on the driving road exceeds the range of a preset threshold value, automatically updating the high-precision map by the images corresponding to the map elements;
if the driving road in the updated high-precision map meets the automatic driving condition, enabling the unmanned vehicle to continue to drive in the automatic driving mode and acquiring images in real time; and if the driving road in the updated high-precision map does not meet the automatic driving condition, remotely controlling the unmanned vehicle to drive and acquiring images in real time, continuously comparing the images acquired in real time with the historical images in the high-precision map, and judging whether the high-precision map is updated or not.
2. The high-precision map updating method according to claim 1, wherein the map elements include at least: road lane lines, traffic lights, flow guide belts, pedestrian crossing lines, stop lines, guardrails, kerbs, light poles, sewer openings, building signs and overpasses,
and, the map element change exceeding a preset threshold range includes:
at least one of the road lane line, the traffic light, the diversion area, the pedestrian crossing line, the stop line, the guardrail, the kerbstone, the light pole, the sewer opening, the building sign and the overpass is changed.
3. The high-precision map updating method according to claim 1, wherein the case where the automatic driving condition is not satisfied includes at least one of:
the map elements are not identifiable by current lighting conditions;
the current weather conditions cannot identify roads;
the unmanned vehicle cannot automatically identify and plan a driving route under the condition of complicated current roads.
4. The high-precision map updating method according to claim 1, wherein before the step of the unmanned vehicle pulling the local high-precision map, the high-precision map updating method further comprises:
receiving remote control, and acquiring images in real time during the driving process of the unmanned vehicle along the road; and
and manufacturing the high-precision map according to the acquired image.
5. The high-precision map updating method according to claim 3, wherein if the driving road in the updated high-precision map does not meet the automatic driving condition, the step of remotely controlling the unmanned vehicle to drive and acquiring the image in real time comprises the following steps:
if the running road in the updated high-precision map does not meet the automatic driving condition, sending an inquiry request to a server for inquiring whether the server is switched from automatic driving to remote control driving;
and after receiving a response of switching to remote control driving, receiving remote control of the server, so that the unmanned vehicle runs and acquires images in real time.
6. The high-precision map updating method according to claim 1, wherein after the comparison result is generated, the high-precision map updating method further comprises:
and if the comparison result shows that the change of the map elements on the driving road does not exceed the range of a preset threshold value, automatically storing the image into the image set corresponding to the map elements in the high-precision map.
7. The high-precision map updating method according to claims 1-6, wherein the step of remotely controlling the unmanned vehicle to run and acquiring the image in real time if the running road in the updated high-precision map does not satisfy the automatic driving condition, further comprises:
and if the unmanned vehicle determines that the automatic driving condition is met again in the process of remote control driving, switching back to automatic driving.
8. A high-precision map updating device for an unmanned vehicle, comprising an acquisition module installed on the unmanned vehicle, wherein the high-precision map updating device is used for executing the high-precision map updating method of any one of the claims 1-7.
9. The updating apparatus of claim 7, wherein the acquisition module comprises: the system comprises a binocular camera, a laser radar, a global positioning system and an inertia measurement unit;
or, the acquisition module comprises: monocular cameras, lidar, global positioning systems, and inertial measurement units.
10. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor,
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the high precision map updating method of any one of claims 1-7.
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