CN114689069A - Navigation route processing method and device of automatic driving equipment and electronic equipment - Google Patents
Navigation route processing method and device of automatic driving equipment and electronic equipment Download PDFInfo
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- 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
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Abstract
The disclosure provides a navigation route processing method and device of automatic driving equipment and electronic equipment, and relates to the technical field of computers, in particular to the technical fields of intelligent transportation, automatic driving technology and the like. The specific implementation scheme is as follows: acquiring static data of lanes in an initial navigation route; the static data comprises lane communication data, lane operation safety data and lane operation area data; acquiring dynamic data of the lane in the navigation route; and screening the navigation route according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
Description
Technical Field
The present disclosure relates to the field of computer technology, and more particularly to the field of intelligent transportation and automatic driving technology.
Background
The automatic driving equipment can realize driving decision planning according to the navigation information, and providing more appropriate navigation route information for the automatic driving equipment is an important attention direction of automatic driving technology.
Currently, the navigation route provided to the autopilot device is generally a route such as the shortest route, the traffic light-minimum route, and the like.
Disclosure of Invention
The disclosure provides a navigation route processing method and device of an automatic driving device, an electronic device and a storage medium.
According to an aspect of the present disclosure, there is provided a navigation route processing method of an automatic driving apparatus, including:
acquiring static data of lanes in an initial navigation route; the static data comprises lane communication data, lane operation safety data and lane operation area data;
acquiring dynamic data of the lane in the navigation route;
and screening the navigation route according to the static data, the dynamic data and a preset screening strategy to obtain the navigation route based on the lane.
According to another aspect of the present disclosure, there is provided a navigation route processing apparatus of an autonomous driving device, including:
the static data acquisition unit is used for acquiring static data of lanes in an initial navigation route; the static data comprises lane communication data, lane operation safety data and lane operation area data;
the dynamic data acquisition unit is used for acquiring dynamic data of the lane in the navigation route;
and the route screening processing unit is used for screening the navigation route according to the static data, the dynamic data and a preset screening strategy so as to obtain the lane-based navigation route.
According to still another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of the aspects and any possible implementation described above.
According to yet another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the above-described aspect and any possible implementation.
According to yet another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method of the aspect and any possible implementation as described above.
According to yet another aspect of the present disclosure, there is provided an autonomous vehicle comprising an electronic device as described above.
According to the technical scheme, the static data of the lanes in the initial navigation route are obtained, the static data can comprise lane communication data, lane operation safety data and lane operation area data, and the dynamic data of the lanes in the navigation route can be obtained, so that the navigation route can be screened according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a schematic diagram according to a first embodiment of the present disclosure;
FIG. 2 is a schematic diagram according to a second embodiment of the present disclosure;
FIG. 3 is a schematic diagram of the principles of a navigation route processing method of an autonomous device according to a second embodiment of the present disclosure;
FIG. 4 is a schematic diagram according to a third embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device for implementing a navigation route processing method of an autonomous driving apparatus according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It is to be understood that the described embodiments are only a few, and not all, of the disclosed embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It should be noted that the terminal device involved in the embodiments of the present disclosure may include, but is not limited to, a mobile phone, a Personal Digital Assistant (PDA), a wireless handheld device, a Tablet Computer (Tablet Computer), and other intelligent devices; the display device may include, but is not limited to, a personal computer, a television, and the like having a display function.
In addition, the term "and/or" herein is only one kind of association relationship describing the association object, and means that there may be three kinds of relationships, for example, a and/or B, and may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The automatic driving equipment can realize driving decision planning according to the navigation information, and along with the development of the automatic driving technology, the automatic driving equipment is provided with more proper navigation route information, which is an important attention direction of the automatic driving technology.
Currently, the navigation route provided to the autopilot device is generally a route such as a shortest route, a traffic light-minimum route, and the like. However, the navigation route information provided by the related art is not highly accurate, and cannot effectively meet the actual driving requirements of the automatic driving equipment.
Therefore, it is desirable to provide a navigation route processing method for an autonomous driving device, which can obtain a more accurate navigation route at a lane level to ensure the accuracy of the navigation route according to the autonomous driving device.
Fig. 1 is a schematic diagram according to a first embodiment of the present disclosure, as shown in fig. 1.
101. Acquiring static data of lanes in an initial navigation route; wherein the static data comprises lane communication data, lane operation safety data and lane operation area data.
102. And acquiring dynamic data of the lane in the navigation route.
103. And screening the navigation route according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
Up to this point, the automatic driving apparatus may travel according to the obtained lane-based navigation route.
Note that the automatic driving apparatus may include an automatic driving vehicle, and an apparatus having an automatic traveling function. Wherein the autonomous vehicle may be an L3/L4 class autonomous vehicle.
It should be noted that the initial navigation route may be obtained according to the driving end point of the automatic driving device. The driving end points of the autonomous device may include a departure point to a destination point. The navigation route may be at least one navigation route from a departure location to a destination location.
It should be noted that the acquired initial navigation route may be a navigation route based on a high-precision map.
In particular, the initial navigation route may include, but is not limited to, a road-based navigation route and a lane-based navigation route to be processed. The road-based navigation route may be a road-level navigation route. The lane-based navigation route to be processed may be a lane-level navigation route to be processed.
The road-level navigation route may be a road-level navigation route based on a high-precision map. The lane-level navigation route to be processed may also be a lane-level navigation route based on a high-precision map.
It can be understood that, if the initial navigation route is a road-based navigation route, the road-based navigation route may be searched by using a preset search algorithm according to a lane connectivity and a lane line false-true condition in the road-based navigation route, so as to obtain a to-be-processed lane-based navigation route.
Specifically, the preset search algorithm may include, but is not limited to, a depth search algorithm.
It will be appreciated that the initial navigation route may also be a lane-based navigation route to be processed that is obtained directly from the server.
It should be noted that part or all of the execution subjects of 101 to 103 may be an application located at the local terminal, or may also be a functional unit such as a plug-in or Software Development Kit (SDK) set in the application located at the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, for example, a processing engine or a distributed system in an autopilot processing platform on the network side, which is not particularly limited in this embodiment.
It is to be understood that the application may be a native application (native app) installed on the local terminal, or may also be a web page program (webApp) of a browser on the local terminal, which is not limited in this embodiment.
In this way, static data of lanes in the initial navigation route can be acquired, the static data can comprise lane communication data, lane operation safety data and lane operation area data, and dynamic data of the lanes in the navigation route can be acquired, so that the navigation route can be screened according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
Optionally, in a possible implementation manner of this embodiment, the preset filtering policy may include a static data filtering policy and a dynamic data filtering policy, and in 103, the navigation route may be specifically filtered according to the static data and the static data filtering policy to obtain a static data filtering result, and then the static data filtering result may be filtered according to the dynamic data and the dynamic data filtering policy to obtain a lane-based navigation route.
In this implementation, the static data may include lane connectivity data, lane operational safety data, and lane operational area data.
Specifically, the lane connection data may be a connection relationship at a lane level, that is, may be a topological relationship at a lane level.
The lane operation safety data may include, but is not limited to, the number of times the autonomous device traveling in the lane has been manually taken over and the safety factor of the autonomous device traveling in the lane. The lane operation safety data may characterize how difficult the autonomous device is to travel on the lane.
The lane operating area data may include operating Design area (ODD) data and lane geofence data of the autonomous driving device.
The ODD data may be area data that allows the automatic driving apparatus to travel. An ODD may be defined as an operating condition specifically designed for a particular drive automation system or function thereof, and may specifically include, but is not limited to, environmental, geographic, and temporal limitations, and/or the presence or absence of certain traffic or road characteristics.
It is to be understood that the lane geofence data may be area data that does not allow the autonomous device to travel, i.e., lane level geofence data. The lane geofence data may be static data that is predicted to be relevant to the lane status based on the road status. For example, lane geofence data may include, but is not limited to, curvature overrun, grade overrun, head break, toll gate, and the like. The curvature overrun and gradient overrun may refer to the fact that the curvature and gradient of the lane exceed the threshold values of the curvature and gradient which can be driven by the automatic driving device.
In this implementation, the static data screening policy may include at least one of:
and if the lane communication data meet the preset lane communication relationship, screening out a lane-based navigation route meeting the preset lane communication relationship from the navigation routes as a static data screening result.
And if the lane operation safety data meet the preset safety conditions, screening out a lane-based navigation route meeting the preset safety conditions from the navigation routes as a static data screening result.
And if the lane operation area data meet the preset operation area conditions, screening out a lane-based navigation route meeting the preset operation area conditions from the navigation routes as a static data screening result.
In a specific implementation process of the implementation manner, the navigation route may be screened according to the lane connectivity data and the static data screening strategy, so as to obtain a static data screening result.
In the specific implementation process, the static data screening strategy may be to screen a lane-based navigation route satisfying a preset lane connectivity relationship from the navigation routes as a static data screening result if the lane connectivity data satisfies the preset lane connectivity relationship.
Specifically, the preset lane communication relationship may be that there is a communication relationship between lanes. And if the lanes in the lane communication data have a communication relation, screening a lane-based navigation route with the lane communication relation from the navigation routes, and taking the lane-based navigation route with the lane communication relation as a static data screening result.
In another specific implementation process of the implementation manner, the navigation route may be screened according to the lane connectivity data, the lane operation safety data, and the static data screening policy, so as to obtain a static data screening result.
In the specific implementation process, the static data screening policy may include screening a lane-based navigation route satisfying a preset lane connectivity relationship from the navigation routes as a static data screening result if the lane connectivity data satisfies the preset lane connectivity relationship.
And if the lane operation safety data meet the preset safety conditions, screening out the lane-based navigation route meeting the preset safety conditions from the navigation routes as a static data screening result.
Specifically, the preset safety conditions may include, but are not limited to, the number of times the autonomous driving apparatus traveling on the lane is historically manually taken over being below a preset take-over threshold and the safety factor with which the autonomous driving apparatus travels on the lane reaching a preset safety factor threshold.
In the specific implementation process, whether the lanes in the navigation route have the lane communication relation or not is judged according to the lane communication data, the lane operation safety data and the static data screening strategy, and determining whether the number of times that the autonomous driving apparatus driving on the lane is historically manually taken over is lower than a preset take-over threshold, or judging whether the safety factor of the automatic driving equipment running on the lane reaches a preset safety factor threshold value or not, if the lane in the navigation route has a lane communication relation and the historical manual takeover frequency of the automatic driving equipment running on the lane is lower than the preset takeover frequency threshold value or not, or the safety factor of the automatic driving equipment running on the lane reaches the preset safety factor threshold value, the lane-based navigation route satisfying the preset lane connectivity and the preset safety condition may be obtained as a static data screening result.
In another specific implementation process of the implementation manner, the navigation route may be screened according to lane connectivity data, lane operation safety data, lane operation area data, and a static data screening policy, so as to obtain a static data screening result.
In the specific implementation process, the static data screening strategy may include, in addition to the two strategies, screening a lane-based navigation route satisfying a running area condition from the navigation routes as a static data screening result if the lane running area data satisfies a preset running area condition.
In particular, the preset operating area condition may be that the lane is an area where the autonomous device is allowed to travel, i.e. the preset operating area condition may be that there is no geo-fence of the lane on the lane.
In the specific implementation process, according to the lane communication data, the lane operation safety data, the lane operation area data and the static data screening strategy, whether a lane in the navigation route has a lane communication relation or not can be judged, whether the number of times of manual takeover of the history of the automatic driving equipment driving on the lane is lower than a preset takeover number threshold or not can be judged, whether the safety factor of the automatic driving equipment driving on the lane reaches a preset safety factor threshold or not and whether the lane has lane geofence data or not can be judged, if the lane in the navigation route has the lane communication relation, whether the number of times of manual takeover of the history of the automatic driving equipment driving on the lane is lower than the preset takeover number threshold or not, or whether the safety factor of the automatic driving equipment driving on the lane reaches the preset safety factor threshold or not and the lane has no lane geofence data, the lane-based navigation route satisfying the preset lane connectivity relationship, the preset safety condition, and the preset operation area condition may be obtained as a static data screening result.
Therefore, the navigation route can be screened according to the static data and the static data screening strategy, the lane-based navigation route obtained by screening lanes in the navigation route through the lane-based static data can be obtained, the pertinence and the accuracy of data processing are improved, and the accuracy of the obtained lane-based navigation route is improved.
In this implementation, the dynamic data screening policy may include: and if the dynamic data are not matched with the preset dynamic events, screening out a lane-based navigation route with the dynamic data not matched with the preset dynamic events from the static data screening result, and taking the lane-based navigation route as the lane-based navigation route.
In particular, the dynamic data may include, but is not limited to, lane-level events and real-time road conditions. The preset dynamic events may include preset lane-level events and road conditions.
Specifically, the lane-level events may include, but are not limited to, traffic accident events, congestion events, regulatory events, construction events, and dynamic event information such as weather events on the lanes.
Specifically, the preset road conditions may include, but are not limited to, vehicle road surface driving conditions, lane speed limit conditions obtained based on historical driving data, and other road surface conditions.
It is understood that the lane speed limit situation obtained based on the historical travel data may be a lane speed limit situation based on an empirical value, and the lane speed limit situation based on the empirical value may not be the highest lane speed limit specified when the lane is designed.
In yet another specific implementation of this implementation, the static data filtering result may include a lane-based navigation route obtained by filtering processing of the lane-based static data. According to the dynamic data of the lanes of the lane-based navigation route and the preset dynamic events in the static data screening result, whether the dynamic data of the lanes in the lane-based navigation route is matched with the preset dynamic events or not can be judged, namely whether the dynamic data of the lanes in the lane-based navigation route comprises the preset dynamic events or not can be judged, and if the dynamic data of the lanes in the lane-based navigation route does not comprise the preset dynamic events, the lane-based navigation route can be used as the lane-based navigation route provided for the automatic driving equipment.
In this way, the static data screening result may be further subjected to the screening process according to the dynamic data of the lane-based navigation route and the preset dynamic event in the static data screening result, and the screening result of the lane-based dynamic data, that is, the lane-based navigation route provided for the autonomous driving apparatus may be obtained. Therefore, the pertinence and the accuracy of data processing can be further improved, and the accuracy of the obtained lane-based navigation route is further improved.
In this implementation, the obtained lane-based navigation route may be a lane-based navigation route obtained by performing a plurality of screening processes on an initial navigation route.
In yet another specific implementation of this implementation, the obtained lane-based navigation route, i.e., the lane-based navigation route provided for use by the autonomous driving apparatus, may be the lane-based navigation route having the least number of historical manual takeoffs/highest safety factor and the longest ratio of autonomous driving distance. The ratio of the driving distance may be a ratio of a driving distance in the lane-based navigation route, which the automatic driving device may automatically drive, to a total distance of the lane-based navigation route.
Thus, in the implementation mode, the lanes in the navigation route can be screened for a plurality of times through the screening strategy based on the static data and the screening strategy based on the dynamic data and the dynamic data to obtain the lane-based navigation route provided for the automatic driving equipment.
Optionally, in a possible implementation manner of this embodiment, in 102, image data of the lane in the navigation route within a preset time period may be specifically obtained, and then image recognition processing may be performed on the image data within the preset time period to obtain a dynamic event and a real-time road condition of the lane, so that the dynamic data of the lane in the navigation route may be obtained according to the dynamic event and the real-time road condition of the lane.
In this implementation, the preset time period may be determined according to a driving condition of the automatic driving apparatus. For example, the preset time period may be a current time period during which the autonomous driving apparatus is traveling. Or alternatively. The preset time period may be a history time period during which the automatic driving apparatus travels.
Specifically, the image data may be video image data, that is, may be continuous multi-frame image data.
In a specific implementation process of the implementation manner, video image data within a preset time period of a lane acquired by using an acquisition device is acquired, and then event detection can be performed on the video image data to acquire a dynamic event and a real-time road condition in each frame of image data, and then the dynamic event and the real-time road condition in all the frames of image data are clustered to acquire the dynamic event and the real-time road condition of the lane, so that the dynamic data of the lane in the navigation route can be acquired according to the dynamic event and the real-time road condition of the lane.
Therefore, the dynamic data of the lane can be identified more accurately by carrying out image identification processing on the acquired image data of the lane, the accuracy of the dynamic data of the lane is improved, and then the lane in the navigation route is subsequently screened based on the dynamic data, so that the accuracy and effectiveness of the screened navigation route based on the lane can be improved, and the accuracy of the obtained navigation route based on the lane can be further improved.
It is understood that, in the present embodiment, the dynamic data of the lanes in the initial navigation route may also be directly acquired from the storage server for storing the dynamic data of the relevant lanes.
It should be noted that, based on the implementation manner provided in the present implementation manner for obtaining dynamic data of lanes in the initial navigation route, the navigation route processing method of the autopilot device of the present embodiment may be implemented by combining a plurality of specific implementation procedures of the implementation manner provided in the foregoing implementation manner for obtaining the lane-based navigation route. For a detailed description, reference may be made to the related contents in the foregoing implementation manners, and details are not described herein.
Optionally, in a possible implementation manner of this embodiment, before 101, a road-based navigation route in the navigation map may be further obtained according to a driving endpoint of the automatic driving device, and then trajectory data of the road-based navigation route in the navigation map may be obtained according to the road-based navigation route in the navigation map, so that the road-based navigation route in the high-precision map may be obtained by using a preset matching model according to the trajectory data of the road-based navigation route in the navigation map and the road connectivity data in the high-precision map.
In this implementation, the travel endpoints of the autonomous device may include a start point and a target point. The road-based navigation route in the navigation map may be a road-based navigation route between a start location and a target location in the navigation map.
In a specific implementation process of the implementation, the trajectory data according to the road-based navigation route in the navigation map may be acquired according to the road-based navigation route in the navigation map. Then, data thinning processing is performed on the trajectory data to obtain processed trajectory data. Again, road connectivity data in the high precision map may be obtained. And finally, obtaining a navigation route based on the road in the high-precision map by using a preset matching model according to the processed track data and the road communication data.
In this specific implementation process, the road-based navigation route in the navigation map may include Point of Interest (POI) data of the navigation map. After the data matching fusion processing is performed by using the preset matching model, the obtained road-based navigation route in the high-precision map may include mapping the point of interest data of the navigation map to the point of interest data obtained in the high-precision map.
In another specific implementation process of the implementation manner, the road line data in the high-precision map can be specifically acquired, and then the road communication data in the high-precision map can be acquired according to the road line data.
Specifically, the road line data between the travel end points of the autonomous devices in the high-precision map may be acquired from the travel end points of the autonomous devices. The roadway line data may include roadway baseline data and roadway centerline data. The road baseline data may be based on the leftmost road baseline data of the road.
It is to be understood that, here, the road-based navigation route in the obtained high-precision map may be used as the initial navigation route.
In yet another specific implementation of this implementation, after obtaining the road-based navigation route in the high-precision map, the lane connectivity data and the geo-fence data may be further obtained. Then, at least one navigation route based on the lane in the navigation routes based on the road in the high-precision map can be obtained by utilizing a depth search algorithm according to the lane communication data, and then the at least one navigation route based on the lane can be screened according to the geo-fence data so as to obtain a navigation route based on the lane to be processed.
It is to be understood that the obtained to-be-processed lane-based navigation route may also serve as the initial navigation route.
In this way, in the implementation manner, the navigation route based on the road in the high-precision map and the acquired road communication data can be obtained by performing matching fusion processing on the navigation route based on the road in the navigation map and the acquired road communication data by using the preset matching model, so that the accuracy of the navigation route based on the road in the obtained high-precision map can be improved, and the more accurate navigation route based on the lane in the high-precision map can be obtained subsequently.
It should be noted that, based on the implementation manner provided in the present implementation manner for acquiring the dynamic data of the obstacle in the preset area, the navigation route processing method of the automatic driving device of the embodiment may be implemented by combining a plurality of specific implementation processes provided in the foregoing implementation manner for outputting the dynamic data of the obstacle. For a detailed description, reference may be made to the related contents in the foregoing implementation manners, and details are not described herein.
In the embodiment, static data of lanes in an initial navigation route can be acquired, the static data can include lane communication data, lane operation safety data and lane operation area data, and dynamic data of the lanes in the navigation route can be acquired, so that the navigation route can be screened according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
In addition, according to the technical scheme provided by the embodiment, the lanes in the navigation route can be screened for multiple times through the static data and static data screening strategy and the dynamic data and dynamic data screening strategy to obtain the lane-based navigation route provided for the automatic driving equipment.
In addition, by adopting the technical scheme provided by the embodiment, the navigation route can be screened according to the static data and the static data screening strategy, the lane-based navigation route obtained by screening lanes in the navigation route by the lane-based static data can be obtained, the pertinence and the accuracy of data processing are improved, and the accuracy of the obtained lane-based navigation route is improved.
In addition, by adopting the technical scheme provided by the embodiment, the static data screening result can be further screened according to the dynamic data of the lane-based navigation route in the static data screening result and the preset dynamic event, so that the screening result of the lane-based dynamic data, namely the lane-based navigation route provided for the automatic driving equipment can be obtained. Therefore, the pertinence and the accuracy of data processing can be further improved, and the accuracy of the obtained lane-based navigation route can be further improved.
In addition, by adopting the technical scheme provided by the embodiment, the dynamic data of the lane can be identified more accurately by carrying out image identification processing on the acquired image data of the lane, the accuracy of the dynamic data of the lane is improved, so that the lane in the navigation route is subsequently screened based on the dynamic data, the accuracy and the effectiveness of the screened lane-based navigation route can be improved, and the accuracy of the obtained lane-based navigation route can be further improved.
Fig. 2 is a schematic diagram according to a second embodiment of the present disclosure, as shown in fig. 2.
201. And acquiring lane communication data, lane operation safety data and lane operation area data of the lane in the initial navigation route.
In the present embodiment, the initial navigation route is obtained according to the travel end point of the automatic driving apparatus. The initial navigation route may be at least one navigation route from a starting point to a destination.
The initial navigation route may include, but is not limited to, a road-based navigation route and a lane-based navigation route to be processed. The road-based navigation route may be a road-level navigation route. The lane-based navigation route to be processed may be a lane-level navigation route to be processed.
In this embodiment, the lane connection data may be a lane connection relationship, that is, may be a lane topology relationship. The lane connectivity data may be determined from the acquired navigation route.
In particular, the lane operation safety data may include, but is not limited to, the number of times the autonomous device traveling in the lane has been manually taken over and the safety factor of the autonomous device traveling in the lane.
In particular, the lane operating area data may include ODD data and lane geofence data.
202. And acquiring dynamic events and real-time road conditions of the lanes in the initial navigation route.
203. And screening the navigation route according to the lane communication data, the lane operation safety data, the lane operation area data and the static data screening strategy of the lane to obtain a static data screening result.
In this embodiment, the static data screening policy may include screening, if the lane connectivity data satisfies the preset lane connectivity relationship, a lane-based navigation route satisfying the preset lane connectivity relationship from the navigation routes, as a static data screening result; if the lane operation safety data meet the preset safety conditions, screening out a lane-based navigation route meeting the preset safety conditions from the navigation routes as a static data screening result; and if the lane operation area data meet the preset operation area conditions, screening out a lane-based navigation route meeting the preset operation area conditions from the navigation routes as a static data screening result.
Specifically, the method can be used for screening strategies according to the lane communication data, the lane operation safety data, the lane operation area data and the static data, judging whether a lane in a navigation route has a lane communication relationship, judging whether the historical manual takeover frequency of the automatic driving equipment driving on the lane is lower than a preset takeover frequency threshold value or not, judging whether the safety factor of the automatic driving equipment driving on the lane reaches a preset safety factor threshold value or not, judging whether the lane has the lane geo-fence data or not, if the lane in the navigation route has the lane communication relationship, the historical manual takeover frequency of the automatic driving equipment driving on the lane is lower than the preset takeover frequency threshold value or the safety factor of the automatic driving equipment driving on the lane reaches the preset safety factor threshold value or the lane has no lane geo-fence data, the lane-based navigation route satisfying the preset lane connectivity relationship, the preset safety condition, and the preset operation area condition may be obtained as a static data screening result.
204. And screening the static data screening result according to the dynamic event, the real-time road condition and the dynamic data screening strategy of the lane to obtain a lane-based navigation route.
In this embodiment, the dynamic data filtering policy may include: and if the dynamic data is not matched with the preset dynamic event, screening out a lane-based navigation route with the dynamic data not matched with the preset dynamic event from the static data screening result, and taking the lane-based navigation route as the lane-based navigation route.
Specifically, whether the dynamic data of the lane in the lane-based navigation route matches with the preset dynamic event may be determined according to the dynamic data of the lane-based navigation route in the static data screening result and the preset dynamic event, that is, whether the dynamic data of the lane in the lane-based navigation route includes the preset dynamic event may be determined, and if the dynamic data of the lane in the lane-based navigation route does not include the preset dynamic event, the lane-based navigation route may be used as the lane-based navigation route provided to the automatic driving device.
In this embodiment, the lane-based navigation route provided for use by the autonomous device may be a lane-based navigation route having the least number of historical manual takeoffs/the highest safety factor, the longest proportion of autonomous driving distance, and the shortest transit time.
In addition, in this embodiment, before obtaining the static data of the lanes in the initial navigation route, the navigation route based on the roads in the navigation map may be obtained according to the driving end point of the automatic driving device, and then the trajectory data of the navigation route based on the roads in the navigation map may be obtained according to the navigation route based on the roads in the navigation map, so that the navigation route based on the roads in the high-precision map may be obtained by using a preset matching model according to the trajectory data of the navigation route based on the roads in the navigation map and the road connection data in the high-precision map.
Fig. 3 is a schematic diagram of the principle of a navigation route processing method of an autonomous driving apparatus according to a second embodiment of the present disclosure. As shown in fig. 3. In the implementation process of this embodiment, the navigation route may be filtered by comprehensively considering the connectivity 301 at the lane level, the number of times that the autonomous driving device driving on the lane is manually taken over, and the safety factor of the autonomous driving device driving on the lane, that is, the number of times of manual taking over/safety factor 302, the geo-fence data 303 at the lane level, the event 304 at the lane level, and the real-time road condition 305, that is, the navigation route 306 is processed by comprehensively considering various data, so as to determine the lane-based navigation route 307 recommended to the autonomous driving device.
In the embodiment, static data of lanes in the initial navigation route can be acquired, the static data can include lane communication data, lane operation safety data and lane operation area data, and dynamic data of the lanes in the initial navigation route can be acquired, so that the navigation route can be screened according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
In addition, by adopting the technical scheme provided by the embodiment, the lanes in the navigation route can be screened for multiple times through the static data and static data screening strategy and the dynamic data and dynamic data screening strategy to obtain the lane-based navigation route provided for the automatic driving equipment.
Moreover, during driving, the automatic driving equipment can switch lanes in time based on the obtained lane-based navigation route, and the driving reliability of the automatic driving equipment is further guaranteed.
In addition, by adopting the technical scheme provided by the embodiment, the driving experience of the automatic driving equipment can be effectively optimized.
It is noted that while for simplicity of explanation, the foregoing method embodiments have been described as a series of acts or combination of acts, it will be appreciated by those skilled in the art that the present disclosure is not limited by the order of acts, as some steps may, in accordance with the present disclosure, occur in other orders and concurrently. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required for the disclosure.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
Fig. 4 is a schematic diagram according to a third embodiment of the present disclosure, as shown in fig. 4. The navigation route processing apparatus 400 of the autopilot device of the present embodiment may include a static data acquisition unit 401, a dynamic data acquisition unit 402, and a route filtering processing unit 403. The static data acquiring unit 401 is configured to acquire static data of a lane in an initial navigation route; the static data comprises lane communication data, lane operation safety data and lane operation area data; a dynamic data acquiring unit 402 configured to acquire dynamic data of the lane in the navigation route; a route screening processing unit 403, configured to perform screening processing on the navigation route according to the static data, the dynamic data, and a preset screening policy, so as to obtain a lane-based navigation route.
It should be noted that, part or all of the navigation route processing device of the autopilot apparatus of this embodiment may be an application located at the local terminal, or may also be a functional unit such as a Software Development Kit (SDK) or a plug-in provided in the application located at the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, for example, a processing engine or a distributed system in an autopilot processing platform on the network side, and this embodiment is not particularly limited to this.
It is to be understood that the application may be a native application (native app) installed on the local terminal, or may also be a web page program (webApp) of a browser on the local terminal, which is not limited in this embodiment.
Optionally, in a possible implementation manner of this embodiment, the preset filtering policy includes a static data filtering policy and a dynamic data filtering policy, and the route filtering processing unit 403 is specifically configured to perform filtering processing on the navigation route according to the static data and the static data filtering policy to obtain a static data filtering result, and perform filtering processing on the static data filtering result according to the dynamic data and the dynamic data filtering policy to obtain a lane-based navigation route.
Optionally, in this implementation, the static data screening policy may include at least one of: and if the lane communication data meet the preset lane communication relationship, screening out a lane-based navigation route meeting the preset lane communication relationship from the navigation routes as a static data screening result.
If the lane operation safety data meet the preset safety conditions, screening out a lane-based navigation route meeting the preset safety conditions from the navigation routes as a static data screening result; and
and if the lane operation area data meet the preset operation area conditions, screening out a lane-based navigation route meeting the preset operation area conditions from the navigation routes as a static data screening result.
Optionally, in this implementation, the dynamic data screening policy may include: and if the dynamic data are not matched with the preset dynamic events, screening out a lane-based navigation route with the dynamic data not matched with the preset dynamic events from the static data screening result, and taking the lane-based navigation route as the lane-based navigation route.
Optionally, in a possible implementation manner of this embodiment, the dynamic data obtaining unit 402 may be specifically configured to obtain image data of the lane in the navigation route within a preset time period; carrying out image recognition processing on the image data in the preset time period to obtain the dynamic events and real-time road conditions of the lane; and acquiring dynamic data of the lane in the navigation route according to the dynamic event and the real-time road condition of the lane.
In this embodiment, the static data of the lane in the initial navigation route may be acquired by the static data acquisition unit; the static data comprises lane communication data, lane operation safety data and lane operation area data, the dynamic data of the lanes in the navigation route can be acquired by the dynamic data acquisition unit, so that the route screening processing unit can screen the navigation route according to the static data, the dynamic data and a preset screening strategy to acquire the lane-based navigation route.
In addition, according to the technical scheme provided by the embodiment, the lanes in the navigation route can be screened for multiple times through the static data and static data screening strategy and the dynamic data and dynamic data screening strategy to obtain the lane-based navigation route provided for the automatic driving equipment.
In addition, by adopting the technical scheme provided by the embodiment, the navigation route can be screened according to the static data and the static data screening strategy, the lane-based navigation route obtained by screening lanes in the navigation route by the lane-based static data can be obtained, the pertinence and the accuracy of data processing are improved, and the accuracy of the obtained lane-based navigation route is improved.
In addition, by adopting the technical scheme provided by the embodiment, the static data screening result can be further screened according to the dynamic data of the lane-based navigation route in the static data screening result and the preset dynamic event, so that the screening result of the lane-based dynamic data, namely the lane-based navigation route provided for the automatic driving equipment can be obtained. Therefore, the pertinence and the accuracy of data processing can be further improved, and the accuracy of the obtained lane-based navigation route is further improved.
In addition, by adopting the technical scheme provided by the embodiment, the dynamic data of the lane can be identified more accurately by carrying out image identification processing on the acquired image data of the lane, the accuracy of the dynamic data of the lane is improved, so that the lane in the navigation route is subsequently screened based on the dynamic data, the accuracy and the effectiveness of the screened lane-based navigation route can be improved, and the accuracy of the obtained lane-based navigation route can be further improved.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
Further, the present disclosure also provides an autonomous vehicle including the provided electronic device. The autonomous vehicle may be an L3/L4 class of autonomous vehicles.
FIG. 5 illustrates a schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 5, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 can be stored. The calculation unit 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the electronic device 500 are connected to the I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, or the like; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508, such as a magnetic disk, optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 501 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 501 executes the respective methods and processes described above, such as the navigation route processing method of the automatic driving apparatus. For example, in some embodiments, the navigation route processing method of the autopilot device may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the navigation route processing method of the autopilot device described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured in any other suitable way (e.g., by means of firmware) to perform the navigation route processing method of the autonomous device.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on 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.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (14)
1. A navigation route processing method of an autonomous driving apparatus, comprising:
acquiring static data of lanes in an initial navigation route; the static data comprises lane communication data, lane operation safety data and lane operation area data;
acquiring dynamic data of the lane in the navigation route;
and screening the navigation route according to the static data, the dynamic data and a preset screening strategy to obtain the lane-based navigation route.
2. The method of claim 1, wherein the preset filtering strategies include static data filtering strategies and dynamic data filtering strategies, and the filtering the navigation route according to the static data, the dynamic data and the preset filtering strategies to obtain the lane-based navigation route comprises:
screening the navigation route according to the static data and the static data screening strategy to obtain a static data screening result;
and screening the static data screening result according to the dynamic data and the dynamic data screening strategy to obtain a lane-based navigation route.
3. The method of claim 2, wherein the static data screening policy comprises at least one of:
if the lane communication data meet a preset lane communication relation, screening a lane-based navigation route meeting the preset lane communication relation from the navigation routes as a static data screening result;
if the lane operation safety data meet the preset safety conditions, screening out a lane-based navigation route meeting the preset safety conditions from the navigation routes as a static data screening result; and
and if the lane operation area data meet the preset operation area conditions, screening out a lane-based navigation route meeting the preset operation area conditions from the navigation routes as a static data screening result.
4. The method of claim 2 or 3, wherein the dynamic data screening policy comprises:
and if the dynamic data are not matched with the preset dynamic events, screening out a lane-based navigation route with the dynamic data not matched with the preset dynamic events from the static data screening result, and taking the lane-based navigation route as the lane-based navigation route.
5. The method of any of claims 1-4, wherein the obtaining dynamic data for the lane in the navigation route comprises:
acquiring image data of the lane in the navigation route within a preset time period;
performing image recognition processing on the image data in the preset time period to obtain dynamic events and real-time road conditions of the lane;
and acquiring dynamic data of the lane in the navigation route according to the dynamic event and the real-time road condition of the lane.
6. A navigation route processing apparatus of an autonomous driving device, comprising:
the static data acquisition unit is used for acquiring static data of lanes in an initial navigation route; the static data comprises lane communication data, lane operation safety data and lane operation area data;
the dynamic data acquisition unit is used for acquiring dynamic data of the lane in the navigation route;
and the route screening processing unit is used for screening the navigation route according to the static data, the dynamic data and a preset screening strategy so as to obtain the navigation route based on the lane.
7. The apparatus according to claim 6, wherein the preset filtering policy includes a static data filtering policy and a dynamic data filtering policy, and the route filtering processing unit is specifically configured to:
screening the navigation route according to the static data and the static data screening strategy to obtain a static data screening result;
and screening the static data screening result according to the dynamic data and the dynamic data screening strategy to obtain a lane-based navigation route.
8. The apparatus of claim 7, wherein the static data screening policy comprises at least one of:
if the lane communication data meet a preset lane communication relationship, screening out a lane-based navigation route meeting the preset lane communication relationship from the navigation routes as a static data screening result;
if the lane operation safety data meet the preset safety conditions, screening out a lane-based navigation route meeting the preset safety conditions from the navigation routes as a static data screening result; and
and if the lane operation area data meet the preset operation area conditions, screening out a lane-based navigation route meeting the preset operation area conditions from the navigation routes as a static data screening result.
9. The apparatus of claim 6 or 7, wherein the dynamic data screening policy comprises:
and if the dynamic data are not matched with the preset dynamic events, screening out a lane-based navigation route with the dynamic data not matched with the preset dynamic events from the static data screening result, and taking the lane-based navigation route as the lane-based navigation route.
10. The apparatus according to any one of claims 6 to 9, wherein the dynamic data acquisition unit is specifically configured to:
acquiring image data of the lane in the navigation route within a preset time period;
carrying out image recognition processing on the image data in the preset time period to obtain the dynamic events and real-time road conditions of the lane; and
and acquiring dynamic data of the lane in the navigation route according to the dynamic event and the real-time road condition of the lane.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
13. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-5.
14. An autonomous vehicle comprising the electronic device of claim 11.
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