CN115658832A

CN115658832A - Map updating method and device, electronic equipment and storage medium

Info

Publication number: CN115658832A
Application number: CN202211341499.3A
Authority: CN
Inventors: 徐秋阳; 刘吉羽; 曹婷婷; 杨鹏
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-10-28
Filing date: 2022-10-28
Publication date: 2023-01-31

Abstract

The present disclosure provides a map updating method, which relates to the technical field of artificial intelligence, in particular to the technical fields of electronic maps, high-precision maps, intelligent transportation, etc. The specific implementation scheme is as follows: determining a plurality of target road routes related to the N obstacles in response to determining that the recognition result of the input image indicates that the relationship between the N obstacles and the road satisfies a preset condition, wherein N is an integer greater than 1; determining a first boundary line according to two obstacles which are not positioned on the same road in the N obstacles; determining a target area according to the first boundary line and a plurality of target road routes; and updating the target map by using the related information of the target area to obtain the updated target map. The present disclosure also provides a map updating apparatus, an electronic device, and a storage medium.

Description

Map updating method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of artificial intelligence technology, and in particular, to the field of electronic maps, high-precision maps, intelligent transportation technology, and the like. More particularly, the present disclosure provides a map updating method, apparatus, electronic device, and storage medium.

Background

With the development of artificial intelligence technology, the application scenarios of electronic maps are continuously increasing. Drive test data may be collected using a vehicle in which a collection device is deployed. According to the drive test data, whether a preset event occurs on the road and the area related to the preset event can be determined. For example, the preset event may be a road construction event.

Disclosure of Invention

The present disclosure provides a map updating method, apparatus, device, and storage medium.

According to an aspect of the present disclosure, there is provided a map updating method, including: determining a plurality of target road routes related to the N obstacles in response to determining that the recognition result of the input image indicates that the relationship between the N obstacles and the road satisfies a preset condition, wherein N is an integer greater than 1; determining a first boundary line according to two obstacles which are not positioned on the same road in the N obstacles; determining a target area according to the first boundary line and a plurality of target road routes; and updating the target map by using the related information of the target area to obtain the updated target map.

According to another aspect of the present disclosure, there is provided a map updating apparatus including: a first determination module, configured to determine a plurality of target road routes associated with N obstacles in response to determining that the recognition result of the input image indicates that a relationship between the N obstacles and a road satisfies a preset condition, where N is an integer greater than 1; the second determining module is used for determining a first boundary line according to two obstacles which are not positioned on the same road in the N obstacles; a third determining module for determining a target area according to the first boundary line and the plurality of target road routes; and the updating module is used for updating the target map by utilizing the relevant information of the target area to obtain the updated target map.

According to 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 memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method provided in accordance with the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform a method provided according to the present disclosure.

According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method provided according to the present disclosure.

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 of an exemplary system architecture to which the map update methods and apparatus may be applied, according to one embodiment of the present disclosure;

FIG. 2 is a flow diagram of a map update method according to one embodiment of the present disclosure;

FIG. 3A is a schematic diagram of an input image according to one embodiment of the present disclosure;

FIG. 3B is a schematic diagram of an input image according to another embodiment of the present disclosure;

FIG. 3C is a schematic diagram of an input image according to another embodiment of the present disclosure;

FIG. 3D is a schematic diagram of an input image according to another embodiment of the present disclosure;

FIG. 4 is a flow diagram of image recognition according to one embodiment of the present disclosure;

FIG. 5A is a schematic diagram of an input image according to another embodiment of the present disclosure;

FIG. 5B is a schematic illustration of a recognition result according to another embodiment of the present disclosure;

FIG. 6 is a schematic illustration of a target area according to one embodiment of the present disclosure;

FIG. 7 is a block diagram of a map updating apparatus according to one embodiment of the present disclosure; and

fig. 8 is a block diagram of an electronic device to which a map updating method may be applied according to one 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.

Drive test data may be collected by a drive test vehicle in which the collection device is deployed. The collected drive test data mainly comprises information such as road length, road width, road trend, road bending degree, road grade, whether the road is a split road and the like. The information is objectively presented in an electronic map system so as to provide daily travel navigation service for the user. With the progress of the collection and manufacturing process, not only can a simpler traditional map be manufactured, but also a more precise map with more comprehensive information can be manufactured. On the application level, the product is gradually applied to a plurality of traditional industries. Therefore, it is important to provide refined data mining for the subdivided scenes.

In real scenes, roads may need maintenance to ensure the normal use of the roads. However, the timeliness of obtaining the construction information based on the drive test data is poor, so that the change of the construction road cannot be obtained in time (for example, some roads are changed from closed construction roads to passable construction roads or from other situations to passable construction roads, and the like), so that when the navigation service is provided for the user, a reasonable route cannot be planned for the user (for example, a navigation route which is easy to plan can cause the user to detour), and the user navigation experience is poor easily.

Fig. 1 is a schematic diagram of an exemplary system architecture to which the map update method and apparatus may be applied, according to one embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.

As shown in fig. 1, a system architecture 100 according to this embodiment may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.

A user may use

terminal devices

101, 102, 103 to interact with a server 105 over a network 104 to receive or send messages or the like. The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the

terminal devices

101, 102, 103. The backend management server may analyze and process the received data such as the user request, and feed back a processing result (for example, a web page, information, or data obtained or generated according to the user request) to the terminal device.

It should be noted that the map updating method provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the map updating apparatus provided by the embodiment of the present disclosure may be generally disposed in the server 105. The map updating method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server 105 and is capable of communicating with the

terminal devices

101, 102, 103 and/or the server 105. Accordingly, the map updating apparatus provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the

terminal devices

101, 102, 103 and/or the server 105.

Fig. 2 is a flowchart of a map updating method according to one embodiment of the present disclosure.

As shown in fig. 2, the method 200 may include operations S210 to S240.

In operation S210, a plurality of target road routes associated with the N obstacles are determined in response to determining that the recognition result of the input image indicates that the relationship between the N obstacles and the road satisfies a preset condition.

In the disclosed embodiment, the input image is captured by a capture device. For example, the acquisition device may be disposed in a drive test vehicle, or may be disposed in a general vehicle. Also for example, the input image may be captured by the relevant person holding the relevant device.

In the embodiment of the present disclosure, in a case where it is determined that the positional relationship between the obstacle and the road satisfies the preset condition, it may be determined that the preset event occurs. For example, the preset event may be a road occupation construction event. For another example, the preset event may be other events that cause the road not to be used normally.

In the disclosed embodiments, N is an integer greater than 1.

In the disclosed embodiments, the road may be at least one of a motorway, a non-motorway and a sidewalk. For example, a road may include an area between two road routes. These two road routes may be used as the road line associated with the road.

In the embodiment of the present disclosure, the preset condition may be that the obstacle is inside the road. For example, taking N =7 as an example, the 3 rd obstacle may be within the 1 st road. The 5 th obstacle may be in the 2 nd road.

In the embodiment of the present disclosure, a road line related to a road on which the obstacle is located may be used as the target road line. For example, two road routes related to the 1 st road may be taken as the two target road routes. Two road routes associated with the 2 nd road may also be taken as the two target road routes.

In operation S220, a first boundary line is determined according to two obstacles that are not on the same road among the N obstacles.

For example, as described above, taking N =7 as an example, one first boundary line may be determined from the position of the 3 rd obstacle and the position of the 5 th obstacle.

In operation S230, a target area is determined according to the first boundary line and the plurality of target road routes.

For example, taking N =7 as an example, a second boundary line may be determined based on the 1 st obstacle and a third boundary line may be determined based on the 7 th obstacle. A closed area can be generated based on the first boundary line, the second boundary line, the third boundary line, and the plurality of target road lines. The closed area is taken as a target area.

In operation S240, the target map is updated using the relevant information of the target area update target map, resulting in an updated target map.

For example, a plurality of vertex coordinates of the target area may be added to the target map in order to update the target map.

Through the embodiment of the disclosure, the image is identified, and the position of the obstacle is determined according to the identification result. Therefore, whether a preset event (such as a construction event) occurs or not can be determined in time. Next, an area is determined based on the position of the obstacle. The target map is updated by using the relevant information of the area, so that the area can be avoided in time when services such as navigation and the like are provided for the user, the driving risk of the user caused by incomplete information is reduced, and the travel experience is improved. In addition, in emerging fields such as automatic driving, relevant information in the area can enable the machine to make avoidance behavior in advance, and the accident rate is reduced.

It is to be understood that the methods provided by the present disclosure are described above. The above-described input image will be described in detail with reference to the related embodiments.

Fig. 3A is a schematic diagram of an input image according to one embodiment of the present disclosure.

As shown in fig. 3A, in the input image 301, the cone 311 is located within the road 321. The road level of the road 321 may be, for example, a county road.

Fig. 3B is a schematic diagram of an input image according to another embodiment of the present disclosure.

As shown in fig. 3B, in the input image 302, the cone 312 is within the road 322.

Fig. 3C is a schematic diagram of an input image according to another embodiment of the present disclosure.

As shown in fig. 3C, in the input image 303, the tapered barrel 313 is closer to the road line 331, and the tapered barrel 331 can be considered to be located above the road line 331. The road route 331 may be a part of the road 323. It will be appreciated that conical cylinder 313 is also within road 323.

Fig. 3D is a schematic diagram of an input image according to another embodiment of the present disclosure.

As shown in fig. 3D, in the input image 304, no obstacle exists within the road 324. Outside of the road 324 there is a tapered barrel 314.

After the input image is obtained, the input image may be subjected to image recognition to obtain a recognition result, which will be described in detail below with reference to fig. 4.

Fig. 4 is a flow diagram of image recognition according to one embodiment of the present disclosure.

As shown in fig. 4, the method 401 may include operations S4011 through S4014. The method 401 may be performed before the above-described operation S210.

In operation S4011, image recognition is performed on each of the plurality of input images to obtain a plurality of recognition results.

In the embodiment of the present disclosure, the input image may be recognized by using a deep learning model, so as to obtain a recognition result. For example, the deep learning model may be, for example, a semantic segmentation model. For another example, the deep learning model may be, for example, an object detection model.

In the disclosed embodiment, the recognition result may include a plurality of original objects. For example, the category of the original object may be various categories.

Next, it may be determined whether an obstacle satisfying a preset condition exists in the recognition result. In some embodiments, the preset condition comprises at least one of: the obstacle is in the road; the category of the obstacle is a target obstacle category. In embodiments of the present disclosure, the target obstacle category may be a baffle, a fence, a spacer column, a water injection spacer, a sand injection spacer, a cone, and the like. Details will be described below in conjunction with operation S4012 and operation S4013.

In operation S4012, it is determined whether an obstacle of the target obstacle class exists in the plurality of original objects in the recognition result.

In the present disclosed embodiment, in response to determining that there is an obstacle of the target obstacle category among the plurality of original objects, operation S4013 is performed. For example, there may be K target obstacle classes of obstacles in the plurality of original objects. K may be an integer greater than 1.

In the embodiment of the present disclosure, in response to determining that there is no obstacle of the target obstacle category in the plurality of original objects, operation S4015 is performed, and the flow ends. For example, the original object type in the recognition results of the plurality of input images is not the target obstacle type, and the flow may be ended, and another plurality of input images may be newly acquired for recognition.

In operation S4013, it is determined whether an obstacle is in the road.

In the disclosed embodiment, in response to determining that the obstacle is within the road, operation S4014 is performed. For example, a plurality of obstacles that are adjacent to each other and located in the road may be determined from the K obstacles. The number of these obstacles may be N.

In the disclosed embodiment, in response to determining that none of the obstacles is within the road, operation S4015 is performed. For example, if all the K obstacles are outside the road, the process may be ended, and the other input images may be obtained again for recognition.

In operation S4014, N obstacles are obtained.

For example, as described above, N obstacles in the road among the K obstacles may be obtained.

It is to be understood that some embodiments of the image recognition of the input image in the present disclosure are described in detail above, and the recognition result will be described in detail with reference to the related examples.

Fig. 5A is a schematic diagram of an input image according to another embodiment of the present disclosure.

As shown in fig. 5A, the input image 505 includes a barrier 515, a road 525, and a road line 532.

Fig. 5B is a schematic diagram of a recognition result according to another embodiment of the present disclosure.

As shown in fig. 5B, the recognition result 5051 of the input image 505 may include an original object 515', an original object 525', and an original object 532'. The category of the original object 515' may be a target obstacle category. The category of the original object 525' may be a road. The category of the original object 532' may be a road route. The original object 515' may act as an obstacle.

It is understood that, from the recognition result 5051, it is determined that the obstacle 515 is located outside the road 525. The recognition result 5051 indicates that the positional relationship between the obstacle and the road does not satisfy the preset condition.

It is to be understood that some preset conditions of the present disclosure are described in detail above, and other preset conditions of the present disclosure are described in detail below with reference to the related embodiments.

In some embodiments, the preset conditions further include: two obstacles with a distance greater than or equal to a first preset distance exist in the N obstacles. For example, the first preset distance may be 50 meters. For example, in a vehicle failure scenario, the driver of the vehicle may place a safety marker (which may be, for example, a cone) near the vehicle. These security markers are fewer in number and closer in distance. The vehicle can be pulled away from the area by the trailer in a short time, and the long-term influence on the passing of other vehicles can not be caused. Therefore, after the preset condition related to the distance between the obstacles is set, the map can be prevented from being updated according to the temporary road occupation event such as vehicle faults, the effective updating times of the map can be improved, and the user experience is further improved.

In some embodiments, the preset conditions further include: in the case where a merging road exists among the plurality of roads, a distance between the obstacle and a merging area formed by at least two roads is greater than or equal to a second preset distance. For example, the second preset distance may be 100 meters. The merge area may be an area where traffic is prohibited. A marker may be placed near the confluence area to alert the driver. Therefore, after the preset condition related to the distance between the barrier and the confluence area is set, the confluence area can be prevented from being determined as the target area, the effective updating times of the map can be improved, and the user experience is further improved.

In some embodiments, the preset conditions further include: in the case where there is a diversion road among the plurality of roads, a distance between the obstacle and a diversion area formed by at least two roads is greater than or equal to a second preset distance. For example, the second preset distance may be 100 meters. The diversion area may be a no-pass area. A marker may be placed near the diversion area to alert the driver. Therefore, after the preset condition related to the distance between the barrier and the shunting area is set, the shunting area can be prevented from being determined as the target area, the effective updating times of the map can be improved, and the user experience is further improved.

In some embodiments, the preset conditions further include: the distance between the obstacle and the preset ground object is greater than or equal to a third preset distance. For example, the preset feature may be a toll booth. For example, the third preset distance may be 100 meters. The toll station can be provided with a guide marker in front of the toll station to remind a driver of the toll station in front of the driver. Therefore, after the preset condition related to the distance between the obstacle and the preset ground object is set, the region where the toll station is located can be prevented from being determined as the target region, the number of effective updating times of the map is improved, and the user experience is further improved.

It is to be understood that the preset conditions of the present disclosure are described in detail above, and some ways of determining the target area of the present disclosure will be described in detail below with reference to the related embodiments.

FIG. 6 is a schematic view of a target area according to one embodiment of the present disclosure.

As shown in fig. 6, a road 6201 may include an area between a 1 st road line 6301 and a 2 nd road line 6302. The roadway 6202 may include an area between the 2 nd road line 6302 and the 3 rd road line 6302. The roadway 6203 may include an area between the 3 rd road line 6303 and the 4 th road line 6304.

After the input image is recognized, N obstacles can be obtained. In the present embodiment, taking N =7 as an example, the positional relationship between 7 obstacles in total and the road satisfies the preset condition. For example, the 1 st obstacle 6101 is within the road 6201. The 2 nd obstacle 6102 is in the road 6201. The 3 rd obstacle 6103 is in the road 6201. The 4 th obstacle 6104 is on road line 6302. The 5 th obstacle 6105 is in the road 6202. The 6 th obstacle 6106 is in the road 6202. The 7 th obstacle 6107 is in the road 6202. The class of these obstacles may be the target obstacle class (cone).

In some embodiments, in some implementations of operation S210 described above, the road lines associated with the N obstacles may be used as the target road route.

For example, as shown in fig. 6, 7 obstacles are both within the road 6201 and the road 6202. The road line associated with these two roads may be taken as the target road route. In one example, road line 6301, road line 6302, and road line 6303 may be the target road route.

In some embodiments, in some implementations of operation S220 described above, determining the first boundary line based on two obstacles that are not on the same road in the plurality of obstacles comprises: in response to determining that the nth obstacle is in a first road of the plurality of roads and that the n + mth obstacle is in a second road of the plurality of roads, a first boundary line is determined from the nth obstacle and the n + mth obstacle.

In the embodiments of the present disclosure, m is an integer greater than or equal to 1, N is an integer greater than or equal to 1 and less than or equal to N, and N + m is an integer less than or equal to N.

In an embodiment of the present disclosure, the plurality of target road routes are I target road routes, I being an integer greater than 1. For example, in this embodiment, I may be 3.

In the disclosed embodiment, the first road is associated with the i-th target road route and the i + 1-th target road line, and the second road is associated with the i + j-th target road route and the i + j + 1-th target road line. For example, j is an integer greater than or equal to 1, I is an integer greater than or equal to 1 and less than I, and I + j +1 is an integer less than or equal to I. For example, as shown in fig. 6, the 3 rd obstacle 6103 is within the road 6201. The 5 th obstacle 6105 is in the road 6202. It is understood that n may be 3 and m may be 2. The road 6201 may be the first road. The road 6202 may be the second road. As described above, the road 6201 may include an area between the 1 st road line 6301 and the 2 nd road line 6302. The road 6202 may include an area between the 2 nd road line 6302 and the 3 rd road line 6302. The 1 st road line 6301 may be the ith target road route, the 2 nd road line 6302 may be the (i + 1) th target road route and the (i + j) th target road route, and the 3 rd road line 6303 may be the (i + j + 1) th target road route. It is understood that, in this embodiment, i = j =1.

In the embodiment of the present disclosure, in the case where m is greater than 1, m-1 obstacles located between the nth obstacle and the n + mth obstacle are on the road line between the first road and the second road. For example, as described above, m =2, and the obstacle between the 3 rd obstacle and the 5 th obstacle 6105 is the 4 th obstacle 6104. The 4 th obstacle 6104 may be on the road line 6302.

In an embodiment of the present disclosure, determining the first boundary line based on the nth obstacle and the n + mth obstacle includes: determining a first projection position of the nth obstacle on the (i + 1) th target road route; determining a second projection position of the (n + m) th obstacle on the (i + j + 1) th target road route; and determining the first boundary line according to the first projection position and the second projection position. For example, a first projected location 61031 of a 3 rd obstacle 6103 on a 2 nd road line may be determined. A second projected location 61051 of the 5 th obstacle 6105 on the 3 rd lane route may also be determined. From the first 61031 and the second 61051 projection position, a first boundary line E661 can be determined. Through the embodiment of the disclosure, the boundary line related to two lanes can be accurately generated. Thereby, the safety can be sufficiently improved, and also as many passable areas as possible can be provided in the target map.

In some embodiments, in some implementations of operation S230 described above, determining the target area based on the first boundary line and the plurality of target road routes includes: the second boundary line is determined on the basis of the 1 st obstacle. A third boundary line is determined based on the nth obstacle. And determining the target area according to the first boundary line, the second boundary line, the third boundary line and the plurality of target road routes. For example, a straight line passing through the 1 st obstacle 6101 and perpendicular to the road line may be used as the second boundary line E662. A straight line passing through the 7 th obstacle 6107 and perpendicular to the road line may be taken as the third boundary line E663. From the first boundary line E661, the second boundary line E662, the third boundary line E663, the 1 st road line 6301, the second road line 6302 and the 3 rd road line 6303, one target region 660 can be determined.

In some embodiments, in some implementations of operation S240 described above, updating the target map with the relevant information of the target area includes: generating a visual area according to the related information of the target area; and adding the visual area to a visual interface for displaying the target map. For example, the visible region is generated from the vertex coordinates of the target region 660. And adding the visual area into a visual interface of the target map so as to update the target map.

Fig. 7 is a block diagram of a map updating apparatus according to one embodiment of the present disclosure.

As shown in fig. 7, the apparatus 700 may include a first determination module 710, a second determination module 720, a third determination module 730, and an update module 740.

A first determining module 710, configured to determine a plurality of target road routes related to the N obstacles in response to determining that the recognition result of the input image indicates that the relationship between the N obstacles and the road satisfies a preset condition. For example, N is an integer greater than 1.

The second determining module 720 is configured to determine the first boundary line according to two obstacles that are not on the same road in the N obstacles.

A third determining module 730, configured to determine the target area according to the first boundary line and the plurality of target road routes.

The updating module 740 is configured to update the target map by using the relevant information of the target area, so as to obtain an updated target map.

In some embodiments, the preset condition comprises at least one of: the obstacle is in the road; the category of the obstacle is a target obstacle category.

In some embodiments, the second determining module comprises: a first determination submodule for determining a first boundary line from an nth obstacle and an N + mth obstacle in response to determining that the nth obstacle is in a first road of the plurality of roads and the N + mth obstacle is in a second road of the plurality of roads, where m is an integer greater than or equal to 1, N is an integer greater than or equal to 1 and less than or equal to N, and N + m is an integer less than or equal to N.

In some embodiments, in the case where m is greater than 1, m-1 obstacles located between the nth obstacle and the n + mth obstacle are on the target road line between the first road and the second road.

In some embodiments, the plurality of target road routes are I target road routes, I is an integer greater than 1, the first road is associated with an I-th target road route and an I + 1-th target road line, the second road is associated with an I + j-th target road route and an I + j + 1-th target road line, j is an integer greater than or equal to 1, I is an integer greater than or equal to 1 and less than I, I + j +1 is an integer less than or equal to I, the first determination submodule includes: the first determining unit is used for determining a first projection position of the nth obstacle on the (i + 1) th target road route; the second determining unit is used for determining a second projection position of the n + m obstacle on the i + j +1 th target road route; and a third determination unit for determining the first boundary line based on the first projection position and the second projection position.

In some embodiments, the second determining module comprises: the second determining submodule is used for determining a second boundary line according to the 1 st obstacle; a third determining submodule for determining a third boundary line based on the nth obstacle; and a fourth determination submodule for determining the target area based on the first boundary line, the second boundary line, the third boundary line, and the plurality of target road lines.

In some embodiments, the update module comprises: the generation submodule is used for generating a visual area according to the relevant information of the target area; and the adding submodule is used for adding the visual area into a visual interface for displaying the target map.

In some embodiments, the input image is multiple, and the apparatus 700 further comprises: the identification module is used for respectively carrying out image identification on the plurality of input images to obtain a plurality of identification results, wherein the plurality of identification results comprise N obstacles.

In some embodiments, the preset conditions further comprise at least one of: two obstacles with the distance greater than or equal to a first preset distance exist in the N obstacles; in the case where there is a merging road among the plurality of roads, a distance between the obstacle and a merging area formed by at least two roads is greater than or equal to a second preset distance; when a shunting road exists in the plurality of roads, the distance between the barrier and a shunting area formed by at least two roads is greater than or equal to a second preset distance; the distance between the obstacle and the preset ground object is greater than or equal to a third preset distance.

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.

FIG. 8 shows a schematic block diagram of an example electronic device 800 that may 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. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, 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. 8, the apparatus 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data necessary for the operation of the device 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.

A number of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

Computing unit 801 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 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 the like. The calculation unit 801 performs the respective methods and processes described above, such as the map update method. For example, in some embodiments, the map update method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto device 800 via ROM 802 and/or communications unit 809. When the computer program is loaded into RAM 803 and executed by the computing unit 801, one or more steps of the map updating method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the map update method in any other suitable manner (e.g., by means of firmware).

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 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) display or an LCD (liquid crystal display)) 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.

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

1. A map updating method, comprising:

in response to determining that the recognition result of the input image indicates that the relationship between the N obstacles and the road satisfies a preset condition, determining a plurality of target road routes associated with the N obstacles, wherein N is an integer greater than 1;

determining a first boundary line according to two obstacles which are not positioned on the same road in the N obstacles;

determining a target area according to the first boundary line and the plurality of target road routes; and

and updating the target map by using the relevant information of the target area to obtain the updated target map.

2. The method of claim 1, wherein the preset condition comprises at least one of: the obstacle is within the road;

the type of the obstacle is a target obstacle type.

3. The method of claim 1, wherein said determining a first boundary line from two of said N obstacles that are not on the same road comprises:

in response to determining that the nth obstacle is in a first road of the plurality of roads and that the N + mth obstacle is in a second road of the plurality of roads, determining the first boundary line from the nth obstacle and the N + mth obstacle, where m is an integer greater than or equal to 1, N is an integer greater than or equal to 1 and less than or equal to N, and N + m is an integer less than or equal to N.

4. The method according to claim 3, wherein in the case where m is greater than 1, m-1 of the obstacles located between the nth obstacle and the n + mth obstacle are on a target road line between the first road and the second road.

5. The method of claim 3, wherein a plurality of the target road routes are I target road routes, I being an integer greater than 1,

said first road being associated with an I-th said destination road route and an I + 1-th said destination road route, said second road being associated with an I + j-th said destination road route and an I + j + 1-th said destination road route, j being an integer greater than or equal to 1, I being an integer greater than or equal to 1 and less than I, I + j +1 being an integer less than or equal to I,

said determining said first boundary line from said nth obstacle and said n + mth obstacle comprises:

determining a first projection position of the nth obstacle on the (i + 1) th target road route;

determining a second projection position of the (n + m) th obstacle on the (i + j + 1) th target road route; and

and determining the first boundary line according to the first projection position and the second projection position.

6. The method of claim 1, wherein said determining a target area based on said first boundary line and a plurality of said target road routes comprises:

determining a second boundary line according to the 1 st obstacle;

determining a third boundary line based on the nth barrier; and

and determining the target area according to the first boundary line, the second boundary line, the third boundary line and the plurality of target road routes.

7. The method of claim 1, wherein the updating the target map with the information related to the target area comprises:

generating a visual area according to the related information of the target area; and

adding the visual area to a visual interface for displaying the target map.

8. The method of claim 1, the input image being a plurality,

the method further comprises the following steps:

and respectively carrying out image recognition on the plurality of input images to obtain a plurality of recognition results, wherein the plurality of recognition results comprise N obstacles.

9. The method of claim 2, wherein the preset conditions further comprise at least one of:

two obstacles with a distance greater than or equal to a first preset distance exist in the N obstacles;

in the case where a merging road exists among the plurality of roads, the distance between the obstacle and a merging area formed by at least two of the roads is greater than or equal to a second preset distance;

in the case that a diversion road exists in the plurality of roads, the distance between the obstacle and a diversion area formed by at least two roads is greater than or equal to the second preset distance;

the distance between the obstacle and the preset ground object is greater than or equal to a third preset distance.

10. A map updating apparatus comprising:

a first determination module, configured to determine a plurality of target road routes related to N obstacles in response to determining that a recognition result of the input image indicates that a relationship between the N obstacles and a road satisfies a preset condition, where N is an integer greater than 1;

the second determining module is used for determining a first boundary line according to two obstacles which are not positioned on the same road in the N obstacles;

a third determining module, configured to determine a target area according to the first boundary line and the plurality of target road routes; and

and the updating module is used for updating the target map by utilizing the relevant information of the target area to obtain the updated target map.

11. The apparatus of claim 10, wherein the preset condition comprises at least one of:

the obstacle is within the road;

the type of the obstacle is a target obstacle type.

12. The apparatus of claim 11, wherein the second determining means comprises:

a first determination submodule configured to determine the first boundary line based on an nth obstacle and an N + mth obstacle in response to determining that the nth obstacle is on a first road of the plurality of roads and the N + mth obstacle is on a second road of the plurality of roads, where m is an integer greater than or equal to 1, N is an integer greater than or equal to 1 and less than or equal to N, and N + m is an integer less than or equal to N.

13. The apparatus of claim 12, wherein in case m is greater than 1, m-1 of the obstacles located between the nth obstacle and the n + mth obstacle are located on a target road line between the first road and the second road.

14. The apparatus of claim 12, wherein the plurality of target road routes is I target road routes, I being an integer greater than 1,

the first determination submodule includes:

a first determination unit, configured to determine a first projection position of the nth obstacle on the (i + 1) th target road route;

a second determining unit, configured to determine a second projection position of the n + m-th obstacle on the i + j + 1-th target road route; and

a third determining unit, configured to determine the first boundary line according to the first projection position and the second projection position.

15. The apparatus of claim 10, wherein the second determining means comprises:

the second determining submodule is used for determining a second boundary line according to the 1 st obstacle;

a third determining submodule for determining a third boundary line based on the nth obstacle; and

a fourth determining submodule, configured to determine the target area according to the first boundary line, the second boundary line, the third boundary line, and the plurality of target road lines.

16. The apparatus of claim 10, wherein the update module comprises:

the generation submodule is used for generating a visual area according to the relevant information of the target area; and

and the adding sub-module is used for adding the visual area into a visual interface for displaying the target map.

17. The apparatus of claim 10, the input image being a plurality,

the device further comprises:

and the identification module is used for respectively carrying out image identification on the input images to obtain a plurality of identification results, wherein the identification results comprise the N obstacles.

18. The apparatus of claim 11, wherein the preset conditions further comprise at least one of:

in the case where a merging road exists in a plurality of the roads, the distance between the obstacle and a merging area formed by at least two of the roads is greater than or equal to a second preset distance;

in the case that a diversion road exists in a plurality of roads, the distance between the obstacle and a diversion area formed by at least two roads is greater than or equal to the second preset distance;

19. 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 method of any one of claims 1 to 9.

20. 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 to 9.

21. A computer program product comprising a computer program which, when executed by a processor, implements the method of any one of claims 1 to 9.