CN114090642A

CN114090642A - Map road network matching method, device, equipment and medium

Info

Publication number: CN114090642A
Application number: CN202111390414.6A
Authority: CN
Inventors: 陈志祥; 申雅倩; 郭运韬
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2021-11-22
Filing date: 2021-11-22
Publication date: 2022-02-25

Abstract

The disclosure provides a map network matching method, device, equipment and medium, and relates to the technical field of computers, in particular to the field of intelligent transportation. The map road network matching method has the specific implementation scheme that: acquiring first road network data of a first map and second road network data of a second map; determining at least one candidate traffic flow change point in the second road network data within a preset offset range by taking the first traffic flow change point in the first road network data as a reference point; screening at least one candidate traffic flow change point according to the characteristics of the first traffic flow change point and the characteristics of at least one candidate traffic flow change point, and determining a second traffic flow change point matched with the first traffic flow change point; and matching the road in the first map with the road in the second map according to the first traffic flow change point and the second traffic flow change point.

Description

Map road network matching method, device, equipment and medium

Technical Field

The present disclosure relates to the field of computer technology, and more particularly, to the field of intelligent transportation technology.

Background

In the related art, the electronic map data may be divided into map data of different accuracy levels. For example, the accuracy of general electronic map road data is on the meter level, and such electronic map road data is called standard navigation map data (SD). Along with the improvement of the precision of the positioning equipment, the precision of the electronic map road data can be improved to a sub-meter level, and data expressed in detail by lane information is added, wherein the electronic map road data is called lane level navigation map data (LD). The accuracy of electronic map road data, which is called high-precision navigation map data (HD), can also be set to centimeter level, such as maps applied in the field of automatic driving.

Disclosure of Invention

The disclosure provides a map network matching method, device, equipment and medium.

According to an aspect of the present disclosure, there is provided a map network matching method, including:

acquiring first road network data of a first map and second road network data of a second map;

determining at least one candidate traffic flow change point in the second road network data within a preset offset range by taking the first traffic flow change point in the first road network data as a reference point;

screening at least one candidate traffic flow change point according to the characteristics of the first traffic flow change point and the characteristics of at least one candidate traffic flow change point, and determining a second traffic flow change point matched with the first traffic flow change point;

and matching the roads in the first map with the roads in the second map according to the first traffic flow change point and the second traffic flow change point.

According to another aspect of the present disclosure, there is provided a map network matching apparatus, including:

the acquisition module is used for acquiring first road network data of a first map and second road network data of a second map;

a first determining module, configured to determine at least one candidate traffic flow change point in the second road network data, where the candidate traffic flow change point is located within a preset offset range, with a first traffic flow change point in the first road network data as a reference point;

a second determining module, configured to filter at least one candidate traffic flow change point according to a feature of the first traffic flow change point and a feature of the at least one candidate traffic flow change point, and determine a second traffic flow change point matching the first traffic flow change point;

and the matching module is used for matching the road in the first map with the road in the second map according to the first traffic flow change point and the second traffic flow change point.

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; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method.

According to 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 as described above.

According to another aspect of the present disclosure, there is provided a computer program product comprising computer programs/instructions which, when executed by a processor, implement the method as described above.

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 schematically illustrates an exemplary system architecture to which a map network matching method may be applied, according to an embodiment of the present disclosure;

FIG. 2 schematically shows a flow chart of a map network matching method according to an embodiment of the present disclosure;

3(a) -3 (d) schematically illustrate traffic flow change points in a first map as diversions, confluence, intersections and rotary islands according to an embodiment of the disclosure;

4(a) -4 (d) schematically illustrate traffic flow change points in a second map as diversion ports, confluence ports, intersection ports and rotary islands according to an embodiment of the disclosure;

FIG. 5 schematically illustrates a flow chart of a method of determining a preset offset range according to an embodiment of the disclosure;

FIG. 6 schematically illustrates a flow chart of a method of setting a preset offset range according to an embodiment of the present disclosure;

FIG. 7 schematically illustrates a schematic diagram of traffic flow change point matching according to an embodiment of the disclosure;

fig. 8 schematically illustrates a flowchart of a method of determining a second traffic flow change point according to an embodiment of the present disclosure;

FIG. 9 schematically shows a flow chart of a method of obtaining an epidemic matching result, in accordance with an embodiment of the present disclosure;

FIG. 10 schematically shows a schematic diagram of epidemic matching, in accordance with an embodiment of the disclosure;

FIG. 11 schematically shows a flow chart of a map network matching method according to an embodiment of the present disclosure;

fig. 12 schematically shows a block diagram of a map network matching apparatus according to an embodiment of the present disclosure; and

fig. 13 schematically shows a block diagram of an electronic device for implementing the map network matching method according to the 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 embodiments of the present 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.

Due to the manufacturing cost and the application requirement, the application range of the current standard navigation map is inconsistent with that of the lane-level navigation map and the high-precision navigation map. Some high-grade roads such as high speed, urban express roads or roads with strong traffic capacity can be made with higher precision, and some low-grade roads such as district inner roads, country roads and the like can meet the navigation requirements by making standard navigation maps.

Because the data coverage of different maps is different, and for the purpose of navigation computation efficiency, the SD data is generally used for long-distance planning, the LD or HD data is locally reused, and the SD data and the LD/HD data need to be switched back and forth. The switching among different types of navigation maps requires the establishment of mapping matching relations among a standard navigation map road network, a lane-level navigation map road network and a high-precision navigation map data road network. For example, for the same road, there is one road in the standard navigation map, and there is one road in the lane level navigation map and the high-precision navigation map, respectively, and a mapping relationship is established among the three, and the establishment of the mapping relationship needs to be realized by using a map network matching method.

In implementing the present disclosure, it is found that the association matching between the standard map and the high-precision map generally has the following manner.

One matching method is spatial position matching, a high-precision map can represent a road area by one surface due to the fact that the high-precision map comprises data such as lane lines, road boundaries and the like, roads of a standard map are generally represented by one line segment, spatial position analysis is conducted between the road surface of the high-precision map and the road lines of the standard map, and the roads in the standard map can be considered to be matched with the roads represented by the road surface of the high-precision map when the road lines of the standard map fall in the road surface of the high-precision map.

Another matching method is to adopt a closest distance method, match the road network nodes in the standard map with the road network nodes in the high-precision map according to the closest distance method, and after the node matching is completed, match the road articulated between two nodes in the standard map with the road articulated between two nodes in the high-precision map, which is also called as a node matching method.

Based on the spatial position matching and the closest distance node matching, the map precision requirement is high. The high-precision map can meet the matching requirement generally, but the standard map precision is low, satellite signals are greatly influenced by the environment in places such as high-rise buildings, tunnels and the like, the precision of the acquired standard map data is generally low, and in addition, in places with branches on high-speed roads, in order to be smoothly hooked, a large angle is avoided to be hooked, and the deviation of the shunting or converging position of the standard map data and the on-site shunting or converging position is often large. There may be more mismatches with spatial location matching or closest distance node matching.

In addition, high-precision map roads in a certain surrounding space range can be obtained according to a certain road in the standard map, and then the matching mode of screening is carried out by considering conditions such as road direction, angle, nearest distance and the like.

However, due to the adoption of the matching method, the accuracy of the standard map is low, and if the standard map road is greatly staggered in a place with poor accuracy, the high-accuracy road parallel to the standard map road in the surrounding range of the standard map road may not be the matched road, so that mismatching is caused.

On the other hand, for certain specific scenarios, such as a main road scenario, it may happen that a main road of a standard map matches a side road of a high-precision map or that a side road of a standard map matches a side road of a high-precision map. For example, in the case of an elevated road, if there is no elevation information, there may be a problem that the upper road matches the lower road.

To at least partially solve the technical problems in the related art, the present disclosure provides a method for matching a road network of maps, comprising: acquiring first road network data of a first map and second road network data of a second map; determining at least one candidate traffic flow change point in the second road network data within a preset offset range by taking the first traffic flow change point in the first road network data as a reference point; screening at least one candidate traffic flow change point according to the characteristics of the first traffic flow change point and the characteristics of at least one candidate traffic flow change point, and determining a second traffic flow change point matched with the first traffic flow change point; and matching the road in the first map with the road in the second map according to the first traffic flow change point and the second traffic flow change point. The disclosure also provides a map network matching device, equipment and medium.

Fig. 1 schematically shows an exemplary system architecture to which the map network matching method may be applied according to an 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

smart driving devices

101, 102, 103 and a server 104. The

smart driving devices

101, 102, 103 and the server 104 may communicate with each other via a network, which may include various connection types, such as wired and/or wireless communication links, etc.

The

smart driving devices

101, 102, 103 may interact with the server 104 to receive or transmit positioning information or the like. The

smart driving devices

101, 102, 103 may have installed thereon various client applications that may provide positioning and navigation functions, such as a map-like application, a navigation-like application, and the like (for example only).

The

smart driving devices

101, 102, 103 may be various vehicles that support positioning and navigation functions, including but not limited to smart cars, smart school buses, smart vans, and the like.

The server 104 may be a server that provides various services, such as a background management server (for example only) that provides support for positioning information acquired by the

smart driving devices

101, 102, 103. The back-office management server may analyze and/or otherwise process the received positioning information obtained by the

smart driving apparatuses

101, 102, and 103, and feed back the processing result (e.g., the route, information, or data obtained or generated from the positioning information of the smart driving apparatuses) to the smart driving apparatuses.

It should be noted that the map network matching method provided by the embodiment of the present disclosure may be generally executed by the server 104. Accordingly, the map network matching device provided by the embodiment of the present disclosure may be generally disposed in the server 104. The map network matching 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 104 and is capable of communicating with the

smart driving apparatuses

101, 102, 103 and/or the server 104. Accordingly, the map network matching device provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 104 and capable of communicating with the

intelligent driving apparatuses

101, 102, 103 and/or the server 104.

For example, the road network data may be obtained by any one of the

smart driving devices

101, 102, or 103 (e.g., the smart driving device 101, but not limited thereto), or the road network data may be stored in the server 104, and the server 104 may match the road network data obtained by the smart driving device 101 with the road network data stored in the server 104. Then, the server 104 may execute the map road network matching method provided by the embodiment of the present disclosure, or send the road network data to another server or server cluster, and execute the map road network matching method provided by the embodiment of the present disclosure by another server or server cluster receiving the road network data.

It should be understood that the number of smart driving devices and servers in fig. 1 is merely illustrative. There may be any number of smart driving devices and servers, as desired for implementation.

Fig. 2 schematically shows a flow chart of a map network matching method according to an embodiment of the present disclosure.

As shown in fig. 2, the map network matching method includes operations S210 to S240.

In operation S210, first road network data of a first map and second road network data of a second map are acquired.

According to the embodiment of the disclosure, the road network can be a network architecture composed of road segments with different functions, grades and locations in a city range, and in a certain density and a proper form. The road network may include road segments and connection relations between road segments, wherein a road segment may be formed by connecting at least two reference points.

According to an embodiment of the present disclosure, the first map may be a map used when a local match is made or when higher accuracy road navigation is required. The application scenarios of the first map may include, for example, but are not limited to: high speed, urban express way or road with strong traffic capacity.

According to an embodiment of the present disclosure, the first network data may be, for example: sub-meter level lane level navigation map data (LD), centimeter level high-precision navigation map data (HD), and the like. The first network data may include, for example, but is not limited to: data detailing lane information, for example, may include road data such as lane information such as the position, type, width, gradient, and curvature of a lane line; and fixed object information around the lane, such as traffic signs, traffic lights, etc., lane limits, junctions, obstacles, and other road details, and further includes infrastructure information such as overhead objects, guard rails, number, road edge types, roadside landmarks, etc.

According to an embodiment of the present disclosure, the second map may be a map used when global planning or when less accurate road navigation is required. Application scenarios of the second map may include, for example, but are not limited to: intra-district roads, country roads, etc.

According to an embodiment of the present disclosure, the second network data may be, for example: standard navigation map data (SD) with a data accuracy of 1-10 meters, and the like. The second network data may include, for example, but is not limited to: a line segment representing a road, etc.

According to the embodiment of the disclosure, the acquisition, storage, application and the like of the road network data of the related map are all in accordance with the regulations of related laws and regulations, and do not violate the good customs of the public order.

In operation S220, at least one candidate traffic flow change point located within a preset offset range in the second road network data is determined using the first traffic flow change point in the first road network data as a reference point.

According to an embodiment of the present disclosure, the first traffic flow change point may be represented by a type and a position of the traffic flow change point in the first road network data.

According to the embodiment of the present disclosure, a preset offset range may be set for each of the traffic flow change points in the second road network data. Then, at least one candidate traffic flow change point in the second road network data within the preset offset range can be determined by taking the first traffic flow change point in the first road network data as a reference point and taking the preset offset range as a search radius.

According to the embodiment of the disclosure, the candidate traffic flow change point may be represented by the type and the position of the candidate point, which is located within the preset offset range and matches the position of the first traffic flow change point, in the second road network data.

In operation S230, at least one candidate traffic flow change point is screened according to the feature of the first traffic flow change point and the feature of the at least one candidate traffic flow change point, and a second traffic flow change point matching the first traffic flow change point is determined.

According to the embodiment of the disclosure, the candidate traffic flow change point obtained by position matching can be further subjected to change point feature matching, so that a second traffic flow change point matched with both the position and the feature of the first traffic flow change point is screened out.

According to an embodiment of the present disclosure, the second traffic flow change point may represent a type and a location of a change point that is located within a preset offset range and matches a feature of the first traffic flow change point, among the candidate traffic flow change points in the second road network data.

In operation S240, roads in the first map and roads in the second map are matched according to the first traffic flow change point and the second traffic flow change point.

According to an embodiment of the present disclosure, the method of matching the road in the first map and the road in the second map may employ a map matching Model, such as a Hidden Markov Model (HMM), for example. The hidden markov model may be used to compare a road in the first map with roads in a plurality of second maps, and to find a route from the roads in the second maps that is closest to the trajectory of the road in the first map as a road in the second map that matches the road in the first map. It is to be understood that the map matching model described above is only used as an example for understanding the embodiments of the present disclosure, and the embodiments of the present disclosure are not limited to the map matching model specifically, for example, the map matching model may also be a kalman filtering model, a fuzzy logic model, or the like.

According to the embodiment of the present disclosure, the method of Matching the roads in the first map and the roads in the second map may also use a map Matching algorithm, such as ST-Matching algorithm, for example. The ST-Matching algorithm is a global algorithm that can determine a road in a second map that matches a road in each first map among roads in a plurality of second maps by integrating geometric information, road topology information, road attribute information, and the like. It is to be understood that the above map matching algorithm is only used as an example for understanding the embodiments of the present disclosure, and the embodiments of the present disclosure are not limited to the map matching algorithm specifically, for example, the map matching algorithm may also be a Forward algorithm, a Baum-Welch algorithm, or the like.

According to the embodiment of the disclosure, the road matching may be to establish a mapping correspondence relationship for corresponding roads in different maps. For example, an expressway from a certain point a to a point B has a corresponding road in the SD map, and also has a corresponding road in the HD/LD map, and a mapping correspondence relationship is established between the two roads, that is, the expressway is matched.

According to an embodiment of the present disclosure, based on a position of a first traffic flow change point in road network data, a candidate traffic flow change point located within a preset offset range may be determined; screening the candidate traffic flow change points based on the characteristics of the first traffic flow change point and the candidate traffic flow change points, and determining a second traffic flow change point; performing road matching according to the first traffic flow change point and the second traffic flow change point; by utilizing the technical scheme of combining position matching of traffic flow change points in road network data with feature matching, the problem of mismatching caused by different map road network data is at least partially solved, so that map road network matching can be well completed, and a more ideal matching effect is obtained.

The method shown in fig. 2 is further described with reference to fig. 3-13 in conjunction with specific embodiments. Those skilled in the art will appreciate that the following example embodiments are only for the understanding of the present disclosure, and the present disclosure is not limited thereto.

According to an embodiment of the present disclosure, the area where the traffic flow change exists may be referred to as a traffic flow change point, for example, may include but is not limited to: a flow dividing port, a flow combining port, a road junction, a roundabout and the like.

Fig. 3(a) -3 (d) schematically show a first map in which traffic flow change points are a diversion port, a confluence port, an intersection and a roundabout respectively according to an embodiment of the disclosure.

According to an embodiment of the present disclosure, as shown in fig. 3(a), a schematic diagram when a traffic flow change point is a diversion port in a first map may be represented; as shown in fig. 3(b), a schematic diagram when the traffic flow change point in the first map is a confluence; as shown in fig. 3(c), a schematic diagram when the traffic flow change point in the first map is an intersection can be shown; as shown in fig. 3(d), a schematic diagram when the traffic flow change point in the first map is a rotary may be shown.

According to the embodiment of the present disclosure, the first network data of the first map may give the position of each lane line in the road and the road boundary, and may generally surround a stateful surface with the road boundary.

Fig. 4(a) -4 (d) schematically show a second map in which traffic flow change points are a diversion port, a confluence port, an intersection and a roundabout respectively according to an embodiment of the disclosure.

According to an embodiment of the present disclosure, as shown in fig. 4(a), a schematic diagram when a traffic flow change point in a first map is a diversion port may be represented; as shown in fig. 4(b), a schematic diagram when the traffic flow change point in the first map is a confluence port may be shown; as shown in fig. 4(c), a schematic diagram when the traffic flow change point in the first map is an intersection can be shown; as shown in fig. 4(d), a schematic diagram when the traffic flow change point in the first map is a rotary may be shown.

According to an embodiment of the present disclosure, the roads in the second road network data of the second map are generally represented by one line segment.

According to an embodiment of the present disclosure, at least one of the following traffic flow change points is included in the first and second road network data, respectively: a flow dividing port, a flow combining port, a road junction and a roundabout.

According to embodiments of the present disclosure, a diversion port may divide traffic flow from one direction into two different directions. In a diversion port, one traffic entity can generally only select one direction at a time.

According to embodiments of the present disclosure, a junction may be a junction where two or more traffic flows in different directions merge into one direction. At the junction, traffic entities may interfere with each other at the same time.

According to an embodiment of the present disclosure, an intersection may be where two roads intersect.

According to the embodiment of the disclosure, the rotary island can be composed of a circular lane and a central island, so that after traffic flow coming from any direction enters the rotary island, the rotary island is required to rotate in a single direction according to a central diagram of the rotary island until the rotary island is turned to a required driving direction and leaves. In a roundabout there are typically 4 inlets and 4 outlets (or more).

According to an embodiment of the present disclosure, the characteristic of the traffic flow change point may include at least one of: change point type, number of entering roads, number of exiting roads, road azimuth, number of lanes, and road morphology.

According to an embodiment of the present disclosure, the change point types may include a diversion port, a confluence port, an intersection, a roundabout, and the like.

According to an embodiment of the present disclosure, the number of entering roads may be the number of entrances to different traffic flow change points. For example, the number of entry ways of the diversion port is 1, the number of entry ways of the merging port is 2, and the like.

According to an embodiment of the present disclosure, the number of exit roads may be the number of exits of different traffic flow change points. For example, the number of exit roads at the diversion port is 2, and the number of exit roads at the merging port is 1.

According to an embodiment of the present disclosure, the road azimuth may be one of methods of measuring an angle difference between objects on a plane. The road azimuth is a horizontal included angle from a north-seeking direction line of a certain point to a target direction line along a clockwise direction.

According to embodiments of the present disclosure, a certain number of lanes may be maintained over the full length of an expressway or over a longer stretch between important nodes. The balance of the number of lanes must be kept at the branch and confluence of the main line and the ramp or the ramp and the ramp group.

According to the embodiments of the present disclosure, roads are greatly different depending on the types of vehicles passing through, the purposes of use, and the like, and the road shape can be determined by observing the types, the number, the proportions, and the areas where the roads pass through. For example, some traffic flow interchange areas usually have some unique features, such as turning around, main and auxiliary road entrances and exits, and turning left and right to dedicated lanes.

According to the embodiment of the disclosure, after the traffic flow change point and the corresponding characteristic information are found from the first road network data of the first map and the second road network data of the second map, the subsequent matching link can be performed.

Fig. 5 schematically illustrates a flow chart of a method of determining a preset offset range according to an embodiment of the present disclosure.

As shown in fig. 5, the method of determining the preset offset range includes operations S510 to S520.

In operation S510, the drawing accuracy of the second map is determined.

According to the embodiment of the disclosure, the drawing precision can represent the precision of the map, namely the error size of the map, the drawing precision is one of important marks for measuring the quality of the map, and the drawing precision is related to map projection, a scale, a manufacturing method and a process.

According to the embodiment of the present disclosure, the drawing accuracy of the first map is different from the drawing accuracy of the second map.

In operation S520, a preset offset range is determined according to the drawing accuracy of the second map.

According to the embodiment of the disclosure, because the drawing precision of the first map is different from that of the second map, when the drawing precision of the second map is poor, a large deviation may exist between the first map and the second map, and a preset deviation range can be set according to the drawing precision of the second map, so that the technical effects of reducing mismatching between the first map and the second map and optimizing a matching result are achieved.

Fig. 6 schematically shows a flow chart of a method of setting a preset offset range according to an embodiment of the present disclosure.

As shown in fig. 6, the method of setting the preset offset range includes operations S610 to S620.

In operation S610, the type of each traffic flow change point in the second network data is determined.

According to an embodiment of the present disclosure, the types of traffic flow change points may include, for example, but are not limited to: a flow dividing port, a flow combining port, a road junction, a roundabout and the like.

In operation S620, preset offset ranges are respectively set for different types of traffic flow change points according to the drawing accuracy of the second map and the types of the respective traffic flow change points.

According to the embodiment of the present disclosure, when the drawing accuracy of the second map is poor, there may be a large deviation from the first map. At this time, according to the accuracy of the second map, a preset offset range may be set for different types of traffic flow change points, for example, the preset offset ranges of the diversion port and the merging port may be set to 200 meters, and the preset offset ranges of the intersection and the roundabout may be set to 40 meters. After the preset offset range is set, the traffic flow change point in the first map may be used as a center, the preset offset range may be used as a search radius, the traffic flow change point may be searched on the second map, and the traffic flow change point in one or more second maps may be searched within the search radius.

According to the embodiment of the disclosure, a preset offset range can be set for different types of traffic flow change points respectively according to the drawing precision of the second map and the types of the traffic flow change points, and position matching can be performed on the different types of traffic flow change points respectively, so that the technical effects of reducing mismatching and optimizing the matching result are achieved.

Fig. 7 schematically illustrates a schematic diagram of traffic flow change point matching according to an embodiment of the present disclosure.

As shown in fig. 7, it can be shown that the diversion ports formed by the road segments GA, GB, and GC in the first map are successfully matched with the diversion ports formed by the road segments L4, L7, L3, L3, L6, L2, L2, L5, and L1 in the second map, that is, the diversion ports in 1 first map are successfully matched with the diversion ports in 3 second maps, and at this time, 3 matching success items are formed.

According to the embodiment of the disclosure, a preset offset range can be used as a search radius, and a matching pair between a traffic flow change point in a first map and a traffic flow change point in a second map is found according to spatial position analysis; and then screening according to the characteristics of the traffic flow change points, such as the type of the change points, the number of entering roads, the number of exiting roads, road azimuth angles, the number of lanes, road forms and the like.

According to the embodiment of the disclosure, the traffic flow change point characteristics of the second map and the first map are different and used as matching failure items, and after the matching failure items are filtered, one-to-one or one-to-many or many-to-many matching success items may exist. One-to-many and many-to-many matching success items which cannot be precisely matched temporarily can be stored in a candidate matching set and are called candidate matching items; and the one-to-one matching success item can be subjected to the next operation.

Fig. 8 schematically illustrates a flowchart of a method of determining a second traffic flow change point according to an embodiment of the present disclosure.

As shown in fig. 8, the method of determining the second traffic flow change point includes operations S810 to S840.

In operation S810, at least one candidate traffic flow change point is screened to obtain a plurality of candidate second traffic flow change points matched with the first traffic flow change point.

According to the embodiment of the disclosure, the characteristics of the candidate traffic flow change point may be determined, and the characteristics may include, but are not limited to: and (4) screening the types of the change points, the number of entering roads, the number of exiting roads, road azimuth angles, the number of lanes, road forms and the like.

According to an embodiment of the disclosure, the candidate second traffic flow change point may represent a change point obtained by further performing feature matching for a candidate traffic flow change point for which the position matching is successful.

In operation S820, matched roads in the first map and the second map are determined.

According to an embodiment of the present disclosure, the matched road may represent a corresponding road in which both the location matching and the feature matching are successful in the first map and the second map.

In operation S830, road propagation matching is performed along the matched road in the second map, taking the matched road as a starting point, and a propagation matching result is obtained.

According to the embodiment of the disclosure, the one-to-one matching success item may be regarded as a correct matching, and after roads connected with the traffic flow change point are matched one by one, the matched roads may be taken as starting points, and road spreading matching is performed along the matched roads in the first map and the second map respectively.

According to the embodiment of the disclosure, the road spreading matching can be carried out in real time by utilizing the road network database and adopting a proper algorithm according to the initial positioning result, and the moving target positioning point is directly projected onto the actual road. By the method, on one hand, a means for avoiding the display confusion of the moving target is provided, so that the moving target is prevented from deviating from the road during the display due to the positioning error; on the other hand, through projection, the mobile target positioning data only remain the radial component of the initial positioning error in the advancing route of the mobile target, thereby achieving the purpose of improving the positioning accuracy.

In operation S840, a second traffic flow change point is determined from the plurality of candidate second traffic flow change points according to the epidemic matching result.

According to an embodiment of the present disclosure, the second traffic flow change point may represent a true matching success item selected from the candidate second traffic flow change points according to the propagated matching result.

According to the embodiment of the disclosure, by referring to the spreading matching result, a true matching success item is selected from the candidate second traffic flow change points, and the combination of position matching, feature matching and spreading matching can be realized, so that the association matching of the whole road network between the first map and the second map is completed.

Fig. 9 schematically shows a flow chart of a method of obtaining an epidemic matching result, according to an embodiment of the present disclosure.

As shown in fig. 9, the method of obtaining an epidemic matching result includes operations S910 to S920.

In operation S910, a road propagation matching is performed according to a propagation length, starting from the matched road, along the matched road in the second map.

According to the embodiment of the disclosure, road spread matching can be performed according to the spread length, for example, the length of the road segment a in the second map is equal to the sum of the lengths of the road segments X1+ X2 in the first map, and then the road segment a can be considered to be successfully matched with the road segment X1+ X2 at the same time.

In operation S920, in the road spreading matching process, if the road is spread to a new traffic flow change point, the spreading is stopped, and the current spreading matching result is output.

According to the embodiment of the present disclosure, in the road creep matching process, for example, when the road segment a in the second map creeps to the confluence formed with the road segment B, C, the creep matching may be stopped; when the section X in the first map spreads to the confluence formed with the section Y, Z, the spread matching may be stopped. At this time, the current epidemic matching result may be output, that is, the road segment a is successfully matched with the road segment X.

According to the embodiment of the disclosure, road spreading matching is carried out through the spreading length, when the road spreading is carried out to a new traffic flow change point, spreading is stopped, and the current spreading matching result is output, so that support is provided for selecting a true matching success item from candidate second traffic flow change points, and combination of position matching, feature matching and spreading matching can be realized.

Figure 10 schematically shows a schematic diagram of epidemic matching, according to an embodiment of the disclosure.

As shown in fig. 10, the road segments GA, GB, and GC in the first map form a diversion port, the road segments L1, L2, and L3 in the second map also form a diversion port, and the road segments GA, GB, and GC are one-to-one matched with the road segments L1, L2, and L3, so that the road segments GA and L1 are successfully matched, the road segments GB and L2 are successfully matched, and the road segments GC and L3 are successfully matched. And (4) taking the matched road as a starting point, and carrying out road spreading matching according to the spreading length.

For example, a topological propagation may be performed with the link L3 in the second map as a starting point and the link GC in the first map as a starting point, and the starting point L3(GC) may be noted. When road spread matching is performed, segment-by-segment matching can be performed in the second map and the first map according to the spread length, for example, if the length of the link L3 is the sum of the lengths of the links GC + GD + GE, it can be considered that the link L3 is successfully matched with the links GC, GD, GE at the same time.

As shown in fig. 10, in the road spread matching process, if the next traffic flow change point is encountered, the spread matching is stopped. For example, when the link L4 in the second map spreads to the junction formed with the links L5, L9, the spread matching may be stopped; when the road section GF in the first map has propagated to the junction with the road sections GI, GH, the propagation matching may be stopped. At this time, it can also be considered that the link L4 is successfully matched with the link GF.

As shown in fig. 10, when a one-to-many match occurs, for example, matching of the merging point of the links GI, GH, and GF in the first map obtained by feature matching with the merging point of the links L4, L9, and L5 in the second map and the merging point of the links L6, L7, and L8 is successful, and the links GI, GH, and GF and the links L4, L9, and L5, and the links GI, GH, and GF and the links L6, L7, and L8 may be used as candidate matching items. At this time, the link L4 and the link GF can be obtained by epidemic matching, and it can be considered that the link GI, GH, GF and the link L5, L9, L4 in the candidate matching item are successfully matched, and the link L5 and the link GI, the link L9 and the link GH, and the link L4 and the link GF are matched can be obtained. And then, taking the newly obtained matching success items as starting points L5(GI), L9(GH) and L4(GF) to continue road spreading matching.

Fig. 11 schematically shows a flow chart of a map network matching method according to an embodiment of the present disclosure.

As shown in fig. 11, a key facility is obtained by first performing location matching using first road network data of a first map and second road network data of a second map, where the first road network data of the first map may include, but is not limited to: LD map data, HD map data, and the like; the second network data of the second map may include, for example, but is not limited to: SD map data and the like; the critical facility may be, for example, a point of change in traffic flow, such as a diversion, a junction, an intersection, a roundabout, and the like.

Then extracting the characteristics of the traffic flow change points, setting a certain preset offset range according to the precision of the second map, and performing matching screening on the characteristics of the traffic flow change points in the two maps within the preset offset range to obtain one-to-one matching or one-to-many and many-to-many matching, wherein the one-to-one matching can be regarded as a matching success item; and then the spreading matching is carried out by taking the road sections matched into the success items as starting points.

Meanwhile, the spreading matching result can be referred to in the spreading process, and the real matching item can be selected from the candidate matching items; the relevance matching between different map networks can be realized by combining the matching result of the traffic flow change point with the spreading matching result.

Fig. 12 schematically shows a block diagram of a map network matching apparatus according to an embodiment of the present disclosure.

As shown in fig. 12, the map network matching apparatus 1200 includes an obtaining module 1210, a first determining module 1220, a second determining module 1230, and a matching module 1240.

The obtaining module 1210 is configured to obtain first road network data of a first map and second road network data of a second map.

The first determining module 1220 is configured to determine at least one candidate traffic flow change point located within a preset offset range in the second road network data by using the first traffic flow change point in the first road network data as a reference point.

The second determining module 1230 is configured to filter the at least one candidate traffic flow change point according to the feature of the first traffic flow change point and the feature of the at least one candidate traffic flow change point, and determine a second traffic flow change point matched with the first traffic flow change point.

And the matching module 1240 is used for matching the roads in the first map with the roads in the second map according to the first traffic flow change point and the second traffic flow change point.

According to the embodiment of the disclosure, candidate traffic flow change points within a preset offset range are determined by adopting a position based on a first traffic flow change point in road network data; screening the candidate traffic flow change points based on the characteristics of the first traffic flow change point and the candidate traffic flow change points, and determining a second traffic flow change point; performing road matching according to the first traffic flow change point and the second traffic flow change point; by utilizing the technical scheme of combining position matching of traffic flow change points in road network data with feature matching, the problem of mismatching caused by different map road network data is at least partially solved, so that map road network matching can be well completed, and a more ideal matching effect is obtained.

According to an embodiment of the present disclosure, the first network data and the second network data respectively include at least one of the following traffic flow change points:

a flow dividing port, a flow combining port, a road junction and a roundabout.

According to an embodiment of the present disclosure, the above feature includes at least one of:

change point type, number of entering roads, number of exiting roads, road azimuth, number of lanes, and road morphology.

According to the embodiment of the present disclosure, the map network matching device 1400 further includes a third determining module and a fourth determining module.

And the third determining module is used for determining the drawing precision of the second map.

And the fourth determining module is used for determining the preset offset range according to the drawing precision of the second map.

According to an embodiment of the present disclosure, the drawing accuracy of the first map is different from the drawing accuracy of the second map.

According to an embodiment of the present disclosure, the fourth determination module includes a third determination unit and a setting unit.

And the third determining unit is used for determining the type of each traffic flow change point in the second road network data.

And the setting unit is used for respectively setting preset offset ranges for different types of traffic flow change points according to the drawing precision of the second map and the types of the traffic flow change points.

According to an embodiment of the present disclosure, the second determining module 1230 includes a screening unit, a first determining unit, a matching unit, and a second determining unit.

And the screening unit is used for screening at least one candidate traffic flow change point to obtain a plurality of candidate second traffic flow change points matched with the first traffic flow change point.

A first determination unit for determining matched roads in the first map and the second map.

And the matching unit is used for performing road spreading matching along the matched road in the second map by taking the matched road as a starting point to obtain a spreading matching result.

And the second determining unit is used for determining a second traffic flow change point from the plurality of candidate second traffic flow change points according to the spreading matching result.

According to an embodiment of the present disclosure, a matching unit includes an epidemic matching subunit and an output subunit.

And the spreading matching subunit is used for performing road spreading matching according to the spreading length by taking the matched road as a starting point along the matched road in the second map.

And the output subunit is used for stopping spreading and outputting the current spreading matching result if the road is spread to a new traffic flow change point in the road spreading matching process.

Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.

For example, any number of the obtaining module 1210, the first determining module 1220, the second determining module 1230, and the matching module 1240 may be combined and implemented in one module/unit/sub-unit, or any one of the modules/units/sub-units may be split into multiple modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the obtaining module 1210, the first determining module 1220, the second determining module 1230 and the matching module 1240 may be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or may be implemented in any one of three implementations of software, hardware and firmware, or in a suitable combination of any of them. Alternatively, at least one of the obtaining module 1210, the first determining module 1220, the second determining module 1230 and the matching module 1240 may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.

It should be noted that the map network matching device part in the embodiment of the present disclosure corresponds to the map network matching method part in the embodiment of the present disclosure, and the description of the map network matching device part specifically refers to the map network matching method part, which is not described herein again.

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.

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; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method. According to an embodiment of the present disclosure, an electronic apparatus may be applied to a vehicle.

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

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 described above.

Fig. 13 schematically shows a block diagram of an electronic device for implementing the map network matching method according to the embodiment 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. 13, the apparatus 1300 includes a computing unit 1301 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)1302 or a computer program loaded from a storage unit 1308 into a Random Access Memory (RAM) 1303. In the RAM 1303, various programs and data necessary for the operation of the device 1300 can also be stored. The calculation unit 1301, the ROM 1302, and the RAM 1303 are connected to each other via a bus 1304. An input/output (I/O) interface 1305 is also connected to bus 1304.

A number of components in the device 1300 connect to the I/O interface 1305, including: an input unit 1306 such as a keyboard, a mouse, or the like; an output unit 1307 such as various types of displays, speakers, and the like; a storage unit 1308 such as a magnetic disk, optical disk, or the like; and a communication unit 1309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 1309 allows the device 1300 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.

Computing unit 1301 may be a variety of general and/or special purpose processing components that include processing and computing capabilities. Some examples of computing unit 1301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized 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 1301 performs the respective methods and processes described above, such as the map network matching method. For example, in some embodiments, the map network matching method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 1308. In some embodiments, some or all of the computer program may be loaded onto and/or installed onto device 1300 via ROM 1302 and/or communications unit 1309. When the computer program is loaded into the RAM 1303 and executed by the computing unit 1301, one or more steps of the map network matching method described above may be performed. Alternatively, in other embodiments, the computing unit 1301 may be configured in any other suitable way (e.g. by means of firmware) to perform the map network matching method.

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), load 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 code 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 code, when executed by the processor or controller, causes the functions/acts 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, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

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 network matching method comprises the following steps:

2. The method of claim 1, wherein the screening at least one of the candidate traffic flow change points, and determining a second traffic flow change point that matches the first traffic flow change point comprises:

screening at least one candidate traffic flow change point to obtain a plurality of candidate second traffic flow change points matched with the first traffic flow change point;

determining matched roads in the first map and the second map;

performing road spreading matching along the matched road in the second map by taking the matched road as a starting point to obtain a spreading matching result;

and determining the second traffic flow change point from the candidate second traffic flow change points according to the spreading matching result.

3. The method of claim 2, wherein along the matched road in the second map, performing road propagation matching with the matched road as a starting point, and obtaining a propagation matching result comprises:

carrying out road spreading matching according to a spreading length by taking the matched road as a starting point along the matched road in the second map;

in the road spreading matching process, if the road spreads to a new traffic flow change point, the spreading is stopped, and the current spreading matching result is output.

4. The method of claim 1, further comprising:

determining the drawing precision of the second map;

and determining the preset offset range according to the drawing precision of the second map.

5. The method of claim 4, wherein determining the preset offset range according to the rendering accuracy of the second map comprises:

determining the type of each traffic flow change point in the second road network data;

and respectively setting the preset offset range for the different types of the traffic flow change points according to the drawing precision of the second map and the type of each traffic flow change point.

6. The method of claim 1, wherein a rendering accuracy of the first map is different from a rendering accuracy of the second map.

7. The method according to claim 1, wherein at least one of the following traffic flow change points is included in the first and second road network data, respectively:

a flow dividing port, a flow combining port, a road junction and a roundabout.

8. The method of claim 1, wherein the features comprise at least one of:

9. A map network matching apparatus comprising:

the first determining module is used for determining at least one candidate traffic flow change point which is located in a preset offset range in the second road network data by taking a first traffic flow change point in the first road network data as a reference point;

the second determination module is used for screening at least one candidate traffic flow change point according to the characteristics of the first traffic flow change point and the characteristics of at least one candidate traffic flow change point and determining a second traffic flow change point matched with the first traffic flow change point;

10. The apparatus of claim 9, wherein the second determining means comprises:

the screening unit is used for screening at least one candidate traffic flow change point to obtain a plurality of candidate second traffic flow change points matched with the first traffic flow change point;

a first determination unit configured to determine a matched road in the first map and the second map;

the matching unit is used for performing road spreading matching along the matched road in the second map by taking the matched road as a starting point to obtain a spreading matching result;

and the second determining unit is used for determining the second traffic flow change point from a plurality of candidate second traffic flow change points according to the spreading matching result.

11. The apparatus of claim 10, wherein the matching unit comprises:

the matching subunit is used for performing road spreading matching according to a spreading length by taking the matched road as a starting point along the matched road in the second map;

12. The apparatus of claim 9, further comprising:

a third determination module, configured to determine a drawing accuracy of the second map;

13. The apparatus of claim 12, the fourth determination module comprising:

the third determining unit is used for determining the type of each traffic flow change point in the second road network data;

14. The apparatus of claim 9, wherein a rendering accuracy of the first map is different from a rendering accuracy of the second map.

15. The apparatus according to claim 9, wherein at least one of the following traffic flow change points is included in the first and second road network data, respectively:

a flow dividing port, a flow combining port, a road junction and a roundabout.

16. The apparatus of claim 9, wherein the characteristic comprises at least one of:

17. An electronic device, comprising:

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 enable the at least one processor to perform the method of any one of claims 1-8.

18. 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 1-8.

19. A computer program product comprising a computer program/instructions which, when executed by a processor, implement the method according to any one of claims 1-8.