CN110795822A - Traffic network semantic modeling method and device, electronic equipment and storage medium - Google Patents
Traffic network semantic modeling method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of computer simulation modeling, in particular to a semantic modeling method, a semantic modeling device, electronic equipment and a storage medium for a traffic network, wherein the method comprises the steps of cutting off the central axes of roads intersected at a crossing according to the vector data of the central axes of the roads, and reserving the non-intersected central axes of the roads after cutting off; respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane; the traditional Lane at the same side of the intersection form a set link; traversing the traditional Lane vector data, and generating the current interaction according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road; automatically generating Intersection Lane according to the relationship between the current interaction and the traditional Lane; traversing the current interaction, and generating a connector between the traditional Lane belonging set Link intersected with the same current interaction; and aggregating Link and interaction generated by a central axis of a Road to generate Road. By building a topological data relation in the road network, input data of road network modeling is reduced to a road central axis, so that early data collection work is reduced, and dynamic editing is supported.
Description
Technical Field
The invention relates to the technical field of computer simulation modeling, in particular to a semantic modeling method and device for a traffic network, electronic equipment and a storage medium.
Background
Since 1908 automobiles were mass produced, the traffic congestion problems associated therewith began to become increasingly prominent worldwide. Many cities relieve traffic pressure by measures such as road extension, tidal lane setting, open and closed cells, etc. However, these measures are taken blindly, not only to fundamentally solve traffic congestion, but instead may exacerbate the congestion and cause irreparable damage to the environment.
The method for building the road network semantic modeling supporting dynamic editing is used for carrying out traffic simulation and deduction based on the road network, can dynamically edit road network traffic attributes (newly added roads, road widening/narrowing, tide lane setting, road connectivity setting and the like) while visually displaying a simulation process, and carries out simulation deduction on the edited traffic, so that traffic design and planning are effectively guided, and the method has important practical significance.
At present, there are many methods available for road network modeling. From different purposes, the existing methods can be divided into two types: the method is used for constructing the scene, does not pay attention to organization and generation of various topological relations in the road network, and generally cannot be directly applied to traffic simulation. The other type is a road network modeling method for traffic simulation, which generates fine-grained road data from coarse-grained road network data and then further generates topological relation data between lanes. However, the existing road network modeling method for traffic simulation has the following problems: (1) it is necessary to provide intersection shape data or intersection topological relation data, which is difficult to directly obtain from existing open source road network data (data is difficult to obtain). (2) The road network structure is generally modeled by using a fully connected graph, so that changes of local adjacency/connection relations in the road network (such as new roads, road widening/narrowing, tide lane arrangement, road connectivity arrangement and the like) can cause changes of the topology structure of the whole road network.
Disclosure of Invention
In order to solve the technical problems, the invention provides a traffic network semantic modeling method, a traffic network semantic modeling device, electronic equipment and a storage medium, and the adopted technical scheme is as follows:
in a first aspect, an embodiment of the present invention provides a semantic modeling method for a traffic network, where the semantic modeling method includes the following steps:
according to the vector data of the central axis of the road, cutting off the central axis of the road which is intersected at the intersection, and reserving the non-intersected central axis of the road after cutting off; respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane;
forming a set link by the traditional Lane extended from the same side of the intersection;
traversing the traditional Lane vector data, and generating a current interaction according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road;
automatically generating Intersection Lane according to the relationship between the current interaction and the traditional Lane;
traversing the current interaction, and generating a connector between the traditional Lane belonging set Link intersected with the same current interaction;
and aggregating Link and interaction generated by a central axis of a Road to generate Road.
Further, the method for intercepting the central axis of the road intersected at the intersection comprises the following steps:
taking the intersection point of the road central axes intersected in the space as the center, taking r as the radius, and cutting the intersected road central axes, wherein the r is max { the road width related to each intersected road central axis }.
Further, the relationship between the conventional Lane vector data and the interaction is as follows:
if the distance between the terminal point of the current traditional Lane and the Intersection point of the road central axis for generating the interaction is smaller than the distance between the starting point of the current traditional Lane and the Intersection point, the traditional Lane and the interaction are in positive relation; otherwise it is a negative relationship.
Further, the method for automatically generating the Intersection Lane according to the relationship between the current interaction and the traditional Lane comprises the following steps:
sequencing the set Link to which the traditional Lane intersected with the current interaction belongs clockwise, and sequencing the traditional Lane in the same set Link counterclockwise;
and generating all the intersections Lane in the current interaction by adopting the sorted set Link in a curve fitting mode.
In a second aspect, another embodiment of the present invention provides a semantic modeling apparatus for traffic network, including:
the acquisition traditional lane module is used for cutting off the road central axis intersected at the intersection according to the road central axis vector data and reserving the non-intersected road central axis after cutting off; respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane;
the acquisition aggregation Link module is used for forming the traditional Lane extended at the same side of the intersection into an aggregation Link;
the intersectional module is used for traversing the traditional Lane vector data and generating a current intersectional according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road;
the Intersection Lane obtaining module is used for automatically generating an Intersection Lane according to the relationship between the current interaction and the traditional Lane; and
a connector obtaining module, configured to traverse the current interaction and generate a connector between the set links to which the traditional Lane belongs and which intersect with the same current interaction;
and the Road generating module is used for aggregating Link and interaction generated by a central axis of a Road to generate Road.
Further, the acquiring the conventional lane module further includes:
and the truncation module is used for truncating the intersected road central axis by taking the intersection point of the road central axis as the center and r as the radius, wherein r is max { the road width related to each intersected road central axis }.
Further, the obtaining interaction module further comprises:
the relationship acquisition module is used for determining that the distance between the terminal point of the current traditional Lane and the Intersection point of the road central axis generating the interaction is smaller than the distance between the starting point of the current traditional Lane and the Intersection point, and the traditional Lane and the interaction are in positive relationship; otherwise it is a negative relationship.
Further, the module for obtaining the intersection lane further comprises:
the sorting module is used for sorting the set Link to which the traditional Lane intersected with the current interaction belongs clockwise, and sorting the traditional Lane in the same set Link anticlockwise; and
and the fitting module is used for generating all the intersections Lane in the current interaction by adopting a curve fitting mode for the sorted set Link.
In a third aspect, another embodiment of the present invention provides an electronic device, including a memory and a processor, wherein:
the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement any one of the road network semantic modeling methods described above.
In a third aspect, another embodiment of the present invention provides a storage medium, where the storage medium stores a computer-readable program, and when the program is executed, the method for modeling road network semantics according to any one of the above-mentioned items is implemented.
The invention has the following beneficial effects:
the implementation of the invention provides a semantic modeling method for a traffic network, which is characterized in that according to the vector data of the central axis of a road, the central axis of the road at a non-intersection is extended towards the direction of an internal normal and an external normal to obtain the traditional Lane vector data; summarizing the traditional Lane extended at the same side of the intersection to form a set link; generating a current intersectional according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road; automatically generating Intersection Lane according to the relationship between the current interaction and the traditional Lane; and generating a connector between the set links to which the traditional Lane intersected with the same current interaction belongs, thereby generating a road network. According to the embodiment of the invention, the input data is reduced to the road central axis by building the topological data relation in the road network, and the complete road network modeling can be completed according to the road central axis vector data, so that the road central axis vector data is easy to obtain, the data collection work in the early stage is reduced, and the labor cost is saved. The tight coupling relationship between the two is reduced, the lane direction and the road width in the road network are dynamically edited and modified, and the communication relationship at the intersection can be automatically updated and generated after a road is newly built. The semantic modeling of the road network supports dynamic editing, can be modified, and provides very convenient bottom data support for traffic research and judgment.
Drawings
Fig. 1 is a schematic diagram of a road network semantic structure provided in an embodiment of the present invention;
FIG. 2 is a flow chart of a traffic network semantic modeling method according to an embodiment of the present invention;
FIG. 3 is a schematic structural view of a central axis of a road according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a cut-off central axis of an unwanted road according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a conventional Lane according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an embodiment of generating an interaction;
fig. 7 is a schematic structural diagram of an intersection Lane generation according to an embodiment of the present invention;
fig. 8 is a schematic diagram of generating an intersection Lane using a conventional Lane as a starting point in Link according to an embodiment of the present invention;
FIG. 9 is a diagram illustrating a conventional Lane clockwise ordering of interaction intersections according to an embodiment of the present invention;
fig. 10 is a structural block diagram of a traffic network semantic modeling apparatus according to an embodiment of the present invention;
fig. 11 is a block diagram of an electronic device according to another embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description will be given to a semantic modeling method and device for traffic network according to the present invention, and the detailed implementation, structure, features and effects thereof with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "an embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein the term "and/or" includes any and all combinations of one or more of the associated listed items.
The following describes a detailed scheme of a traffic network semantic modeling method and a device thereof with reference to specific embodiments.
Referring to fig. 1, the present invention redefines a topological semantic structure, where the elements involved in the semantic structure include: lane, Link, interaction, Connection, and Road. Lane is used to describe the running track of the vehicle. The elements in the topology data relationship within the network include: link, Connection, interaction, and Road. The input data required by the embodiment of the invention is road central axis data in an open source map data platform OpenStreetMap. Based on the road central axis data, the embodiment of the invention can automatically generate the topological data relationship in the road network. The following details are provided for the specific definition of the relevant elements:
1. about Lane
Lane includes both traditional Lane and crossing Lane.
Specifically, conventional Lane is used to describe the trajectory of a vehicle at a non-intersection. The traditional Lane is represented by the central axis of the Lane, and the central axis of the Lane is parallel to the central axis of the road, namely the traditional Lane can be represented by the central axis of the Lane of a normal road section except the intersection. The traditional Lane contains its own vector data information (central axis curve of road) and simple topological data information, such as left and right neighbor relation, front and back connection relation, etc.
The intersection Lane is used for describing the driving track of vehicles at each intersection in the road network. For any intersection Lane, the following conditions are met:
1) taking the terminal point of the traditional Lane ending at the current intersection as a starting point, and tangent with the traditional Lane at the point;
2) taking the starting point of the traditional Lane starting at the current intersection as an end point, and tangent with the traditional Lane at the end point;
3) smoothing the second order of each point on the Lane curve of the intersection;
4) at most one intersection Lane can be generated between the terminal point of any one traditional Lane and the starting point of another traditional Lane in the same intersection;
5) the traffic flow flowing out from the same Link in the same intersection is forbidden to cross again in the intersection;
6) any two intersections Lane with the same trend have no cross inside the curves except the starting point and the end point. The same trend means that tangent vectors of two intersections Lane at the starting point and the ending point are approximately equal.
2. Link related
Link is the set of all traditional Lane's obtained by extending the central axis of a road at a non-intersection to a single side. Any two Lanes in the same Link have a direct or indirect neighbor relation. The indirect neighbor relation means that one party can find the other party by finding the neighbor of the neighbor and continuing.
3. With respect to interaction
The Intersection represents an Intersection in the road network, including all intersections Lane generated at the Intersection, and the relationship between the traditional Lane connected with the intersections Lane and the Intersection.
The embodiment of the invention adopts the thought of a symbol network to define the relationship between the interaction and the traditional Lane connected with the interaction. The relationship between interaction and traditional Lane includes positive and negative relationships. Wherein, the positive relationship means that the end point of the traditional Lane is the starting point of a certain Lane port in the interaction and is represented by "+"; the negative relation means that the starting point of the traditional Lane is the end point of a certain Intersection Lane in the interaction and is indicated by "-".
4. About Connector
The connectors give the connection relationships between links, and one Connector defines the following set of relationships:
connector { < Link1, Link2>, Link2 is connected to Link1}
Wherein Link1 and Link2 represent two separate links. Link2 is connected to Link1, meaning that Link1 is connected to Link2 if there is one Lane in Link1 that is the same Lane as the Lane that is the next to one Lane in Link2, and that Lane is the intersection Lane.
5、Road
Road is a collection of links and interactions. A Road central axis corresponds to a Road, and Link and interaction generated based on the Road central axis belong to the current Road.
Referring to fig. 2, a flow chart of a semantic modeling method for a traffic network according to the present invention is shown, and the method includes the following steps:
step S001, cutting off the road central axis intersected at the intersection according to the road central axis vector data, and reserving the non-intersected road central axis after cutting off; and respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane.
The conventional Lane contains vector data and topology data.
The generation mode of the traditional Lane vector data comprises the following steps: referring to fig. 3, in the embodiment of the present invention, taking fig. 3 as an example, the input data is road central axis vector data, and the road central axis vector data does not distinguish between a normal road segment and an intersection, and intersection information needs to be filtered out in order to obtain a traditional Lane. Firstly, taking the intersection point of the central axes of the roads intersected in the space as the center and taking r as the radius, and cutting off the central axes of the roads intersected in the space, wherein:
max (central axis of intersecting road relates to road section width) }
Referring to fig. 4, after the above-mentioned cutting operation is performed, the central axes of the roads at the intersection are discarded, and the central axes of the roads at the intersection are retained. In order to facilitate the calculation of the relationship between the interaction and the traditional Lane in the subsequent steps, the non-intersecting road central axis is referred to as a set S.
The method for generating the road network Lane line oriented to traffic simulation proposed by Mao et al (please refer to Mao, T., H.Wang, Z.Deng, Z.Wang.an effective Lane model for complex traffic simulation [ J ]. Computer simulation and Virtual industries, 2015.26(3-4): 397-one 403.) is adopted to extend the two sides of the cut-off disjoint road central axis line to generate the traditional Lane vector data on the two sides of the road central axis line.
Referring to fig. 5, the conventional Lane topology data generation method includes the following steps: when the central axis of the road extends towards the direction of the inner normal and the outer normal, two traditional lanes generated by two adjacent extensions are mutually adjacent to each other. The vector directions of two traditional Lanes which are in a neighbor relation with each other are consistent. The continuation step length is determined by the lane width, and if no lane width information exists in the central axis of the current lane, the default is 3.8 meters. The number of conventional Lane generated by the unilateral continuation is determined by the link width.
And step S002, forming a set link by the traditional Lane extended at the same side of the intersection in the step S001.
The set of all traditional Lane generated by the extension of the axis to one side in a single road forms a Link. One road central axis may generate two links.
And S003, traversing the traditional Lane vector data obtained in the step S001, and generating the current interaction according to the relationship between the traditional Lane vector data and the intersection of the road central axis.
Referring to FIG. 6, the interaction includes the relationship of intersecting traditional Lane and Intersection Lane. In order to obtain the relationship between an interaction and the traditional Lane intersected with the interaction, the traditional Lane intersected with the current interaction needs to be calculated and obtained first. And traversing all road central axes in the set S in the step S001, wherein the traditional Lane obtained based on the road central axis continuation in the set S is intersected with the current interaction. And then obtaining the relationship between the traditional Lane vector data and the interaction according to the traditional Lane vector data: recording an Intersection point of the central axis of the road before truncation as P, and if the distance between the end point of the current traditional Lane and the P is smaller than the distance between the start point of the current traditional Lane and the P, taking the relation between the traditional Lane and the current interaction as an active relation and using a plus sign to represent the positive relation; otherwise, the relationship is negative and is indicated by "-".
And step S004, automatically generating an Intersection Lane according to the relationship between the current interaction and the traditional Lane in the step S003.
And automatically generating vector data of the Intersection Lane according to the relationship between the current interaction and the traditional Lane. According to the definition of the intersection Lane and the combination of the reality, the intersection Lane accords with the following rules:
1) the Intersection Lane always takes the end point of the traditional Lane with the Intersection relationship of "+" as the starting point, and takes the starting point of the traditional Lane with the Intersection relationship of "-" as the end point;
2) respectively enabling the traditional Lane intersected with the current interaction to belong to M links, wherein M is an even number, and the traditional Lane and the interaction in any Link are all plus or minus;
3) in the M links, the traditional Lane and interaction relationship in M/2 links is "+", and the traditional Lane and interaction relationship in M/2 links is "-";
4) the traditional Lane in two adjacent links has opposite relation with the current interaction.
5) The traditional Lane with the Intersection relationship of "+" and the traditional Lane with the next relationship of "-" in the clockwise direction are two Lanes generated by continuation of the central axis of the same road, namely the two traditional Lanes are two lanes in opposite directions on the same road;
6) if the relationship between the traditional Lane in a Link and the current Intersection is "+", the Intersection Lane generated by using the traditional Lane in the Link as a starting point satisfies the following conditions: (a) the traditional Lanes in the Link take the anticlockwise direction as a sequence, the first traditional Lane and the next traditional Lane in the clockwise direction can generate a crossing Lane, and the crossing Lane corresponds to an actual turning track of the vehicle; (b) and the traditional Lanes in the links are sequentially connected with the traditional Lanes in the M/2 links with the Intersection relation of "-" in a clockwise way to generate the Intersection Lane, and the Intersection Lane corresponds to the actual Intersection track of the vehicle.
Referring to fig. 8 and fig. 9, according to the above rule, in order to generate a reasonable Intersection Lane, Link to which the traditional Lane intersected by the current Intersection belongs is first sorted clockwise, and the traditional lanes in the same Link are sorted counterclockwise. Then, based on the above sorted Link, generating all intersections Lane in the current interaction by adopting Bezier curve fitting, and finally generating intersections Lane, please refer to fig. 6.
Step S005, traversing the current interaction, and generating a connector between the traditional Lane belonging set Link intersected with the same current interaction.
The Connector represents a connection relationship between a certain set Link and another set Link. In the embodiment of the invention, two links are connected through an intersection Lane. In the embodiment of the invention, the traditional Lane belonging sets Link intersected with the same interaction have a connection relationship. Therefore, the Connector can be generated by traversing the interaction in the embodiment of the present invention.
Step S006, aggregating Link and interaction generated by a Road central axis to generate Road.
The Road is directly generated based on the central axis of the Road, one central axis of the Road corresponds to one Road, and both Link and interaction generated based on the central axis of the Road belong to the current Road.
In summary, the embodiment of the present invention provides a semantic modeling method for a traffic network, where intersection information is filtered according to road axis vector data, and then non-intersecting road axes are respectively extended to two sides to obtain traditional Lane vector data; summarizing traditional Lane extended at the same side of the intersection to form a set link; generating a current interaction according to the relationship between the traditional Lane vector data and the intersection point of the central axis of the road; automatically generating Intersection Lane according to the relationship between the current interaction and the traditional Lane; and generating a connector between the traditional Lane belonging set Link intersected with the same current interaction, thereby generating a road network. According to the embodiment of the invention, the input data is reduced to the road central axis by building the topological data relation in the road network, and the complete road network modeling can be completed according to the road central axis vector data, so that the road central axis vector data is easy to obtain, the data collection work in the early stage is reduced, and the labor cost is saved.
Referring to fig. 10, a structural block diagram of a traffic network semantic modeling apparatus according to an embodiment of the present invention is shown, where the semantic modeling apparatus includes a traditional Lane obtaining module 101, a set Link obtaining module 102, an intersection obtaining module 103, an intersection obtaining module 104, a connector obtaining module 105, and a Road generating module 106, where the traditional Lane obtaining module 101 is specifically configured to cut off a Road central axis intersecting at an intersection according to Road central axis vector data, and retain a non-intersecting Road central axis after the cutting off; and respectively extending the non-intersected central axis of the road to two sides to generate corresponding traditional Lane. The get set Link module 102 is configured to combine the traditional Lane extended on the same side of the intersection into a set Link. The intersectional obtaining module 103 is configured to traverse the traditional Lane vector data, and generate a current intersectional according to a relationship between the traditional Lane vector data and an intersection of the road central axis. The Intersection Lane obtaining module 104 is configured to automatically generate an Intersection Lane according to a relationship between the current interaction and the traditional Lane. The get connector module 105 is configured to traverse the current interaction and generate a connector between the sets Link to which the traditional Lane belongs, where the traditional Lane belongs, and the traditional Lane intersects with the current interaction. The Road generating module 106 is configured to aggregate Link and interaction generated by a central axis of a Road, and generate Road.
Preferably, the obtaining of the traditional Lane module 101 further includes a truncation module 1011, specifically, the truncation module 1011 is configured to truncate the central axis of the intersected road by taking an intersection point of the central axes of the roads intersected in the space as a center and taking r as a radius, where: and r is max { the road width related to the central axis of each road intersected }.
Preferably, the obtaining interaction module 103 further includes a relationship obtaining module 1031, and specifically, the relationship obtaining module 1031 is configured to obtain that the distance between the end point and the Intersection point of the current traditional Lane is smaller than the distance between the start point and the Intersection point of the current traditional Lane, so that a positive relationship is obtained between the traditional Lane and the current interaction; otherwise it is a negative relationship.
Preferably, the intersection Lane obtaining module 104 further includes a sorting module 1041 and a fitting module 1042, specifically: the sorting module 1041 is configured to sort, clockwise, a set Link to which a traditional Lane intersected with the current interaction belongs, and sort, counterclockwise, traditional lanes in the same set Link. The fitting module 1042 is configured to generate all intersections Lane in the current Intersection in a curve fitting manner for the sorted set Link.
Referring to fig. 11, it shows that another embodiment of the present invention further provides an electronic device including a memory 110 and a processor 111, based on the same inventive concept, wherein:
the memory 110 is used to store instructions required by the processor 111 to perform tasks.
The processor 111 is configured to execute the instruction stored in the memory 110, intercept the road central axis intersecting at the intersection according to the road central axis vector data, and reserve the road central axis that does not intersect after the interception; respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane; forming a set link by the traditional Lane extended from the same side of the intersection; traversing the traditional Lane vector data, and generating the current interaction according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road; automatically generating Intersection Lane according to the relationship between the current interaction and the traditional Lane; traversing the current interaction, and generating a connector between the traditional Lane belonging set Link intersected with the same current interaction; and aggregating Link and interaction generated by a central axis of a Road to generate Road.
In other embodiments, the electronic device further comprises a communication interface 112 for enabling the subject to communicate with other devices or a communication network.
Preferably, the processor 111 is configured to execute the instructions stored in the memory 110, and when performing modeling, perform a semantic modeling method for a traffic network provided in any of the above embodiments.
The embodiment of the invention also provides a storage medium, wherein the storage medium can store a computer-readable program, and when the program is executed, the semantic modeling method for the traffic network provided by any one of the above embodiments is executed.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A semantic modeling method for a traffic network is characterized by comprising the following steps:
according to the vector data of the central axis of the road, cutting off the central axis of the road which is intersected at the intersection, and reserving the non-intersected central axis of the road after cutting off; respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane;
forming a set link by the traditional Lane extended from the same side of the intersection;
traversing the traditional Lane vector data, and generating a current interaction according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road;
automatically generating Intersection Lane according to the relationship between the current interaction and the traditional Lane;
traversing the current interaction, and generating a connector between the traditional Lane belonging set Link intersected with the same current interaction;
and aggregating Link and interaction generated by a central axis of a Road to generate Road.
2. The semantic modeling method for traffic networks according to claim 1, characterized in that said method for intercepting said central axis of said roads intersecting at an intersection comprises the following steps:
taking the intersection point of the road central axes intersected in the space as the center, taking r as the radius, and cutting the intersected road central axes, wherein the r is max { the road width related to each intersected road central axis }.
3. The traffic network semantic modeling method according to claim 1, characterized in that the relationship between the conventional Lane vector data and the interaction is:
if the distance between the terminal point of the current traditional Lane and the Intersection point of the road central axis for generating the interaction is smaller than the distance between the starting point of the current traditional Lane and the Intersection point, the traditional Lane and the interaction are in positive relation; otherwise it is a negative relationship.
4. The traffic network semantic modeling method according to any one of claims 1 to 3, characterized in that the method for automatically generating an Intersection Lane according to the relationship between the current Intersection and the traditional Lane comprises the following steps:
sequencing the set Link to which the traditional Lane intersected with the current interaction belongs clockwise, and sequencing the traditional Lane in the same set Link counterclockwise;
and generating all the intersections Lane in the current interaction by adopting the sorted set Link in a curve fitting mode.
5. A traffic network semantic modeling apparatus, the semantic modeling apparatus comprising:
the acquisition traditional lane module is used for cutting off the road central axis intersected at the intersection according to the road central axis vector data and reserving the non-intersected road central axis after cutting off; respectively extending the non-intersected road central axis to two sides to generate corresponding traditional Lane;
the acquisition aggregation Link module is used for forming the traditional Lane extended at the same side of the intersection into an aggregation Link;
the intersectional module is used for traversing the traditional Lane vector data and generating a current intersectional according to the relation between the traditional Lane vector data and the intersection point of the central axis of the road;
the Intersection Lane obtaining module is used for automatically generating an Intersection Lane according to the relationship between the current interaction and the traditional Lane; and
a connector obtaining module, configured to traverse the current interaction and generate a connector between the set links to which the traditional Lane belongs and which intersect with the same current interaction;
and the Road generating module is used for aggregating Link and interaction generated by a central axis of a Road to generate Road.
6. The traffic network semantic modeling method according to claim 5, characterized in that said obtaining a traditional lane module further comprises:
and the truncation module is used for truncating the intersected road central axis by taking the intersection point of the road central axis as the center and r as the radius, wherein r is max { the road width related to each intersected road central axis }.
7. The traffic network semantic modeling method according to claim 5, wherein said acquisition interaction module further comprises:
the relationship acquisition module is used for determining that the distance between the terminal point of the current traditional Lane and the Intersection point of the road central axis generating the interaction is smaller than the distance between the starting point of the current traditional Lane and the Intersection point, and the traditional Lane and the interaction are in positive relationship; otherwise it is a negative relationship.
8. The traffic network semantic modeling device according to any one of claims 5 to 7, wherein the intersection lane acquiring module further comprises:
the sorting module is used for sorting the set Link to which the traditional Lane intersected with the current interaction belongs clockwise, and sorting the traditional Lane in the same set Link anticlockwise; and
and the fitting module is used for generating all the intersections Lane in the current interaction by adopting a curve fitting mode for the sorted set Link.
9. An electronic device comprising a memory and a processor, wherein:
the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the road network semantic modeling method according to any one of claims 1 to 4.
10. A storage medium, characterized in that said storage medium stores a computer readable program which when executed implements the road network semantic modeling method according to any one of claims 1 to 4.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111578948A (en) * | 2020-06-12 | 2020-08-25 | 弗徕威智能机器人科技（上海）有限公司 | Lane adding method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104217580A (en) * | 2014-08-14 | 2014-12-17 | 中国科学院计算技术研究所 | Vehicle crowd animation oriented method and vehicle crowd animation oriented system for semantically modeling road networks |
| US20180240026A1 (en) * | 2017-02-22 | 2018-08-23 | Here Global B.V. | Method and apparatus for providing semantic-free traffic prediction |
-
2019
- 2019-09-29 CN CN201910934193.0A patent/CN110795822A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104217580A (en) * | 2014-08-14 | 2014-12-17 | 中国科学院计算技术研究所 | Vehicle crowd animation oriented method and vehicle crowd animation oriented system for semantically modeling road networks |
| US20180240026A1 (en) * | 2017-02-22 | 2018-08-23 | Here Global B.V. | Method and apparatus for providing semantic-free traffic prediction |
Non-Patent Citations (1)
| Title |
|---|
| 黄敏;钮中铭;张小兰;潘嘉杰;张学强;: "基于GIS-T的交通仿真路网构建研究" * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111578948A (en) * | 2020-06-12 | 2020-08-25 | 弗徕威智能机器人科技（上海）有限公司 | Lane adding method and system |
| CN111578948B (en) * | 2020-06-12 | 2022-04-05 | 弗徕威智能机器人科技（上海）有限公司 | Lane adding method and system |
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