Method for automatically generating a topological map for traffic analysis based on a navigation map

Abstract

The application provides a topological map automatic generation method based on a navigation map for traffic research and judgment, extracts road sections, nodes, intersections, turning relationship objects and corresponding attributes required by traffic research and judgment through geographic information data such as navigation sections, nodes and device layers, generates traffic section objects through device object information, logically associates with a road network, thereby forming logical digital expression of road sections, intersections, nodes and device security, and providing a base support for traffic research and judgment algorithms; through the development of coding rules, the fast query between objects is realized, the originally isolated data in the traffic system is connected into a network, and the development time and hardware cost are saved.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and more specifically to a method for automatically generating topological maps for traffic analysis based on navigation maps. Background Technology

[0002] The transportation system is a vast and complex system, encompassing hundreds of facilities and equipment, an intricate road network, and multiple business systems. In the past, these systems operated like silos, with limited hardware and data interoperability, and business systems heavily reliant on manual labor. In recent years, with the continuous development of communication and big data technologies, products such as data platforms and data lakes have emerged, but the data integration and application effects have been less than ideal. With the continuous development of integrated transportation services and the increasing demand for transportation, the requirements for multi-source data fusion analysis and judgment are becoming increasingly stringent, making it particularly important to connect the "Ren and Du meridians" of digital transportation (transportation topology map).

[0003] Existing electronic traffic maps are mainly geared towards applications such as autonomous driving, navigation, intelligent connected vehicles, and traffic data visualization. The main map formats are electronic navigation maps, high-precision maps, and segmented maps.

[0004] These maps are not entirely suitable for intelligent traffic analysis applications. For example, navigation maps may have problems such as overly detailed road segments, excessively dense map breaks, lack of intersection objects, and some single-lane two-way roads, which will greatly increase computational complexity. High-precision maps, on the other hand, are mostly in Opendrive and Shp formats, which are mainly for display applications and are not suitable for traffic analysis.

[0005] In existing engineering projects, one or more maps are often required for defining road objects, extracting attribute features, and associating road equipment with electronic maps. This process is time-consuming, and due to the numerous steps and details involved in map adjustment and extraction, configuration errors are prone to occur, affecting algorithm accuracy and application effectiveness. With the addition, removal, and reconstruction of equipment and facilities during operation, the association between intelligent devices and the road network also needs to be updated regularly, requiring dedicated personnel for adjustment and maintenance. However, due to differences in work habits among staff and the lack of relevant map configuration workflows and standards during manual adjustments, configuration results often vary significantly, frequently leading to disordered road network topology and inaccurate road attributes. Summary of the Invention

[0006] The technical problem solved by this invention is that due to differences in the work habits of various staff members during the manual adjustment process, as well as the lack of relevant map configuration workflows and standards, the configuration results often vary greatly, frequently resulting in disordered road network topology and inaccurate road attributes.

[0007] To address the aforementioned technical problems, a method for automatically generating topological maps for traffic analysis based on navigation maps is provided, characterized by the following steps:

[0008] Step 1: Based on the requirements of the traffic analysis object, preprocess the navigation segment data to obtain a road segment object map that redraws the road segment objects and node objects; redraw the nodes and intersection nodes of the road segment object map.

[0009] Step 2: According to the merging rules, use a recursive method to merge road segment objects, extract road segment attributes, obtain the merging result, draw road objects based on the key node information of the merging result, and obtain the merging effect diagram;

[0010] Step 3: Based on the merged effect diagram and directional arrow information, identify the road segments and road segment objects associated with the intersection, extract the turning relationships and draw the turning relationship curves;

[0011] Step 4: Based on Step 3, establish a buffer area based on the equipment location, and set a reference section within the threshold range within the buffer area. Divide the reference section according to the direction of the equipment to obtain the cross-sectional diagram.

[0012] Step 5: Based on Step 4, associate road segment objects to form the relationship between cross sections and the road network, and obtain a topology map.

[0013] Preferably, the object screening retains highways, urban expressways, and ground roads, while removing ground road shipping, pedestrian overpasses, and internal roads within residential areas.

[0014] Preferably, the road segment attributes include: road length attribute, width attribute, number of lanes, road grade attribute, bridge attribute, speed limit attribute, height limit attribute, and road segment description.

[0015] Preferably, the road segment attributes are extracted using the following methods: summing the lengths of the sub-segments of the merged road segment to obtain the road length attribute; using the maximum width of the merged sub-segments as the width attribute of the merged object; using the maximum number of lanes of the merged sub-segments as the number of lanes of the merged object; dividing according to the road attribute field to obtain the road grade attribute; dividing according to the road grade field to obtain the road administrative grade; dividing according to the attribute value to obtain the bridge attribute; obtaining the speed limit attribute based on the minimum speed limit of the merged sub-segments; obtaining the height limit attribute based on the minimum height limit of the merged sub-segments; extracting the intersection name information of the starting and ending points of the road segment, determining whether the starting and ending points of the road segment are intersection points, and if not, continuing to search for intersection points forward or backward; if they are intersection points, extracting the intersection name, numbering and describing the road segments according to the order of the sub-segments between the intersections corresponding to the intersection names, to obtain the road segment description.

[0016] Preferably, step 3 includes the following steps: based on the merged effect diagram, read the directional arrow information according to the navigation segment information and related lane information associated in the merged road segment of the merged result; calculate the direction angle of the intersection associated road in the merged result; determine whether the angle between the direction of the road ahead and the road behind is within the straight-ahead threshold range according to the direction angle, and if it is within the straight-ahead threshold range, it is determined to be the straight-ahead direction, and straight-ahead guidance is drawn; determine whether the angle between the direction of the road ahead and the road behind is within the left-turn threshold range according to the direction angle, and if it is within the left-turn threshold range, it is determined to be the left-turn direction, and left-turn guidance is drawn; determine whether the angle between the direction of the road ahead and the road behind is within the right-turn threshold range according to the direction angle, and if it is within the left-turn threshold range, it is determined to be the right-turn direction, and right-turn guidance is drawn; determine whether a U-turn is allowed according to the road rule file, and if a U-turn is allowed, U-turn guidance is drawn.

[0017] This invention proposes an automated method for generating topological maps for traffic analysis based on navigation maps. By utilizing geographic information data such as navigation segments, nodes, and equipment layers, this method extracts the necessary road segments, nodes, intersections, turning relationships, and their corresponding attributes for traffic analysis. Furthermore, it generates traffic cross-section objects using equipment object information and logically associates them with the road network. This forms a logical digital representation of road segments, intersections, nodes, and equipment, providing a foundation for traffic analysis algorithms. By establishing coding rules, it enables rapid querying between objects, connecting previously isolated data within the traffic system into a network, saving development time and hardware costs. Attached Figure Description

[0018] The accompanying drawings, which are provided to further illustrate this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application.

[0019] Figure 1 This is a schematic diagram of an embodiment of an automated method for generating topological maps for traffic analysis based on navigation maps;

[0020] Figure 2 This is a schematic diagram of navigation routes and nodes;

[0021] Figure 3 Simplified diagram of navigation route

[0022] Figure 4 A diagram illustrating the filtering of road names;

[0023] Figure 5 The diagram shows the integration of road name information into the navigation road segment layer;

[0024] Figure 6This is a schematic diagram of the road segment object before preprocessing.

[0025] Figure 7 A schematic diagram of the road segment object after preprocessing;

[0026] Figure 8 This is a schematic diagram of intersection extraction;

[0027] Figure 9 Flowchart for merging navigation segments;

[0028] Figure 10 This is a schematic diagram of the merged road sections;

[0029] Figure 11 Flowchart for extracting road segment descriptions;

[0030] Figure 12 This is a schematic diagram describing the road segment;

[0031] Figure 13 This is a diagram illustrating the merged effect;

[0032] Figure 14 Draw a schematic diagram of the steering relationship for a single-entry lane;

[0033] Figure 15 This is a schematic diagram of the cross-section formation. Detailed Implementation

[0034] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0035] In this embodiment, an automated method for generating topological maps for traffic assessment based on navigation maps is provided. Based on the relevant coding rules of navigation map data, it extracts road objects, node objects, intersection objects, and related attributes relevant to traffic assessment, as well as the segment association relationship and transformation relationship between road objects and POI point objects. Figure 1 As shown, the steps are as follows:

[0036] Based on the requirements of traffic analysis, extraction rules were designed to filter navigation segment objects. The filtering criteria included highways, urban expressways, and surface roads, removing objects such as surface road shipping, pedestrian overpasses, and internal roads within residential areas. The navigation segment layer was then completed, and the road names and the forward, reverse, and bidirectional road segments were redrawn. The specific steps are as follows:

[0037] Navigation segment data preprocessing. Navigation segment filtering: Filter the navigation segment layer based on its attribute fields, selecting highways, urban expressways, and surface roads. Remove objects such as surface road shipping, pedestrian overpasses, and internal roads within residential areas to complete the filtering of the navigation segment layer. Node layer filtering: Based on the node layer and road segment layer, extract the nodes relevant to the filtered navigation segments and save them to a new node layer. Before and after filtering and simplification of navigation segments, as shown... Figure 2 and Figure 3 As shown.

[0038] Add extracted attribute associations to road names in navigation segments. Filter road name files: Remove English names and aliases from navigation segments, extract the Chinese names of roads in the navigation segments, and add the Chinese names of the road segments to the navigation segment attribute list, such as... Figure 4 As shown, road names are associated with navigation segments, and the road name information is incorporated into the navigation segment layer, such as... Figure 5 As shown. Navigation map object relocation: Because some road segment objects in the navigation map are drawn in reverse and some bidirectional road segment objects are combined into a single road segment object, which does not meet the requirements of the backend algorithm design and the frontend interface display, the road segment objects and node objects are redrawn. The specific drawing steps are as follows:

[0039] Roads with a bidirectional direction attribute (direction=3) are extracted from road objects in the navigation map and transformed into forward and reverse road segment objects, forming a road object set "link_set1" and a node object set "node_set1". Roads with a forward direction attribute (direction=1) are extracted from road objects in the navigation map and transformed into a road object set "link_set2" and a node object set "node_set2". Roads with a reverse direction attribute (direction=2) are extracted from road objects in the navigation map and transformed into a road object set "link_set3" and a node object set "node_set3". Virtual road segment sets "link_set4" and node object sets "node_set4" are established at map boundary points. "link_set1", "link_set2", "link_set3", and "link_set4" are merged into a new road segment set "link_set", and "node_set1", "node_set2", "node_set3", and "node_set4" are formed into a new node set "node_set". The before-and-after comparison is as follows. Figure 4 and Figure 5 As shown.

[0040] The process involves identifying the objects to be merged, using a recursive method, and merging road segments according to the merging rules. This includes extracting road segment attributes such as length, width, number of lanes, road grade, bridge attributes, speed limit attributes, height limit attributes, and providing road segment descriptions. The specific steps are as follows:

[0041] Point layer extraction and drawing. Node layer extraction and drawing: A new node set `node_set` is formed based on the start point `Snode_ID` and end point `Enode_ID` of the filtered segment. The coordinate point information of `node_set` is extracted. i lat i The node layer is then drawn. The intersection layer is extracted and drawn; since there is no intersection layer in the navigation layer, this section extracts and draws the intersection layer. The node layer is read, the main node information of the intersection is extracted, and the road segment information associated with the child node numbers corresponding to the main node is merged into the road information of the main node, {RoadName1, RoadName2}. The intersection names RoadName1-RoadName2 are extracted and written to the intersection attribute table. The intersection coordinates, longitude, etc., are extracted. longitude Draw the intersection layer, such as Figure 8 As shown.

[0042] Navigation segment merging, attribute extraction, and drawing. Determine the merging objects and perform the merging using a recursive method, such as... Figure 9 As shown, the merging rules are as follows: Connecting points that connect only two navigation segments will merge them into a single road segment object. During the merging process, if internal roads within an intersection are encountered (road segments with the last two digits of their KIND attribute being 04), the merging process ends. The merged navigation road segment IDs will be aggregated and used as the sub-road segment IDs for the merged segment. This will be updated in the merged object field of the merged segment. Figure 10 As shown.

[0043] Road segment attribute extraction. Road length attribute extraction: sum the lengths of the sub-segments of the merged road segment. Road width attribute extraction: extract the maximum width of the merged sub-segments as the width of the merged object. Road lane number extraction: extract the maximum number of lanes of the merged sub-segments as the number of lanes in the merged object. Road grade attribute extraction: classify roads according to the road attribute field. If the first two digits are "00", it is marked as a highway; if the first two digits are "01", it is marked as an expressway; if the first two digits are "02" or "03", it is marked as a main road; if the first two digits are "04", it is marked as a secondary main road; others are marked as local roads. Road administrative grade extraction: according to the road grade field, if the first two digits are "00" or "02", it is converted to a national highway; if the first two digits are "01" or "03", it is converted to a provincial highway; if the first two digits are "04", it is converted to a county road; if the first two digits are "08" or "09", it is converted to a county road; others are marked as other. Bridge attribute extraction: If "0f" is present in the attribute value, it is marked as a tunnel; if "08" is present, it is marked as a bridge. Speed ​​limit attribute extraction: Extract the minimum speed limit of the merged sub-segments as the speed limit attribute for that segment. Height limit attribute extraction: Extract the minimum height limit of the merged sub-segments as the height limit attribute for that segment. The road segment description is supplemented and improved as follows:

[0044] Extract the intersection names RoadName1-RoadName2 at the starting point of the road segment, and extract the intersection names RoadName1-RoadName3 at the ending point of the road segment. If the starting or ending point is not a node within an intersection, search for intersections forward or backward. The specific flowchart is as follows: Figure 11 As shown, road segments are numbered sequentially according to the sub-segments between intersections, and the road segment descriptions RoadName1 (RoadName1-RoadName3) are written into the road record attribute table, such as... Figure 12 As shown. Based on the key node information of the merged objects, the road objects are drawn, and the drawing result is as follows. Figure 13 As shown.

[0045] Based on the above results and road segment guide arrows, the road segments associated with the intersection are identified, road segment objects are identified, and turning relationships are extracted and drawn. The specific steps include the following:

[0046] Turning relationship extraction. Data association: Based on the navigation segment information associated in the merged road segment, associate relevant lane information and read relevant directional arrow information. Calculate the direction angles of the associated roads at the intersection. For straight-ahead direction determination, if the angle between the preceding road and the following road is within the threshold range [angles1, angles2], it is determined to be a straight-ahead direction. The default values ​​for angles1 and angles2 are -10 and 10, respectively. For left-turn direction determination, if the angle between the preceding road and the following road is within the threshold range [angles1, angles2], it is determined to be a straight-ahead direction. l1 , anglesl2 If the direction is within ], it is determined to be a left turn. l1 , angles l2 Default values ​​are -110 and -70. Right turn direction determination: if the angle between the road ahead and the road behind is within the threshold range [angles], then... r1 , angles r2 ] within, angles r1 , angles r2 Default values ​​are 70 and 110. Whether a U-turn is permitted is determined by reading the road rule file; if so, U-turn guidance drawing is performed. (angles) r1 , angles r2 The default values ​​are [160, 180] or [-180, -160]. Plot the steering relationship curve, as shown below. Figure 14 As shown.

[0047] Based on equipment location information and direction codes, upstream and downstream cross-sectional objects are drawn by associating buffer zone road segments. Specific steps include:

[0048] Cross-section objects are automatically generated. Based on equipment locations, a buffer zone is established, and cross-sections within a threshold range of m meters are defined. According to the equipment direction code, each equipment cross-section is divided into two sections: up and down. The above results are then associated with road segment objects, forming a relationship between the data collection equipment cross-sections and the road network. This creates a digital logical representation of equipment objects, cross-section objects, and road network objects, providing data support for traffic analysis. Specifically: Cross-section object association with the road network: Based on cross-section information matching and road segment direction angle calculation, associated road segment objects are determined. Nearby node information is calculated. If the distance is less than a threshold N meters, the cross-section is associated with that road network node. If the distance is greater than the threshold N meters, the next calculation step is performed. N is typically set to 10. The equipment cross-section finds the corresponding road segment, makes a perpendicular to that segment, breaks at the perpendicular, and then places that perpendicular as a road network node into the road network.

[0049] By following the steps above, a topological road map for traffic analysis can be automatically generated, thereby reducing the workload and error rate of manual configuration and improving update efficiency.

[0050] Compared with existing technologies, the main benefits of the embodiments provided by this invention are: They realize the topological generation of road segments, nodes, and cross-sections required for traffic analysis algorithms, as well as the object attributes required for analysis, reducing the computational complexity of subsequent algorithms and improving operational efficiency. They also reduce situations where road network topology structures are often disordered or road attributes are inaccurate due to differences in work habits among staff and a lack of relevant map configuration workflows, thus improving the accuracy of topological maps.

Claims

1. A method for automatically generating topological maps for traffic analysis based on navigation maps, characterized in that, Includes the following steps: Step 1: Based on the requirements of the traffic analysis object, preprocess the navigation segment data to obtain a road segment object map that redraws the road segment objects and node objects; redraw the nodes and intersection nodes of the road segment object map. Step 2: According to the merging rules, use a recursive method to merge road segment objects, extract road segment attributes, obtain the merging result, draw road objects based on the key node information of the merging result, and obtain the merging effect diagram; Step 3: Based on the merged effect diagram and directional arrow information, identify the road segments and road segment objects associated with the intersection, extract the turning relationships and draw the turning relationship curves; Step 3 includes the following steps: Based on the merged result diagram, the guide arrow information is read according to the navigation segment information and related lane information associated with the merged road segment in the merged result; Calculate the direction angles of the intersection-related roads in the merged results; The angle between the directions of the road ahead and the road behind is determined based on the direction angle. If it is within the straight-ahead threshold range, it is determined to be a straight-ahead direction, and straight-ahead guidance is drawn. The angle between the directions of the road ahead and the road behind is determined based on the direction angle. If it is within the left-turn threshold range, it is determined to be a left-turn direction, and then left-turn guidance is drawn. The direction angle is used to determine whether the angle between the road ahead and the road behind is within the right turn threshold range. If it is within the left turn threshold range, it is determined to be a right turn direction, and then right turn guidance is drawn. Based on the road rules document, determine whether a U-turn is permitted; if so, draw the U-turn guidance diagram. Step 4: Based on Step 3, establish a buffer area based on the equipment location, and set a reference section within the threshold range within the buffer area. Divide the reference section according to the direction of the equipment to obtain the cross-sectional diagram. Step 5: Based on Step 4, associate road segment objects to form the relationship between cross sections and the road network, and obtain a topology map.

2. The method for automatically generating topological maps for traffic analysis based on navigation maps as described in claim 1, characterized in that, The object filtering retains highways, urban expressways, and ground roads, while removing ground road shipping, pedestrian overpasses, and internal roads within residential areas.

3. The method for automatically generating topological maps for traffic analysis based on navigation maps as described in claim 1, characterized in that, The road segment attributes include: road length, width, number of lanes, road grade, bridge, speed limit, height limit, and road segment description.

4. The method for automatically generating topological maps for traffic analysis based on navigation maps as described in claim 3, characterized in that, The road segment attributes are extracted using the following methods: The lengths of the sub-segments of the merged road segment are summed to obtain the road length attribute; the maximum width of the merged sub-segments is used as the width attribute of the merged object; the maximum number of lanes of the merged sub-segments is used as the number of lanes of the merged object; and the road is divided according to the road attribute field to obtain the road level attribute. The administrative level of a road is determined by classifying it according to the road grade field. Bridge attributes are obtained by dividing the road into sections based on attribute values; speed limit attributes are obtained by dividing the road into sections based on the minimum speed limit of the merged sub-sections. Based on the minimum height limit of the merged sub-segments, the height limit attribute is obtained; the intersection name information of the starting point and ending point of the segment is extracted, and it is determined whether the starting point and ending point of the segment are intersection points. If they are not intersection points, the search for intersection points continues forward or backward. If it is an intersection, extract the intersection name, number the road segments according to the order of the sub-road segments between the intersections corresponding to the intersection name, and describe them to obtain the road segment description.

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