Urban cross-domain multi-mode network space modeling method

Abstract

The invention discloses an urban cross-domain multi-mode network space modeling method, and belongs to the technical field of traffic simulation. In order to solve the problem that urban traffic cross-domain spatial modeling is complex, the method comprises the steps that road, hub and track BIM models are classified, traffic semantics in different BIM objects in the BIM models are recognized, and traffic elements are extracted; geometric element abstraction is carried out, spatial topology connection relations and attribute information of geometric elements are defined, and single-mode traffic network model modeling is carried out; coordinate conversion is carried out, and the relative position coordinates of the single-mode traffic network model are converted into 1984 world geodetic surveying geographic coordinates; a walking traffic network is used as an intermediate network, a walking traffic mode and transfer rules of roads, rails, buses and hubs are used as strategies, network fusion is achieved through a map matching algorithm, and a multi-mode network space is modeled; and carrying out topological structure verification on the obtained multi-mode network space. According to the invention, full-link calculation from design to simulation is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic simulation, and particularly relates to a method for modeling urban cross-domain multi-mode network space. Background Art

[0002] With the acceleration of the urbanization process, the traffic system is gradually developing towards multi-mode (roads, rails, hubs, etc.), multi-level (above ground, underground, three-dimensional), and dynamic directions. Traditional modeling methods are difficult to meet the needs of complex cross-domain spatial interactions and refined calculations. Due to its high-precision three-dimensional modeling ability, BIM technology has gradually been applied to the design of traffic infrastructure such as roads and rails. However, cross-domain multi-mode collaborative modeling is still in the exploratory stage, and there are technical bottlenecks especially in heterogeneous data fusion and dynamic generation of topological relationships.

[0003] Traffic network modeling based on GIS. Using the GIS spatial database to construct a two-dimensional road network topology and combining attribute data to achieve path analysis. However, it lacks three-dimensional spatial details (such as overpasses and underground rail layered structures); it is difficult to express the dynamic interactions of multi-mode traffic (such as bus-subway transfers); the topological relationship depends on manual definition and has a low degree of automation.

[0004] Graph theory and complex network modeling. Abstracting the traffic network into a graph structure of nodes and edges to analyze the network connectivity and robustness. However, the technology ignores physical space characteristics (such as the impact of slope and curvature on traffic capacity); it cannot support engineering-level refined calculations (such as BIM parametric design). Summary of the Invention

[0005] The present invention aims to solve the problem of complex cross-domain spatial modeling of urban traffic and proposes a method for modeling urban cross-domain multi-mode network space.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A method for modeling urban cross-domain multi-mode network space includes the following steps: S1. Classify the BIM models of roads, hubs, and rails, identify the traffic semantics in different BIM objects in the BIM models, and extract traffic elements; S2. Abstract the geometric elements of the traffic elements extracted in step S1, define the spatial topological connection relationships and attribute information of the geometric elements, and respectively perform single-mode traffic network model modeling, including self-driving traffic network topology modeling, pedestrian traffic network topology modeling, self-driving and pedestrian intersection network topology modeling, bus traffic network topology modeling, rail transit network topology modeling, and hub traffic network topology modeling; S3. Perform coordinate transformation on the single-mode traffic network models obtained in step S2, and convert the relative position coordinates of the single-mode traffic network models into 1984 World Geodetic System geographic coordinates; S4. Using the pedestrian traffic network as the intermediate network, and taking the transfer rules between the pedestrian traffic mode and roads, rails, buses, and hubs as the strategy, network integration is achieved through the map matching algorithm, and the multi-modal network space is modeled; S5. Perform a topological structure check on the multi-modal network space obtained in step S4.

[0007] Furthermore, the specific implementation method of step S1 includes the following steps: S1.1. Perform traffic element analysis based on the road BIM model. After analysis, the following 8 road BIM object bases and corresponding traffic elements are obtained: The road BIM object 1 is a road section, and the traffic elements include road length, width, pavement material, speed limit, maximum traffic flow, section type, etc., and the section type; The road BIM object 2 is a bridge, tunnel, or slope, and the traffic elements include structural type, span, height, length, such as speed limit, weight limit, and height limit; The road BIM object 3 is a section intersection; the traffic elements include intersection type, traffic flow control, and pedestrian crossing facilities; The road BIM object 4 is a parking lot, and the traffic elements include the number of parking spaces, layout, entrance / exit location, and charging; The road BIM object 5 is a roadside facility, and the traffic elements include facility type, location, and size; The road BIM object 6 is a traffic signal, and the traffic elements include lamp type, signal cycle, timing plan, location, and height; The road BIM object 7 is a ground marking, and the traffic elements include marking type and geometric dimensions. The marking type includes stop lines, prohibition lines, and pedestrian crossing lines; The road BIM object 8 is a guide sign, and the traffic elements include sign type, text, icon content, location, height, and size; S1.2. Perform traffic element analysis based on the hub BIM model. After analysis, the following 7 hub BIM object bases and corresponding traffic elements are obtained: The hub BIM object 1 is a hub entrance / exit, and the traffic elements include location, size, material, structural information, safety requirements, connection with other transportation modes, and barrier-free design; The hub BIM object 2 is a parking lot, and the traffic elements include the number of parking spaces, parking space size, entrance and exit locations, traffic flow, safety system, lighting, and markings; The hub BIM object 3 is a staircase, escalator, and elevator, and the traffic elements include location, number of steps, length, width, load-bearing capacity, size, and floor service range; The hub BIM object 4 is a guiding sign, and the traffic elements include location, size, and text content; The hub BIM object 5 is an obstacle, and the traffic elements include location and size; The hub BIM object 6 is a room, and the traffic elements include location, size, function, connecting channels, entrances and exits; The hub BIM object 7 is a door, and the traffic elements include location and size; S1.3. Analyze the traffic elements based on the track BIM model. After analysis, the following 7 track BIM object bases and corresponding traffic elements are obtained: The track BIM object 1 is an entrance / exit, and the traffic elements include location, size, structural information, connection with other traffic modes, and barrier-free design; The track BIM object 2 is a turnstile, and the traffic elements include location, size, operation mode, and passing speed; The track BIM object 3 is a concourse, and the traffic elements include size, layout, and connection of entrances / exits; The track BIM object 4 is a pedestrian passage, and the traffic elements include location, width, length, and connection with other areas such as concourse and platform; The track BIM object 5 is a platform, and the traffic elements include location, size, and relationship with the track line; The track BIM object 6 is a track line, and the traffic elements include track location, track type, distance, and connected stations; The track BIM object 7 is stairs, escalators and elevators, and the traffic elements include location, number of steps, length, width, load-bearing capacity, size, and floor service area.

[0008] Furthermore, the specific implementation method of step S2 includes the following steps: S2.1. Conduct topological modeling of the self-driving traffic network and pedestrian traffic network based on the road BIM model: S2.1.1. Extract the center lines of the roads. All the center lines of the roads are used as sections of the self-driving traffic network and pedestrian traffic network; the extracted center lines are used as straight sections, and the direction of the sections is determined according to the ground marking lines. Two straight sections in different directions are generated for each center line respectively; S2.1.2. Conduct section division: Use the two end nodes of the road and the road section intersections as the two end nodes of the road section. For internal roads, use the centroid points of the parking lots as the road section nodes, and cut the extracted sections to complete the topological modeling of the self-driving traffic network and pedestrian traffic network; S2.2. Conduct topological modeling of the self-driving and pedestrian intersection networks based on the road BIM model; use the center lines of the roads in the BIM model as the road network sections, calculate the linear intersection points of the road sections as intersection nodes, and generate right-turn and left-turn sections by connecting the intersection nodes to construct the topological structure of the road intersection network. The modeling abstraction process is as follows: S2.2.1. Modeling intersection nodes: An intersection is decomposed into several nodes according to the number of connected directions; S2.2.2. Modeling straight sections: Inside the intersection, a straight section is generated in each direction and linked to the four directions through nodes; S2.2.3. Modeling pedestrian sections: According to the pedestrian crossing facilities at the intersection of road sections extracted from the BIM model, a pedestrian section is generated for each pedestrian crossing facility; S2.2.4. Modeling right-turn sections: According to the traffic flow control elements at the intersection of road sections, a right-turn section is generated between two straight sections with right-turn elements. The direction is determined according to the direction of the straight sections and linked to the nodes of the straight sections; S2.2.5. Modeling left-turn sections: According to the traffic flow control elements at the intersection of road sections, a left-turn section is generated between straight sections with left-turn flows. The direction is determined according to the direction of the straight sections and linked to the nodes of the straight sections; S2.3. Conducting bus traffic network topology modeling based on the road BIM model; S2.3.1. Modeling bus traffic network nodes: Based on the center line of the road in the BIM model as the bus network section, the same BIM model road includes two directions, and a section is generated in each direction; S2.3.2. Modeling bus traffic network edges: The centroid of the bus stop is used as the bus network node; S2.4. Conducting rail transit network topology modeling based on the rail BIM model; S2.4.1. Modeling rail lines: The center line of the rail in the BIM model is used as the rail line; S2.4.2. Modeling rail line stations: One BIM station model is used as one line station node, and the line station node is linked to one of the internal network nodes of the hub; S2.5. Conducting hub traffic network topology modeling based on the hub BIM model; S2.5.1. Modeling internal network nodes of hub stations: Rail platforms, turnstiles, elevator doors, endpoints of straight elevators, and entrance / exit stations are used as rail transit network nodes. The nodes are linked according to the spatial order in the BIM model to form a complete movable route for passengers inside the station; S2.5.2. Modeling the Passenger's Movable Routes Inside the Station: The internal network topology of the hub connects the hub door nodes, staircase nodes, elevator nodes, entrance / exit nodes, rail platforms, turnstiles, elevator doors, endpoints of vertical elevators, and entrance / exit stations through walking arcs, staircase arcs, and elevator arcs. The rail transit network nodes formed are linked according to the spatial sequence of the BIM model to form a complete passenger's movable route inside the station. At the same time, the areas beside elevators, beside vertical elevators, and inside the rail stations are regarded as the passenger's movable routes inside the station.

[0009] Furthermore, the specific implementation method of step S3 includes the following steps: S3.1. Collecting the origin coordinates of the BIM model: Based on the fact that the BIM model uses a local coordinate system, the origin coordinates are obtained by measuring their coordinate values in the geographic coordinate system; based on the fact that the BIM model uses an engineering coordinate system, the origin coordinates are known quantities; S3.2. Converting the relative position coordinates of the origin coordinates of the BIM model into absolute position coordinates: Adding the origin coordinates to the relative position coordinates of each object in the BIM model to obtain the coordinate values of each object in the BIM model in the absolute position coordinate system; S3.3. Converting the coordinate values in the absolute position coordinate system obtained in step S3.2 into geographic coordinates, and the calculation formula is: ; where latitude and longitude are the latitude and longitude in the geographic coordinate system of the model respectively, height is the height in the geographic coordinate system of the model, e is the first eccentricity of the 1984 World Geodetic Coordinate Ellipsoid, latitude0 and longitude0 are the latitude and longitude of the origin of the BIM model respectively, x, y, and z are the coordinate values in the absolute position coordinate system respectively, N is the radius of the prime vertical, and p is the radius of curvature of the meridian; e = ; where, a is the semi-major axis of the 1984 World Geodetic Coordinate Ellipsoid, with a value of 6378137; b is the semi-minor axis of the 1984 World Geodetic Coordinate Ellipsoid; b = a * (1 - f); where f is the flattening of the 1984 World Geodetic Coordinate Ellipsoid, with a value of 1 / 298.257223563; N =

[0010] p = .

[0011] Further, the specific implementation method of step S4 includes the following steps: S4.1. Construct a map matching method: S4.1.1. Traverse and calculate network edge data, and perform geographical hashing encoding on the network edges; S4.1.2. Statistically calculate the set of edge IDs included in and intersecting with the geographical hash grid, and establish a mapping dictionary between the geographical hash grid and the edges; S4.1.3. Perform geographical hashing encoding on the node to be matched, index the geographical hash dictionary. If the dictionary is not empty, traverse and calculate the vertical projection of the node to be matched and the edges included in and intersecting with the geographical hash grid, and match it to the edge with the smallest vertical projection distance; if the dictionary is empty, traverse the adjacent grids of the geographical hash grid and repeat step 4.1.3; S4.1.4. After successful matching, calculate the projection coordinates of the node and the corresponding walking section, and break the walking section based on the projection point; S4.2. Based on the method in step S4.1, convert the node coordinates into a one-dimensional string, index the walking section ID in the geographical hash grid, and match it to the walking section with the closest projection distance. Use the projection point coordinates to break the walking section, establish a connection relationship, realize the integration of a single-mode transportation network, and obtain a multi-mode network space; S4.2.1. The method for integrating the walking transportation network and the bus transportation network is to match the platform nodes of the bus transportation network to the walking road section with the closest projection distance; break the walking road section based on the projection coordinates; connect the bus platform nodes and the walking section nodes; S4.2.2. The method for integrating the walking transportation network and the self-driving transportation network is to match the parking lot nodes of the self-driving transportation network to the walking road section with the closest projection distance; break the walking road section based on the parking lot projection coordinates; connect the parking lot projection nodes and the walking section nodes, and connect the parking lot projection nodes and the parking lot nodes; S4.2.3. The method for integrating the walking transportation network and the rail transit network is to match the track entrance and exit nodes and track elevator nodes of the rail transit network to the closest walking road section of the road; break the road walking section based on the projection coordinates; connect the track entrance and exit projection nodes and the track elevator projection nodes to the road walking section; S4.2.4. The method for integrating the walking transportation network and the hub transportation network is to match the entrance and exit nodes of the hub transportation network to the walking road section with the closest projection distance; break the walking road section based on the projection nodes; connect the hub entrance and exit projection nodes and the walking section nodes, and connect the hub entrance and exit projection nodes and the hub entrance and exit nodes.

[0012] Further, the specific implementation method of step S5 includes the following steps: After the multi-mode cyber space is constructed based on Step S4, use the depth-first search algorithm to traverse the nodes and edges of the multi-mode transportation network, detect the connectivity of the cyber space structure, and screen out the isolated nodes and isolated edges of the cyber space structure; Use the ratio of the number of nodes in the largest connected subgraph to the total number of network nodes to evaluate the network connectivity. The calculation formula is as follows: ; where, is the number of nodes in the largest connected subgraph, is the total number of nodes in the entire transportation network. If is less than 100%, it is considered that there is a non-connected area; S5.2. Based on the vehicle trajectory GPS data, use the map matching algorithm to match the vehicle trajectory to the transportation network section, compare the error between the matched trajectory line type and the actual vehicle trajectory, and verify the traffic network space topology structure.

[0013] Advantages of the present invention: A method for modeling an urban cross-domain multi-mode cyber space according to the present invention fills the technical gap in traffic cross-domain modeling of current BIM. Multi-mode feature extraction: Automatically extract the geometric and semantic information of roads, rails, and hubs from the BIM model, reducing manual intervention.

[0014] A method for modeling an urban cross-domain multi-mode cyber space according to the present invention realizes dynamic topology generation, constructs a cross-domain transportation network topology based on a rule engine, and supports multi-mode interaction analysis. The present invention combines the three-dimensional physical space with the logical topology to realize full-link calculation from design to simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flowchart of a method for modeling an urban cross-domain multi-mode cyber space according to the present invention; Figure 2 is a side view of a heat preservation outer cover for protecting the temperature of a low-temperature-resistant elevator traction machine according to the present invention; Figure 3 is a map matching schematic diagram of the present invention; Figure 4 is a schematic diagram of the latitude coding process of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in combination with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the specific embodiments described are only a part of the embodiments of the present invention, rather than all of the specific embodiments. Usually, the components of the specific embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations, and the present invention can also have other embodiments.

[0017] Therefore, the following detailed description of the specific embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed present invention, but merely represents the selected specific embodiments of the present invention. Based on the specific embodiments of the present invention, all other specific embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0018] To further understand the content, features and effects of the present invention, the following specific embodiments are exemplified and are accompanied by the attached Figure 1 - Attached Figure 4 The detailed description is as follows:

[0019] Embodiment 1: A method for modeling urban cross-domain multi-mode cyberspace, comprising the following steps: S1. Classify the road, hub, and rail BIM models, identify the traffic semantics in different BIM objects in the BIM models, and extract traffic elements; Further, the specific implementation method of step S1 includes the following steps: S1.1. Perform traffic element analysis based on the road BIM model. After the analysis, the following 8 road BIM object bases and corresponding traffic elements are obtained: The road BIM object 1 is a road section, and the traffic elements include road length, width, road surface material, speed limit, maximum flow, road section type, etc., road section type; The road BIM object 2 is a bridge, tunnel, or slope, and the traffic elements include structural type, span, height, length, such as speed limit, weight limit, height limit; The road BIM object 3 is a road section intersection; the traffic elements include intersection type, traffic flow control, and pedestrian crossing facilities; The road BIM object 4 is a parking lot, and the traffic elements include the number of parking spaces, layout, entrance / exit location, and charge; The road BIM object 5 is a roadside facility, and the traffic elements include facility type, location, and size; The road BIM object 6 is a traffic signal, and the traffic elements include lamp type, signal cycle, timing plan, location, and height; The road BIM object 7 is a ground marking, and the traffic elements include the marking type and geometric dimensions. The marking types include stop lines, prohibition lines, and pedestrian crosswalk lines; The road BIM object 8 is a guide sign, and the traffic elements include the sign type, text, icon content, location, height, and dimensions; The road BIM model is used to present relevant information such as the structure, attributes, and spatial relationships of the road. The road BIM model contains basic object information such as road sections of different road types, bridges, tunnels, slopes, road intersections, parking lots, roadside facilities, signal lights, ground markings, and guide signs. For the data requirements of application scenarios such as route planning, traffic control, and traffic simulation, the road traffic network needs to include basic traffic semantics such as road section geometric dimensions, road section types, speed limits, maximum traffic flow, locations of bridges, tunnels, and slopes, height limits, and load-bearing capacities.

[0020] S1.2. Analyze the traffic elements based on the hub BIM model. After analysis, the following 7 hub BIM objects and corresponding traffic elements are obtained: The hub BIM object 1 is the hub entrance and exit, and the traffic elements include location, dimensions, materials, structural information, safety requirements, connections with other transportation modes, and barrier-free design; The hub BIM object 2 is a parking lot, and the traffic elements include the number of parking spaces, parking space dimensions, entrance and exit locations, traffic flow directions, safety systems, lighting, and markings; The hub BIM object 3 is stairs, escalators, and elevators, and the traffic elements include location, number of steps, length, width, load-bearing capacity, dimensions, and floor service areas; The hub BIM object 4 is an indicator sign, and the traffic elements include location, dimensions, and text content; The hub BIM object 5 is an obstacle, and the traffic elements include location and dimensions; The hub BIM object 6 is a room, and the traffic elements include location, dimensions, function, connecting channels, entrance and exit; The hub BIM object 7 is a door, and the traffic elements include location and dimensions; The hub BIM model is used to present relevant information such as the structure, attributes, and spatial relationships of the transportation hub. The hub BIM model contains basic object information such as hub entrances and exits, parking lots, stairs / escaliers / elevators, indicator signs, obstacles, rooms, and doors. For the data requirements of application scenarios such as internal route planning, traffic control, pedestrian evacuation, and traffic simulation in the hub, the hub traffic network needs to include basic traffic semantics such as pedestrian walkable areas, door nodes, platform areas, gate facilities, queuing lines, and guiding information.

[0021] S1.3. Analyze the traffic elements based on the rail BIM model. After analysis, the following 7 rail BIM objects and corresponding traffic elements are obtained: The rail BIM object 1 is an entrance / exit, and the traffic elements include location, dimensions, structural information, connection with other transportation modes, and barrier-free design; The rail BIM object 2 is a turnstile, and the traffic elements include location, dimensions, operation method, and passing speed. The operation method includes swiping a card or scanning a code; The rail BIM object 3 is a concourse, and the traffic elements include size, layout, and connection of the entrances / exits; The rail BIM object 4 is a pedestrian passage, and the traffic elements include location, width, length, and connection with other areas such as the concourse and platform; The rail BIM object 5 is a platform, and the traffic elements include location, dimensions, and relationship with the rail line; The rail BIM object 6 is a rail line, and the traffic elements include rail location, rail type, distance, and connected stations; The rail BIM object 7 is a staircase, escalator, and vertical elevator, and the traffic elements include location, number of steps, length, width, load-bearing capacity, dimensions, and floor service area.

[0022] The rail BIM model is used to present relevant information such as the structure, attributes, and spatial relationships of the rail. The rail BIM model can include basic object information such as entrances / exits, turnstiles, concourses, pedestrian passages, platforms, rail lines, staircases, escalators, and vertical elevators. For the data requirements of application scenarios such as internal path planning, traffic control, and traffic simulation in the hub, the rail transit network needs to include basic traffic semantics such as pedestrian walkable areas, door nodes, platform areas, turnstile facilities, queuing lines, and guiding information.

[0023] S2. Abstract the geometric elements of the traffic elements extracted in step S1, define the spatial topological connection relationships and attribute information of the geometric elements, and conduct single-mode traffic network model modeling respectively, including self-driving traffic network topology modeling, pedestrian traffic network topology modeling, self-driving and pedestrian intersection network topology modeling, bus traffic network topology modeling, rail transit network topology modeling, and hub traffic network topology modeling; Based on the characteristics of roads, rails, and hub infrastructure, and the operation mechanisms and interaction behaviors of different traffic modes such as self-driving, pedestrian, bus, and rail, define the geometric expression forms, topological connection rules, and attribute information structures of multi-mode traffic network elements, and construct a multi-mode traffic network model to realize the semantic expression of the spatial characteristics, topological relationships, and attribute characteristics of traffic elements.

[0024] The urban multi-mode traffic network model mainly consists of a road traffic network, a rail transit network, a bus traffic network, a slow traffic network, and transfer hubs. The specific model construction can be divided into the following three steps: Sub - network Modeling: Geometric elements of traffic elements are abstracted based on traffic rules and actual physical structures of different traffic modes, and the spatial topological connection relationships and attribute information of geometric elements are defined. Separate single - mode traffic network models for roads, rails, buses, and pedestrians are constructed.

[0025] Coordinate Transformation: The relative position coordinates of the multi - mode traffic network are converted to the World Geodetic System 1984 (WGS84) coordinates to ensure the compatibility of this network with other Geographic Information System (GIS) datasets and tools.

[0026] Network Fusion: Based on transfer nodes such as hubs, parking lots, rail - bus stations, etc., transfer associations of sub - networks are established. By establishing virtual transfer nodes and transfer edges, physical nodes located in different - mode traffic networks are connected to describe the transfer relationships between different modes and achieve the fusion of single - mode traffic networks.

[0027] Furthermore, the specific implementation method of step S2 includes the following steps: S2.1. Topological modeling of the self - driving traffic network and the pedestrian traffic network based on the road BIM model: S2.1.1. Extract the center lines of roads. All road center lines are used as sections of the self - driving traffic network and the pedestrian traffic network. Taking the extracted road center lines as straight - line sections, the direction of the sections is determined according to the ground marking lines. Two straight - line sections in different directions are generated for each center line. S2.1.2. Conduct section division: Using the two - end nodes of the road and the intersection of road sections as the two - end nodes of the road section. For internal roads, using the centroid points of parking lots as the section nodes of the road, the extracted sections are segmented to complete the topological modeling of the self - driving traffic network and the pedestrian traffic network. S2.2. Topological modeling of the self - driving and pedestrian intersection network based on the road BIM model; Using the center lines of roads in the BIM model as road network sections, calculating the linear intersection points of road sections as intersection nodes, and generating right - turn and left - turn sections by connecting intersection nodes to construct the topological structure of the road intersection network. The modeling and abstraction process is as follows: S2.2.1. Model intersection nodes: An intersection is decomposed into several nodes according to the number of connected directions. Furthermore, for example, at a crossroads, four nodes are generated for one intersection.

[0028] S2.2.2. Model straight - line sections: Inside the intersection, one straight - line section is generated for each direction and linked to the four directions through nodes. S2.2.3. Model pedestrian sections: According to the pedestrian crossing facilities at the intersections of sections extracted from the BIM model, one pedestrian section is generated for each pedestrian crossing facility. S2.2.4. Modeling the right-turn section: According to the traffic flow control elements at the road intersection, a right-turn section is generated between two straight sections with right-turn elements. The direction is determined according to the direction of the straight sections and is linked to the nodes of the straight sections. S2.2.5. Modeling the left-turn section: According to the traffic flow control elements at the road intersection, a left-turn section is generated between straight sections with left-turn flows. The direction is determined according to the direction of the straight sections and is linked to the nodes of the straight sections. S2.3. Conducting bus traffic network topology modeling based on the road BIM model; S2.3.1. Modeling the nodes of the bus traffic network: Based on the center line of the road in the BIM model as the bus network section, the same BIM model road includes two directions, and a section is generated for each direction; S2.3.2. Modeling the edges of the bus traffic network: The centroid of the bus stop is used as the node of the bus network; S2.4. Conducting rail transit network topology modeling based on the rail BIM model; S2.4.1. Modeling the rail line: The center line of the rail in the BIM model is used as the rail line; S2.4.2. Modeling the rail line stations: One BIM station model is used as a node of the line station, and the line station node is linked to one of the nodes of the internal network of the hub; S2.5. Conducting hub traffic network topology modeling based on the hub BIM model; S2.5.1. Modeling the internal network nodes of the hub stations: Rail platforms, turnstiles, elevator doors, endpoints of straight elevators, and entrance / exit stations are used as nodes of the rail transit network. The nodes are linked according to the spatial order in the BIM model to form a complete movable route for passengers within the station; S2.5.2. Modeling the movable routes for passengers within the station: The internal network topology of the hub connects the hub door nodes, stair nodes, elevator nodes, and entrance / exit nodes through walking arcs, stair arcs, and elevator arcs. The rail transit network nodes formed by rail platforms, turnstiles, elevator doors, endpoints of straight elevators, and entrance / exit stations are linked according to the spatial order in the BIM model to form a complete movable route for passengers within the station. At the same time, the elevator sides, straight elevator sides, and the feasible area inside the rail station are used as the movable routes for passengers within the station.

[0029] S3. Performing coordinate transformation on the single-mode traffic network model obtained in step S2 to convert the relative position coordinates of the single-mode traffic network model into 1984 World Geodetic System geographic coordinates; Furthermore, the specific implementation method of step S3 includes the following steps: S3.1. Collecting the origin coordinates of the BIM model: The local coordinate system is used based on the BIM model, and the origin coordinates are obtained by measuring their coordinate values in the geographic coordinate system; the engineering coordinate system is used based on the BIM model, and the origin coordinates are known quantities; S3.2. Convert the relative position coordinates of the origin coordinates of the BIM model into absolute position coordinates: Add the relative position coordinates of each object in the BIM model to the origin coordinates to obtain the coordinate values of each object in the BIM model in the absolute position coordinate system; S3.3. Convert the coordinate values in the absolute position coordinate system obtained in step S3.2 into geographic coordinates, and the calculation formula is: ; Among them, latitude and longitude are the latitude and longitude in the model geographic coordinate system, height is the height in the model geographic coordinate system, e is the first eccentricity of the 1984 World Geodetic Coordinate Ellipsoid, latitude0 and longitude0 are the latitude and longitude of the origin of the BIM model, x, y, and z are the coordinate values in the absolute position coordinate system, N is the radius of the prime vertical, and p is the radius of curvature of the meridian; e = ; Among them, a is the semi-major axis of the 1984 World Geodetic Coordinate Ellipsoid, with a value of 6378137; b is the semi-minor axis of the 1984 World Geodetic Coordinate Ellipsoid; the parameters can be determined according to the geographical location of the BIM model and the ellipsoid model used.

[0030] b = a * (1 - f); Among them, f is the flattening of the 1984 World Geodetic Coordinate Ellipsoid, with a value of 1 / 298.257223563; N = ; p = .

[0031] S4. Take the pedestrian traffic network as the intermediate network, take the transfer rules of the pedestrian traffic mode with roads, rails, buses, and hubs as the strategy, and realize network fusion through the map matching algorithm to model the multi-mode network space; Furthermore, the specific implementation method of step S4 includes the following steps: S4.1. Construct a map matching method: S4.1.1. Traverse and calculate the network edge data, and perform geographic hashing encoding on the network edges; S4.1.2. Statistically calculate the set of edge IDs included in and intersecting with the geohash grid, and establish a mapping dictionary between the geohash grid and the edges; S4.1.3. Perform geohash encoding on the nodes to be matched, index the geohash dictionary. If the dictionary is not empty, traverse and calculate the vertical projections of the nodes to be matched and the edges included in and intersecting with the geohash grid, and match them to the edge with the smallest vertical projection distance; if the dictionary is empty, traverse the adjacent grids of the geohash grid and repeat step 4.1.3; S4.1.4. After successful matching, calculate the projection coordinates of the node and the corresponding walking section, and break the walking section based on the projection point; The map matching algorithm generates grid data covering the whole city through geohash, calculates the spatial relationship between the grid and the network edges, and obtains the list of network edge IDs included in and intersecting with the grid. Each time, perform geohash encoding on the starting and ending point latitudes and longitudes to obtain the grid IDs to which the starting and ending points belong. Traverse and calculate the vertical projection distances between the starting and ending points and the edges included in and intersecting with the grids to which they belong, and match them to the edge with the smallest distance; if the grid area is empty, traverse and calculate the vertical projection distances between the starting and ending points and the edges included in and intersecting with the adjacent grids, and match them to the edge with the smallest distance.

[0032] S4.2. Based on the method in step S4.1, convert the node coordinates into a one-dimensional string, index the walking section IDs in the geohash grid, match them to the walking section with the closest projection distance, break the walking section using the projection point coordinates, establish a connection relationship, realize the integration of a single-mode transportation network, and obtain a multi-mode network space; S4.2.1. The method for integrating the walking transportation network and the bus transportation network is to match the platform nodes of the bus transportation network to the walking road section with the closest projection distance; break the walking road section based on the projection coordinates; connect the bus platform nodes and the walking section nodes; S4.2.2. The method for integrating the walking transportation network and the self-driving transportation network is to match the parking lot nodes of the self-driving transportation network to the walking road section with the closest projection distance; break the walking road section based on the parking lot projection coordinates; connect the parking lot projection nodes and the walking section nodes, and connect the parking lot projection nodes and the parking lot nodes; S4.2.3. The method for integrating the walking transportation network and the rail transit network is to match the track entrance and exit nodes and track elevator nodes of the rail transit network to the closest walking road section of the road; break the walking road section of the road based on the projection coordinates; connect the track entrance and exit projection nodes and the track elevator projection nodes to the walking road section of the road; S4.2.4. The method for integrating the pedestrian traffic network and the hub traffic network is to match the entrance and exit nodes of the hub traffic network to the pedestrian road section with the closest projection distance; interrupt the pedestrian road section based on the projection nodes; connect the projection nodes of the hub entrance and exit to the pedestrian section nodes, and connect the projection nodes of the hub entrance and exit to the hub entrance and exit nodes.

[0033] The principle of geographical hashing encoding for longitude and latitude data is as follows: Taking the coordinate "30.280245, 120.027162" as an example, calculate its geographical hash string. First, perform binary encoding on the latitude. Divide [-90, 90] into two parts evenly. "30.280245" falls in the right interval (0, 90], so the first digit is 1; divide (0, 90] into two parts evenly. "30.280245" falls in the left interval (0, 45], so the second digit is 0; continuously repeat the above steps, and the target interval will become smaller and smaller, and the two endpoints of the interval will get closer and closer to "30.280245".

[0034] Through the above calculation, the encoding generated by the latitude is 10111 00011; similarly, encode the longitude coordinate 116.390705, and the encoding generated by the longitude is 11010 01011. Put the longitude in the even positions and the latitude in the odd positions, and combine the two strings of encodings to generate a new string: 11100 11101 00100 01111. As shown in Table 1 - Table 3: Table 1 Longitude and Latitude Group Code Table

[0035] Use 32 letters from 0 - 9, b - z (removing a, i, l, o) for base32 encoding. Convert 11100 11101 00100 01111 to decimal, which corresponds to 28, 29, 4, 15. Query the encoding corresponding to the decimal in the encoding table, which is wx4g.

[0036] Table 2 GeoHash Encoding Table

[0037] Table 3 GeoHash Encoding Table

[0038] S5. Perform topological structure verification on the multi - mode network space obtained in step S4.

[0039] Furthermore, the specific implementation method of step S5 includes the following steps: S5.1. After the construction of the multi-mode cyberspace based on Step S4 is completed, use the depth-first search algorithm to traverse the nodes and edges of the multi-mode transportation network, detect the connectivity of the cyberspace structure, and screen out the isolated nodes and isolated edges of the cyberspace structure; Use the ratio of the number of nodes in the largest connected subgraph to the total number of network nodes to evaluate the network connectivity. The calculation formula is as follows: ; where is the number of nodes in the largest connected subgraph, is the number of nodes in the entire transportation network. If is less than 100%, it is considered that there are non-connected areas; S5.2. Based on the vehicle trajectory GPS data, use the map matching algorithm to match the vehicle trajectory to the transportation network section, compare the error between the matched trajectory line type and the actual vehicle trajectory, and verify the topological structure of the transportation cyberspace.

[0040] The key technical points and points to be protected by this invention are as follows: Key technologies for extracting multi-mode transportation network elements: Classify the BIM models of roads, hubs, and tracks, identify the transportation semantics in different BIM model objects, and analyze the transportation element information. Automatically extract the geometric and semantic information of roads, tracks, and hubs from the BIM model to reduce manual intervention. Through standardized data processing methods, establish a complete and systematic basic information set for the multi-mode transportation network.

[0041] Topological modeling of multi-mode transportation network: By setting transfer rules between different modes, realize the integration of multi-mode transportation network through the map matching algorithm.

[0042] It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0043] Although the present application has been described above with reference to specific embodiments, various improvements can be made thereto and components thereof can be replaced with equivalents without departing from the scope of the present application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in the present application can be combined with each other in any way, and the exhaustive description of these combinations is not given in this specification only for the consideration of saving space and resources. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for modeling urban cross-domain multi-mode network space, characterized in that: The steps include: S1. Classify the BIM models of roads, hubs, and rails, identify the traffic semantics in different BIM objects in the BIM models, and extract traffic elements; S2. Perform geometric element abstraction on the traffic elements extracted in step S1, define the spatial topological connection relationship and attribute information of the geometric elements, and model single-mode traffic network models respectively, including self-driving traffic network topology modeling, pedestrian traffic network topology modeling, self-driving and pedestrian intersection network topology modeling, bus traffic network topology modeling, rail transit network topology modeling, and hub traffic network topology modeling; S3. The single mode transportation network model obtained in step S2 is subjected to coordinate transformation, and the relative position coordinates of the single mode transportation network model are converted into 1984 World Geodetic Geographic Coordinates; S4. Taking the pedestrian traffic network as the intermediate network and the transfer rules between pedestrian traffic mode and roads, rails, buses and hubs as the strategy, the network fusion is realized through the map matching algorithm to model the multi-modal network space; S5. Perform a topology check on the multi-mode network space obtained in step S4.

2. According to claim 1, a method for modeling urban cross-domain multi-mode network space is characterized in that: The specific implementation method of step S1 includes the following steps: S1.

1. Traffic elements are analyzed based on the road BIM model. The following 8 road BIM object bases and corresponding traffic elements are obtained after analysis: Road BIM object 1 is a road section, and traffic elements include road length, width, pavement material, speed limit, maximum flow, section type, etc., section type; Road BIM object 2 is a bridge, tunnel and slope, and traffic elements include structure type, span, height, length, such as speed limit, weight limit, and height limit; Road BIM object 3 is the road section intersection; traffic elements include intersection type, traffic flow control, and pedestrian crossing facilities; Road BIM object 4 is a parking lot, and the traffic elements include the number of parking spaces, layout, entrance / exit location, and charges; Road BIM object 5 is the roadside facility, and the traffic elements include facility type, location, and size; Road BIM object 6 is a traffic light, and traffic elements include lamp type, signal cycle, timing scheme, location, and height; Road BIM object 7 is ground markings, and traffic elements include marking types and geometric dimensions. The marking types include stop lines, prohibited lines, and pedestrian crossing lines. Road BIM object 8 is a road sign, and traffic elements include sign type, text, icon content, location, height, and size; S1.

2. Traffic elements are analyzed based on the hub BIM model. The following 7 hub BIM object bases and corresponding traffic elements are obtained after analysis: Hub BIM object 1 is the hub entrance and exit, and the traffic elements include location, size, material, structural information, safety requirements, connection with other modes of transportation, and barrier-free design; Hub BIM object 2 is the parking lot, and the traffic elements include the number of parking spaces, parking space dimensions, entrance and exit locations, traffic flow, safety systems, lighting, and markings; Hub BIM object 3 is stairs, escalators and elevators, and the traffic elements include location, number of steps, length, width, load capacity, size, and floor service range; Hub BIM object 4 is a signboard, and the traffic elements include location, size, and text content; Hub BIM object 5 is an obstacle, and the traffic elements include location and size; Hub BIM object 6 is a room, and the traffic elements include location, size, function, connecting passage, entrance and exit; Hub BIM object 7 is the door, and the traffic elements include location and size; S1.

3. Traffic elements are analyzed based on the rail BIM model. The following 7 rail BIM object bases and corresponding traffic elements are obtained after analysis: Track BIM object 1 is the entrance and exit, and the traffic elements include location, size, structural information, connection with other modes of transportation, and barrier-free design; The rail BIM object 2 is a gate, and the traffic elements include location, size, operation mode, and travel speed; Rail BIM object 3 is the station hall, and the traffic elements include size, layout, and connection of entrances and exits; Rail BIM object 4 is a pedestrian passage, and the traffic elements include location, width, length, and connections to other areas such as the station hall and platform; Track BIM object 5 is the platform, and the transportation elements include location, size, and relationship with the track line; Rail BIM object 6 is the rail line, and the transportation elements include rail location, rail type, distance, and connected stations; Rail BIM object 7 is stairs, escalators and elevators, and the transportation elements include location, number of steps, length, width, load capacity, size, and floor service range.

3. A method for modeling urban cross-domain multi-mode network space according to claim 2, characterized in that: The specific implementation method of step S2 includes the following steps: S2.

1. Self-driving traffic network topology modeling and pedestrian traffic network topology modeling based on road BIM model: S2.1.

1. Extract the center line of the road. All the center lines of the road are used as the road sections of the self-driving traffic network and the pedestrian traffic network. The extracted center line of the road is used as the straight road section. The direction of the road section is determined according to the ground markings. Each center line generates two straight road sections in different directions. S2.1.

2. Divide the road sections: Use the road end nodes and the road section intersections as the road end nodes. For internal roads, use the parking lot centroid as the road section node. Divide the extracted road sections to complete the self-driving traffic network topology modeling and the pedestrian traffic network topology modeling. S2.

2. Based on the road BIM model, the network topology modeling of the self-driving and pedestrian intersection is carried out; based on the BIM model, the road center line is used as the road network segment, and the intersection points of the road segments are calculated as the intersection nodes. By connecting the intersection nodes, right-turn and left-turn sections are generated to construct the road intersection network topology structure. The modeling abstraction process is as follows: S2.2.

1. Modeling intersection nodes: An intersection is decomposed into several nodes according to the number of connected directions; S2.2.

2. Modeling through sections: Inside the intersection, a through section is generated for each direction, which is connected to the four directions through nodes; S2.2.

3. Model pedestrian segments: Generate a pedestrian segment for each pedestrian crossing facility at the intersection extracted from the BIM model; S2.2.

4. Modeling right-turn sections: Based on the traffic flow control elements at the intersection, a right-turn section is generated between two straight sections with right-turn elements. The direction is determined by the direction of the straight section and is linked to the nodes of the straight section. S2.2.

5. Modeling left-turn sections: Based on the traffic flow control elements at the intersections, a left-turn section is generated between the straight sections with left-turn flow. The direction is determined by the direction of the straight section and is linked to the nodes of the straight section. S2.

3. Modeling of bus transportation network topology based on road BIM model; S2.3.

1. Modeling bus network nodes: The middle line of the BIM model road is used as the bus network segment. The same BIM model road includes two directions, and a segment is generated in each direction. S2.3.

2. Modeling bus transportation network edges: The centroids of bus stops are used as bus network nodes; S2.

4. Modeling of rail transit network topology based on rail BIM model; S2.4.

1. Modeling track route: The center line of the BIM model track is used as the track route; S2.4.

2. Modeling rail line stations: A BIM station model is a line station node, which is linked to one of the internal network nodes of the hub; S2.

5. Model the hub transportation network topology based on the hub BIM model; S2.5.

1. Modeling the internal network nodes of the hub station: rail platforms, gates, elevator doors, elevator endpoints, and entrance and exit stations are used as rail transit network nodes. The nodes are linked according to the spatial order of the BIM model to form a complete passenger movable route within the station; S2.5.

2. Modeling of passenger movable routes within the station: The internal network topology of the hub connects the hub door nodes, stair nodes, elevator nodes, entrance and exit nodes through walking arcs, stair arcs, and elevator arcs. The rail transit network nodes formed by the rail platform, gate, elevator door, elevator endpoint, and entrance and exit stations are linked according to the spatial order of the BIM model to form a complete passenger movable route within the station. At the same time, the elevator edge, elevator edge, and the feasible domain inside the rail station are used as the passenger movable route within the station.

4. The method for modeling urban cross-domain multi-mode network space according to claim 3 is characterized in that: The specific implementation method of step S3 includes the following steps: S3.

1. Collect the origin coordinates of the BIM model: The local coordinate system is used based on the BIM model, and the origin coordinates are obtained by measuring their coordinate values ​​in the geographic coordinate system; the engineering coordinate system is used based on the BIM model, and the origin coordinates are known quantities; S3.

2. Convert the relative position coordinates of the origin of the BIM model to absolute position coordinates: Add the relative position coordinates of each object in the BIM model to the origin coordinates to obtain the coordinate value of each object in the BIM model in the absolute position coordinate system; S3.

3. Convert the coordinate values ​​in the absolute position coordinate system obtained in step S3.2 into geographic coordinates using the following calculation formula: ； Among them, latitude and longitude are the latitude and longitude in the model geographic coordinate system, height is the height in the model geographic coordinate system, e is the first eccentricity of the 1984 World Geodetic Coordinate Ellipsoid, latitude0 and longitude0 are the latitude and longitude of the origin of the BIM model, x, y and z are the coordinate values ​​in the absolute position coordinate system, N is the radius of the meridian circle, and p is the meridian curvature radius; e= ； in, a The semi-major axis of the 1984 World Geodetic Coordinate Ellipsoid is 6378137; b The semi-minor axis of the 1984 world geodetic coordinate ellipsoid; b = a * (1 - f) ； Where, f is the flattening of the 1984 World Geodetic Coordinate Ellipsoid, which is 1 / 298.257223563; N= ； p= 。 5. A method for modeling urban cross-domain multi-mode network space according to claim 4, characterized in that: The specific implementation method of step S4 includes the following steps: S4.

1. Constructing a map matching method: S4.1.

1. Traverse and calculate the network edge data and perform geo-hash encoding on the network edges; S4.1.

2. Count the edge ID sets that are included in and intersected by the geo-hash grid, and establish a mapping dictionary between the geo-hash grid and the edge; S4.1.

3. Perform geo-hash encoding on the node to be matched, index the geo-hash dictionary, and if the dictionary is not empty, traverse and calculate the vertical projection of the edge contained in and intersecting the node to be matched and the geo-hash grid, and match it to the edge with the smallest vertical projection distance; if the dictionary is empty, traverse the adjacent grids of the geo-hash grid and repeat step 4.1.3; S4.1.

4. After the matching is successful, the projection coordinates of the node and the corresponding walking section are calculated, and the walking section is interrupted based on the projection point; S4.

2. Based on the method in step S4.1, the node coordinates are converted into a one-dimensional string, and the walking segment ID in the geohash grid is indexed and matched to the walking segment with the closest projection distance. The walking segment is interrupted by the projection point coordinates, and a connection relationship is established to realize the fusion of a single-mode transportation network and obtain a multi-mode network space; S4.2.

1. The pedestrian transportation network and the bus transportation network are integrated by matching the bus station nodes of the bus transportation network to the pedestrian road segment with the closest projection distance; breaking the pedestrian road segment based on the projection coordinates; and connecting the bus station nodes with the pedestrian road segment nodes. S4.2.

2. The pedestrian traffic network and the self-driving traffic network are integrated by matching the parking lot nodes of the self-driving traffic network to the pedestrian road segments with the closest projection distance; and breaking the pedestrian road segments based on the parking lot projection coordinates; Connect the parking lot projection node with the walking section node, and connect the parking lot projection node with the parking lot node; S4.2.

3. The pedestrian transportation network and the rail transportation network are integrated by matching the rail entrance and exit nodes and rail elevator nodes of the rail transportation network to the pedestrian road segment with the closest projection distance; breaking the pedestrian road segment based on the projection coordinates; Connect the track entrance and exit projection nodes and the track elevator projection nodes with the road walking section; S4.2.

4. The pedestrian transportation network and the hub transportation network are integrated by matching the entrance and exit nodes of the hub transportation network to the pedestrian road segment with the closest projection distance; and breaking the pedestrian road segment based on the projection node; Connect the hub entrance and exit projection nodes with the pedestrian section nodes, and connect the hub entrance and exit projection nodes with the hub entrance and exit nodes.

6. A method for modeling urban cross-domain multi-mode network space according to claim 5, characterized in that: The specific implementation method of step S5 includes the following steps: S5.

1. After the multimodal network space is constructed based on step S4, a depth-first search algorithm is used to traverse the nodes and edges of the multimodal transportation network, detect the connectivity of the network space structure, and screen out isolated nodes and isolated edges of the network space structure; Use the ratio of the maximum number of connected subgraph nodes to the total number of network nodes Evaluate network connectivity, the calculation formula is as follows: ； in, is the maximum number of connected subgraph nodes, is the number of nodes in the entire transportation network, if If it is less than 100%, it is considered that there is a non-connected area; S5.

2. Based on the vehicle trajectory GPS data, use the map matching algorithm to match the vehicle trajectory to the traffic network section, compare the matched trajectory line shape with the actual vehicle trajectory error, and verify the spatial topology of the traffic network.

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