Urban landmark optimal touring path optimization selection method

Abstract

The invention discloses an optimal touring path optimization selection method for urban landmarks. The method comprises the following steps: acquiring data such as a road network in a research area, geographic positions of the urban landmarks and starting points of the urban landmarks in a path, and converting the data into travel path space data; screening out the short metric distance path on the basis of the output result of the short metric distance path through vision field analysis from a plurality of paths between the landmarks; screening out a plurality of minimum angle paths from the short metric distance paths; screening out a plurality of paths with high traffic facility accessibility from the plurality of paths with the minimum angle; through abundance calculation of urban rest facilities, cultural buildings and commercial buildings, a path with the highest abundance is screened out on the basis of an output result of a path with relatively high traffic facilities; on the basis of the path with the highest richness, through pedestrian pixel proportion calculation, the path with high vitality is screened out, space setting and attribute improvement are carried out, a touring path with excellent path, view angle and interface richness is generated, finally attribute information is connected, a target city touring route is formed, and the target city touring route is output.

Description

Technical Field

[0001] The present invention relates to the field of computers, and particularly to a method for optimizing the selection of the optimal tour path of urban landmarks. Background Art

[0002] Modern urban tours face compound scenario requirements: In the modern urban tour scenario, tourists expect to efficiently connect urban landmark buildings, cultural nodes, and vibrant blocks within a limited time to achieve multiple goals such as "optimal perspective, shortest path, high accessibility of transportation facilities, high functional richness, and vitality". The configuration of various functional elements in the city is closely related to people's movement trajectories. The richness of the public interface and the complexity of the roads deeply affect the way people navigate the urban grid. The perception of space and the sense of direction also influence the choices of movers during the tour. These elements together constitute a complex and diverse urban tour scenario.

[0003] Limitations of existing methods: For a long time, at the technical level, relying on single Baidu Maps and Gaode Maps makes it difficult to achieve ideal tour path planning. Existing path planning technologies cannot effectively connect real road traffic paths with urban representative landmarks. At the same time, when using the concept of integration degree in the route optimization process, key elements such as the served population and people's travel characteristics are not fully considered. Moreover, Gaode Maps and Baidu Maps have not been able to screen and quantify data such as "optimal perspective", "shortest path", "optimal perspective", "high accessibility of transportation facilities", "functional richness", and "vitality" to determine an effective tour route for a comprehensive experience of the city.

[0004] Technical bottlenecks and user experience gaps: In such a scenario and technical status quo, many problems are exposed. The lack of connection between urban landmarks and the transportation network forces tour routes to make a split choice between "efficiency first" and "experience first". The lack of quantitative integration of the street function mixing degree (such as the distribution of commercial, rest, and cultural facilities) makes it difficult to fit the different interest preferences of tourists. Dynamic vitality scenarios (such as real-time pedestrian flow and activity density) cannot be incorporated into path planning, making route decisions static and homogeneous, and out of touch with the real urban vitality rhythm. Previous studies focused on single considerations, ignoring many other factors. The proposed optimization schemes cannot provide the best route, and only starting from the spatio-temporal connection level, it is difficult to support tourists to complete the tour of tourist destinations on foot. Summary of the Invention

[0005] The present invention provides a method for optimizing the selection of the optimal tour path of urban landmarks. Based on the shortest topological distance, the present invention extracts the optimal tour path with the optimal perspective and the highest interface richness. Based on the real traffic trajectories of the city, it provides the optimal tour path between different landmarks for urban residents or tourists within an effective time, improving the user experience. See the following description for details:

[0006] An optimal tour path optimization selection method for urban landmarks, the method comprising:

[0007] Obtain the road network and urban landmark spatial data of the research area and convert them into travel path spatial data;

[0008] Convert the obtained road map into an axis map, and convert the points corresponding to the landmarks in the landmark positions into corresponding entrance routes;

[0009] Among the many paths between landmarks, screen out the minimum angle path based on the output result of the short metric distance path through visibility analysis; screen out several short metric distance paths from the minimum angle paths;

[0010] Screen out several paths with high accessibility of transportation facilities from several minimum angle paths; through the calculation of the richness of urban rest facilities, cultural buildings, and commercial buildings, screen out the path with the highest richness based on the output result of the path with higher transportation facilities;

[0011] Based on the path with the highest richness, screen out the path with high vitality through the calculation of the pedestrian pixel ratio, perform spatial positioning and attribute improvement, generate a tour path with excellent path, perspective, and interface richness, and finally connect the attribute information to form a target city tour route and output the target city tour route.

[0012] Wherein, the conversion of the obtained road map into an axis map and the conversion of the points corresponding to the landmarks in the landmark positions into corresponding entrance routes is:

[0013] Convert the road network geometric data into a topological structure model composed of continuous axes, and quantify the spatial accessibility characteristics of the road network through topological integration. Combine the landmark distribution path to systematically analyze the global spatial organization relationship of the urban traffic network. Wherein, the screening of the short metric distance path from the many paths between landmarks through visibility analysis based on the output result of the short metric distance path is:

[0014] Calculate the metric topological distance according to the spatio-temporal range of the walking speed; perform a registration operation on the specific position of the landmark to make it accurately correspond to a specific route in the axis map for selection;

[0015] Select a topological mode for calculation to obtain the shortest path connecting two line segments based on the topological mode. Through algorithms such as backtracking and traversal, all connected routes can be found on this basis; select several relatively short routes from these connected routes.

[0016] Wherein, the screening of the path with high vitality through the calculation of the pedestrian pixel ratio based on the path with the highest richness is:

[0017] Among several selected paths, Python software is used to batch capture street view images of the main path scenic spots, and the "person" elements on the pictures are divided by image segmentation;

[0018] Count the number of people in each path, and combine the data of multiple dimensions such as "high accessibility of transportation facilities", "shortest path", "optimal perspective", "functional richness", and "vitality". Through screening and quantification, reconfirm several routes of the usage scenarios.

[0019] Among them, through the integration of multi-dimensional data, using the data of "high accessibility of transportation facilities", "shortest path", "optimal perspective", "functional richness", and "vitality", a path planning paradigm of "efficiency - experience - vitality" trinity is formed.

[0020] The beneficial effects of the technical solution provided by the present invention are:

[0021] 1. The present invention obtains information elements and conversion elements, which are used to obtain road network information and urban landmark information for georegistration, and replaces the route where the entrance is located with the urban landmark entrance (as a point element);

[0022] 2. The present invention calculates and selects the "optimal perspective", and screens out the path with the smallest angle change based on the output result of the "shortest path" through view analysis;

[0023] 3. The present invention calculates and selects the "shortest path", and selects several relatively short metric distance routes between landmarks;

[0024] 4. The present invention selects the path with "high accessibility of transportation facilities". For example, factors such as the accessibility of transportation facilities such as buses and subways, and the density of bus stops and subway stations are comprehensively calculated to obtain a path with relatively high transportation facilities;

[0025] 5. The present invention selects "functional richness", and screens out the path with the highest richness by calculating the richness of public interfaces such as urban rest facilities, cultural buildings, and commercial buildings;

[0026] 6. The present invention selects "vitality", and screens out the path with relatively high street vitality through the calculation of the proportion of pedestrian pixels;

[0027] 7. Finally, the present invention performs spatial location and attribute improvement to generate a tour path with excellent path, perspective, interface richness, and vitality; the present invention organically integrates three-dimensional spatial path optimization methods and extracts the optimal experience path for urban residents or tourists to visit urban landmarks. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flowchart of an optimal tour path optimization selection method for urban landmarks. DETAILED DESCRIPTION OF THE INVENTION

[0029] To make the objectives, technical solutions, and advantages of the present invention clearer, the following further describes the embodiments of the present invention in detail.

[0030] For a long time, due to the difficulty in effectively connecting the real road traffic paths with the representative landmarks in the city, it has been difficult to plan an ideal tour path and it is very hard to achieve a tour path based solely on Baidu Map and Gaode Map, thus restricting the development and application of providing a comprehensive and optimal tour path for local people or tourists within an effective time.

[0031] The embodiments of the present invention are based on the real traffic trajectories in the city, register traffic data and conduct spatial analysis, extract the shortest traffic distance, the best line of sight, and the most abundant functional element information. Through precise processing of the traffic trajectories, an optimal tour path is provided for local people or tourists in the city within an effective time, improving the user experience.

[0032] Figure 1 is a schematic flowchart of a method for extracting an optimal tour path through traffic integration degree and line of sight, as Figure 1 shown. The method includes the following five steps: obtaining the road network and landmark data for urban spatial reference; conversion between urban elements and element registration; screening the best perspective, short distance, and interface richness for quantitative analysis; organically integrating the spatial paths in three dimensions and spatially locating urban traffic elements; connecting attribute information to form a tour route for the target city.

[0033] Among them, urban element extraction includes: obtaining the specific points of cad landmarks of the urban traffic road network, replacing them with the routes where the landmarks are located, and obtaining arcgis data and gis data of the specific locations of the landmarks. The urban spatial reference integration module conducts georegistration and spatial integration on spatial data such as urban traffic network data, thereby establishing a spatial reference system, converting the road network into an axis map, and calculating the paths between landmarks. Establish a quantitative analysis of short metric distances, field of view analysis data, and urban street functions. Provide the optimal path for tourists by comparing and superimposing in three aspects: distance, perspective, and function.

[0034] The analysis method specifically includes steps S1 - S7.

[0035] S1: Obtain the cad and gis data of the road traffic network;

[0036] Among them, the cad data is used to draw the road map, and the gis data is used to mark the landmark locations.

[0037] S2: Conversion between urban elements and element registration;

[0038] Among them, the road map obtained in step S1 is converted into an axis map, and the points corresponding to the landmarks in the landmark positions are converted into corresponding entrance routes.

[0039] S3: Based on the output result of step S3, filter out the path with the smallest angle change through field of view analysis;

[0040] S4: Calculate and select the "shortest path", and select the path with the shortest metric distance among many paths between landmarks;

[0041] S5: Select the path with "high accessibility of transportation facilities", and comprehensively calculate the path with relatively high accessibility of transportation facilities considering factors such as the accessibility of transportation facilities, the accessibility of buses and subways, and the density of bus stops and subway stations;

[0042] S6: Based on the output result of step S4, filter out the path with the highest richness by calculating the richness of public interfaces such as urban recreation facilities, cultural buildings, and commercial buildings;

[0043] Among them, the path with the highest richness is the richness of functions.

[0044] S7: Select "vitality", and filter out the path with relatively high street vitality by calculating the proportion of pedestrian pixels;

[0045] S8: Perform spatial positioning and attribute improvement to generate a tour path with excellent path, perspective, and interface richness;

[0046] Among them, first select several relatively short routes, then select several routes with the smallest angle change from these several relatively short routes, and select the routes with relatively high richness from these routes.

[0047] S9: Connect the attribute information to form a tour route of the target city, and output the tour route of the target city.

[0048] The following introduces the specific implementation method of step S1.

[0049] In a possible implementation method, step S1: Obtain cad and gis data of the road traffic network, including the following steps:

[0050] S11: Determine the geographical location and approximate scope of the target city or research area, and obtain the gis data of the road traffic network of the target city;

[0051] S12: Determine the geographical location and approximate scope of the target city or research area, and obtain the gis data of the specific locations of the landmarks in the target city;

[0052] S13: According to the requirements of the axis method of GIS data and space syntax, first, in order to be more accurate and stable, draw the road axis map of the target area in Auto CAD, draw the pedestrian walkways within the target area, and draw each pedestrian walkway as an axis map;

[0053] S14: Import the drawn axis map and landmark positions (point elements) into the GIS data for spatial location and attribute improvement, and confirm the routes where the landmarks are located. According to the landmarks, download the poi data of each landmark on the Internet, and mark them on arcgis (latitude and longitude data of urban landmarks) according to the specific positions of the poi data. Then import the cad road network map onto the GIS data. Mark the landmark points on the map and extract the road intersection lines related to them. The tool of the embodiment of the present invention will create two new GIS layers. The data consists of two shapefiles, one for nodes and one for edges. The nodes are landmarks, and the edges contain all road networks. Create node IDs and road network IDs on the GIS. The IDs correspond to the points and lines in the generated GIS file.

[0054] In a possible implementation manner, step S2: Convert the road network into an axis map (the cad road network map is converted into an axis map in the software depthmap and registered with the specific positions of the landmarks for spatial location), including the following steps:

[0055] S21: To build the basic model of the target area, after drawing in Cad, then open the Depthmap software, and perform analysis after checking by NodeCount without errors;

[0056] S22: After modifying the errors, use the Depthmap software to convert the cad road network into an axis map;

[0057] S23: Use the Depthmap software to perform integration analysis, and conduct an overall analysis of the urban traffic road network based on the routes where the landmarks are located; because the accessibility of each node to the landmarks is not considered, so when analyzing, one of the landmarks must be a starting point, and the next landmark is used as the target location while considering the urban landmark roads that tourists must pass through, and perform an accessibility analysis on the set of all paths between the landmarks to reveal the connectivity characteristics and accessibility degrees of different landmarks in the traffic system.

[0058] In a possible implementation manner, step S3: Calculate / obtain the relatively short metric distance between two landmarks (two nodes), including the following steps:

[0059] S31: Calculate the metric topological distance according to the spatio-temporal range of the walking speed;

[0060] S32: Perform a registration operation on the specific location of the landmark so that it precisely corresponds to a specific route in the axis diagram and make a selection.

[0061] S33: Select the topological mode for calculation, and the shortest path connecting two line segments based on the topological mode can be obtained. All connected routes can be found based on this through algorithms such as backtracking and traversal.

[0062]

[0063] Among them, m is the total length of the route between landmarks, n is the number of line segments, and d a is the total length from the starting point to the corner point.

[0064] (Among them, what this formula means is to successively accumulate the lengths d a of the n line segments between each landmark, and the resulting m is the total length of the route between these landmarks).

[0065] S34: Select several relatively short routes from these connected routes.

[0066]

[0067] Among them, C is the combination, R is the shortest paths between several landmarks, S is the total paths between landmarks, and several "shortest paths" are selected from many total paths.

[0068] In a possible implementation manner, step S4: Select several short metric distances and perform a field of view analysis of the real road distance on the paths of these short metric distances, including the following steps:

[0069] S41: On the axis diagram of the Depthmap software, select the line segment where the landmark is located and perform Run Angular SegmentAnalysis.

[0070] S42: Calculate the angular changes between 300m, 500m, 800m, 1000m, 1200m, 1500m, 1800m, 2000m, 2200m, 2500m, 2800m, and 3000m according to the scale change of the real path (radius). When selecting these distance parameters, based on the walking distance, it aims to achieve a better experience of the city.

[0071] S43: Cumulative angular deviation: Calculate the cumulative angular deviation from the starting point to the end point. Because the "shortest path" refers to the path with the smallest angular deviation (i.e., the straightest path) through the system.

[0072] The angular changes between each landmark are obtained through angular analysis, and the route with the smallest angular change of the line segment angles between landmarks is selected, or the sum of the smallest angular changes is calculated, and the line segments are connected to form a perspective route map.

[0073] S44: The calculation method for angular line segment selection is to calculate the distance between two corner points (referred to as "radius"), and the "shortest path" refers to the path with the smallest angular deviation (i.e., the straightest route) through the system. Suppose there is a direction vector of an actual path as and the direction vector of the axis in space syntax is The vector dot product formula can be used to calculate the included angle θ between them, and then the angular deviation is obtained.

[0074] According to the definition of the vector dot product:

[0075] Then the calculation formula for the included angle θ is:

[0076]

[0077] The θ obtained here is the included angle between the two lines represented by the two vectors, that is, the angular deviation. In practical applications, minimizing the angular deviation means making θ as small as possible. When θ = 0, it means that the directions of the two lines are completely the same, and the angular deviation is 0, reaching the minimum.

[0078] If considering multiple paths or multiple angular deviation situations, it may be necessary to further calculate statistical quantities such as the average angular deviation to comprehensively evaluate the overall angular deviation situation. For example, for n angular deviations i = 1, 2, 3, 4, n, the average angular deviation can be expressed as:

[0079]

[0080] The situation with the smallest overall angular deviation is found by minimizing θ.

[0081] In one possible implementation, step S5: Calculate the functional richness (function) of the street based on the selection of short distance and optimal line of sight, including the following steps:

[0082] Conduct functional richness analysis on several paths selected under the "shortest path" and "optimal perspective", and the urban landmarks coherently experience the overall cultural, shopping, and rest elements of the city.

[0083] S5: Select the path with "high accessibility of transportation facilities". The accessibility of transportation facilities is comprehensively calculated based on factors such as the accessibility of buses, subways, and the density of bus stops and subway stations to find the path with relatively high transportation facilities.

[0084] S51: Collect data of bus stops and subway stations;

[0085] S52: Bus stop data: It can be obtained from the official website of the bus company, the bus operation management system or the bus stop information provided by the transportation department. This data should include information such as the location (coordinates) of the bus stop, the stop name, etc. and calculate the bus stop density.

[0086]

[0087] Among them, D is the bus density, N is the number of bus stops, S is the area, and the unit can be "stops per square kilometer".

[0088] S53: Subway station data: Usually obtained from the urban rail transit company, including the location (coordinates) of the subway station, the station name, etc. and calculate the subway station density;

[0089] S54: Considering the overall public transportation station density of bus stops and subway stations, the total public transportation station density can be calculated.

[0090]

[0091] Step S6: By calculating the richness of public interfaces such as urban recreational facilities, cultural buildings, commercial buildings, etc., select the path with the highest richness based on the output result of step S4;

[0092] Among them, this step includes: S61: Count the density of each urban function on both sides of the street;

[0093] S62: Conduct a quantitative analysis of the density of each urban function on both sides of the street. The several functions considered here are: the density of buildings such as cultural function, shopping function, park, and rest function.

[0094]

[0095] Among them, n is the number of line segments, and T a is the density of each function on the line segment, and take the density of each function building on each line of each path.

[0096] In a possible implementation manner, step S7: Screen and quantify the data in three dimensions, and spatially locate the urban traffic elements, including the following steps:

[0097] S71: Re-confirm several lines for comprehensively experiencing the city through screening and quantifying the data of "shortest path", "optimal perspective", and "function richness".

[0098] In a possible implementation manner, step S8: Connect the attribute information to form a target city tour route, including the following steps:

[0099] S8: Select "vitality", calculate through the proportion of pedestrian pixels, and screen out the paths with higher street vitality.

[0100] S81: Among the selected several paths, use Python software to batch capture the street view images of the main path scenic spots, and use image segmentation to divide the "person" elements on the pictures.

[0101] S82: Count the number of people in each street.

[0102] S83: Count the number of people in each path. The data of "shortest path", "optimal perspective", "function richness", and "vitality" are reconfirmed through screening and quantification to comprehensively experience several lines of the city.

[0103] Step S9: Connect the attribute information to form a tourist route of the target city and output the tourist route of the target city.

[0104] Among them, this step includes:

[0105] S91: Generate a line of "shortest path", "optimal perspective", "function richness", and "vitality" between the walk and the landmark.

[0106] Those skilled in the art can understand that the attached drawings are only schematic diagrams of a preferred embodiment. The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0107] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the selection of the best tour path for city landmarks, characterized in that: The method comprises: Obtain data such as the road network, geographical locations of urban landmarks, and starting points of urban landmarks in the study area and convert them into travel path spatial data; The obtained road map is converted into an axis map, and the points corresponding to the landmarks in the landmark positions are converted into corresponding entry routes; Among the many paths between landmarks, the short metric distance path is selected based on the output result of the short metric distance path through the viewshed analysis; and several minimum angle paths are selected from the short metric distance paths; Select several paths with high accessibility to transportation facilities from several minimum angle paths; select the paths with the highest richness based on the output results of paths with higher transportation facilities by calculating the richness of urban recreational facilities, cultural buildings, and commercial buildings; Based on the paths with the highest richness, the proportion of pedestrian pixels is calculated to screen out paths with high vitality, and spatial positioning and attribute improvement are carried out to generate a tour path with excellent path, perspective, and interface richness. Finally, the attribute information is connected to form a target city tour route, and the target city tour route is output.

2. The method for optimizing and selecting the best tour path of a city landmark according to claim 1, characterized in that: The obtained road map is converted into an axis map, and the points corresponding to the landmarks in the landmark positions are converted into the corresponding entrance routes: The road network geometry data is transformed into a topological structure model composed of continuous axes, and the spatial accessibility characteristics of the road network are quantified through topological integration. Combined with the landmark distribution paths, a systematic analysis of the global spatial organization relationship of the urban transportation network is carried out.

3. The method for optimizing and selecting the best tour path of a city landmark according to claim 1 is characterized in that: The short metric distance path is selected from the many paths between landmarks through the viewshed analysis based on the output results of the short metric distance path as follows: The metric topological distance is calculated according to the spatial and temporal range of walking speed; the specific location of the landmark is registered so that it corresponds accurately to the specific route in the axis map and selected; Select the topological mode for calculation and obtain the shortest path between two line segments based on the topological mode. Through algorithms such as backtracking and traversal, all connected routes can be found on this basis; among these connected routes, several shorter routes can be selected.

4. The method for optimizing and selecting the best tour path of a city landmark according to claim 1, characterized in that: Based on the path with the highest richness, the path with high vitality is screened out by calculating the proportion of pedestrian pixels: Among the selected routes, Python software was used to batch capture street view images of the main routes and scenic spots, and image segmentation was used to divide the "people" elements in the images; The number of people on each path was counted, and the data from multiple dimensions such as "optimal perspective", "shortest path", "high accessibility to transportation facilities", "functional richness" and "vitality" were combined to reconfirm several routes for the usage scenarios through screening and quantification.

5. The method for optimizing and selecting the best tour path of a city landmark according to claim 1, characterized in that: Combining multi-dimensional data fusion through "optimal perspective", "shortest path", "high accessibility of transportation facilities", "functional richness" and "vitality" data, a path planning paradigm of "efficiency-experience-vitality" is formed.

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