OSM-based route evaluation method

Abstract

The invention discloses an OSM-based flight route evaluation method, which comprises the following steps: S1, discretizing a flight route, and dividing the flight route into a plurality of sub-flight segments; s2, obtaining the OSM geographic data information of each sub-route segment, and merging to obtain the OSM geographic data information of the route; s3, classifying the geographic data information acquired from the OSM according to different label types, and performing classified statistics according to the airline safety degree, the operation environment reliability, the operation technology reliability and the public acceptability; and S4, evaluating the route according to the counted number of the labels and the weight of the class where the labels are located. According to the method, the OSM is utilized to open the data source, geographic information in the global range can be flexibly obtained, and the method is suitable for various urban environments; the specific geographic information of each sub-route segment can be independently inquired and evaluated through discretization processing of the route, the limitation that evaluation is carried out only depending on a starting point and an end point is avoided, and therefore a high-risk area is accurately recognized.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) technology, specifically relating to an OSM-based route evaluation method. Background Technology

[0002] With the rapid development of urban logistics, drones are increasingly being used in services such as express delivery. However, drone logistics in complex urban environments faces numerous challenges, particularly in terms of flight route planning safety, operational reliability, and public acceptability. The flight environment for drones involves not only safety in densely populated areas but also obstacles, buildings, and potential secondary disaster risks.

[0003] Existing route planning methods often focus on the shortest flight path or minimum energy consumption, while neglecting the potential impact on ground personnel and buildings, as well as the public's acceptance of privacy and noise. The civil aviation industry standard MH / T 4054-2022, "Specification for the Design of Logistics Routes for Light and Small Unmanned Aerial Vehicles in Urban Scenarios," provides qualitative assessment methods for four aspects: safety of the entire route, reliability of the operating environment, reliability of operational technology, and public acceptability. However, it lacks the feasibility for automated quantitative assessment. Summary of the Invention

[0004] The purpose of this invention is to provide an OSM-based route assessment method to achieve a comprehensive, automated, and quantitative assessment of the environment and facilities in the areas traversed by the route.

[0005] This invention is achieved through the following technical solution: The OSM-based route evaluation method includes the following steps: S1. Route discretization: dividing the route into multiple sub-segments; S2. Obtain OSM geographic data information for each sub-segment and merge them to obtain OSM geographic data information for the route. S3. Classify the geographic data information obtained from OSM according to different label types, and perform statistical analysis based on route safety, operational environment reliability, operational technology reliability, and public acceptability. S4. Evaluate the routes based on the number of tags counted and the weight of their respective categories.

[0006] In some embodiments, in step S1, the route is divided into multiple sub-segments at a fixed distance.

[0007] In some embodiments, obtaining OSM geographic data information for each sub-segment in step S2 includes: Based on the start and end coordinates of each sub-segment, construct the geometric buffer zone for that sub-segment; The buffer is converted to WKT format, and the OSM API is used to query geographic information to obtain geographic data around the sub-segment, including land use, roads, buildings, facilities, natural resources, and label information of man-made objects.

[0008] In some embodiments, the width of the geometric buffer is set according to the navigation accuracy of the route.

[0009] In some embodiments, in step S3, the tag type includes: Flight route safety assessment labels are used to assess the potential impact of drones on ground personnel, facilities, secondary disasters, and search difficulty; The operational environment reliability assessment label is used to assess environmental factors in the area through which the flight path passes, including the complexity of weather, electromagnetic interference, and obstacle environments. The technology reliability assessment label is used to evaluate the navigation, communication, and surveillance performance of unmanned aerial vehicles (UAVs). The public acceptability assessment label is used to assess the privacy and noise impacts on ground residents in the areas through which the flight path passes.

[0010] In some embodiments, the route safety assessment label includes: Ground personnel safety tags are used to assess population density in areas traversed by the flight path and the potential harm to ground personnel in the event of a crash. Ground facility safety tags are used to assess the importance of infrastructure in the areas the flight path passes through and the severity of the impact in the event of a drone crash; Secondary disaster risk labels are used to assess the degree of secondary disaster risk that may be caused by a drone crash; Search difficulty tags are used to assess the difficulty of searching for wreckage after a drone crash.

[0011] In some embodiments, the runtime environment reliability assessment label includes: Meteorological environment labels are used to assess the impact of meteorological conditions in the areas through which the flight route passes on the flight; Electromagnetic environment tags are used to assess electromagnetic interference in the areas traversed by flight routes. Obstacle environment labels are used to assess obstacles in the area traversed by the flight path.

[0012] In some embodiments, the operational technology reliability assessment label includes: Navigation performance labels are used to assess navigation conditions in areas traversed by the route; Communication performance tags are used to assess communication coverage in areas traversed by flight routes; Monitoring performance tags are used to assess whether a drone can effectively identify other targets or ground objects in flight along its flight path.

[0013] In some embodiments, public acceptability assessment labels include: Privacy impact labels are used to assess the level of privacy requirements in the areas the flight route passes through; Noise impact labels are used to assess the noise sensitivity of the area through which the flight path passes.

[0014] In some embodiments, in step S4, the evaluation score of the route is weighted according to the number of statistical labels and the weight of the class, and the route evaluation result is output.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: This invention can conduct a comprehensive assessment of flight routes from multiple dimensions, including ground personnel safety, ground facility safety, secondary disaster risk, search difficulty, environment, and technical reliability, to ensure the safety and feasibility of flight routes. By combining OSM data and classification statistical methods, it realizes quantitative assessment based on the "Specification for the Delineation of Logistics Flight Routes for Light and Small Unmanned Aerial Vehicles in Urban Scenarios", and achieves automated assessment of flight route feasibility.

[0016] This invention utilizes the OSM open data source, which can flexibly acquire geographic information worldwide and is applicable to various urban environments. By discretizing the flight route, the specific geographic information of each sub-segment can be independently queried and evaluated, avoiding the limitations of relying solely on the origin and destination for evaluation, thereby achieving accurate identification of high-risk areas.

[0017] This invention employs an automated data acquisition and evaluation process, which can quickly calculate the comprehensive score of a flight route, providing a scientific basis for route selection and adapting to different flight requirements and environmental changes. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the OSM-based route evaluation method in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0021] To address the problems existing in route feasibility assessment, this invention proposes a route assessment method based on OSM (Open Street Map), which achieves automated assessment of route feasibility by comprehensively evaluating the environment and facilities of the areas through which the route passes.

[0022] In some embodiments of the present invention, the OSM-based route evaluation method includes the following steps: S1. Route discretization: The route is divided into multiple sub-segments according to a fixed distance; The flight route is discretized into multiple sub-segments based on a fixed distance, and OSM geographic data information is obtained for each sub-segment.

[0023] S2. Obtain OSM geographic data information for each sub-segment and merge them to obtain OSM geographic data information for the route. Based on the start and end coordinates of each sub-segment, a geometric buffer is constructed for that sub-segment. The width of the geometric buffer is set according to the navigation accuracy of the route.

[0024] Then, the buffer is converted to WKT (Well-Known Text) format, and the OSM API is used to query geographic information to obtain geographic data around the sub-segment, including land use, highway, building, facility, and tag information such as natural resources and man-made objects.

[0025] Once the OSM geographic data information for all sub-segments has been acquired, it is merged into the OSM geographic data information for the flight route.

[0026] S3 and OSM geographic label statistics are categorized and statistically analyzed based on route safety, operational environment reliability, operational technology reliability, and public acceptability. The geographic information obtained from OSM will be categorized according to different label types, which are used to assess the multi-dimensional risks of flight routes.

[0027] OSM defines and publishes all tag names. These published tags only need to be pre-classified into four main categories based on their usage: route safety assessment, operational environment reliability assessment, operational technology reliability assessment, and public acceptability assessment. The pre-classified results are then stored in a database. When a program dynamically retrieves tags for a specific area, it automatically matches these tags with the pre-classified tags in the data to determine which category each tag belongs to and performs statistical analysis. This allows for the classification of geographic information obtained from OSM according to different tag types.

[0028] Specifically, the assessment includes the following four aspects, each involving multiple types of tags of interest, including: 3.1 Route Safety Assessment Label The flight route safety assessment focuses primarily on the potential impact of drones on ground personnel, facilities, secondary disasters, and search difficulty.

[0029] Related tags include: 1) Ground Personnel Safety Tag: Used to assess population density in areas traversed by the flight path and the potential harm to ground personnel in the event of a crash; including: Land use type: such as residential area, commercial area, etc.

[0030] Highway (road type): such as primary (main road), secondary (secondary road), etc., indicating roads with high population flow.

[0031] Building: such as residential buildings, office buildings, etc., indicating areas where people may gather.

[0032] Amenity (facility type): such as park, store, school, etc., facilities closely related to human activities.

[0033] 2) Ground Facility Safety Labels: Assess whether the area traversed by the flight path contains critical infrastructure that could have a serious impact if the drone crashes; including: Building: refers to a building containing essential facilities, such as a hospital or school.

[0034] amenity (facility type): such as hospitals, fire stations, etc.

[0035] man_made (man-made facilities): such as communication base stations, broadcast towers, power generation facilities and other key facilities.

[0036] 3) Secondary disaster risk label: Assess the potential secondary disaster risks that may be caused by a drone crash, such as fire, water pollution, etc.; including: Natural resources, such as rivers and forests, may exacerbate disaster risks.

[0037] Hazardous facilities: such as chemical plants, which pose a risk of secondary disasters such as chemical leaks or explosions.

[0038] 4) Search Difficulty Label: Used to assess the difficulty of searching for wreckage after a drone crash. For example, searching in areas with water or dense forest is more difficult; including: land use type: such as forest, farmland.

[0039] natural (natural resources): such as water (water bodies) and wood (forests), indicating areas with complex terrain.

[0040] Buildings: High-rise buildings or densely packed buildings may affect the progress of the search.

[0041] 3.2 Operating Environment Reliability Assessment Label The operational environment reliability assessment mainly targets environmental factors in the area through which the route passes, including weather, electromagnetic interference, and the complexity of the obstacle environment.

[0042] Related tags include: 1) Meteorological Environment Label: Assess the impact of meteorological conditions in the area through which the flight route passes on the flight, especially in areas with unstable air currents such as those near buildings or lakes; including: Natural resources, such as water or open areas, may generate unstable air currents.

[0043] Buildings: Areas with a high density of tall buildings may cause wind shear and airflow instability.

[0044] 2) Electromagnetic Environment Label: Assessing the electromagnetic interference in the area the flight path traverses, such as communication base stations and high-voltage power lines, which may affect the drone's navigation and communication performance; including: man_made (man-made facilities): such as tower (communication tower), power_tower (high voltage power tower), etc.

[0045] 3) Obstacle Environmental Labeling: Assess the potential impact of obstacles in the flight path area, such as tall buildings and tower cranes, on the drone's flight; including: Building: Tall buildings can become obstacles to flight.

[0046] man_made (man-made facilities): such as crane (tower crane), etc.

[0047] 3.3 Operational Technology Reliability Assessment Label Operational reliability assessment includes evaluating the navigation, communication, and surveillance performance of the UAV. Related tags include: 1) Navigation performance label: Used to assess whether the area traversed by the route has good navigation conditions, including satellite signal visibility, ground navigation equipment, etc.; including: natural resources: such as open areas or water bodies, which are conducive to satellite signal reception.

[0048] Buildings: Densely built-up areas may block satellite signals and affect navigation performance.

[0049] 2) Communication Performance Label: Assess the communication coverage of the area traversed by the flight route, including mobile communication signals and ground communication facilities; including: man_made (man-made facilities): such as tower (communication tower), etc.

[0050] 3) Surveillance Performance Label: This assesses whether the UAV can effectively identify other targets or ground objects in flight along its flight path. This label overlaps with obstacle environment labels.

[0051] 3.4 Public Acceptability Assessment Label The public acceptability assessment primarily focuses on the privacy and noise impacts on residents in the areas traversed by the flight path. Related tags include: 1) Privacy Impact Label: Assess whether the area the flight route passes through is a place with high privacy requirements, such as residential areas or government buildings; including: Land use type: such as residential (residential area) and commercial (commercial area).

[0052] Buildings: such as villas, office buildings, and other buildings where privacy is a high priority.

[0053] 2) Noise Impact Labels: Assess the noise sensitivity of the area through which the flight path passes. For example, areas such as schools and hospitals are highly sensitive to noise; including: Amenity (facility type): such as school, hospital.

[0054] S4. Calculate the weighted scores of the routes based on the number of tags counted and the weight of their respective categories, and output the route evaluation results. According to the weighting requirements in the "Specifications for the Design of Logistics Routes for Light and Small Unmanned Aerial Vehicles in Urban Scenarios", the scores of each evaluation aspect are calculated by weighting to obtain the comprehensive evaluation result of the route.

[0055] The OSM-based route evaluation method of the present invention will be further explained below with reference to specific embodiments.

[0056] Taking the assessment of the safety of a drone flight route from a logistics distribution center to a residential area in the city center as an example, the route starts at the edge of the city and ends at the residential area in the city center, passing through multiple areas, including commercial areas, industrial areas, residential areas, rivers and other natural areas.

[0057] Flight missions require a comprehensive assessment of route safety, particularly considering four factors: ground personnel safety, ground facility safety, secondary disaster risk, and search difficulty. To achieve this assessment, data from Open Street Maps (OSM) is used to independently evaluate each factor, ultimately providing a comprehensive safety score for the flight route.

[0058] Includes the following steps: 1. Data input; Origin: Distribution Center (Latitude: 30.1234, Longitude: 120.1234); Destination: Residential area (Latitude: 30.5678, Longitude: 120.5678); Flight path width: 30 meters.

[0059] 2. Four factors used for route safety assessment; 1) Ground personnel safety assessment Background: The flight path traverses residential, commercial, and industrial areas. Ground personnel safety primarily concerns the population density within the areas the flight path passes through, and the potential impact on ground personnel in the event of a drone malfunction.

[0060] Assessment Process: Landuse, highway, building, and facility labels are extracted from OSM data to identify land use types, roads, and building information in the areas traversed by the flight path. In residential and commercial areas, lower scores are given due to higher population density; conversely, industrial areas receive higher scores due to relatively lower population density. The safety score for each area is calculated using the assessGroundPersonSafety function. The number of high, medium, and low-risk areas is determined based on the distribution of people on the ground and population density, and a final score is given for that section.

[0061] 2) Safety assessment of ground facilities Background: The flight path passes over important ground facilities such as industrial sites, communication base stations, and power facilities. Ground facility safety assessment primarily evaluates the risk to these facilities in the event of a drone malfunction and crash.

[0062] Assessment Process: Important facilities, such as communication base stations (man_made=tower) and power towers (man_made=power_tower), are identified using the building, facility, and man_made tags in the OSM data. The `assessGroundFacilitySafety` function is used to score the safety risk of each facility based on its type and distribution. Power facilities and communication base stations are considered high-risk areas and receive lower scores; ordinary buildings have lower risk and receive higher scores.

[0063] 3) Secondary disaster risk assessment Background: The secondary disaster risk assessment involves the potential secondary disasters that may occur after a drone crash, such as fires and chemical spills. The flight path passes through industrial areas and river regions, which are considered high-risk areas.

[0064] Assessment Process: Identify areas traversed by the flight path that are labeled "natural" and "hazard," including rivers (natural = water) and hazardous facilities (hazard = chemical plant). Using the `assessSecondaryDamage` function, identify areas containing rivers and chemical facilities, and assess the potential risk of water pollution and chemical spills. Industrial areas and hazardous facilities have a higher risk of secondary disasters and receive lower scores; general areas receive higher scores.

[0065] 4) Search difficulty assessment Background: Assessing the difficulty of searching for drone wreckage and cargo when a drone malfunctions and crashes is particularly important. The flight path passes through rivers, residential areas, and industrial zones.

[0066] Evaluation Process: The system assesses the terrain and building density along the route based on the natural, landuse, and building labels in the OSM data. The `assessSearchDifficulty` function is used to score each area along the route. Areas with complex terrain, such as rivers and forests, are more difficult to search and receive lower scores; while open areas and residential areas are less difficult to search and receive higher scores.

[0067] 3. Evaluation results; The final safety score for the flight route is generated by weighting and summing the scores of each factor. Ground personnel safety: The assessment score was low, at 0.65, because the flight path passed over a densely populated area; Ground infrastructure safety: The route passes by multiple communication base stations and power facilities, resulting in a low score of 0.6; Secondary disaster risk: The route passes through industrial facilities and chemical hazard areas, resulting in a high risk of secondary disasters, with a score of 0.5. Search difficulty: The search difficulty is increased due to the route passing through some river areas, with a score of 0.7.

[0068] 4. Overall safety rating; The overall safety score is calculated based on the weights of different assessment items, with the weights set as follows: Ground personnel safety: weight 0.2; Ground facility safety: weight 0.15; Secondary disaster risk: weight 0.03; Search difficulty: weight 0.04.

[0069] Based on the weighted calculation, the final safety assessment score of the route is: Overall safety score = (0.65×0.2) + (0.6×0.15) + (0.5×0.03) + (0.7×0.04) = 0.13 + 0.09 + 0.015 + 0.028 = 0.263.

[0070] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. An OSM-based route evaluation method, characterized in that, Includes the following steps: S1. Route discretization: dividing the route into multiple sub-segments; S2. Obtain OSM geographic data information for each sub-segment and merge them to obtain OSM geographic data information for the route. S3. Classify the geographic data information obtained from OSM according to different label types, and perform statistical analysis based on route safety, operational environment reliability, operational technology reliability, and public acceptability. S4. Evaluate the routes based on the number of tags counted and the weight of their respective categories.

2. The OSM-based route evaluation method according to claim 1, characterized in that, In step S1, the route is divided into multiple sub-segments at fixed distances.

3. The OSM-based route evaluation method according to claim 1, characterized in that, Step S2 involves obtaining OSM geographic data information for each sub-segment, including: Based on the start and end coordinates of each sub-segment, construct the geometric buffer zone for that sub-segment; The buffer is converted to WKT format, and the OSM API is used to query geographic information to obtain geographic data around the sub-segment, including land use, roads, buildings, facilities, natural resources, and label information of man-made objects.

4. The OSM-based route evaluation method according to claim 3, characterized in that, The width of the geometric buffer zone is set according to the navigation accuracy of the route.

5. The OSM-based route evaluation method according to claim 1, characterized in that, In step S3, the tag types include: Flight route safety assessment labels are used to assess the potential impact of drones on ground personnel, facilities, secondary disasters, and search difficulty; The operational environment reliability assessment label is used to assess environmental factors in the area through which the flight path passes, including the complexity of weather, electromagnetic interference, and obstacle environments. The technology reliability assessment label is used to evaluate the navigation, communication, and surveillance performance of unmanned aerial vehicles (UAVs). The public acceptability assessment label is used to assess the privacy and noise impacts on ground residents in the areas through which the flight path passes.

6. The OSM-based route evaluation method according to claim 5, characterized in that, The route safety assessment labels include: Ground personnel safety tags are used to assess population density in areas traversed by the flight path and the potential harm to ground personnel in the event of a crash. Ground facility safety tags are used to assess the importance of infrastructure in the areas the flight path passes through and the severity of the impact in the event of a drone crash; Secondary disaster risk labels are used to assess the degree of secondary disaster risk that may be caused by a drone crash; Search difficulty tags are used to assess the difficulty of searching for wreckage after a drone crash.

7. The OSM-based route evaluation method according to claim 5, characterized in that, Operating environment reliability assessment labels include: Meteorological environment labels are used to assess the impact of meteorological conditions in the areas through which the flight route passes on the flight; Electromagnetic environment tags are used to assess electromagnetic interference in the areas traversed by flight routes. Obstacle environment labels are used to assess obstacles in the area traversed by the flight path.

8. The OSM-based route evaluation method according to claim 5, characterized in that, Operational technology reliability assessment labels include: Navigation performance labels are used to assess navigation conditions in areas traversed by the route; Communication performance tags are used to assess communication coverage in areas traversed by flight routes; Monitoring performance tags are used to assess whether a drone can effectively identify other targets or ground objects in flight along its flight path.

9. The OSM-based route evaluation method according to claim 5, characterized in that, Public acceptability assessment labels include: Privacy impact labels are used to assess the level of privacy requirements in the areas the flight route passes through; Noise impact labels are used to assess the noise sensitivity of the area through which the flight path passes.

10. The OSM-based route evaluation method according to claim 1, characterized in that, In step S4, the evaluation score of the route is weighted according to the number of statistical labels and the weight of the class, and the route evaluation result is output.

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