Intelligent site selection method for eVTOL take-off and landing point considering noise propagation

Abstract

The application discloses an eVTOL take-off and landing point intelligent site selection method considering noise propagation, and relates to the technical field of urban air traffic infrastructure planning. The method acquires candidate take-off and landing points, three-dimensional data of buildings and sensitive target distribution. The take-off and landing sound source intensity is determined according to the take-off, hovering, climbing, approach and landing working conditions of the candidate take-off and landing points as sound sources. The noise exposure distribution is constructed along the propagation path by taking into account the geometric diffusion attenuation, air absorption and building shielding diffraction. The effectiveness of the roof diffraction line shielding is determined for each working condition section, and the equivalent sound pressure level is accumulated in the sound energy domain. The disturbed population size is integrated according to the equivalent sound pressure level to serve as a cost item. The multi-objective site selection model is formed by combining the passenger flow accessibility, airspace availability and ground connection convenience. The non-inferior solution set is obtained and the score ranking is output. When networking, the noise sound energy domain superposition is used as the coupling constraint for collaborative optimization. The building shielding is reversed to a sound barrier resource, and the noise disturbance to the public is quantitatively minimized. The application provides a basis for the compliance landing of infrastructure.

Description

Technical Field

[0001] This invention relates to the field of urban air traffic infrastructure planning technology, and specifically to an intelligent site selection method for eVTOL take-off and landing points that takes into account noise propagation. Background Technology

[0002] With the development of the low-altitude economy and urban air traffic, electric vertical takeoff and landing (eVTOL) aircraft are considered an important means of transportation to alleviate ground traffic congestion. The takeoff and landing sites, as the ground infrastructure for eVTOL operation, directly determine operational efficiency and compliance levels through their spatial layout. Takeoff and landing site selection must balance operational needs such as passenger accessibility, airspace availability, and convenient ground connections within limited urban land. Urban air traffic differs from ground transportation hubs; its takeoff and landing sites are often located in densely populated urban centers. These sites are typically surrounded by noise-sensitive targets such as residential areas, schools, and hospitals, resulting in a high degree of overlap between the acoustic impact range of the takeoff and landing sites and densely populated areas. Furthermore, during takeoff, hovering, climb, approach, and landing, the aerodynamic noise generated by the multi-rotor propagates to surrounding residential areas, schools, hospitals, and other sensitive targets. If site selection only considers passenger flow and land use while neglecting noise propagation, it can easily lead to public complaints after operation, forcing the relocation of takeoff and landing sites and repeated site selections, resulting in losses in infrastructure investment. Therefore, quantifying the impact of noise propagation and incorporating it into site selection decisions is a key step in ensuring the compliant implementation of urban air mobility infrastructure.

[0003] Most existing landing site selection technologies follow the site selection approach of ground transportation hubs, treating noise as a static attribute that can be attached to candidate sites. For example, US patent application US20220067863A1 discloses a landing site assessment method entitled "Vertiport assessment and mobility operations systems." This method divides a geographical area into grid sub-regions, assigns suitability values ​​to suitability factors such as land use zoning (including noise), proximity to rail stations, and proximity to fire stations and hospitals, and calculates a weighted average of these factors according to configurable weights to obtain a comprehensive suitability value for each sub-region. Sub-regions with comprehensive suitability values ​​exceeding a threshold are identified as candidate landing sites. However, the noise factor in this scheme is taken from the measured background ground noise of each sub-region, which is a static value attached to the location of the candidate point itself. It neither reconstructs the propagation process of rotor noise to sensitive targets along the propagation path with the candidate take-off and landing points as the sound source, nor does it take into account the correction of the propagation path by the obstruction and diffraction of sound waves by urban three-dimensional buildings. Therefore, it cannot answer the core technical problem that this invention aims to solve, namely, how to quantify and minimize the disturbed population caused by the propagation of eVTOL rotor noise to sensitive targets in an urban three-dimensional building environment. Since the propagation of noise in an urban three-dimensional building environment does not decrease monotonically with distance, but is significantly modulated by building obstruction and street valley structure, a candidate take-off and landing point that is close to a sensitive target but is obstructed by tall buildings may generate less noise at the sensitive target than a candidate take-off and landing point that is farther away but on an open and direct sound path. In this case, the site selection method that treats noise as a static point attribute will make an inverted judgment on the merits of candidate take-off and landing points. The take-off and landing points selected in this way are difficult to meet the sound environment requirements in actual operation, and will eventually lead to disturbance to residents and repeated site selection. Furthermore, during a single takeoff and landing, eVTOL sequentially undergoes takeoff, hovering, climb, approach, and landing. The vertical height of the sound source changes accordingly. Climb and approach occur along inclined climb and approach profiles, and the sound source also shifts horizontally. Building shielding of the sound source is effective when the sound source is below the roof of the shielding building, but fails when the sound source exceeds the roof. Location methods that treat noise as a static point attribute unchanging with operating conditions cannot reflect this shielding variation. Simultaneously, when multiple takeoff and landing points are networked, noise from multiple points at the same sensitive target will superimpose. Location methods that treat the noise of each candidate takeoff and landing point as independent point attributes also cannot reflect the superposition of noise at a shared sensitive target. All these shortcomings stem from the same core problem: treating the noise impact of takeoff and landing points as a static attribute that can be attached to candidate points, instead of reconstructing the noise propagation process from the candidate takeoff and landing points as sound sources to the sensitive target. Summary of the Invention

[0004] Addressing the core bottleneck of existing technologies in urban air traffic take-off and landing point selection—treating noise as a static attribute attached to candidate points and failing to quantify and minimize the disturbance to the population caused by the propagation of eVTOL rotor noise to sensitive targets—this invention provides an intelligent eVTOL take-off and landing point selection method that considers noise propagation. By using candidate take-off and landing points as sound sources, reconstructing the building-shading and diffraction propagation process of noise to sensitive targets according to operating conditions, and incorporating the affected population as a cost term into multi-objective optimization, the method uses the size of the affected population and operational efficiency, which is a normalized weighted combination of passenger accessibility, airspace availability, and ground connection convenience, as optimization objectives. This achieves the goal of quantifying and minimizing noise disturbance to residents through take-off and landing point selection from the perspective of sound propagation mechanisms.

[0005] The technical solution of this invention is: an intelligent location selection method for eVTOL take-off and landing points considering noise propagation, comprising the following steps: acquiring candidate take-off and landing points, geographic data, three-dimensional building data, and the distribution of sensitive targets within an urban air traffic area, wherein the sensitive targets are residential areas, schools, or hospitals; using each candidate take-off and landing point as a sound source, determining the take-off and landing sound source intensity of each candidate take-off and landing point based on the sound power characteristics of eVTOL under take-off, hovering, climb, approach, and landing conditions; and along the propagation path from the candidate take-off and landing point to the sensitive target, taking into account geometric diffusion attenuation, air absorption, and building density based on the three-dimensional building data. Object occlusion and diffraction are used to construct a noise exposure distribution covering the surrounding land area. Based on the noise exposure distribution and the population distribution at the sensitive target, the size of the affected population at each candidate take-off and landing point under a preset number of take-offs and landings is estimated. The size of the affected population is used as a cost term, which, together with passenger accessibility, airspace availability, and ground connection convenience, constitutes a multi-objective site selection model. The passenger accessibility, airspace availability, and ground connection convenience are normalized and weighted to form an operational efficiency. The non-dominated solution set between the operational efficiency and the size of the affected population is obtained through multi-objective optimization, and the comprehensive site selection score and ranking of each candidate take-off and landing point are output.

[0006] The beneficial effects of this invention are as follows: First, this invention uses each candidate take-off and landing point as a sound source and incorporates building occlusion diffraction based on three-dimensional building data to construct the noise exposure distribution along the propagation path from the candidate take-off and landing point to the sensitive target. Its mechanism is to reverse the building occlusion, which is regarded as a flight obstacle or an error to be eliminated by the existing site selection method, into a usable sound barrier resource, so that the candidate take-off and landing points that are blocked by high-rise buildings are disturbed. Compared with the existing scheme that only takes the measured background noise, this invention obtains the directional sound field projected by the candidate take-off and landing point to the sensitive target rather than the static value attached to the candidate point itself, thereby avoiding the reversal of the judgment of the merits of the candidate take-off and landing points due to ignoring the building occlusion. Secondly, this invention determines the sound source altitude trajectory according to takeoff, hovering, climb, approach, and landing conditions, and judges the shielding effectiveness of the roof diffraction line for each condition segment. The mechanism is that the sound barrier provided by the building shielding is only effective when the sound source is below the roof diffraction line of the shielding building, and the shielding immediately fails when the sound source is above the roof. Including the barrier attenuation only for the effective shielding conditions can avoid overestimating or underestimating the disturbance degree of the shielded candidate takeoff and landing points. Thirdly, this invention converts the sound pressure level of each condition segment to the sound energy domain, accumulates it according to the exposure time weight, and then integrates it to the disturbed population. The mechanism is that the sound pressure level is not linearly averaged across the number of people, across conditions, and across flights. The energy domain accumulation, the shielding effectiveness judgment, and the building shielding diffraction are coupled layer by layer, which together produce a synergistic effect that makes the shielded near point a new non-dominated solution for site selection, exceeding the sum of the individual effects of each feature. Fourth, this invention uses the superposition of acoustic energy domains of overlapping flight routes and noise exposure distribution as coupling constraints for collaborative optimization during network construction. The mechanism lies in the fact that noise from multiple take-off and landing points at shared sensitive targets is superimposed according to energy domains. Even if a group of individually compliant take-off and landing points are combined, the noise may still exceed the standard at the shared sensitive target. This invention thus avoids the problem of single-point optimization leading to overall noise superposition exceeding the standard. In summary, this invention reverses building obstruction from a flight hindrance to a sound barrier resource, determines the effectiveness of rooftop ray shielding based on operating conditions, accumulates exposure and integrates the disturbed population in the acoustic energy domain, and uses the superposition of noise acoustic energy domains as a coupling constraint for collaborative network construction. Each link is coupled sequentially and progressively, enabling take-off and landing point selection to quantify and minimize noise disturbance while considering operational efficiency derived from a normalized weighted average of passenger accessibility, airspace availability, and ground connection convenience. Compared to existing solutions that treat noise as a static point attribute, this invention obtains site selection results consistent with actual sound propagation, avoiding disturbance and repeated site selection due to neglecting noise propagation, and providing a quantitative basis for the compliant implementation of urban air traffic infrastructure. Attached Figure Description

[0007] Figure 1 This is an overall flowchart of the intelligent location selection method for eVTOL take-off and landing points that takes into account noise propagation, as described in this invention. Figure 2 This is a flowchart illustrating the process of determining the intensity of the takeoff and landing sound source in this invention; Figure 3This is a flowchart illustrating the construction of noise exposure distribution according to the present invention; Figure 4 This is a flowchart illustrating the estimation of the affected population size according to the present invention; Figure 5 This is a flowchart of the present invention for obtaining non-dominated solution sets and network collaborative optimization. Detailed Implementation

[0008] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0009] Example 1.

[0010] This embodiment uses the site selection of a batch of eVTOL take-off and landing points to be evaluated in the central urban area of ​​a city as an example to illustrate the complete implementation process of the method of the present invention. This implementation process is a pure methodological process, and each step can be executed by a computing device. Its overall flow is as follows: Figure 1 As shown, the process includes five steps in sequence: data acquisition, determination of take-off and landing sound source intensity, construction of noise exposure distribution, estimation of the size of the disturbed population, and multi-objective optimization and output.

[0011] Step S1: Obtain candidate take-off and landing points, geographic data, 3D building data, and the distribution of sensitive targets within the urban air traffic area.

[0012] Within the urban air traffic area, candidate take-off and landing sites are identified for evaluation. These sites are land parcels suitable for the construction of take-off and landing platforms, such as rooftop platforms, transportation hubs, or vacant land. In this embodiment, 32 candidate take-off and landing sites are selected within the evaluation area, and each candidate site is represented by its planar coordinates and the elevation of the take-off and landing platform.

[0013] Geographic data and 3D building data are acquired. This data includes the distribution of land use types, road and rail transit networks, and the planar outlines and heights of each building within the area to be evaluated. In this embodiment, building heights are extracted from a 3D urban model or oblique photogrammetry data, with a spatial resolution of 1m. Building planar outlines are represented by vector polygons. The building planar outlines and heights are used in subsequent steps to determine building occlusion and diffraction along the propagation path, while land use types and network data are used in subsequent steps to assess passenger accessibility and ground-level connectivity convenience.

[0014] Obtain the distribution of sensitive targets. These sensitive targets are residential areas, schools, or hospitals. For each sensitive target within the assessment area, record its coverage area and the population distribution within that coverage area. Population distribution is represented by population density, which is obtained from population raster data. In this embodiment, the population density of residential areas is based on the resident population, while the population density of schools and hospitals is based on the time-of-day distribution of students and patients. The coverage area and population distribution of sensitive targets are used in subsequent steps to convert the noise exposure distribution into the size of the affected population.

[0015] In addition, basic data for evaluating operational efficiency is acquired in step S1. Specifically, travel demand within the service area of ​​each candidate take-off and landing point is obtained from land use type distribution and travel demand data, used to evaluate passenger accessibility in subsequent steps; control constraints and route capacity of the airspace where each candidate take-off and landing point is located are obtained from airspace control data and route planning data, used to evaluate airspace availability in subsequent steps; and connection distances and connection methods from each candidate take-off and landing point to rail transit stations and main roads are obtained from road and rail transit network data, used to evaluate ground connection convenience in subsequent steps. The above basic data and the aforementioned geographic data and 3D building data are from the same source and are all acquired in one go in step S1 to avoid repeated collection in subsequent steps.

[0016] At this point, step S1 has obtained candidate take-off and landing points, geographic data, 3D building data, and the distribution of sensitive targets. In step S2, candidate take-off and landing points are used as sound source locations, and in step S5, they are used as scoring and ranking objects. In step S3, the 3D building data is used as the basis for determining the occlusion of the propagation path. In steps S3 and S4, the distribution of sensitive targets is used as the integration object for the end point of the propagation path and the affected population. The basic data for evaluating operational efficiency is used as the source of indicators for constructing the multi-objective location model in step S5. There is no data that is not used in subsequent steps.

[0017] Step S2: Using each candidate take-off and landing point as a sound source, determine the take-off and landing sound source intensity of each candidate take-off and landing point based on the sound power characteristics of eVTOL under take-off, hovering, climb, approach and landing conditions.

[0018] The process for this step is as follows: Figure 2As shown. Using the candidate take-off and landing points obtained in step S1 as sound sources, the operating state of the eVTOL during take-off and landing is divided into five conditions: take-off, hovering, climbing, approach, and landing. The take-off condition corresponds to the stage from when the eVTOL leaves the take-off and landing platform to when it reaches the hovering altitude; the hovering condition corresponds to the stage when the eVTOL hovers at a fixed point above the take-off and landing platform; the climbing condition corresponds to the stage when the eVTOL rises and leaves the field along the climbing profile from the hovering altitude; the approach condition corresponds to the stage when the eVTOL approaches and descends along the approach profile to the hovering altitude above the take-off and landing platform; and the landing condition corresponds to the stage when the eVTOL descends vertically from the hovering altitude to touch down and dock at the take-off and landing platform.

[0019] The acoustic power characteristics include the acoustic power level and directivity for each of the following conditions: takeoff, hovering, climb, approach, and landing. The directivity describes the distribution of the takeoff and landing sound source intensity with respect to the propagation path direction angle. The acoustic radiation of a multi-rotor eVTOL exhibits significant directionality; the acoustic power level directly below and diagonally below is typically higher than in the horizontal direction, and varies with the harmonic components of the blade's passing frequency. Therefore, this invention does not characterize the sound source with a single acoustic power value, but rather characterizes the takeoff and landing sound source intensity using both the operating condition and the direction angle.

[0020] For the Under each operating condition, the candidate take-off and landing points are used as the sound source along the directional angle. The directional sound power level is determined by the following formula: ,in: For candidate take-off and landing points in the 1st Direction angle under various working conditions The directional sound power level is a scalar with a value range of 60 to 120 and a unit of dB. It is calculated by this formula and represents the intensity of the take-off and landing sound source of the candidate take-off and landing point under the corresponding working conditions and directions. For the first The reference sound power level for each operating condition is a scalar value ranging from 60 to 120 dB. It is determined by the sound power test data of the eVTOL model according to the operating condition and characterizes the total radiation intensity of the sound source under that operating condition. The value is the operating condition number, which is a scalar with values ​​of 1, 2, 3, 4 and 5, corresponding to takeoff, hovering, climb, approach and landing operating conditions respectively. It is dimensionless and determined by the operating condition classification, representing the current operating condition. The azimuth angle is a scalar value ranging from 0 to 360 degrees, with the unit being deg. It is determined by the horizontal direction from the sound source to the sensitive target and represents the horizontal direction of the propagation path. is the pitch angle, is a scalar, with a value range from -90 to 90, and the unit is deg. It is determined by the angle between the line connecting the sound source to the sensitive target and the horizontal plane, and represents the vertical direction of the propagation path. For the first Each working condition along the direction angle The directivity factor is a scalar with a value ranging from 0.1 to 10. It is dimensionless and is obtained by interpolation of the sound radiation directivity curve under this working condition. It characterizes the radiation gain of the sound source relative to the non-directive spherical sound source in this direction. This is a base-10 logarithmic operator. In this embodiment, the reference sound power level for takeoff is 98 dB, for hovering it is 95 dB, for climb it is 92 dB, for approach it is 94 dB, and for landing it is 96 dB. The reference sound power levels for these five conditions are all obtained by A-weighted synthesis of the 1 / 3 octave band sound power level measured by the aircraft noise measurement method for the eVTOL model under the corresponding conditions, rather than by empirical estimation. It should be noted that the reference sound power level for approach is higher than that for climb because when the eVTOL descends along the approach profile, the rotor enters the downdraft field formed by its own wake vortex, and the interference between the blades and the shedding vortex enhances the mid-to-high frequency radiation. The reference sound power level for landing is higher than that for hovering because the sound source is closer to the takeoff and landing platform in this condition, and the interaction between the downwash and the platform surface, as well as the sound reflection from the platform, increases the total radiation intensity. The directivity factor is obtained by interpolating the measured sound power levels of the aircraft directly below, diagonally below at 45 degrees, and horizontally. Thus, the takeoff and landing sound source intensity, characterized by operating conditions and azimuth angle, is obtained for each candidate takeoff and landing point, serving as the sound source input for constructing the noise exposure distribution in subsequent step S3.

[0021] Step S3: Along the propagation path from the candidate take-off and landing point to the sensitive target, take into account geometric diffusion attenuation, air absorption, and building occlusion diffraction based on the building's three-dimensional data to construct a noise exposure distribution covering the surrounding plots.

[0022] The process for this step is as follows: Figure 3 As shown. For each candidate take-off and landing point and each sensitive target in the surrounding plot, a propagation path from the candidate take-off and landing point to the sensitive target is constructed. Along the propagation path, three propagation attenuation factors are successively included: geometric diffusion attenuation, air absorption, and building obstruction diffraction. This converts the take-off and landing sound source intensity obtained in step S2 into the received sound pressure level at the sensitive target. Covering all sensitive targets in the surrounding plot yields the noise exposure distribution of the candidate take-off and landing point.

[0023] Geometric diffusion attenuation is determined based on the spherical diffusion law of a point sound source, and it increases with the propagation distance. This is a known propagation attenuation in the art. In this embodiment, the calculation is based on the free-field spherical diffusion over the propagation distance from the candidate take-off and landing point to the sensitive target. The propagation distance is determined by the three-dimensional coordinates of the candidate take-off and landing point and the sensitive target. For every doubling of the propagation distance, the geometric diffusion attenuation increases by approximately 6 dB. Since the candidate take-off and landing point, as the sound source, is located at the elevation of the take-off and landing platform, the propagation distance is calculated based on the three-dimensional coordinates of the sound source and the sensitive target, rather than solely based on the planar distance, thus taking into account the influence of the take-off and landing platform elevation on the propagation distance.

[0024] Air absorption is determined based on the absorption of sound energy by the propagation medium. Air absorption is determined by frequency band, and is related to geometric diffusion attenuation, the air absorption coefficient corresponding to the frequency band, and the propagation distance. The air absorption coefficient is determined by ambient temperature and relative humidity, and is a known propagation attenuation in the art. In this embodiment, air absorption is calculated based on octave bands, with an ambient temperature of 25°C and a relative humidity of 70%. The propeller frequencies and harmonic components of multi-rotor eVTOLs are mainly concentrated in the mid-to-high frequency band. The air absorption coefficient in the mid-to-high frequency band is larger than that in the lower frequency band. Therefore, for the same propagation distance, the air absorption attenuation in the mid-to-high frequency band is more significant. This invention calculates air absorption separately for each frequency band and then synthesizes the received sound pressure level at the sensitive target to accurately reflect the differential attenuation of sound energy with propagation distance in different frequency bands.

[0025] Furthermore, in densely populated urban areas with high-rise buildings, a valley structure often exists between the sound source and the sensitive target, formed by buildings on both sides. The obstruction of sound waves by the buildings on both sides of the valley, along with the width-to-height ratio of the valley, jointly affects the propagation path of the sound waves to the sensitive target. This invention identifies the valley structure on the propagation path based on three-dimensional building data, incorporating the obstruction of the propagation path by the buildings on both sides of the valley into the determination of building obstruction diffraction, thereby avoiding the underestimation or overestimation of actual noise propagation under the flat ground assumption.

[0026] Building obstruction diffraction is determined based on the three-dimensional building data obtained in step S1. The building obstruction diffraction includes: determining, based on the three-dimensional building data, the obstruction of the line of sight between the sound source and the sensitive target by the obstructing building along the propagation path; and incorporating the propagation path of the obstructed line of sight into the attenuation of the blade-edge diffraction barrier, thereby reducing the disturbance of candidate take-off and landing points obstructed by the obstructed building relative to unobstructed candidate take-off and landing points. Unlike existing site selection methods that treat building obstruction merely as a flight obstacle or a propagation error to be eliminated, this invention reverses building obstruction into a usable sound barrier resource: when the direct line of sight between the sound source and the sensitive target is blocked by the obstructing building, the sound waves must bypass the roof edge of the obstructing building to reach the sensitive target. This diffraction process generates additional propagation attenuation, reducing the received sound pressure level of the candidate take-off and landing points obstructed by the obstructing building at the sensitive target. It should be noted that the obstructing building acting as a sound barrier does not mean that the acoustic environment of the obstructing building itself is excluded from the calculation. Buildings in cities often serve as both residences and offices, and the shielding building itself may also be considered a sensitive target. Therefore, this invention treats shielding buildings in two ways. First, when the shielding building is located in a residential area, school, or hospital, it participates in the construction of noise exposure distribution and the integration of the affected population size as an independent sensitive target. The receiving point is the facade of the shielding building facing the candidate take-off and landing point. The line of sight from the sound source to the receiving point is not blocked by the building itself. Therefore, the propagation path is calculated based on the direct sound, including geometric diffusion attenuation and air absorption, but not the attenuation of the blade diffraction barrier. The shielding building is not exempted from the calculation of its own disturbance simply because it provides shielding for the sensitive target behind it. Second, when the shielding building is not located in a residential area, school, or hospital, but is located in non-sound-sensitive areas such as commercial offices or warehousing and logistics facilities, it only participates in the determination of shielding diffraction as a barrier on the propagation path and is not included in the integration of the affected population size. Therefore, the sound barrier effect of building shielding and the noise exposure of the shielding building itself are calculated separately. There is no situation where the cost of sacrificing the sound environment of the shielding building itself in exchange for a reduction in disturbance to sensitive targets behind it is not taken into account.

[0027] For cases where the propagation path is blocked by a building, the attenuation of the blade diffraction barrier is calculated using the following formula: ,in: , where is the attenuation of the blade diffraction barrier, and is a scalar with a value ranging from 0 to 30, in dB. It is calculated by this formula and characterizes the additional propagation attenuation caused by the sound wave bypassing the edge of the roof of the shielding building. The Fresnel number is a scalar with a value ranging from 0 to 50. It is dimensionless and is calculated by the second equation of this formula. It represents the multiple of the diffraction range difference relative to the wavelength of the sound wave. Where is the wavelength of the sound wave, and is a scalar quantity with a value ranging from 0.017 to 6.8, and the unit is meters (m). It is determined by the frequency of the sound wave according to... It is determined by dividing the speed of sound by the frequency, and represents the wavelength of the sound wave in the calculated frequency band; The distance from the sound source to the ray around the roof of the shielding building is a scalar with a value ranging from 1 to 5000 in meters. It is determined by the coordinates of the sound source and the coordinates of the ray around the roof and represents the length of the first segment of the diffraction path. The distance from the building roof to the sensitive target is a scalar value ranging from 1 to 5000, in meters. It is determined by the coordinates of the roof ray and the sensitive target, and represents the length of the latter part of the diffraction path. The straight-line distance from the sound source to the sensitive target is a scalar value ranging from 1 to 5000, with units of meters. It is determined by the coordinates of the sound source and the sensitive target, and represents the length of the direct path between the sound source and the sensitive target. The roof ray is the edge of the building top that blocks the line of sight between the sound source and the sensitive target. The definition is the same as the formula mentioned above.

[0028] The received sound pressure level at the sensitive target is obtained by subtracting the sum of geometric diffusion attenuation, air absorption, and blade diffraction barrier attenuation from the take-off and landing sound source intensity in step S2. The received sound pressure level is calculated for each sensitive target within the surrounding area of ​​the candidate take-off and landing point, thus constructing a noise exposure distribution covering the surrounding area with the candidate take-off and landing point as the sound source. This noise exposure distribution serves as the input for the subsequent step S4 to estimate the size of the disturbed population.

[0029] Step S4: Based on the noise exposure distribution and the population distribution at the sensitive target, estimate the size of the disturbed population at each candidate take-off and landing point under a preset number of take-offs and landings.

[0030] The process for this step is as follows: Figure 4 As shown. The noise exposure distribution constructed in step S3 is the received sound pressure level projected from the candidate take-off and landing point to the sensitive target under a given operating condition. However, during a single take-off and landing, the eVTOL sequentially experiences five operating conditions: takeoff, hovering, climb, approach, and landing. The vertical height of the sound source varies with the operating condition, and the climb and approach operating conditions proceed along inclined climb and approach profiles, while the sound source also shifts horizontally. This results in the obstruction of the line of sight between the sound source and the sensitive target by the shielding building not being constant under different operating conditions. Ignoring this point and either including or omitting the attenuation of the razor beam diffraction barrier in all operating conditions will either overestimate or underestimate the degree of disturbance to the shielded candidate take-off and landing point. Therefore, this step first determines the sound source height trajectory according to the operating conditions and judges the shielding effectiveness of the roof diffraction line in each operating condition segment. Then, the sound pressure levels of each operating condition segment are accumulated in the sound energy domain to obtain the equivalent sound pressure level, and finally, the disturbed population is integrated.

[0031] The vertical height trajectory of the sound source was determined according to the takeoff, hovering, climb, approach, and landing conditions. The effectiveness of the sound source's obstruction relative to the roof of the shielding building was then assessed for each condition. During the near-landing platform phase of the hovering, takeoff, and landing conditions (i.e., the initial liftoff phase of takeoff and the final touchdown phase of landing), the sound source was at a relatively low altitude, mostly below the roof's ray, and obstruction was effective. However, during the climb condition, the sound source rose along the climb profile. Once it passed the roof height of the shielding building, the line of sight between the sound source and the sensitive target was no longer blocked by the building, and obstruction failed, with direct sound dominating. The approach condition was the opposite of the climb condition; the sound source descended along the approach profile from above the roof height of the shielding building. Obstruction failed and direct sound dominated until it reached that roof height, after which obstruction became effective again. It should be noted that both the climbing profile and the approach profile are inclined profiles. In addition to the vertical height change, the sound source also undergoes horizontal displacement during the climbing and approach conditions. Therefore, for these two conditions, the horizontal distance from the sound source to the shielding building and the horizontal distance from the sound source to the sensitive target are taken segment by segment according to the plane coordinates of the representative position of the sound source in each condition segment. The representative position of the sound source is obtained by offsetting the plane coordinates of the take-off and landing platform along the horizontal projection direction of the climbing or approach profile. The offset is equal to the ratio of the change in sound source height in that condition segment to the tangent of the profile inclination angle. As a simplified implementation, when the inclination angle between the climbing profile and the approach profile is not less than 60 degrees, the horizontal displacement of the sound source within a single working condition segment is less than 0.58 times its height change. In this case, the horizontal displacement can be ignored, and the planar coordinates of the take-off and landing platform can be directly used as the representative position of the sound source for each working condition segment in the climbing and approach conditions. However, when the inclination angle is less than 60 degrees, ignoring the horizontal displacement will cause a deviation in the determination of the shielding effectiveness, and the horizontal displacement should be included in each working condition segment according to the aforementioned offset. The effectiveness of occlusion in each working condition segment is determined by the following formula: , in: For the first The shielding effectiveness indicator for each working condition segment is a scalar, taking a value of 0 or 1, dimensionless, and calculated by this formula. Taking 1 indicates that the shielding of the working condition segment is effective and takes into account the attenuation of the blade diffraction barrier. Taking 0 indicates that the shielding of the working condition segment is ineffective and takes into account the direct sound. It indicates whether the shielding of the building for the sound source of the working condition segment is effective. For the first The height of the sound source in each working condition section is a scalar with a value range of 0 to 600 and a unit of m. It is determined by the value of the sound source height trajectory in that working condition section, that is, the height of the representative position of the sound source in that working condition section is taken, which represents the height of the sound source relative to the ground in that working condition section. The height of the receiving point of the sensitive target is a scalar with a value ranging from 0 to 300, and the unit is m. It is determined by the sound receiving position of the sensitive target and represents the height of the receiving point of the sensitive target relative to the ground. The height of the shading building is a scalar with a value ranging from 3 to 600, and the unit is m. It is determined by the building height of the shading building in the three-dimensional building data and represents the height of the roof relative to the ground around the ray. The horizontal distance from the sound source to the shielding building is a scalar value ranging from 1 to 5000, with the unit being m. It is determined by the planar coordinates of the sound source and the shielding building. For climbing and approach conditions, it is determined by the planar coordinates of the representative position of the sound source in that condition segment. It represents the horizontal projected distance from the sound source to the shielding building. The horizontal distance from the sound source to the sensitive target is a scalar with a value ranging from 1 to 5000, and the unit is m. It is determined by the planar coordinates of the sound source and the sensitive target. For climbing and approach conditions, it is determined by the planar coordinates of the position of the sound source in that condition segment. It represents the horizontal projected distance from the sound source to the sensitive target. The definition is the same as the formula mentioned above.

[0032] After determining the effectiveness of the shielding in each operating condition segment, the sound pressure level received by the sensitive target in each operating condition segment is converted to the sound energy domain and accumulated according to the exposure time weight of each operating condition segment, and then converted to the equivalent sound pressure level. The reason for accumulating in the sound energy domain instead of directly averaging the sound pressure level is that the sound pressure level is logarithmic, and the sound pressure level across operating conditions and across sorties cannot be linearly averaged. It is necessary to first convert the sound pressure level into sound energy according to the exposure time weight of each operating condition segment before accumulating. The equivalent sound pressure level of the sensitive target is calculated by the following formula: , , in: For sensitive targets The equivalent sound pressure level, a scalar value ranging from 20 to 100, is expressed in dB and is calculated using the first equation of this formula. It characterizes the sensitive target. The equivalent noise exposure level after summing up the noise levels across all operating conditions during a single takeoff and landing; The total exposure time for a single flight is a scalar quantity, ranging from 10 to 600, measured in seconds (s). It is determined by the sum of the exposure times for each operating condition segment. equal to each The sum represents the total duration of a single takeoff and landing process; For the first The exposure duration of each operating condition segment is a scalar value ranging from 1 to 300, with the unit being seconds. It is determined by the duration of the operating condition segment, i.e., the weight of the exposure duration of the operating condition segment, which represents the time share of the operating condition segment in the total exposure duration. Let be the number of the summation for the operating condition segment, and be a scalar with a value range of 1 to 1. , dimensionless, represents the currently accumulated working condition segment; is the total number of operational segments, is a scalar with a value of 5, dimensionless, determined by the operational segment division, and represents the five operational segments of takeoff, hovering, climb, approach and landing. For sensitive targets In the The sound pressure level received in each working condition section is a scalar with a value range of 20 to 110 and a unit of dB. It is calculated by the second formula and represents the received sound pressure level at the sensitive target in that working condition section. For geometric diffusion attenuation, is a scalar with a value range of 0 to 80, and the unit is dB. It is determined by the spherical diffusion of the point sound source according to the propagation distance and characterizes the attenuation of the sound wave as it spreads with the propagation distance. For air absorption, it is a scalar quantity with a value range of 0 to 50, and the unit is dB. It is determined by the air absorption coefficient and the propagation distance, and characterizes the attenuation caused by the absorption of the propagation medium. , , The definition is the same as the aforementioned formula; The definition is the same as the formula mentioned above.

[0033] The affected population size is obtained by integrating the population covered by sensitive targets whose equivalent sound pressure level exceeds a preset disturbance threshold. The affected population size is calculated using the following formula under a preset number of takeoffs and landings: ,in: , where is the size of the disturbed population, is a scalar with a value range of 0 to 1,000,000, and is in human units. It is calculated by this formula and represents the total size of the disturbed population generated by the candidate take-off and landing point for all sensitive targets under the preset number of take-off and landing flights. The correlation coefficient of the preset take-off and landing flights is a scalar with a value ranging from 1 to 1000. It is dimensionless and is determined by the weighted average of the preset take-off and landing flights with the exposure frequency. It characterizes the amplification effect of the take-off and landing flights on the scale of the disturbance. Let be the index of the sensitive target summation, and be a scalar with a value range of 1 to 1. , dimensionless, represents the sensitive target of the current integration; The total number of sensitive targets is a scalar with a value ranging from 1 to 100,000. It is dimensionless and is determined by the distribution of sensitive targets obtained in step S1. It represents the number of sensitive targets within the surrounding plots. For sensitive targets The population density at a location is a scalar quantity, ranging from 0 to 200,000, and is expressed in units of people per square kilometer (people / km²). 2 The population distribution obtained in step S1 is used to determine the population density within the coverage area of ​​the sensitive target. For sensitive targets The coverage area is a scalar, ranging from 0 to 100, and the unit is km².2 It is determined by the coverage range of the sensitive target and characterizes the spatial coverage area of ​​the sensitive target; This is an indicator function that takes the value 1 when the condition in parentheses is true and 0 otherwise. It is dimensionless and represents whether the sensitive target is determined to be disturbed. The preset disturbance threshold is a scalar value ranging from 40 to 70 dB, determined by the acoustic environment functional zone standard. It represents the equivalent sound pressure level threshold for determining whether a sensitive target is disturbed. If the value is too high, it will miss the actual disturbed sensitive targets; if the value is too low, it will include the disturbed sensitive targets. In this embodiment, the value is 55 dB during the day and 45 dB at night in residential areas. The definition is the same as the formula mentioned above.

[0034] At this point, each candidate take-off and landing point obtains the size of the population affected by sensitive targets under the preset number of take-offs and landings, which serves as the cost term input for the subsequent step S5 multi-target optimization.

[0035] Step S5: Using the size of the affected population as a cost term, together with passenger accessibility, airspace availability, and ground connection convenience, a multi-objective site selection model is formed. The passenger accessibility, airspace availability, and ground connection convenience are normalized and weighted to form the operational efficiency. The non-dominated solution set between the operational efficiency and the size of the affected population is obtained through multi-objective optimization, and the comprehensive site selection score and ranking of each candidate take-off and landing point are output.

[0036] The process for this step is as follows: Figure 5As shown. The affected population size obtained in step S4 is used as a cost term, which, together with passenger accessibility, airspace availability, and ground connection convenience, constitutes a multi-objective site selection model. Passenger accessibility is assessed based on the distribution of travel demand within the service area of ​​the candidate take-off and landing point; the greater the travel demand within the service area, the higher the accessibility. Airspace availability is assessed based on the airspace control constraints and route capacity of the candidate take-off and landing point; the fewer the airspace control constraints and the larger the route capacity, the higher the airspace availability. Ground connection convenience is assessed based on the connection distance and connection method from the candidate take-off and landing point to rail transit stations and main roads; the shorter the connection distance and the more convenient the connection method, the higher the ground connection convenience. These three indicators are normalized and weighted to form the comprehensive operational efficiency value of the candidate take-off and landing point. These are all known evaluation indicators in the field, determined by the travel demand, airspace control, and network connection data obtained in step S1. A higher comprehensive operational efficiency value indicates better overall operational conditions for the candidate take-off and landing point in terms of passenger flow, airspace, and connections. It should be noted that passenger accessibility and ground connection convenience are not overlapping indicators. Passenger accessibility, taken from the demand side, measures the total travel demand covered by the service area of ​​the candidate take-off and landing point. It varies with the increase or decrease of travel demand within the service area and is unrelated to whether the candidate take-off and landing point is adjacent to a rail transit station. Ground connection convenience, taken from the supply side, measures the transfer cost for travelers to reach the candidate take-off and landing point from the ground transportation network. It varies with the connection distance and connection method and is unrelated to the total travel demand within the service area of ​​the candidate take-off and landing point. A candidate take-off and landing point located in a high-demand area but far from a rail transit station has high passenger accessibility but low ground connection convenience; a candidate take-off and landing point adjacent to a rail transit station but located in a sparse-demand area has high ground connection convenience but low passenger accessibility. The two indicators have opposite values ​​for the two types of candidate take-off and landing points and therefore cannot be substituted for each other. It should also be noted that passenger accessibility, airspace availability, and ground connection convenience have different dimensions. Travel demand is measured in passenger trips, airway capacity in flight trips per hour, and connection distance in meters. These three cannot be directly weighted and summed. Therefore, they must first be normalized to dimensionless values ​​from 0 to 1 before being weighted and combined to obtain operational efficiency. After this normalization and weighting, the target space of the multi-objective location model is spanned by only two coordinate axes: operational efficiency and the size of the affected population. The multi-objective optimization is to find a non-dominated solution set between these two conflicting objectives, rather than finding a non-dominated solution set between the four objectives of passenger accessibility, airspace availability, ground connection convenience, and the size of the affected population.

[0037] The non-dominated solution set between operational efficiency and the size of the disturbed population is obtained through multi-objective optimization. This multi-objective optimization seeks a non-dominated solution set between two conflicting objectives: operational efficiency and the size of the disturbed population. Higher operational efficiency and a smaller disturbed population size are preferred. Obtaining the non-dominated solution set can be achieved using multi-objective evolutionary optimization known in the art. The key to this invention is that the size of the disturbed population exhibits a non-convex distribution due to the inversion effect of building obstruction and diffraction with the candidate take-off and landing point positions. That is, a candidate take-off and landing point obstructed by tall buildings, even if close to the sensitive target, has a smaller disturbed population size than a candidate take-off and landing point further away but located on an open, direct sound path. These obstructed candidate take-off and landing points are located in the non-convex leading edge region within the objective space formed by the disturbed population size and operational efficiency. If a weighted summation method is used to linearly merge the two objectives into a single objective, only candidate take-off and landing points located at the vertices of the convex hull will be selected, while obstructed candidate take-off and landing points located in the non-convex leading edge region will be missed. Therefore, this invention constructs a set of non-dominated solutions using the size of the disturbed population as one coordinate axis and operational efficiency as another. When the size of the disturbed population follows a non-convex distribution with respect to the candidate take-off and landing point locations, the non-dominated solutions formed by candidate take-off and landing points blocked by obstructed buildings are retained. Whether a candidate take-off and landing point is a non-dominated solution is determined by the following formula: , in: is the set of non-dominated solutions, and is a set whose elements are the numbers of candidate take-off and landing points. It is dimensionless and is determined by this formula. It represents the set of candidate take-off and landing points that are not mutually dominated under the two objectives of operational efficiency and the size of the disturbed population. The candidate take-off and landing point number to be determined is a scalar, ranging from 1 to the total number of candidate take-off and landing points. It is dimensionless and represents the candidate take-off and landing point currently being determined. The other candidate take-off and landing points are numbered; this is a scalar, with a value ranging from 1 to the total number of candidate take-off and landing points and not equal to 1. , dimensionless, characterizing other candidate takeoff and landing points used for comparison; Candidate take-off and landing points The overall operational efficiency value is a scalar, ranging from 0 to 1, dimensionless, and is obtained by normalized weighting of passenger accessibility, airspace availability, and ground connection convenience, representing the candidate take-off and landing points. operational efficiency; Candidate take-off and landing points The overall operational efficiency value is a scalar, ranging from 0 to 1, dimensionless, and has the same meaning as... Characterizing candidate take-off and landing points operational efficiency; Candidate take-off and landing points The size of the affected population, a scalar value ranging from 0 to 1,000,000 (in people), is calculated in step S4 and represents the candidate take-off and landing points. The noise cost; Candidate take-off and landing points The size of the affected population is a scalar, ranging from 0 to 1,000,000, with the unit being people, and has the same meaning as... Characterizing candidate take-off and landing points The noise cost; This indicates that it does not exist. This represents logical AND. This represents a logical OR. The above expression indicates that if no other candidate takeoff and landing point exists... Operating efficiency is no less than And the size of the affected population is no higher than and strictly superior to at least one objective Then the candidate take-off and landing points This is a non-dominated solution. In terms of dimensions, operational efficiency... Dimensionless, size of the affected population The unit is a person, and comparison operations are performed between quantities of the same kind. The determination result is the set affiliation of a dimensionless entity.

[0038] After obtaining the non-dominated solution set, a comprehensive site selection score is given to the candidate take-off and landing points in the non-dominated solution set according to the relative importance of operational efficiency and the size of the affected population. The candidate take-off and landing points are then ranked according to the comprehensive site selection score, and the comprehensive site selection score and ranking of each candidate take-off and landing point are output. In this embodiment, several candidate take-off and landing points that are blocked by high-rise buildings are included in the non-dominated solution set because the size of the affected population is significantly lower than that of open candidate take-off and landing points. These become recommended sites that take into account both operational efficiency and acoustic environment impact. In the existing scheme that uses weighted summation, these blocked candidate take-off and landing points would be directly excluded because they are close to sensitive targets.

[0039] Step S6, collaborative optimization when candidate take-off and landing points form a multi-point network layout, see Example 2.

[0040] Example 2: Coordinated optimization of take-off and landing points in a multi-point networking scenario.

[0041] This embodiment, based on Embodiment 1, illustrates the collaborative optimization process of take-off and landing points in a multi-point network scenario for urban air traffic. In a multi-point network scenario, multiple take-off and landing points need to be selected simultaneously within the area to be evaluated to form a network to cover different travel corridors. At this time, the take-off and landing points are no longer independent of each other: on the one hand, the air routes between different take-off and landing points may overlap in the airspace; on the other hand, the noise exposure distribution generated by multiple take-off and landing points at the same sensitive target will be superimposed at that sensitive target. Therefore, even after a group of take-off and landing points that meet the standards are combined into a network, they may still exceed the standard due to noise superposition at the shared sensitive target, resulting in a situation where a single point is optimal but the overall noise superposition exceeds the standard.

[0042] Therefore, when forming a multi-point network layout for candidate take-off and landing points, the overlapping airspace routes of multiple take-off and landing points, as well as the superposition of the acoustic energy domains of noise exposure distribution at shared sensitive targets, are used as coupling constraints. The scale of the disturbed population at each take-off and landing point is coupled through the superposition of shared sensitive targets to collaboratively optimize the multi-point network layout. The network superposition equivalent sound pressure level at shared sensitive targets is calculated using the following formula: , in: To share sensitive targets The network superposition equivalent sound pressure level at the location is a scalar, ranging from 20 to 110 dB, and is calculated using this formula. It characterizes the area of ​​multiple takeoff and landing points sharing a sensitive target. The equivalent noise exposure level after superposition; The set of take-off and landing points selected for the multi-point network layout is a set whose elements are take-off and landing point numbers, which are dimensionless and determined by the network optimization, representing the take-off and landing points participating in the network. The take-off and landing point number in the network is a scalar with a value range from 1 to the total number of take-off and landing points in the network. It is dimensionless and represents the currently superimposed take-off and landing point. Take-off and landing points For shared sensitive targets The equivalent sound pressure level is a scalar, ranging from 20 to 100, and is expressed in dB. It is determined by step S4 based on the take-off and landing points. The calculations show that the takeoff and landing points are represented. Acting alone on shared sensitive targets Noise exposure level; To share sensitive target numbers, the meaning is the same as in the aforementioned formula; The definition is the same as the formula mentioned above.

[0043] The route overlap is determined based on the spatial relationship of routes between takeoff and landing points in the airspace. When the arrival and departure routes of two takeoff and landing points overlap in the same airspace corridor, they occupy the same airspace capacity and mutually restrict operational intervals, thereby reducing the overall operational efficiency of the network. At the same time, the noise from eVTOLs on the overlapping routes will also be superimposed on sensitive targets below that airspace segment. Therefore, this invention uses route overlap as a measure of airspace coupling constraints. The route overlap is determined based on the degree of overlap of routes at each takeoff and landing point in the airspace corridor; the higher the overlap, the greater the route overlap.

[0044] The noise coupling constraint is set at the network superposition equivalent sound pressure level not exceeding a preset disturbance threshold, and the airspace coupling constraint is set at the route overlap degree not exceeding a preset overlap threshold. Under the premise of satisfying these two coupling constraints, the goal is to minimize the sum of the disturbed population sizes of all take-off and landing points within the network. The noise coupling constraint couples the noise exposure distribution of each take-off and landing point at the shared sensitive target through sound energy domain superposition, and the airspace coupling constraint couples the arrival and departure routes of each take-off and landing point through route overlap. The combined effect of these two coupling constraints ensures that network optimization cannot be obtained by simply merging the results of individual optimization of each take-off and landing point. Since the network superposition equivalent sound pressure level at the shared sensitive target is obtained by superimposing the equivalent sound pressure levels of all take-off and landing points in the network in the sound energy domain, changing the selection of any take-off or landing point in the network will change the disturbance determination of the remaining take-off and landing points through the shared sensitive target. Therefore, the disturbed population sizes of each take-off and landing point are mutually coupled through the shared sensitive target, and the network layout cannot be obtained by simply merging the results of individual optimization of each take-off and landing point. In this embodiment, two candidate take-off and landing points whose disturbed population size is below the threshold when evaluated individually are not selected into the network at the same time because their noise exposure distribution exceeds the disturbance threshold when superimposed in a certain shared residential area. Instead, the collaborative optimization selects a combination of take-off and landing points whose noise exposure distribution does not superimpose in the same sensitive target, thereby ensuring network coverage while avoiding the overall noise superposition exceeding the standard.

[0045] To illustrate the effect of this invention in taking into account building obstruction and diffraction, two candidate take-off and landing points within the area to be evaluated are compared as examples. The first candidate take-off and landing point is 320m horizontally away from a residential area, and there are no tall buildings obstructing it between it and the residential area, so there is an open and direct sound path between the sound source and the sensitive target. The second candidate take-off and landing point is 180m horizontally away from the residential area, but there is a 90m high obstructing building between it and the residential area, which blocks the direct line of sight between the sound source and the sensitive target.

[0046] In existing site selection methods that treat noise as a static point attribute, the noise cost monotonically decreases with distance. Second-choice takeoff and landing points, being closer to residential areas, are judged to have a greater noise impact, thus ranking them lower than the first-choice takeoff and landing point, or even being directly excluded. However, in the method of this invention, for the second-choice takeoff and landing point, the direct line of sight between the sound source and the residential area is blocked by a 90m-high obstructing building. During hovering, the initial stage of takeoff, and the final stage before touchdown in landing, the sound source height is below the roof's diffraction line, and the obstruction effectiveness indicator is set to 1. The attenuation from the blade-like diffraction barrier is taken into account, and the additional attenuation from diffraction significantly reduces the received sound pressure level in the residential area during this phase. During the climb phase, after the sound source crosses the 90m roof height, and during the approach phase, before the sound source descends to the 90m roof height, the obstruction effectiveness indicator is set to 0, and the direct sound is taken into account. After the sound energy domain is accumulated, the equivalent sound pressure level of the second candidate take-off and landing point in the residential area is lower than that of the first candidate take-off and landing point in the same residential area, and the affected population size is also correspondingly smaller than that of the first candidate take-off and landing point. Therefore, this invention determines the shielded second candidate take-off and landing point as the site with less noise impact, contrary to the judgment given by existing methods. This comparative example shows that ignoring building obstruction and diffraction will lead to a reversed judgment on the merits of candidate take-off and landing points, while this invention, by taking into account building obstruction and diffraction and determining the effectiveness of obstruction in each operating condition segment, obtains the affected population size consistent with the actual sound propagation, avoiding repeated site selection.

[0047] Those skilled in the art should understand that the specific values ​​in the above embodiments are merely examples, and the method of the present invention can be applied to different urban air traffic areas and different aircraft types' eVTOL. In addition to being divided according to takeoff, hovering, climb, approach, and landing conditions, the acoustic power characteristics can be further subdivided into condition segments based on the measured acoustic power data of the aircraft type. The total number of condition segments can be adjusted accordingly, and the acoustic energy domain accumulation holds true for any number of condition segments. Residential areas, schools, and hospitals in the sensitive target distribution can be assigned different disturbance weights, and population distribution can be determined separately for daytime and nighttime periods. The size of the disturbed population is obtained by weighting the disturbance weights by time period, reflecting the different sensitivities of schools to noise during teaching hours, hospitals throughout the day, and the more stringent disturbance threshold at night. It should be noted that urban air traffic takeoffs and landings are mainly during the daytime, while nighttime periods typically only retain operational needs such as medical transport, emergency rescue, and logistics freight. Therefore, the preset takeoff and landing times are also set separately for daytime and nighttime periods. For candidate take-off and landing points that operate only during daytime hours, the preset number of take-offs and landings during nighttime hours is set to 0, and the corresponding nighttime affected population size is also 0, requiring no further processing. For candidate take-off and landing points with nighttime operation requirements, since the nighttime disturbance threshold is 10 dB lower than the daytime threshold, the same noise exposure distribution will result in a larger affected population size at night. In this case, taking values ​​for different time periods can avoid underestimating the affected population by using the daytime threshold to evaluate nighttime operations. The air absorption coefficient can be taken based on an ambient temperature of 25°C and a relative humidity of 70%, or it can be taken based on meteorological statistics of the area to be evaluated according to different seasons and time periods.

[0048] In the output stage, the present invention can also overlay the influence range of noise exposure distribution of each candidate take-off and landing point and the comprehensive site selection score on a map, and output the recommended order of the candidate take-off and landing points in order of sorting, thereby intuitively presenting the noise influence range and site selection score of each candidate take-off and landing point, providing a quantitative basis for site selection decisions for urban air traffic infrastructure planners.

[0049] In summary, this invention uses candidate take-off and landing points as sound sources, reconstructs the noise diffraction propagation process towards sensitive targets by building shielding under different operating conditions, determines the shielding effectiveness of roof diffraction rays for each operating condition segment, accumulates the equivalent sound pressure level in the sound energy domain and integrates the affected population size, incorporates the affected population size as a cost term into multi-objective optimization to obtain a non-dominated solution set between the operational efficiency and the affected population size, and uses the superposition of the sound energy domain of noise exposure distribution as a coupling constraint to collaboratively optimize the layout of take-off and landing points during network construction. This achieves the quantitative minimization of noise disturbance while taking into account the operational efficiency, which is a normalized weighted combination of passenger accessibility, airspace availability and ground connection convenience, providing a quantitative basis for the compliant implementation of urban air traffic infrastructure.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent location selection method for eVTOL take-off and landing points considering noise propagation, characterized in that, include: Acquire candidate take-off and landing points, geographic data, three-dimensional building data, and the distribution of sensitive targets within the urban air traffic area. The sensitive targets are residential areas, schools, or hospitals. Using each candidate take-off and landing point as a sound source, the intensity of the take-off and landing sound source at each candidate take-off and landing point is determined based on the sound power characteristics of eVTOL under take-off, hovering, climb, approach and landing conditions. Along the propagation path from the candidate take-off and landing point to the sensitive target, taking into account geometric diffusion attenuation, air absorption, and building occlusion diffraction based on the building's three-dimensional data, a noise exposure distribution covering the surrounding plot is constructed. Based on the noise exposure distribution and the population distribution at the sensitive target, estimate the size of the affected population at each candidate take-off and landing point under a preset number of take-offs and landings. Using the size of the affected population as a cost term, together with passenger accessibility, airspace availability, and ground connection convenience, a multi-objective site selection model is formed. The passenger accessibility, airspace availability, and ground connection convenience are normalized and weighted to form the operational efficiency. The non-dominated solution set between the operational efficiency and the size of the affected population is obtained through multi-objective optimization, and the comprehensive site selection score and ranking of each candidate take-off and landing point are output.

2. The method according to claim 1, characterized in that, The building obstruction diffraction includes: determining the obstruction of the line of sight between the sound source and the sensitive target by the obstructing building on the propagation path based on the three-dimensional data of the building, and incorporating the propagation path of the obstructed line of sight into the attenuation of the blade diffraction barrier, so that the candidate take-off and landing points obstructed by the obstructed building are less disturbed than the candidate take-off and landing points that are not obstructed.

3. The method according to claim 2, characterized in that, The inclusion of the blade-edge diffraction barrier attenuation includes: determining the sound source height trajectory along the vertical direction according to the takeoff, hovering, climbing, approach, and landing conditions. The sound source height trajectory is the vertical component of the sound source's three-dimensional motion trajectory. The effectiveness of the sound source's obstruction of the roof diffraction rays relative to the shielding building is determined for each condition segment. Only the conditions with effective obstruction are included in the blade-edge diffraction barrier attenuation, while the conditions with ineffective obstruction are included in the direct sound, thus obtaining the condition segment exposure time weights for the sensitive target.

4. The method according to claim 3, characterized in that, Estimating the size of the affected population includes: converting the sound pressure level received by the sensitive target in each operating condition segment to the sound energy domain according to the exposure time weight of the operating condition segment, and then converting it to the equivalent sound pressure level; integrating the population covered by the sensitive target whose equivalent sound pressure level exceeds the preset disturbance threshold to obtain the size of the affected population.

5. The method according to claim 4, characterized in that, The process of obtaining a non-dominated solution set through multi-objective optimization includes: constructing a non-dominated solution set with the size of the disturbed population as one coordinate axis and the operational efficiency as another coordinate axis; and retaining the non-dominated solution formed by the candidate take-off and landing points that are blocked by the obstructed buildings when the size of the disturbed population is non-convex with respect to the candidate take-off and landing point locations.

6. The method according to claim 5, characterized in that, When the candidate take-off and landing points form a multi-point network layout, the overlapping of airspace routes of multiple take-off and landing points and the superposition of acoustic energy domains of noise exposure distribution of multiple take-off and landing points at shared sensitive targets are used as coupling constraints. The scale of the disturbed population of each take-off and landing point is coupled through the superposition of the shared sensitive targets to collaboratively optimize the multi-point network layout.

7. The method according to claim 1, characterized in that, The acoustic power characteristics include the acoustic power level and directivity of each of the takeoff, hovering, climbing, approach, and landing conditions. The directivity is used to describe the distribution of the intensity of the takeoff and landing sound source with respect to the direction angle of the propagation path.

8. The method according to claim 1, characterized in that, The air absorption is determined by frequency band, and the geometric diffusion attenuation, the air absorption coefficient corresponding to the frequency band, and the propagation distance of the propagation path are related. The air absorption coefficient is determined by ambient temperature and relative humidity.

9. The method according to claim 1, characterized in that, Residential areas, schools, and hospitals in the sensitive target distribution are assigned different disturbance weights, and the preset take-off and landing numbers and the population distribution are both taken according to daytime and nighttime periods respectively. The size of the disturbed population is obtained by weighting the disturbance weights with the time periods.

10. The method according to claim 1, characterized in that, Also includes: The influence range of the noise exposure distribution of each candidate take-off and landing point is overlaid on the map with the comprehensive site selection score, and the recommended order of the candidate take-off and landing points is output according to the sorting.

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