A Travel Route Optimization Method and System Based on Cumulative Thermal Stress

Abstract

The present invention discloses a travel route optimization method and system based on cumulative thermal stress. The regional thermal environment is simulated according to regional basic data to obtain regional thermal environment data; all travel routes are determined, and the thermal environment data of each travel route is obtained; the travelable routes that meet the set requirements are screened out; the cumulative thermal stress of each travelable route is calculated, and the route with the minimum cumulative thermal stress is selected as the optimal travel route. The present invention provides a travel route optimization method and system based on cumulative thermal stress to solve the problem in the prior art that there is a lack of enabling travelers to adapt to the urban thermal environment orderly according to their subjective consciousness, and to achieve the purpose of providing adaptive guidance measures for outdoor activities of urban residents, supporting residents' travel, reducing thermal effects and thermal hazards.

Description

Technical Field

[0001] The present invention relates to the field of research on the thermal environment of outdoor activities, and particularly to a travel route optimization method and system based on cumulative heat stress. Background Art

[0002] Currently, in response to urban high-temperature heatwaves and the urban heat island effect, existing research mainly focuses on aspects such as urban heat impact assessment, the formation and driving factors of the urban heat island, and urban high-temperature mitigation technologies and strategies. Although urban high-temperature mitigation technologies and strategies can alleviate urban heat problems, they have not been widely promoted and applied, resulting in residents still being severely affected by urban heat and suffering from heat hazards during outdoor activities and daily travel. At the same time, urban space is heterogeneous, and the urban heat problems and the degree of harm vary in different communities and streets. Therefore, it is particularly important to make a refined judgment on urban heat problems.

[0003] Existing decision-making systems related to the urban thermal environment mainly serve government departments, planners and designers, and related industries, and are used to explore different urban heat island effect mitigation technologies, providing support for the planning and design of resilient cities and healthy cities. However, in response to urban heat problems, not only heat island effect mitigation technologies are needed, but people also need to take corresponding strategies for active adaptation. At present, the adaptive decision-making system that serves people and targets urban heat problems has not been taken seriously, and there is a lack of a decision-making method that combines people's orderly, conscious, and subjective urban heat adaptation. Summary of the Invention

[0004] The present invention provides a travel route optimization method and system based on cumulative heat stress to solve the problem in the prior art that there is a lack of enabling travelers to adapt to the urban thermal environment orderly according to their subjective consciousness, and to achieve the purpose of providing adaptive guidance measures for urban residents' outdoor activities, supporting residents' travel, and reducing heat impact and heat hazards.

[0005] The present invention is achieved through the following technical solutions:

[0006] A travel route optimization method based on cumulative heat stress, comprising:

[0007] Simulating the regional thermal environment based on regional basic data to obtain regional thermal environment data;

[0008] Determining all travel routes and obtaining the thermal environment data of each travel route;

[0009] Screening out the travelable routes that meet the set requirements;

[0010] Calculating the cumulative heat stress of each travelable route, and selecting the route with the minimum cumulative heat stress as the optimal travel route.

[0011] In view of the problem in the prior art that there is a lack of a method for allowing travelers to adapt to the urban thermal environment in an orderly manner according to their subjective awareness, the present invention first proposes an optimized travel route method based on cumulative heat stress. This method first obtains regional basic data according to the research area, simulates the regional thermal environment, and obtains the thermal environment data within the area. Then, according to the travel plans of residents, all travel routes are determined, and based on the aforementioned regional thermal environment data, the thermal environment data corresponding to each travel route is obtained. Then, according to the thermal environment data of each travel route, route screening is carried out to obtain feasible travel routes. Among them, the setting requirements for screening are not specifically limited here and can be adaptively set according to differences such as user type, travel mode, and activity intensity, so as to best meet the relevant indicators of human thermal comfort. Finally, the cumulative heat stress of each feasible travel route is calculated, and the route with the minimum cumulative heat stress is selected as the optimal travel route. When residents travel along the optimal travel route, they can reach their destinations under the least thermal impact and thermal hazard, thereby achieving the purpose of providing outdoor activity guidance measures for urban residents in this application and effectively supporting the safe travel of residents in hot weather.

[0012] It can be seen that this method: (1) can quickly and finely identify the thermal environment problems in the outdoor activity areas of residents, analyze the dynamic changes of urban microclimate and thermal comfort from the perspective of adaptability, evaluate their thermal impacts and hazards on residents' health, outdoor activities and travel; and intelligently propose adaptive guidance measures to support the regulation of residents' travel and outdoor activity patterns, which is conducive to protecting residents' health, reducing the thermal impacts and hazards on residents' travel and outdoor activities, promoting the development of low-carbon smart cities, and providing effective support for coping with climate change; (2) different from the traditional research on evaluating thermal impacts based on microclimate and thermal comfort indicators, this method comprehensively considers the community space microclimate, thermal comfort, and community travel demand, analyzes the thermal impacts and hazards within the community space; and further correlates the feedback of residents' adaptive behaviors to thermal impacts and hazards to establish a multi-objective outdoor thermal adaptation behavior evaluation model; (3) can start from the construction requirements of future communities, propose a set of intelligent and accurate urban thermal adaptation decision-making methods, in order to predict, evaluate and warn the thermal impacts and hazards of community streets, make real-time feedback for residents to adaptively reduce thermal impacts and hazards, and provide a scientific and reasonable decision-making basis.

[0013] Furthermore, the regional basic data includes meteorology, terrain, buildings, vegetation, water bodies and public facilities within the area. Through the above basic data, a sufficient basis can be provided for the subsequent modeling process. Among them, public facilities refer to facilities related to the thermal environment that can be understood by those skilled in the art and are used or enjoyed by the public, such as sunshades, artificial sprays, etc.

[0014] Further, the method for simulating the regional thermal environment includes: establishing a model based on regional basic data, verifying the accuracy of the model, simulating the regional thermal environment through the model, and obtaining regional thermal environment data.

[0015] This solution obtains the thermal environment data of the entire region through modeling, including parameters such as air temperature, mean radiant temperature, universal thermal climate index, etc. at all locations within the entire region, making full preparations for subsequent extraction of the thermal environment data of each travel path.

[0016] Further, the regional thermal environment data includes any one or more of the following: air temperature within the region, mean radiant temperature (MRT), universal thermal climate index (UTCI), physiological equivalent temperature (PET), standard effective temperature (SET), wet bulb globe temperature (WBGT), heat intensity index (HI).

[0017] Those skilled in the art can flexibly select any one or more of the above parameters according to actual needs as the criteria for screening travelable paths and / or calculating the cumulative heat stress of each travelable path.

[0018] Further, the method for obtaining the thermal environment data of each travel path includes:

[0019] Obtaining all travel paths based on the travel starting point and the travel ending point;

[0020] Importing the regional thermal environment data into the parametric software Rhino - Grasshopper to establish a data grid matching the model;

[0021] Drawing all travel paths in Rhino and using the Grasshopper plugin to obtain the thermal environment data of all travel paths.

[0022] Rhino - Grasshopper is an existing parametric optimization platform software. This application uses this software to directly read the data file containing the regional thermal environment data, and then simply and quickly builds the required platform.

[0023] This solution also establishes a data grid matching the model established in the previous step through Rhino - Grasshopper, and assigns the corresponding thermal environment data to each grid according to the regional thermal environment data, so that each grid has its own thermal environment value, providing a scientific and effective basis for subsequent simulation of paths based on the grid and extraction of their thermal environment data.

[0024] Further, the setting requirements are as follows: when walking along a certain path, the duration of continuous exposure of pedestrians to sunlight does not exceed a first set threshold, and the cumulative exposure duration of pedestrians to sunlight does not exceed a second set threshold; where the second set threshold is greater than the first set threshold.

[0025] As a common understanding in the art, it is generally believed that the shorter the travel path of people during high-temperature periods, the better the thermal comfort. Therefore, according to the setting requirements set according to common understanding, the path with a shorter distance should be directly used as the travelable path. However, the applicant in this case found during the research process that if the travel path is short but the continuous exposure time to direct sunlight is too long or the cumulative exposure time to sunlight is too long, then this thermal experience may lead to thermal discomfort and even heatstroke in severe cases.

[0026] Based on the above problems, this solution abandons the common understanding in the art, adopts the duration of continuous exposure to sunlight as the evaluation criterion for the setting requirements, and limits the duration of continuous exposure of pedestrians to sunlight not to exceed the first set threshold; if it exceeds the first set threshold, it is considered that this path does not meet the setting requirements and needs to be excluded. At the same time, it is limited that the cumulative exposure duration of pedestrians to sunlight does not exceed the second set threshold; if it exceeds the second set threshold, it is considered that this path does not meet the setting requirements and needs to be excluded.

[0027] Both the first set threshold and the second set threshold can be adaptively set and adjusted by those skilled in the art according to the tolerance of the travel personnel and the solar radiation intensity, and their specific values are not limited here.

[0028] In addition, since the continuous time of direct exposure to sunlight is difficult to intuitively reflect from the travel path, the thermal environment data of each travel path obtained in the foregoing steps can be used in this application to characterize it. A threshold range is set for one or more parameters in the thermal environment data. If the corresponding parameter does not meet its threshold range, it is considered to be exposed to sunlight; then, the continuous length and cumulative length when the one or more parameters in the travel path do not meet their threshold ranges can be used to respectively characterize the duration of continuous exposure of residents to sunlight and the cumulative exposure duration of residents to sunlight.

[0029] Of course, for residents of different ages and different travel modes, the travel distances corresponding to the first set threshold and the second set threshold may vary. Therefore, this method can also classify and take values for the path lengths used to characterize continuous exposure to sunlight according to population categories, activity types, travel modes, etc. The specific classification method is not limited here, and those skilled in the art can make adaptive settings according to the specific application environment of this application.

[0030] Further, the setting requirements are to meet any of the following conditions:

[0031] Condition 1: The average radiant temperature along the entire path is less than 50°C;

[0032] Condition 2: There is at least one section on the path where the average radiant temperature is greater than or equal to 50°C, and the length of each section is less than 45m. At the same time, the cumulative length of the path with an average radiant temperature greater than or equal to 50°C is less than 150m.

[0033] This solution considers the situation when healthy and normal adults travel on foot, so that the proposed setting requirements have better generality and a wider scope of application.

[0034] This solution uses the average radiant temperature (MRT) as the thermal environment data parameter to evaluate whether residents are directly exposed to sunlight. It has the advantage of being unaffected by humidity factors, can characterize the radiation effect of the surrounding environment on the human body, and most directly represents whether the human body is exposed to sunlight, with extremely strong practical application value. In addition, the threshold of the average radiant temperature is set at 50°C: below 50°C, it is considered that the human body is not directly exposed to sunlight; above or equal to 50°C, it is considered that the human body is directly exposed to sunlight. Whether the threshold of 50°C is selected to be lower or higher, the judgment error will be significantly increased.

[0035] In this solution, Condition 1 is used to indicate that there is no section on this path that is directly exposed to sunlight, so it obviously meets the setting requirements; Condition 2 is used to indicate that although there is a section on this path that is directly exposed to sunlight, for healthy and normal adults, the time taken to walk through this section is less than 30s; at the same time, the cumulative time taken to walk through all sections directly exposed to sunlight is less than 100s. Of course, if none of the travel paths meet either condition, then it is considered that it is not suitable to travel normally at this time, and corresponding reasonable suggestions can be put forward for users to subjectively and orderly reduce heat damage.

[0036] It can be seen that in the process of traveling during high-temperature periods in this application, the MRT value and path length are comprehensively considered to screen travelable paths, filling the gap in the prior art.

[0037] Of course, the method of using the average radiant temperature as an index to screen travelable paths given in this solution is only a preferred implementation manner. Those skilled in the art should understand that when screening travelable paths, other parameters in the aforementioned regional thermal environment data can also be used to formulate regional thermal environment thresholds or path length thresholds; and the specific threshold settings can be adjusted according to different human thermal comfort, health risks, and characteristics of travel personnel, such as age, health level, clothing situation, exercise mode, exercise speed, load situation, etc.

[0038] Furthermore, the cumulative heat stress of the travelable path is the cumulative value of the general thermal climate index on the path.

[0039] Different from the indoor thermal environment, the distribution of the outdoor thermal environment is extremely uneven. To fully evaluate the interference of the outdoor thermal environment on travelers, this solution uses the cumulative value of the Universal Thermal Climate Index (UTCI) on the path to characterize the cumulative thermal stress of each travelable path. Since the lengths of different travelable paths are different, the cumulative value method comprehensively considers the path length and thermal comfort parameters to comprehensively determine the optimal solution for the outdoor thermal comfort of users traveling in hot weather.

[0040] Among them, the specific calculation method of the Universal Thermal Climate Index (UTCI) belongs to the prior art. For example, through the UTCI official website and other means, it will not be elaborated here.

[0041] Of course, the method of using the cumulative value of the Universal Thermal Climate Index as the way to determine the optimal travel path given in this solution is only a preferred implementation. Those skilled in the art should understand that when determining the optimal travel path, the cumulative thermal stress of each travelable path can also be replaced with other regional thermal environment data.

[0042] Furthermore, the cumulative value of the Universal Thermal Climate Index is calculated by any of the following methods:

[0043] Method 1: Sum the Universal Thermal Climate Index on each grid.

[0044] Method 2: Sum the product of the Universal Thermal Climate Index on each grid and the time required to pass through this grid.

[0045] Method 3: Sum the product of the Universal Thermal Climate Index on each grid and the path length on this grid.

[0046] Among them, Method 1 can be expressed as the following formula: Σ UTCI = UTCI1 + UTCI2 + … UTCI i + … + UTCI n ; In the formula, Σ UTCI is the cumulative thermal stress, UTCI i is the Universal Thermal Climate Index of the i-th grid on this path, and n is the total number of grids on this path. Method 1 directly extracts the Universal Thermal Climate Index of all grids corresponding to the travelable path and adds them according to the data grid established in the parametric software Rhino-Grasshopper in the previous steps and the thermal environment data assigned to each grid, and then the cumulative thermal stress of this travelable path can be obtained.

[0047] Both Method 2 and Method 3 sum the corresponding products of each grid, and can also characterize the cumulative value of the Universal Thermal Climate Index. They comprehensively consider the total number of grids on the path, grid size, path distance, and travel time.

[0048] It can be seen that when calculating the cumulative value of the general thermal climate index in this solution, the corresponding relationship between the path distance, travel time and grid size within a certain grid is considered; taking the thermal environment data assigned to the grid as the calculation basis, the calculation process is simple and fast, avoiding the need to establish complex integral functions for cumbersome calculations, significantly improving the response time and reducing the requirements for the carrier hardware, which is conducive to the rapid popularization of this method in the community and among residents.

[0049] An outdoor travel route optimization system based on cumulative heat stress, comprising:

[0050] A modeling module, configured to establish a model according to regional basic data, simulate the regional thermal environment, and obtain regional thermal environment data;

[0051] A path determination module, configured to determine all travel paths and obtain the thermal environment data of each travel path;

[0052] A path screening module, configured to screen out the travelable paths that meet the set requirements and calculate the cumulative heat stress of each travelable path;

[0053] An output module, configured to output the path with the minimum cumulative heat stress as the optimal travel path.

[0054] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0055] 1. The outdoor travel route optimization method and system based on cumulative heat stress of the present invention can quickly and finely identify the thermal environment problems in the outdoor activity areas of residents, analyze the dynamic changes of urban microclimate and thermal comfort from the perspective of adaptability, evaluate their thermal impacts and hazards on residents' health, outdoor activities and travel; and intelligently propose adaptive guidance measures to support the regulation of residents' travel and outdoor activity patterns, which is beneficial to protecting residents' health, reducing the thermal impacts and hazards on residents' travel and outdoor activities, promoting the development of low-carbon smart cities, and providing effective support for coping with climate change.

[0056] 2. The outdoor travel route optimization method and system based on cumulative heat stress of the present invention are different from the traditional research on evaluating thermal impacts based on microclimate and thermal comfort indicators. This application comprehensively considers community space microclimate, thermal comfort, community travel demand and social and economic characteristic indicators to analyze the thermal impacts and hazards within the community space; and further correlates the feedback of residents' adaptive behaviors to thermal impacts and hazards to establish a multi-objective outdoor thermal adaptation behavior evaluation model.

[0057] 3. The travel route optimization method and system based on cumulative thermal stress of the present invention can, starting from the construction requirements of future communities, propose an intelligent and accurate urban thermal adaptability decision-making method, aiming to predict, evaluate, and give early warnings of the thermal impacts and hazards on community streets, provide real-time feedback for residents to adaptively reduce thermal impacts and hazards, and offer a scientific and reasonable decision-making basis.

[0058] 4. The travel route optimization method and system based on cumulative thermal stress of the present invention uses the duration of continuous exposure to sunlight as the evaluation criterion for setting requirements and gives a quantitatively evaluation criterion with good generality.

[0059] 5. The travel route optimization method and system based on cumulative thermal stress of the present invention uses the mean radiant temperature as the thermal environment data parameter to evaluate whether residents are directly exposed to sunlight. It has the advantage of being not interfered by humidity factors, can characterize the radiation effect of the surrounding environment on the human body, most directly represents whether the human body is exposed to sunlight, and has extremely strong practical application value.

[0060] 6. The travel route optimization method and system based on cumulative thermal stress of the present invention uses the cumulative value of the universal thermal climate index on the path to characterize the cumulative thermal stress of each travelable path. Since the lengths of different travelable paths are different, the cumulative value method comprehensively considers the path length and thermal comfort parameters and comprehensively determines the optimal solution for the outdoor thermal comfort of users traveling in hot weather. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, form a part of this application, and do not limit the embodiments of the present invention. In the drawings:

[0062] Figure 1 is a schematic flowchart of a specific embodiment of the present invention;

[0063] Figure 2 is a site model diagram in a specific embodiment of the present invention;

[0064] Figure 3 is a UTCI result diagram in a specific embodiment of the present invention;

[0065] Figure 4 is a schematic diagram of all travel routes in a specific embodiment of the present invention;

[0066] Figure 5 is a data grid diagram in a specific embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] To make the objectives, technical solutions, and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to embodiments and drawings. The illustrative embodiments of the present invention and their descriptions are only used to explain the present invention and do not limit the present invention. In the description of this application, it should be understood that the orientation or positional relationships indicated by the terms "front", "rear", "left", "right", "upper", "lower", "vertical", "horizontal", "high", "low", "inner", "outer", etc. are based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be construed as limiting the protection scope of this application.

[0068] Embodiment 1:

[0069] As Figure 1 shown, an optimized travel path method based on cumulative thermal stress, the main steps are as follows:

[0070] S1. Simulate the regional thermal environment according to the regional basic data to obtain regional thermal environment data;

[0071] Wherein the regional basic data includes meteorology, terrain, buildings, vegetation, water bodies, and public facilities;

[0072] The method for simulating the regional thermal environment includes: establishing a model according to the regional basic data, verifying the accuracy of the model, simulating the regional thermal environment through the model, and obtaining regional thermal environment data;

[0073] The regional thermal environment data includes any one or more of the following: air temperature, mean radiant temperature, universal thermal climate index, physiological equivalent temperature, standard effective temperature, wet bulb globe temperature, thermal intensity index, etc. in the region, and other existing thermal comfort evaluation indicators can also be used.

[0074] S2. Determine all travel paths and obtain the thermal environment data of each travel path:

[0075] According to the travel starting point and the travel ending point, all travel paths are obtained;

[0076] Import the regional thermal environment data into the parametric software Rhino - Grasshopper to establish a data grid matching the model;

[0077] Draw all travel paths in Rhino, and use the Grasshopper plugin to obtain the thermal environment data of all travel paths.

[0078] S3. Screen out the travelable paths that meet the set requirements;

[0079] S4. Calculate the cumulative thermal stress of each travelable path, and select the path with the minimum cumulative thermal stress as the optimal travel path.

[0080] Preferably, the setting requirements in this embodiment are as follows: when walking along a certain path, the duration of continuous exposure of pedestrians to sunlight does not exceed the first set threshold, and the cumulative duration of exposure of pedestrians to sunlight does not exceed the second set threshold; where the second set threshold is greater than the first set threshold. In this embodiment, the first set threshold is 30 s and the second set threshold is 100 s.

[0081] Preferably, the cumulative thermal stress in this embodiment is the cumulative value of the Universal Thermal Climate Index (UTCI) on the path, and is calculated by the following formula:

[0082] Σ UTCI = UTCI1 + UTCI2 + … + UTCI i + … + UTCI n ;

[0083] In the formula, Σ UTCI is the cumulative thermal stress, UTCI i is the Universal Thermal Climate Index of the i-th grid on this path, and n is the total number of grids on this path.

[0084] Embodiment 2:

[0085] A travel path optimization method based on cumulative thermal stress, which is different from Embodiment 1 in that the adopted setting requirements and the calculation method of the cumulative value of the Universal Thermal Climate Index are different. Specifically,

[0086] The setting requirements in this embodiment are to meet any one of the following conditions:

[0087] Condition 1: The average radiant temperature on the entire path is less than 50 °C;

[0088] Condition 2: There is at least one section of the path where the average radiant temperature is greater than or equal to 50 °C, and the length of each section of the path is less than 45 m, and at the same time, the cumulative length of the path with an average radiant temperature greater than or equal to 50 °C is less than 150 m.

[0089] The cumulative value of the Universal Thermal Climate Index in this embodiment is calculated by the following method:

[0090] Sum the product of the Universal Thermal Climate Index on each grid and the duration required to pass through this grid, with the unit of °C·s;

[0091] Or,

[0092] Sum the product of the Universal Thermal Climate Index on each grid and the path length on this grid, with the unit of °C·m.

[0093] In a more preferred embodiment, when screening for travelable paths, any one or more of the remaining parameters in the aforementioned regional thermal environment data can also be used to formulate "setting requirements", replacing the "mean radiant temperature" in this embodiment, and corresponding thresholds are assigned; the setting of specific thresholds can be adjusted according to different human thermal comfort levels, health risks, and characteristics of travelers, such as age, health level, clothing situation, exercise mode, exercise speed, load-bearing situation, etc.

[0094] In a more preferred embodiment, when determining the optimal travel path, the cumulative heat stress of each travelable path can also use the remaining regional thermal environment data to replace the "cumulative value of the universal thermal climate index".

[0095] Example 3:

[0096] As Figure 1 shown in a travel path optimization method based on cumulative heat stress, on the basis of Example 1, the setting requirements can be classified and valued, and the classification method can be divided according to residents of different age groups, different activity intensities, different travel modes, etc.; the specific classification method can be completed by using common expert scoring methods, empirical methods, or experimental methods.

[0097] For example, it is divided as follows in the following table:

[0098]

[0099] Example 4:

[0100] A travel path optimization method based on cumulative heat stress is applied as follows:

[0101] Step 1,

[0102] Obtain data, including the picking up of meteorology, terrain, buildings, vegetation, water bodies, and public facilities, providing a basis for software simulation.

[0103] Step 2,

[0104] First, based on the data obtained in Step 1, use ENVI-met software to build a model and obtain a site model as Figure 2 shown, and verify the accuracy of the model;

[0105] After that, use ENVI-met software to simulate the regional thermal environment, such as thermal environment parameters such as air temperature, mean radiant temperature (MRT), and universal thermal climate index (UTCI). As Figure 3 shown is the UTCI result at 18:00 on a certain day in summer in this region simulated in this embodiment.

[0106] Step 3,

[0107] Select the starting and ending points of the trip and determine all trip paths. As Figure 4 shown, the starting point of the trip is A and the ending point is B, with a total of three trip paths.

[0108] Export the regional thermal environment data simulated in the second step to the Rhino-Grasshopper software, and establish the same data grid as the site model in the second step. The data grid in this embodiment is as Figure 5 shown.

[0109] Draw the path in Rhino. And use Grasshopper to obtain the thermal environment data corresponding to the path.

[0110] Step Four

[0111] Filter out the paths where the continuous outdoor exposure (MRT≥50) during continuous walking is less than 30s. If the condition is met, output the UTCI value of the corresponding path. If not, output a null value.

[0112] The screening conditions in this embodiment are:

[0113]

[0114] That is, the average radiant temperature on the entire path is less than 50°C; or, there is at least one section on the path where the average radiant temperature is greater than or equal to 50°C, and the path length of each section is less than 45m.

[0115] In this embodiment, paths 2 and 3 are finally screened out as feasible trip paths.

[0116] Step Five

[0117] Use the battery pack of Grasshopper to calculate the cumulative heat stress of the feasible trip paths screened out in Step Four. The calculation formula is: Σ UTCI = UTCI1 + UTCI2 + … + UTCI n . In the formula, Σ UTCI is the cumulative heat stress, UTCI i is the Universal Thermal Climate Index of the i-th grid on the path, and n is the total number of grids on the path.

[0118] In this embodiment, the cumulative heat stresses of paths 2 and 3 are calculated to be 6351.27°C and 6805.45°C respectively.

[0119] Step Six

[0120] According to the cumulative heat comfort values of each path calculated in Step Five, compare their magnitudes, and select the trip path with the minimum cumulative heat stress value. According to the results, path 2 is selected as the optimal path for a safer, healthier, and more comfortable trip.

[0121] Example 5:

[0122] An optimized travel path system based on cumulative thermal stress, comprising:

[0123] A modeling module, configured to establish a model according to regional basic data, simulate the regional thermal environment, and obtain regional thermal environment data;

[0124] A path determination module, configured to determine all travel paths and obtain the thermal environment data of each travel path;

[0125] A path screening module, configured to screen out travelable paths that meet the set requirements and calculate the cumulative thermal stress of each travelable path;

[0126] An output module, configured to output the path with the minimum cumulative thermal stress as the optimal travel path.

[0127] In a more preferred implementation manner, the set requirements are to meet any of the following conditions:

[0128] Condition 1: The average radiant temperature throughout the entire path is less than 50 °C;

[0129] Condition 2: There is at least one section of the path where the average radiant temperature is greater than or equal to 50 °C, and the path length of each section is less than 45 m.

[0130] In a more preferred implementation manner, the cumulative thermal stress is the cumulative value of the general thermal climate index on the path.

[0131] In a more preferred implementation manner, the threshold of the "path length of each section" in Condition 2 is selected according to user information. Specifically, the system may further include an input module for inputting user information such as user age, activity intensity, travel mode, etc. The path determination module obtains the user information from the input module, judges the appropriate "path length of each section" for the user according to the user information, and assigns this length to the path screening module.

[0132] Example 6:

[0133] An optimized travel path terminal device based on cumulative thermal stress, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any of the methods described in Examples 1 to 3.

[0134] The terminal device in this embodiment can be a computing device such as a computer, a notebook, a palm computer, and a cloud server. Preferably, it is a smart phone.

[0135] Example 6:

[0136] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the method described in any one of Embodiments 1 to 3.

[0137] Among them, the computer program includes computer program code, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, dot carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction.

[0138] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0139] It should be noted that in this article, terms such as "including", "comprising", or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such a process, method, article, or device. In addition, the term "connected" used in this article, without special explanation, can be directly connected or indirectly connected via other components.

Claims

1. A travel path optimization method based on cumulative thermal stress, characterized in that Including: Simulating the regional thermal environment based on regional basic data to obtain regional thermal environment data; The regional thermal environment data includes any one or more of the following: air temperature within the region, mean radiant temperature, universal thermal climate index, physiological equivalent temperature, standard effective temperature, wet bulb globe temperature, heat intensity index; The method for simulating the regional thermal environment includes: establishing a model based on regional basic data, verifying the accuracy of the model, simulating the regional thermal environment through the model, and obtaining regional thermal environment data; Determining all travel paths and obtaining the thermal environment data of each travel path; Obtaining all travel paths based on the travel starting point and the travel ending point; Importing the regional thermal environment data into the parametric software Rhino - Grasshopper to establish a data grid matching the model; Drawing all travel paths in Rhino and using the Grasshopper plug - in to obtain the thermal environment data of all travel paths; Filtering out the travelable paths that meet the set requirements; The set requirements are determined by the expert scoring method, the empirical method, or the experimental method, and are divided according to residents of different age groups, different activity intensities, or different travel modes; Calculating the cumulative heat stress of each travelable path and selecting the path with the minimum cumulative heat stress as the optimal travel path; The cumulative heat stress of the travelable path is the cumulative value of the universal thermal climate index on the path; The cumulative value of the universal thermal climate index is calculated by the following method: summing the product of the universal thermal climate index on each grid and the time required to pass through this grid; The set requirements meet the following conditions: When walking along a certain path, the duration of continuous exposure of pedestrians to sunlight does not exceed the first set threshold, and the cumulative duration of exposure of pedestrians to sunlight does not exceed the second set threshold; where the second set threshold is greater than the first set threshold; The set requirements also meet any one of the following conditions: Condition 1: The mean radiant temperature throughout the path is less than 50°C; Condition 2: There is at least one section of the path where the mean radiant temperature is greater than or equal to 50°C, and the length of each section is less than 45m, and the cumulative length of the path with a mean radiant temperature greater than or equal to 50°C is less than 150m.

2. The travel path optimization method based on cumulative thermal stress according to claim 1, wherein The regional basic data includes meteorology, terrain, buildings, vegetation, water bodies, and public facilities.

3. A travel route optimization system based on cumulative thermal stress, characterized in that, For implementing the travel path optimization method as described in claim 1 or 2, including: A modeling module for establishing a model based on regional basic data, simulating the regional thermal environment, and obtaining regional thermal environment data; A path determination module for determining all travel paths and obtaining the thermal environment data of each travel path; A path screening module for screening out the travelable paths that meet the set requirements and calculating the cumulative heat stress of each travelable path; An output module for outputting the path with the minimum cumulative heat stress as the optimal travel path.

Images