A device and method for rapid prediction and display of three-dimensional images of traffic thermal environment

Abstract

The present invention discloses a device and method for rapid prediction and display of three-dimensional images of traffic thermal environment, comprising a 360° rotating camera, a temperature sensor, a wind speed sensor, an image acquisition module, a data processing module and a display. The 360° rotating camera is responsible for capturing real-time vehicle status images on the road; the image acquisition module is responsible for counting vehicles in the real-time vehicle status images; the temperature sensor is responsible for collecting the real-time air temperature around the road; the wind speed sensor is responsible for collecting the real-time wind speed around the road; the data processing module is responsible for processing the acquired data, generating a real-time high-resolution dynamic image of the traffic thermal environment of the road, and determining the average temperature; the display is responsible for displaying the real-time high-resolution dynamic image of the traffic thermal environment, or simultaneously prompting a "high temperature warning". The present invention solves the problem that traditional technologies are limited by the number of monitoring equipment and the cost of use, and can be applied to the prediction and display of three-dimensional images of any road traffic thermal environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic thermal environment prediction and image display, and specifically relates to a device and method for rapid prediction and image display of a three-dimensional image of a traffic thermal environment. Background Art

[0002] With rapid urbanization, the urban heat island effect and extreme heat waves are becoming increasingly severe. Long-term heat exposure can lead to energy imbalances, elevated body temperatures, and even threaten health, health, and cognitive abilities. The deterioration of the traffic thermal environment is a major factor exacerbating the urban heat island effect, with vehicle heat emissions accounting for approximately one-third of a city's total heat emissions. Therefore, rapidly understanding the evolution of the traffic thermal environment and addressing this deterioration is crucial for mitigating the urban heat island effect and reducing the risk of high-temperature exposure.

[0003] The conventional method for acquiring information about the traffic thermal environment is to monitor and perceive meteorological data such as temperature and wind speed, thereby determining the current state of the urban traffic thermal environment and providing a basis for decision-making by traffic management departments. However, obtaining high-resolution traffic thermal environment distribution patterns requires a large number of monitoring devices, which often leads to high monitoring costs and poor feasibility.

[0004] With the advancement of computer technology, computational fluid dynamics (CFD) methods have been widely used to rapidly predict traffic thermal environments. However, the significant dynamic nature of vehicle traffic significantly increases computational cycles and iteration costs, making these methods less practical. Therefore, developing a low-cost, high-resolution rapid prediction model for the traffic thermal environment and its associated graphical display is crucial for dynamically capturing its spatiotemporal evolution and efficiently addressing thermal environmental issues. Summary of the Invention

[0005] In response to the above-mentioned problems in the prior art, the present invention provides a device and method for rapid prediction and display of three-dimensional images of traffic thermal environment, so as to achieve rapid prediction and three-dimensional high-resolution image display of dynamic traffic thermal environment.

[0006] In order to solve the above technical problems, the present invention is implemented through the following technical solutions:

[0007] A device for rapid prediction and display of three-dimensional images of traffic thermal environment, comprising at least a 360-degree rotating camera, a temperature sensor, a wind speed sensor, an image acquisition module, a data processing module and a display;

[0008] The 360° rotating camera is responsible for capturing real-time vehicle conditions on the research road;

[0009] The image acquisition module is responsible for counting the number of real-time vehicles appearing in the real-time vehicle situation picture;

[0010] The temperature sensor is responsible for collecting the real-time air temperature around the research road;

[0011] The wind speed sensor is responsible for collecting the real-time wind speed around the research road;

[0012] The data processing module is responsible for generating a real-time high-resolution dynamic image of the traffic thermal environment of the study road using the acquired real-time vehicle number, real-time air temperature, and real-time wind speed through corresponding processing methods, and generating a "high temperature warning signal" when the average temperature of the study road is too high;

[0013] The display is responsible for displaying the generated real-time high-resolution dynamic image of the traffic thermal environment, or simultaneously displaying the generated "high temperature warning" signal.

[0014] Furthermore, the data processing module at least includes a memory, an arithmetic unit and a controller; wherein,

[0015] The memory is responsible for storing data information including the real-time number of vehicles, real-time air temperature and real-time wind speed, as well as data information processed by the operator and the controller;

[0016] The computing unit is responsible for processing and analyzing input data including the real-time number of vehicles, real-time air temperature, and real-time wind speed, generating a real-time three-dimensional image of the traffic thermal environment of the study road, and generating a "high temperature warning signal" when the average temperature of the study road is too high;

[0017] The controller is responsible for implementing image space difference on the imported real-time traffic thermal environment three-dimensional image to generate a real-time high-resolution traffic thermal environment dynamic image of the research road.

[0018] Furthermore, the display is mounted on the ground through a supporting assembly, the 360° rotating camera, the temperature sensor, and the wind speed sensor are respectively arranged on the top of the display, and the 360° rotating camera is located in the center of the top of the display, the temperature sensor and the wind speed sensor are both located on the same side of the 360° rotating camera or are arranged on the left and right sides of the 360° rotating camera, and the image acquisition module and the data processing module are both arranged inside the display.

[0019] Furthermore, the support assembly consists of a fixed bracket and a telescopic rod, the fixed bracket is placed on the ground, the bottom end of the telescopic rod is fixedly connected to the top end of the fixed bracket, and the top end of the telescopic rod is fixedly connected to the base of the display.

[0020] Furthermore, the display is provided with a switch and a power interface, the switch is embedded on the left side of the front of the display, and the power interface is embedded on the right side of the front of the display.

[0021] A method for rapidly predicting and displaying a three-dimensional image of a traffic thermal environment comprises the following steps:

[0022] S100: Acquire the real-time number of vehicles on the study road, and the real-time air temperature and wind speed around the study road; the acquisition methods are:

[0023] Using a 360-degree rotating camera, at a certain unit time interval, to capture real-time vehicle status images of the study road, and using an image acquisition module to count the vehicles appearing in each of the real-time vehicle status images, thereby obtaining the real-time number of vehicles on the study road;

[0024] Using the temperature sensor, the air temperature around the study road is collected in real time at the same unit time interval, thereby obtaining the real-time air temperature around the study road;

[0025] Using wind speed sensors, the wind speed around the study road is collected in real time at the same unit time interval, thereby obtaining the real-time wind speed around the study road;

[0026] S200: Input all acquired real-time vehicle numbers, real-time air temperature, and real-time wind speed into a data processing module, process and analyze them using a dynamic traffic heat source rapid prediction method, thereby generating a real-time, high-resolution dynamic image of the traffic thermal environment and generating a "high temperature warning" signal when the average temperature is too high;

[0027] S300. Output the generated real-time high-resolution dynamic image of the traffic thermal environment of the research road, or output the generated "high temperature warning" signal at the same time, to the display, which visually presents the real-time high-resolution dynamic image of the traffic thermal environment of the research road and displays the words "high temperature warning" when receiving the "high temperature warning" signal.

[0028] Furthermore, the dynamic traffic heat source rapid prediction method includes three major contents: basic database construction, data processing and analysis, and temperature warning; among which,

[0029] The construction of the basic database includes the following contents: defining the database scene, building a basic three-dimensional geometric model, dividing the basic grid, setting boundary conditions and building a three-dimensional image database of the traffic thermal environment;

[0030] The data processing and analysis includes the following contents: pre-processing input data set, locking interval, and predicting dynamic images of traffic thermal environment;

[0031] The temperature warning includes the following contents: setting temperature threshold, data comparison and warning prompt.

[0032] Furthermore, the specific steps of constructing the basic database are:

[0033] 1) Define the database scenario:

[0034] Combining 3D maps and actual surveys, the characteristics of the n research roads to be monitored and their surrounding influencing factors, including building layout, building density, building height, vegetation type, vegetation height, and vegetation density, are obtained;

[0035] Define the temperature threshold range of summer traffic roads and divide it equally into m temperature threshold intervals;

[0036] Define the wind speed threshold range for summer traffic roads and divide it equally into m wind speed threshold intervals;

[0037] Define the vehicle quantity threshold range for monitoring traffic roads and divide it equally into m vehicle quantity threshold intervals;

[0038] According to the above pre-definition, it is assumed that the database scenario has X=n×m 3 A scene;

[0039] Where n and m are both natural numbers;

[0040] 2) Constructing a basic 3D geometric model:

[0041] First, based on the 3D map, the target range is drawn with the center of the study road as the center of the circle and several times the length of the study road as the diameter.

[0042] Then, based on the characteristics of the surrounding influencing factors within the target range, including building layout, building density, building height, vegetation type, vegetation height, and vegetation density, the geometry of the target area is constructed using 3D geometric partitioning software;

[0043] Then, a cube of a certain height is drawn as the calculation domain in the four directions of due east, due south, due west, and due north, extending a certain distance from the target area.

[0044] Finally, based on the target area and the basic 3D geometric model of the computational domain, a total of n basic 3D geometric models are constructed for the n research roads mentioned above;

[0045] 3) Divide the basic grid:

[0046] For the n basic three-dimensional geometric models constructed, a finite volume meshing algorithm is used to perform unstructured meshing on the basic three-dimensional geometric models using meshing software to form n basic meshes;

[0047] 4) Set boundary conditions:

[0048] For the n basic grids that have been divided, boundary conditions are set using computational fluid simulation software. The initial condition of the inlet temperature of the computational domain is set to a constant temperature, the wind speed is set to a gradient wind, and the boundaries of the building and vegetation are set to constant temperature boundaries respectively.

[0049] Add momentum source terms and energy source terms to the road boundary. The momentum source term is related to the real-time wind speed of the simulation case, and the energy source term is related to the real-time number of vehicles and real-time air temperature of the simulation case. The calculation formula is as follows:

[0050] ;

[0051] Where F is the momentum source; q v is the energy source; C is the vehicle drag coefficient; ρ is the air density; v b is the vehicle speed; A is the vehicle cross-sectional area; h c is the convective heat transfer coefficient; S is the heat transfer surface area; N c is the number of vehicles; ∆T is the temperature difference between the vehicle and the surrounding air; V is the vehicle volume, assuming that there are continuous moving vehicles on the road;

[0052] 5) Construction of a 3D traffic thermal environment image database:

[0053] According to the set boundary conditions, the computational fluid simulation software is used to calculate, and different vertical planes are intercepted by post-processing software to obtain n×m 3 The three-dimensional image of the traffic thermal environment in the simulation scene is converted into n×m 3 The three-dimensional images of the traffic thermal environment of each scene are stored in a memory to obtain a three-dimensional image database of the traffic thermal environment.

[0054] Furthermore, the specific steps of the data processing and analysis are:

[0055] 1) Preprocess input data:

[0056] Inputting all acquired real-time vehicle numbers, real-time air temperatures, and real-time wind speeds into the memory in the data processing module;

[0057] 2) Interval Lock:

[0058] First, the controller in the data processing module calls the real-time number of vehicles, real-time air temperature and real-time wind speed in the memory and transmits them to the calculation unit;

[0059] Then, based on the binary search algorithm, the vehicle number threshold interval where the real-time vehicle number is located is locked, and the position in the vehicle number threshold interval is calculated;

[0060] Lock the temperature threshold interval where the real-time air temperature is located and calculate the position in the temperature threshold interval;

[0061] Lock the wind speed threshold interval where the real-time wind speed is located and calculate the position in the wind speed threshold interval;

[0062] Then, the three-dimensional images of the traffic thermal environment under the locked vehicle quantity threshold range, temperature threshold range and wind speed threshold range are loaded from the memory into the calculation unit;

[0063] Finally, the controller returns the real-time vehicle quantity, real-time air temperature and real-time wind speed position representation values ​​to the memory.

[0064] 3) Predict real-time high-resolution dynamic images of traffic thermal environment:

[0065] After the numerical values ​​representing the real-time number of vehicles, real-time air temperature and real-time wind speed are input into the operator, the thermal environment images are spatially interpolated using the nearest neighbor method in combination with the three-dimensional images of the traffic thermal environment in each scenario, and the real-time high-resolution dynamic images of the traffic thermal environment in the scenarios of the real-time number of vehicles, real-time air temperature and real-time wind speed are quickly predicted and transmitted to the display for display.

[0066] Furthermore, the specific steps of the temperature warning are:

[0067] 1) Set the temperature threshold:

[0068] Preset summer high temperature threshold and store it in memory;

[0069] 2) Comparison data:

[0070] The controller is used to load the predicted real-time high-resolution dynamic image of the traffic thermal environment into the calculation unit, calculate the average temperature of the traffic road under the real-time high-resolution dynamic image of the traffic thermal environment, and then compare the value of the average temperature of the traffic road with the high temperature threshold;

[0071] 3) Early warning tips:

[0072] When the average temperature of the traffic road is greater than the high temperature threshold, the controller will transmit the instruction "high temperature warning" to the display, and the display will display the words "high temperature warning".

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] The present invention only needs to monitor the number of vehicles, air temperature and wind speed on the study road in real time, and can quickly and accurately predict the high-resolution traffic thermal environment dynamic image of the study road through the thermal environment rapid prediction method provided by the present invention, and dynamically display it on the display, which effectively solves the problem that traditional technology is limited by the number of monitoring equipment and the cost of use. It can be applied to the prediction and display of high-resolution traffic thermal environment dynamic images of any road and has universal applicability.

[0075] Moreover, the rapid thermal environment prediction method proposed in the present invention, which takes into account dynamic traffic characteristics, solves the problems of long computation time and high storage cost in traditional traffic thermal environment prediction methods without the need for geometric modeling of moving vehicles (for example, computational fluid dynamics methods often use dynamic mesh algorithms to achieve dynamic traffic thermal environment prediction, which requires geometric modeling of moving vehicles and grid division, greatly increasing computational costs).

[0076] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the invention and to implement it according to the contents of the description, the following preferred embodiments of the present invention are described in detail with reference to the accompanying drawings. The specific implementation methods of the present invention are given in detail by the following embodiments and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0078] Figure 1 This is a schematic diagram of the external structure of the device for rapid prediction and display of three-dimensional images of traffic thermal environment according to the present invention.

[0079] Figure 2 This is a block diagram of the internal electrical connections of the device for rapid prediction and display of three-dimensional images of traffic thermal environment according to the present invention.

[0080] Figure 3 The figure is a schematic flow chart of the steps of the method for rapid prediction and display of three-dimensional images of traffic thermal environment of the present invention.

[0081] Figure 4 This is a schematic diagram of the location of the road studied in an embodiment of the present invention.

[0082] Figure 5 The embodiment constructed for the present invention studies the geometric model of the road and its surrounding elements.

[0083] Figure 6 The embodiment predicted by the present invention studies the dynamic image of the traffic thermal environment of the road.

[0084] Explanation of the numbers in the figure: 1. 360° rotating camera; 2. Temperature sensor; 3. Wind speed sensor; 4. Image acquisition module; 5. Data processing module; 6. Display; 7. Switch; 8. Power interface; 9. Fixed bracket; 10. Telescopic rod; 501. Memory; 502. Arithmetic unit; 503. Controller. DETAILED DESCRIPTION

[0085] The following will be described in detail with reference to the accompanying drawings to better understand the purpose, features and advantages of the invention. It should be understood that the embodiments shown in the accompanying drawings are not intended to limit the scope of the invention, but are only intended to illustrate the essential spirit of the technical solution of the invention.

[0086] In the following description, for the purpose of illustrating the various disclosed embodiments, certain specific details are set forth in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the relevant art will recognize that the embodiments may be practiced without one or more of these specific details. In other cases, well-known devices, structures, and techniques associated with this application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0087] Unless the context requires otherwise, throughout the specification and claims, the word "comprise" and variations such as "include" and "have" should be construed in an open, inclusive sense, that is, should be interpreted to mean "including, but not limited to."

[0088] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any manner in one or more embodiments.

[0089] As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It should be noted that the term "or" is generally employed in its sense including "and / or" unless the context clearly dictates otherwise.

[0090] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0091] See also Figure 1-2 As shown, a device for rapid prediction and display of three-dimensional images of traffic thermal environment mainly includes a 360° rotating camera 1, a temperature sensor 2, a wind speed sensor 3, an image acquisition module 4, a data processing module 5, a display 6, a switch 7, a power interface 8 and a support component.

[0092] The display 6 is mounted on the ground through a supporting assembly, which consists of a fixed bracket 9 and a telescopic rod 10. The fixed bracket 9 is placed on the ground, the bottom end of the telescopic rod 10 is fixedly connected to the top end of the fixed bracket 9, and the top end of the telescopic rod 10 is fixedly connected to the base of the display 6.

[0093] The 360° rotating camera 1, the temperature sensor 2, and the wind speed sensor 3 are respectively arranged on the top of the display 6, and the 360° rotating camera 1 is located in the center of the top of the display 6. The temperature sensor 2 and the wind speed sensor 3 are both located on the same side of the 360° rotating camera 1 or are arranged on the left and right sides of the 360° rotating camera 1.

[0094] The switch 7 and the power interface 8 are both embedded in the front of the display 6 , and the switch 7 is located on the left side of the front of the display 6 , and the power interface 8 is located on the right side of the front of the display 6 .

[0095] The image acquisition module 4 and the data processing module 5 are both arranged inside the display 6 , and the data processing module 5 at least includes a memory 501 , a computing unit 502 and a controller 503 .

[0096] The 360° rotating camera 1 is signal-connected to the memory 501 through the image acquisition module 4, the temperature sensor 2 and the wind speed sensor 3 are directly signal-connected to the memory 501, the memory 501 is signal-connected to the operator 502, the operator 502 is signal-connected to the controller 503, and the controller 503 is signal-connected to the display 6.

[0097] The 360° rotating camera 1 is responsible for capturing real-time vehicle condition images on the study road.

[0098] The temperature sensor 2 is responsible for collecting the real-time air temperature around the research road.

[0099] The wind speed sensor 3 is responsible for collecting the real-time wind speed around the research road.

[0100] The image acquisition module 4 is responsible for counting the number of real-time vehicles appearing in the real-time vehicle situation picture.

[0101] The data processing module 5 is responsible for generating a real-time high-resolution dynamic image of the traffic thermal environment of the research road by using the acquired real-time vehicle number, real-time air temperature and real-time wind speed through corresponding processing methods, and generating a "high temperature warning" signal when the average temperature of the research road is too high. Specifically,

[0102] The memory 501 is responsible for storing data information including the real-time number of vehicles, real-time air temperature and real-time wind speed, as well as data information processed by the operator 502 and the controller 503;

[0103] The computing unit 502 is responsible for processing and analyzing the input data including the real-time number of vehicles, real-time air temperature, and real-time wind speed, generating a real-time three-dimensional image of the traffic thermal environment of the study road, and generating a "high temperature warning signal" when the average temperature of the study road is too high;

[0104] The controller 503 is responsible for performing image space difference on the imported real-time traffic thermal environment three-dimensional image to generate a real-time high-resolution traffic thermal environment dynamic image of the research road.

[0105] The display 6 is responsible for displaying the generated real-time high-resolution dynamic image of the traffic thermal environment, or simultaneously displaying the generated "high temperature warning" signal.

[0106] The switch 7 is responsible for turning the power of the whole device of the present invention on and off.

[0107] The power interface 8 is responsible for connecting the present invention to an external power source to supply power to the entire device of the present invention.

[0108] See also Figure 3 As shown, the working principle and implementation method of the above-mentioned traffic thermal environment three-dimensional image rapid prediction and image display device include the following steps:

[0109] S100: Acquire the real-time number of vehicles on the study road, and the real-time air temperature and wind speed around the study road; the acquisition methods are:

[0110] S101, using the 360° rotating camera 1, at a certain unit time interval, such as 1 second, to capture the real-time vehicle situation picture of the study road, and using the image acquisition module 4 to count the vehicles appearing in each of the real-time vehicle situation pictures, thereby obtaining the real-time vehicle number N of the study road t ;

[0111] S102: Using the temperature sensor, collect the air temperature around the study road in real time at the same unit time interval, such as 1 second, to obtain the real-time air temperature T around the study road. t ;

[0112] S103, using a wind speed sensor, collect the wind speed around the study road in real time at the same unit time interval, such as 1 second interval, to obtain the real-time wind speed V around the study road. t .

[0113] It should be noted that the unit time interval for collecting the real-time vehicle status image, the unit time interval for collecting the real-time air temperature, and the unit time interval for collecting the real-time wind speed must be consistent, so that the real-time (per second) number of vehicles N can be obtained. t , the real-time (per second) air temperature T t , the real-time (per second) wind speed V t The timing corresponds to .

[0114] S200: Input all the acquired real-time vehicle numbers, real-time air temperature, and real-time wind speed into the data processing module 5, and process and analyze them using a dynamic traffic heat source rapid prediction method, thereby generating a real-time high-resolution dynamic image of the traffic thermal environment and generating a "high temperature warning" signal when the average temperature is too high.

[0115] The dynamic traffic heat source rapid prediction method includes three parts: basic database construction, data processing and analysis, and temperature warning;

[0116] S201. The specific methods and contents of basic database construction are as follows:

[0117] 1) Define the database scenario;

[0118] Combined with the three-dimensional map and actual investigation, the n research roads R that need to be monitored i (i=1, 2, …, n) and its surrounding influencing factors including building layout, building density, building height, vegetation type, vegetation height, and vegetation density are obtained.

[0119] The temperature threshold range of summer traffic roads is defined as [T min , T max ] and divide it equally into m temperature threshold intervals, the range of the jth temperature threshold interval is [T min +(T max -T min ) / m×(j-1), T min +(T max -T min ) / m×j], (j=1, 2, …, m).

[0120] The wind speed threshold range for summer traffic roads is defined as [V min , V max ] and divide it equally into m wind speed threshold intervals. The kth wind speed threshold interval range is [V min +(V max -V min ) / m×(k-1), V min +(V max -Vmin ) / m×k], (k=1, 2, …, m).

[0121] The threshold range of the number of vehicles on the monitored traffic road is defined as [N min , N max ] and divide it equally into m vehicle number threshold intervals, the range of the lth vehicle number threshold interval is [N min +(N max -N min ) / m×(l-1), N min +(N max -N min ) / m×l], (l=1, 2, …, m).

[0122] According to the above pre-definition, it is assumed that the database scenario has X=n×m 3 (n roads, m temperatures, m wind speeds, and m numbers of vehicles) scenarios; where n and m are both natural numbers.

[0123] 2) Constructing a basic 3D geometric model:

[0124] First, based on the three-dimensional map, we study the road R i The center of the road is taken as the center of the circle, and the diameter is three times the length of the research road. The range of the geometric model is drawn as the target range.

[0125] Then, based on the characteristics of the surrounding influencing factors within the target range, including building layout, building density, building height, vegetation type, vegetation height, and vegetation density, the geometry of the target area is constructed using three-dimensional geometric division software (such as CAD, Sketchup, etc.).

[0126] Then, a cube with a height of 250m was drawn as the calculation domain, extending 500m in each of the four directions of due east, due south, due west and due north from the target area.

[0127] Finally, based on the basic three-dimensional geometric models of the target area and the computational domain, a total of n basic three-dimensional geometric models are constructed for the n research roads mentioned above.

[0128] 3) Divide the basic grid:

[0129] For the n basic three-dimensional geometric models constructed, a finite volume meshing algorithm is adopted, and meshing software (such as ICEM, Gambit, etc.) is used to perform unstructured meshing on the basic three-dimensional geometric models to form n basic meshes.

[0130] It should be noted that only n grids need to be constructed here, not n×m 3 This saves computing time and storage space.

[0131] 4) Set boundary conditions:

[0132] For the n basic grids that have been divided, boundary conditions are set using computational fluid simulation software (such as Fluent). The initial condition of the calculation domain inlet temperature is set to a constant temperature, the wind speed is set to a gradient wind, and the boundaries of the building and vegetation are set to constant temperature boundaries respectively.

[0133] Add momentum (F) source terms and energy (q v ) source term, momentum (F) source term and the X ijkl (traffic roads are R i , temperature is T j , wind speed is V k , the number of vehicles is N l ) is related to the real-time wind speed of the simulation case, and the energy (q v ) source term and the Xth ijkl (traffic roads are R i , temperature is T j , wind speed is V k , the number of vehicles is N l ) The real-time number of vehicles in the simulation case is related to the real-time air temperature, and the calculation formula is as follows:

[0134] ;

[0135] Where C is the vehicle drag coefficient; ρ is the air density; v b is the vehicle speed; A is the vehicle cross-sectional area; h c is the convective heat transfer coefficient; S is the heat transfer surface area; N c is the number of vehicles; ∆T is the temperature difference between the vehicle and the surrounding air; V is the vehicle volume, assuming that there are continuous moving vehicles on the road.

[0136] 5) Construction of a 3D traffic thermal environment image database:

[0137] According to the set boundary conditions, computational fluid simulation software (such as Fluent, etc.) is used to perform calculations, and post-processing software (such as CFD-Post, etc.) is used to intercept different vertical planes (such as H1,…, H max ), get the traffic road R i , temperature is T j , wind speed is V k and the number of vehicles is N l Thermal environment map of the scene, n×m 3 The three-dimensional images of the traffic thermal environment of each scene are stored in a memory to obtain a three-dimensional image database of the traffic thermal environment.

[0138] S202. The specific methods and contents of data processing and analysis are as follows:

[0139] 1) Preprocess input data:

[0140] All acquired real-time vehicle numbers, real-time air temperatures, and real-time wind speeds are input into the memory 501 in the data processing module 5 .

[0141] 2) Interval Lock:

[0142] First, the controller 503 in the data processing module 5 is used to call the real-time vehicle number N in the memory 501. t , real-time air temperature T t and real-time wind speed V t Sent to the operator 502.

[0143] Then based on the binary search algorithm, lock the real-time vehicle number N t The vehicle number threshold interval [N min +(N max -N min ) / m×(l-1), N min +(N max -N min ) / m×l], and calculate the position N in the vehicle number threshold interval t / {[N min +(N max -N min ) / m×(l-1)]+[ N min +(N max -N min ) / m×l]}×100%;

[0144] Lock the real-time air temperature T t The temperature threshold range [T min +(T max -T min ) / m×(j-1), T min +(T max -T min ) / m×j], and calculate the position T in the temperature threshold interval t / {[T min +(T max -T min ) / m×(j-1)]+[ T min +(T max -T min ) / m×j]}×100%;

[0145] Lock real-time wind speed V t The wind speed threshold interval [V min +(V max -V min) / m×(k-1), V min +(V max -V min ) / m×k], and calculate the position V in the wind speed threshold interval t / {[V min +(V max -V min ) / m×(k-1)]+[ V min +(V max -V min ) / m×k]}×100%.

[0146] Then, the three-dimensional images of the traffic thermal environment in the locked vehicle quantity threshold interval, temperature threshold interval, and wind speed threshold interval are loaded from the memory 501 into the operator 502 .

[0147] Finally, the controller 503 sets the real-time vehicle number N t , real-time air temperature T t and real-time wind speed V t The location indicates that the value is retrieved from the memory 501 .

[0148] 3) Predict real-time high-resolution dynamic images of traffic thermal environment:

[0149] The real-time number of vehicles N t , real-time air temperature T t and real-time wind speed V t After the location representation value is transferred to the operator 502, the three-dimensional image of the traffic thermal environment under each scene is combined and the nearest neighbor method is used to perform spatial difference on the thermal environment image to quickly predict the real-time vehicle number N. t , real-time air temperature T t and real-time wind speed V t The real-time high-resolution dynamic image of the traffic thermal environment in the scene is transmitted to the display 6 for display.

[0150] S203. The specific methods and contents of temperature warning are as follows:

[0151] 1) Set the temperature threshold:

[0152] The preset summer high temperature threshold is T h , storing it in the memory 501;

[0153] 2) Comparison data:

[0154] The controller 503 is used to transfer the predicted real-time high-resolution traffic thermal environment dynamic image into the calculation unit 502, and the average temperature T of the traffic road under the real-time high-resolution traffic thermal environment dynamic image is calculated. a, continue to take the average temperature T a With high temperature threshold T h Make a comparison;

[0155] 3) Early warning tips:

[0156] When T a >T h When the temperature reaches 0, the controller 503 will transmit the instruction "high temperature warning" to the display 6.

[0157] S300. The generated real-time high-resolution dynamic image of the traffic thermal environment of the research road, or the generated "high temperature warning" signal, is output to the display 6, which visually presents the real-time high-resolution dynamic image of the traffic thermal environment of the research road and displays the words "high temperature warning" when receiving the "high temperature warning" signal.

[0158] See also Figure 4 As shown, the following takes a section of Beijing East Road in Nanjing as an example to further explain the device and method of the present invention. The road is a four-lane road, and the specific implementation steps are as follows:

[0159] 1. Use the 360° camera in the device of the present invention to record the vehicle situation on Beijing East Road in real time (every second), and count the vehicles on the road through the image acquisition module.

[0160] 2. Use the temperature acquisition sensor and wind speed acquisition sensor in the device of the present invention to collect the air temperature and wind speed around Beijing East Road in real time (every second).

[0161] 3. By extracting the geometric shapes of Beijing East Road and its surrounding buildings and vegetation (including the area within 500m around the road), we can construct Figure 5 The geometric model shown in the figure is then meshed using the finite volume meshing algorithm to perform unstructured meshing on the basic geometric model.

[0162] 4. Using the collected air temperature, wind speed and number of vehicles on Beijing East Road as input, the momentum (F) source term and energy (q v ) source item, combined with numerical simulation software, the dynamic thermal environment distribution results of Beijing East Road were quickly predicted, and a real-time (per second) three-dimensional image of the traffic thermal environment was obtained.

[0163] 5. All the real-time (per second) traffic thermal environment three-dimensional images are imported into the controller of the device of the present invention to realize the image space difference, and finally the display of the device of the present invention is dynamically displayed as follows: Figure 6 High-resolution dynamic image of the traffic thermal environment is shown.

[0164] It can be seen that the present invention only needs to monitor the number of vehicles, air temperature and wind speed on the study road in real time, and can quickly and accurately predict the high-resolution traffic thermal environment dynamic image of the study road through the thermal environment rapid prediction method of the present invention, and dynamically display it on the display, which effectively solves the problem that traditional technology is limited by the number of monitoring equipment and the cost of use. It can be applied to the prediction and display of high-resolution traffic thermal environment dynamic images of any road and has universal applicability.

[0165] Moreover, the rapid thermal environment prediction method proposed in the present invention, which takes into account dynamic traffic characteristics, solves the problems of long computation time and high storage cost in traditional traffic thermal environment prediction methods without the need for geometric modeling of moving vehicles (for example, computational fluid dynamics methods often use dynamic mesh algorithms to achieve dynamic traffic thermal environment prediction, which requires geometric modeling of moving vehicles and grid division, greatly increasing computational costs).

[0166] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for rapid prediction and display of three-dimensional images of traffic thermal environment, characterized in that: The following steps are involved: S100: Acquire the real-time number of vehicles on the study road, and the real-time air temperature and wind speed around the study road; the acquisition methods are: Using a 360-degree rotating camera (1), taking pictures of real-time vehicle conditions on the study road at intervals of a certain unit time, and using an image acquisition module (4) to count the vehicles appearing in each of the real-time vehicle condition pictures, thereby obtaining the real-time number of vehicles on the study road; Using temperature sensors, the air temperature around the study road is collected in real time at the same unit time interval, thereby obtaining the real-time air temperature around the study road; Using wind speed sensors, the wind speed around the study road is collected in real time at the same unit time interval, thereby obtaining the real-time wind speed around the study road; S200, inputting all the acquired real-time vehicle numbers, real-time air temperature and real-time wind speed into the data processing module (5), processing and analyzing them using a dynamic traffic heat source rapid prediction method, thereby generating a real-time high-resolution dynamic image of the traffic thermal environment, and generating a "high temperature warning" signal when the average temperature is too high; The dynamic traffic heat source rapid prediction method includes three parts: basic database construction, data processing and analysis, and temperature warning; The construction of the basic database includes the following contents: defining the database scene, building a basic three-dimensional geometric model, dividing the basic grid, setting boundary conditions and building a three-dimensional image database of the traffic thermal environment; The specific steps of constructing the basic database are: 1) Define the database scenario: Combining 3D maps and actual surveys, the characteristics of the n research roads to be monitored and their surrounding influencing factors, including building layout, building density, building height, vegetation type, vegetation height, and vegetation density, are obtained; Define the temperature threshold range of summer traffic roads and divide it equally into m temperature threshold intervals; Define the wind speed threshold range for summer traffic roads and divide it equally into m wind speed threshold intervals; Define the vehicle quantity threshold range for monitoring traffic roads and divide it equally into m vehicle quantity threshold intervals; According to the above definition, assuming that the database scenario has X=n×m 3 A scene; Where n and m are both natural numbers; 2) Constructing a basic 3D geometric model: First, based on the 3D map, the target range is drawn with the center of the study road as the center of the circle and several times the length of the study road as the diameter. Then, based on the characteristics of the surrounding influencing factors within the target range, including building layout, building density, building height, vegetation type, vegetation height, and vegetation density, the geometry of the target area is constructed using 3D geometric partitioning software; Then, a cube of a certain height is drawn as the calculation domain in the four directions of due east, due south, due west, and due north, extending a certain distance from the target area. Finally, based on the target area and the basic 3D geometric model of the computational domain, a total of n basic 3D geometric models are constructed for the n research roads mentioned above; 3) Divide the basic grid: For the n basic three-dimensional geometric models constructed, a finite volume meshing algorithm is used to perform unstructured meshing on the basic three-dimensional geometric models using meshing software to form n basic meshes; 4) Set boundary conditions: For the n basic grids that have been divided, boundary conditions are set using computational fluid simulation software. The initial condition of the inlet temperature of the computational domain is set to a constant temperature, the wind speed is set to a gradient wind, and the boundaries of the building and vegetation are set to constant temperature boundaries respectively. Add momentum source terms and energy source terms to the road boundary. The momentum source term is related to the real-time wind speed of the simulation case, and the energy source term is related to the real-time number of vehicles and real-time air temperature of the simulation case. The calculation formula is as follows: ； Where F is the momentum source; q v is the energy source; C is the vehicle drag coefficient; ρ is the air density; v b is the vehicle speed; A is the vehicle cross-sectional area; h c is the convective heat transfer coefficient; S is the heat transfer surface area; N c is the number of vehicles; is the temperature difference between the vehicle and the surrounding air; V is the volume of the vehicle, assuming that there are continuous moving vehicles on the road; 5) Construction of a 3D traffic thermal environment image database: According to the set boundary conditions, the computational fluid simulation software is used to calculate, and different vertical planes are intercepted by post-processing software to obtain n×m 3 The three-dimensional image of the traffic thermal environment in the simulation scene is converted into n×m 3 The three-dimensional image of the traffic thermal environment of each scene is stored in a memory to obtain a three-dimensional image database of the traffic thermal environment; The data processing and analysis includes the following contents: pre-processing input data set, locking interval, and predicting dynamic images of traffic thermal environment; The temperature warning includes the following contents: setting temperature threshold, data comparison and warning prompt; S300, outputting the generated real-time high-resolution dynamic image of the traffic thermal environment of the research road, or simultaneously outputting the generated "high temperature warning" signal to the display (6), the display (6) visually presenting the real-time high-resolution dynamic image of the traffic thermal environment of the research road, and displaying the words "high temperature warning" when receiving the "high temperature warning" signal.

2. The method for rapid prediction and display of three-dimensional images of traffic thermal environment according to claim 1 is characterized in that: The specific steps of the data processing and analysis are: 1) Preprocess input data: Inputting all acquired real-time vehicle numbers, real-time air temperatures, and real-time wind speeds into a memory (501) in the data processing module (5); 2) Interval Lock: First, the controller (503) in the data processing module (5) calls the real-time number of vehicles, real-time air temperature and real-time wind speed in the memory (501) and transmits them to the calculation unit (502); Then, based on the binary search algorithm, the vehicle number threshold interval where the real-time vehicle number is located is locked, and the position in the vehicle number threshold interval is calculated; Lock the temperature threshold interval where the real-time air temperature is located and calculate the position in the temperature threshold interval; Lock the wind speed threshold interval where the real-time wind speed is located and calculate the position in the wind speed threshold interval; Then, the three-dimensional image of the traffic thermal environment under the locked vehicle quantity threshold interval, temperature threshold interval and wind speed threshold interval is loaded from the memory (501) into the calculation unit (502); Finally, the controller (503) returns the real-time vehicle quantity, real-time air temperature and real-time wind speed position representation values ​​to the memory (501); 3) Predict real-time high-resolution dynamic images of traffic thermal environment: After the numerical values ​​representing the positions of the real-time number of vehicles, real-time air temperature and real-time wind speed are transferred into the operator (502), the three-dimensional images of the traffic thermal environment under the transferred scenes are combined, and the nearest neighbor method is used to perform spatial difference on the thermal environment image to quickly predict the real-time high-resolution dynamic image of the traffic thermal environment under the scenes of the real-time number of vehicles, real-time air temperature and real-time wind speed, and the real-time high-resolution dynamic image of the traffic thermal environment is transmitted to the display (6) for display.

3. The method for rapid prediction and display of three-dimensional images of traffic thermal environment according to claim 1 is characterized in that: The specific steps of the temperature warning are: 1) Set the temperature threshold: Preset a summer high temperature threshold and store it in a memory (501); 2) Comparison data: The controller (503) is used to load the predicted real-time high-resolution dynamic image of the traffic thermal environment into the calculation unit (502), calculate the average temperature of the traffic road under the real-time high-resolution dynamic image of the traffic thermal environment, and continue to compare the value of the average temperature of the traffic road with the high temperature threshold; 3) Early warning tips: When the average temperature of the traffic road is greater than the high temperature threshold, the controller (503) transmits the instruction "high temperature warning" to the display (6), and the display (6) displays the words "high temperature warning".

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