Route planning method and system for municipal garbage collection and transportation vehicle

Abstract

The invention relates to the technical field of intelligent environmental sanitation, in particular to a municipal garbage collection and transportation vehicle route planning method and system.The method comprises the steps that a garbage decomposition rate model is established by obtaining data of a block where garbage is located, and garbage decomposition time is calculated to evaluate the block garbage collection and transportation emergency degree; establishing a propagation model of odor at a garbage source, solving to obtain a garbage odor concentration function model, constructing a block population density distribution function, introducing a speed constraint condition to obtain a Lagrange function for optimizing a path, and solving to obtain an actual running speed of the intelligent sanitation vehicle; the value of the target function is calculated to evaluate the influence of the clearance line on the surrounding environment, the calculation result of the target function is compared with the speed reduction condition, and then the speed constraint condition is iterated until the optimal clearance line is obtained and issued to the intelligent sanitation vehicle; the core of the invention is to design an intelligent sanitation vehicle dynamic route planning algorithm so as to reduce the influence of the garbage peculiar smell on the block in the garbage cleaning and transporting process.

Description

Technical Field

[0001] The present invention relates to the field of intelligent sanitation technology, and in particular to a route planning method and system for a municipal garbage removal vehicle. Background Art

[0002] Under the background of the current accelerated urbanization process, the amount of urban garbage generated has increased dramatically, bringing unprecedented challenges to urban management and environmental protection. Although the traditional urban garbage collection and transportation system has met the basic garbage disposal needs to a certain extent, its fixed route and timetable operation mode has gradually exposed many limitations, making it difficult to adapt to the complex and changeable environmental conditions of modern cities and the increasing requirements of residents for the quality of life. First of all, the odor generated by garbage stations and transportation in the city is very easy to spread with the wind direction, affecting the quality of life of surrounding residents. Especially in the high temperature in summer or under specific meteorological conditions, the spread range and intensity of bad odors increase significantly, while traditional collection and transportation methods often ignore the dynamic factor of wind direction and fail to take effective measures to reduce the direct impact of odor on residential areas. Secondly, the decomposition rate of garbage is significantly affected by temperature and humidity. Under high temperature and high humidity environment, the decomposition of organic matter in garbage is accelerated, producing more leachate and gas, which not only increases the difficulty of treatment, but also may cause environmental sanitation problems. However, most of the existing collection and transportation systems do not adjust the collection and transportation frequency according to real-time temperature and humidity data, resulting in excessive accumulation of garbage, aggravating environmental problems. To sum up, the various shortcomings of traditional urban garbage collection methods urgently require an innovative solution that can comprehensively consider environmental factors, dynamically adjust collection strategies, and integrate intelligent technologies to achieve efficient, environmentally friendly and humane garbage collection and meet the needs of sustainable development of modern cities. Summary of the invention

[0003] (1) Technical issues to be solved

[0004] The purpose of the present invention is to provide a method and system for planning the route of a municipal garbage collection vehicle, so as to reduce the impact of garbage odor on the neighborhood during the garbage collection process.

[0005] (2) Technical solution

[0006] To achieve the above object, the present invention provides a method for planning a route for a municipal garbage collection vehicle, the method comprising the following steps:

[0007] S1, obtains the meteorological data, intelligent sanitation vehicle operation data and block data of the block where the garbage collection route is located, and sends the meteorological data, intelligent sanitation vehicle operation data and block data to the model calculation module; the meteorological data includes ambient temperature, relative humidity, and dominant wind direction data; the intelligent sanitation vehicle operation data includes vehicle operation speed; the block data includes residential type, block area, and block center population density;

[0008] S2, establish a garbage decomposition rate model for the block, modify the garbage decomposition rate model by combining the relative humidity correction factor, substitute the meteorological data into the modified garbage decomposition rate model for the block to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions, and evaluate the urgency of garbage removal in the block;

[0009] S3, establish a propagation model of the odor in the air at the garbage source in the block, set the initial conditions and boundary conditions for the location of the garbage source, perform Fourier transform on the diffusion equation to obtain the second equation, transform each term of the quadratic equation, obtain the time derivative term, convection term, and diffusion term in turn, combine all the transformed terms to obtain the third equation in the transformation domain, solve the third equation to obtain the fourth equation, perform inverse Fourier transform on the fourth equation to obtain the fifth equation, perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtain the garbage odor concentration function model;

[0010] S4, constructing a block population density distribution function, and introducing the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle on the basis of considering the garbage odor concentration function and the block population density distribution function, obtaining the Lagrange function used to optimize the path, taking the derivative of each term of the Lagrange function and substituting it into the Euler-Lagrange equation to obtain the differential equation, and then solving the differential equation to obtain the actual running speed of the intelligent sanitation vehicle;

[0011] S5, integrate the odor concentration distribution function and the population density distribution function to obtain the objective function, calculate the value of the objective function to measure the impact of the route of the intelligent sanitation vehicle on the surrounding environment when performing the garbage collection task, compare and verify the objective function calculation result with the speed limit condition, and then iterate and solve the objective function value by increasing the Lagrange multiplier at logarithmic intervals until the optimal collection route conditions are met, and send the optimal collection route to the intelligent sanitation vehicle.

[0012] Furthermore, the method for establishing a block garbage decomposition rate model includes:

[0013] k=Ae ―Ea / RT ;

[0014] Among them, k is the decomposition rate constant, A is the pre-exponential factor, which represents the frequency of molecular collisions and reflects the number of attempts to react per unit time, Ea is the activation energy, R is the gas constant, and T is the absolute temperature.

[0015] Furthermore, the method of correcting the garbage decomposition rate model in combination with the relative humidity correction factor, substituting meteorological data into the corrected block garbage decomposition rate model to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions to evaluate the urgency of block garbage removal includes:

[0016] Modified garbage decomposition rate k a for:

[0017] k a = k·f(RH);

[0018] Among them, f(RH) is the humidity correction function, the value range is 0-1, RH is the relative humidity, when the relative humidity RH is less than the appropriate humidity RH opt hour, When the relative humidity RH is equal to the optimum humidity RH opt When the relative humidity RH is greater than the suitable humidity RH, f(RH) = 1; opt hour, RH opt For suitable humidity;

[0019] The time required for garbage removal is the garbage decomposition time, and the garbage decomposition time t is:

[0020] t=1 / k a ;

[0021] Based on the humidity of different blocks, the garbage decomposition time of different blocks is calculated to evaluate the urgency of garbage removal. The shorter the garbage decomposition time, the higher the urgency of garbage removal. The alarm with the minimum garbage decomposition time is taken, and smart sanitation vehicles are arranged for garbage removal first.

[0022] Furthermore, the method of establishing a propagation model of odor in the air at the garbage source in the block, setting initial conditions and boundary conditions for the location of the garbage source, performing Fourier transform on the diffusion equation to obtain a second equation, transforming each term of the second equation, sequentially obtaining the time derivative term, the convection term, and the diffusion term, combining all the transformed terms to obtain a third equation in the transformation domain, solving the third equation to obtain a fourth equation, performing inverse Fourier transform on the fourth equation to obtain a fifth equation, performing Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtaining the garbage odor concentration function model includes:

[0023] S41. Set the diffusion equation of odor propagation to:

[0024]

[0025] Where C is the odor concentration, x, y, z are the positions in three directions of the spatial coordinates, u, v, w are the wind speed components in the x, y, z directions respectively, and D is the diffusion coefficient of the odor substance;

[0026] S42. Assume that C(x,y,z,t) represents the odor concentration at the location (x,y,z) at time t, and set the initial conditions and boundary conditions for the location of the garbage source:

[0027] The initial conditions are:

[0028] C(x,y,z,0)=Qδ(x-x0)δ(y-y0)δ(z-z0);

[0029] Where C(x,y,z,0) represents the odor concentration at the coordinate (x,y,z) at time t=0, x0, y0, z0 are the positions of the initial source, and Q is the intensity of the garbage source;

[0030] The boundary conditions are:

[0031]

[0032] S43, introduce Fourier transform to get the second equation:

[0033] Forward transformation:

[0034] Inverse transformation:

[0035] S44, transform the terms of the second equation to obtain the time derivative term, convection term, and diffusion term in sequence:

[0036] Since t is independent of the spatial variables, the time derivative term is:

[0037] Using the derivative properties of the Fourier transform Get the convection term:

[0038]

[0039] Use the second derivative property of the Fourier transform: Get the diffusion term:

[0040]

[0041]

[0042] S45. Combine all transformed terms to obtain the third equation in the transformed domain:

[0043]

[0044] Transform the formula to get:

[0045]

[0046] S46. Solve the equation in the transform domain to obtain the fourth equation:

[0047] make Then the equation becomes:

[0048]

[0049] Solving the ordinary differential equation, we obtain:

[0050]

[0051] Where A is determined by the initial conditions;

[0052] S47. Confirm the initial conditions. The initial conditions for Fourier transform are:

[0053]

[0054] therefore,

[0055] A(k x ,k y ,k z )=Qexp(―i(k x x0+k y y0+k z z0)); S48, perform inverse Fourier transform on the formula to obtain the fifth equation:

[0056] The complete inverse transform expression is:

[0057]

[0058] Recombination index term:

[0059] For the x direction, merge k x Item:

[0060] For the y direction, merge with k y Item:

[0061] For the z direction, merge k z Item:

[0062] S49. Perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation:

[0063] Compute the Gaussian integral, using the integral formula for each direction:

[0064]

[0065] Evaluate the triple integral step by step:

[0066] First k x integral:

[0067]

[0068] The y and z directions are handled similarly;

[0069] The final garbage odor concentration function can be expressed as:

[0070]

[0071] Where x0, y0, z0 are the three coordinate positions of the initial source, all defined as 0, and z is 0. The garbage odor concentration function can be simplified as:

[0072]

[0073] Furthermore, the method for planning a route for a municipal garbage collection vehicle and the method for constructing a block population density distribution function include:

[0074] The block population density distribution function P(x,y,z) representing the relative population density is set as:

[0075]

[0076] Among them, x, y, z represent the spatial coordinate position, z is 0, and the population density distribution function can be simplified as:

[0077]

[0078] Furthermore, the method of introducing the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle on the basis of considering the garbage odor concentration function and the block population density distribution function, obtaining the Lagrange function for optimizing the path, performing derivative operations on each term of the Lagrange function, substituting it into the Euler-Lagrange equation to obtain the differential equation, and then solving the differential equation to obtain the actual operating speed of the intelligent sanitation vehicle includes:

[0079] S51. First, construct the Lagrangian function L:

[0080]

[0081] Where λ(t) is the Lagrange multiplier used to ensure that the path satisfies the speed constraint, v m is the expected speed;

[0082] S52. Based on the Euler-Lagrange equation, for the path r(t) = [x(t), y(t)], the z direction is 0, satisfying:

[0083] Therefore, for x(t):

[0084] For y(t):

[0085] S53. Calculate the partial derivatives:

[0086]

[0087] in:

[0088]

[0089] then, The final expression of is:

[0090]

[0091] Similarly:

[0092]

[0093] in:

[0094]

[0095] then, The final expression of is:

[0096]

[0097] S54. Calculate the time derivative of the velocity related term:

[0098]

[0099] S55. Substitute the calculated terms in S54 into the Euler-Lagrange equation to obtain the differential equation: For the x direction:

[0100]

[0101] For the y direction:

[0102]

[0103] S56. For given boundary conditions:

[0104] Initial position: x(0)=0, y(0)=0;

[0105] End position: x(T)=1000, y(T)=1000, T is the total running time;

[0106] Speed ​​Constraints:

[0107] S57. Solve the differential equations:

[0108] Can get and The expression is:

[0109]

[0110] Where θ(t) is obtained by solving the above differential equations;

[0111] The actual running speed of the intelligent sanitation vehicle a for:

[0112]

[0113] Furthermore, the method of integrating the odor concentration distribution function and the population density distribution function to obtain the objective function and calculating the value of the objective function to calculate the impact of the route of the intelligent sanitation vehicle on the surrounding environment when performing the garbage collection task includes:

[0114] S61. Define the objective function:

[0115]

[0116] Among them, C(x, y, z, t) is the odor concentration distribution function, P(x, y, z) is the population density distribution function, Ω is the spatial calculation domain, which represents the entire calculation area, such as a block or urban area, and T is the total operation time; J reflects the impact of the garbage collection route of the intelligent sanitation vehicle on the surrounding environment. The smaller the J value, the better the route;

[0117] From the objective function, it can be concluded that ΔJ = C·P·Δt;

[0118] S62. Calculate the value of the objective function J:

[0119] In the total time T of the intelligent sanitation vehicle performing the garbage removal task, 5 time points are selected, namely t1~t5. Calculation results: Through the formula Δx=v·cos(θ)·Δt, Δy=v·sin(θ)·Δt, we get the coordinate values ​​of the key points (x1,y1)~(x5,y5) corresponding to the five time points; Substitute the known parameters t1~t5, (x1,y1)~(x5,y5) into the formulas C(x,y,t) and P(x,y) to get C1~C5 and P1~P5; Substitute C1~C5 and P1~P5 into ΔJ=C·P·Δt to get ΔJ1~ΔJ5;

[0120] Furthermore, the objective function calculation result is compared and verified with the speed condition, and then the Lagrange multiplier is iteratively solved for the objective function value at logarithmic intervals until the optimal cleaning route condition is met, and the method for sending the optimal cleaning route to the intelligent sanitation vehicle includes:

[0121] S71, define the optimal cleaning route condition as: satisfying the speed constraint condition, and the actual running speed of the intelligent sanitation vehicle is less than the expected speed v m, the deviation between the two is less than Δv, Δv is the speed deviation, which can be defined according to the actual situation; the objective function J is the smallest, and further increasing λ will not reduce J;

[0122] S72, set the Lagrange multiplier λ iteration condition: use logarithmic interval to take values ​​in the range of [0.1,10]; calculate the actual running speed v of the intelligent sanitation vehicle a and the value of the objective function J, iterate λ and compare it with the optimal cleaning route conditions. If it is not met, the current λ value continues to iterate until the optimal cleaning route conditions are met and the optimal cleaning route is sent to the intelligent sanitation vehicle.

[0123] Based on the same inventive concept, on the other hand, the present invention also provides a municipal garbage collection vehicle route planning system, the system comprising:

[0124] The data collection module is used to obtain the meteorological data, intelligent sanitation vehicle operation data and block data of the block where the garbage collection route is located, and send the meteorological data, intelligent sanitation vehicle operation data and block data to the model calculation module; the meteorological data includes ambient temperature, relative humidity, and dominant wind direction data; the intelligent sanitation vehicle operation data includes vehicle operation speed; the block data includes residential type, block area, and block center population density;

[0125] The first calculation module is used to establish a garbage decomposition rate model for the block, and to modify the garbage decomposition rate model by combining the relative humidity correction factor. The meteorological data is substituted into the modified garbage decomposition rate model for the block to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions, so as to evaluate the urgency of garbage removal in the block.

[0126] The second calculation module is used to establish a propagation model of the odor in the air at the garbage source of the block, set initial conditions and boundary conditions for the location of the garbage source, perform Fourier transform on the diffusion equation to obtain the second equation, transform each term of the quadratic equation, obtain the time derivative term, the convection term, and the diffusion term in turn, combine all the transformed terms to obtain the third equation in the transformation domain, solve the third equation to obtain the fourth equation, perform inverse Fourier transform on the fourth equation to obtain the fifth equation, perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtain the garbage odor concentration function model;

[0127] The third calculation module is used to construct a block population density distribution function. On the basis of considering the garbage odor concentration function and the block population density distribution function, the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle is introduced to obtain the Lagrange function used to optimize the path. The Lagrange function is differentiated and substituted into the Euler-Lagrange equation to obtain the differential equation, and then the differential equation is solved to obtain the actual running speed of the intelligent sanitation vehicle;

[0128] The route optimization module is used to integrate the odor concentration distribution function and the population density distribution function to obtain the objective function. The value of the objective function is used to calculate the impact of the route on the surrounding environment when the intelligent sanitation vehicle performs the garbage collection task. The objective function calculation result is compared and verified with the speed condition, and then the Lagrange multiplier is iteratively solved at logarithmic intervals until the optimal collection route conditions are met, and the optimal collection route is sent to the intelligent sanitation vehicle.

[0129] (3) Beneficial effects

[0130] Compared with the prior art, the present invention has the following beneficial effects:

[0131] 1. It can calculate the garbage decomposition rate and time in different blocks, and can be used to evaluate the urgency of garbage removal in the blocks.

[0132] 2. It can calculate the dynamic cleaning routes of smart sanitation vehicles, reduce the impact of garbage odor on residential areas, and reduce the risk of environmental pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0133] Figure 1 A flowchart of a municipal garbage removal vehicle route planning method according to Embodiment 1 of the present invention;

[0134] Figure 2 This is a schematic diagram of the module composition of a municipal garbage collection vehicle route planning system according to Example 2 of the present invention. DETAILED DESCRIPTION

[0135] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0136] Before giving examples, it is necessary to explain the application scenarios of the present invention. The present invention is applied to intelligent garbage removal route planning.

[0137] Example 1: Figure 1 As shown, this embodiment provides a method for planning a route for a municipal garbage collection vehicle, the method comprising the following steps:

[0138] S1, obtains the meteorological data, intelligent sanitation vehicle operation data and block data of the block where the garbage collection route is located, and sends the meteorological data, intelligent sanitation vehicle operation data and block data to the model calculation module; the meteorological data includes ambient temperature, relative humidity, and dominant wind direction data; the intelligent sanitation vehicle operation data includes vehicle operation speed; the block data includes residential type, block area, and block center population density;

[0139] S2, establish a garbage decomposition rate model for the block, modify the garbage decomposition rate model by combining the relative humidity correction factor, substitute the meteorological data into the modified garbage decomposition rate model for the block to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions, and evaluate the urgency of garbage removal in the block;

[0140] S3, establish a propagation model of the odor in the air at the garbage source in the block, set the initial conditions and boundary conditions for the location of the garbage source, perform Fourier transform on the diffusion equation to obtain the second equation, transform each term of the quadratic equation, obtain the time derivative term, convection term, and diffusion term in turn, combine all the transformed terms to obtain the third equation in the transformation domain, solve the third equation to obtain the fourth equation, perform inverse Fourier transform on the fourth equation to obtain the fifth equation, perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtain the garbage odor concentration function model;

[0141] S4, constructing a block population density distribution function, and introducing the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle on the basis of considering the garbage odor concentration function and the block population density distribution function, obtaining the Lagrange function used to optimize the path, taking the derivative of each term of the Lagrange function and substituting it into the Euler-Lagrange equation to obtain the differential equation, and then solving the differential equation to obtain the actual running speed of the intelligent sanitation vehicle;

[0142] S5, integrate the odor concentration distribution function and the population density distribution function to obtain the objective function, calculate the value of the objective function to measure the impact of the route of the intelligent sanitation vehicle on the surrounding environment when performing the garbage collection task, compare and verify the objective function calculation result with the speed limit condition, and then iterate and solve the objective function value by increasing the Lagrange multiplier at logarithmic intervals until the optimal collection route conditions are met, and send the optimal collection route to the intelligent sanitation vehicle.

[0143] For example, the meteorological data, intelligent sanitation vehicle operation data, and block data of the block where the garbage collection route is located are obtained as follows:

[0144] Meteorological parameters: ambient temperature T = 301K (27°C), relative humidity of the three blocks ABC covered by the smart sanitation vehicle is RH A =0.6, RH B=0.5, RHC=0.7, the dominant wind directions of the three blocks ABC are u=2m / s, v=1m / s, w=0;

[0145] Intelligent sanitation vehicle operation data: vehicle running speed is the expected speed v m =10m / s;

[0146] The block data is: A is the commercial area, B is the residential area, C is the park area, and the block area is 1000km 2 , 20000km 2 , 5000km 2 The population density P0 of the block center is 200 people / km 2 , 500 people / km 2 , 50 people / km 2 .

[0147] Furthermore, the method for establishing a block garbage decomposition rate model includes:

[0148] k=Ae ―Ea / RT ;

[0149] Among them, k is the decomposition rate constant, A is the pre-exponential factor, which represents the frequency of molecular collisions and reflects the number of attempts to react per unit time, Ea is the activation energy, R is the gas constant, and T is the absolute temperature.

[0150] For example, according to the meteorological data of the block where the garbage collection route is located, the garbage decomposition parameters are set, activation energy Ea = 50 kJ / mol, gas constant R = 8.314 J / (mol·K), exponential factor A = 1×10 5 s -1 , absolute temperature T = 301K, then the decomposition rate constant k is:

[0151] k=Ae ―Ea / RT =1×10 5 ×e^(-50000 / (8.314×301))=2.31×10 -4 s -1 ;

[0152] Furthermore, the method of correcting the garbage decomposition rate model in combination with the relative humidity correction factor, substituting meteorological data into the corrected block garbage decomposition rate model to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions to evaluate the urgency of block garbage removal includes:

[0153] Modified garbage decomposition rate k a for:

[0154] k a = k·f(RH);

[0155] Among them, f(RH) is the humidity correction function, the value range is 0-1, RH is the relative humidity, when the relative humidity RH is less than the appropriate humidity RH opt hour, When the relative humidity RH is equal to the optimum humidity RH opt When the relative humidity RH is greater than the suitable humidity RH, f(RH) = 1; opt hour, RH opt For suitable humidity;

[0156] The time required for garbage removal is the garbage decomposition time, and the garbage decomposition time t is:

[0157] t=1 / k a ;

[0158] Based on the humidity of different blocks, the garbage decomposition time of different blocks is calculated to evaluate the urgency of garbage removal. The shorter the garbage decomposition time, the higher the urgency of garbage removal. The alarm with the minimum garbage decomposition time is taken, and smart sanitation vehicles are arranged for garbage removal first.

[0159] For example, assume that the smart sanitation vehicle is responsible for garbage collection in three blocks, namely, Area A, Area B, and Area C;

[0160] Area A is the city center with high temperature, dense population, large amount of garbage, heat island effect, moderate humidity, RH A =RH opt =0.6, so the garbage decomposition time k A for:

[0161] k A = k·f(RH A ) = k = 2.31 × 10 ―4 s ―1 ;

[0162]

[0163] Area B has a slightly lower temperature and humidity, RH B =0.5 <RH opt , so the garbage decomposition time k B for:

[0164]

[0165] Zone C has the highest temperature and humidity, RH C =0.7 <RH opt , so the garbage decomposition time k C for:

[0166]

[0167] The calculation results show that the shorter the garbage decomposition time in area A, the more urgent the garbage removal is, and smart sanitation vehicles should be given priority for garbage removal.

[0168] Furthermore, the method of establishing a propagation model of odor in the air at the garbage source in the block, setting initial conditions and boundary conditions for the location of the garbage source, performing Fourier transform on the diffusion equation to obtain a second equation, transforming each term of the second equation, sequentially obtaining the time derivative term, the convection term, and the diffusion term, combining all the transformed terms to obtain a third equation in the transformation domain, solving the third equation to obtain a fourth equation, performing inverse Fourier transform on the fourth equation to obtain a fifth equation, performing Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtaining the garbage odor concentration function model includes:

[0169] S41. Set the diffusion equation of odor propagation to:

[0170]

[0171] Where C is the odor concentration, x, y, z are the positions in three directions of the spatial coordinates, u, v, w are the wind speed components in the x, y, z directions respectively, and D is the diffusion coefficient of the odor substance;

[0172] S42. Assume that C(x,y,z,t) represents the odor concentration at the location (x,y,z) at time t, and set the initial conditions and boundary conditions for the location of the garbage source:

[0173] The initial conditions are:

[0174] C(x,y,z,0)=Qδ(x-x0)δ(y-y0)δ(z-z0);

[0175] Where C(x,y,z,0) represents the odor concentration at the coordinate (x,y,z) at time t=0, x0, y0, z0 are the positions of the initial source, and Q is the intensity of the garbage source;

[0176] The boundary conditions are:

[0177]

[0178] S43, introduce Fourier transform to get the second equation:

[0179] Forward transformation:

[0180] Inverse transformation:

[0181] S44, transform the terms of the second equation to obtain the time derivative term, convection term, and diffusion term in sequence:

[0182] Since t is independent of the spatial variables, the time derivative term is:

[0183] Using the derivative properties of the Fourier transform Get the convection term:

[0184]

[0185] Use the second derivative property of the Fourier transform: Get the diffusion term:

[0186]

[0187]

[0188] S45. Combine all transformed terms to obtain the third equation in the transformed domain:

[0189]

[0190] Transform the formula to get:

[0191]

[0192] S46. Solve the equation in the transform domain to obtain the fourth equation:

[0193] make Then the equation becomes:

[0194]

[0195] Solving the ordinary differential equation, we obtain:

[0196]

[0197] Where A is determined by the initial conditions;

[0198] S47. Confirm the initial conditions. The initial conditions for Fourier transform are:

[0199]

[0200] therefore,

[0201] A(k x ,k y ,k z )=Qexp(―i(k x x0+k y y0+k z z0)); S48, perform inverse Fourier transform on the formula to obtain the fifth equation:

[0202] The complete inverse transform expression is:

[0203]

[0204] Recombination index term:

[0205] For the x direction, merge k x Item:

[0206] For the y direction, merge with k y Item:

[0207] For the z direction, merge k z Item:

[0208] S49. Perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation:

[0209] Compute the Gaussian integral, using the integral formula for each direction:

[0210]

[0211] Evaluate the triple integral step by step:

[0212] First k x integral:

[0213]

[0214] The y and z directions are handled similarly;

[0215] The final garbage odor concentration function can be expressed as:

[0216]

[0217] Where x0, y0, z0 are the three coordinate positions of the initial source, all defined as 0, and z is 0. The garbage odor concentration function can be simplified as:

[0218]

[0219] For example, the garbage removal urgency of area A is the highest, and the intelligent sanitation vehicle is given priority for removal. Set the initial conditions of area A; establish a coordinate system based on the area of ​​area A, with the starting point (x0, y0) at (0, 0) and the end point: (1000, 1000), in m; the diffusion coefficient of the odor substance D = 0.1m 2 / s, garbage source intensity Q = 100kg / s; Substituting the above parameters into the garbage odor concentration function, we get:

[0220]

[0221] Furthermore, the method for constructing a block population density distribution function includes:

[0222] The block population density distribution function P(x,y,z) representing the relative population density is set as:

[0223]

[0224] Among them, x, y, z represent the spatial coordinate position, z is 0, and the population density distribution function can be simplified as:

[0225]

[0226] For example, the population density at the center of block A (0,0) is the highest, P = 1; for example, at point (100,100): x = 100, y = 100; substitute into the formula: P = e^(-(100 2 +100 2 ) / 106)=0.980, indicating that at a location about 141.4 m away from the center point (0,0,0), the population density is 98% of the center point.

[0227] Furthermore, the method of introducing the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle on the basis of considering the garbage odor concentration function and the block population density distribution function, obtaining the Lagrange function for optimizing the path, performing derivative operations on each term of the Lagrange function, substituting it into the Euler-Lagrange equation to obtain the differential equation, and then solving the differential equation to obtain the actual operating speed of the intelligent sanitation vehicle includes:

[0228] S51. First, construct the Lagrangian function L:

[0229]

[0230] Where λ(t) is the Lagrange multiplier used to ensure that the path satisfies the speed constraint, v m is the expected speed;

[0231] S52. Based on the Euler-Lagrange equation, for the path r(t) = [x(t), y(t)], the z direction is 0, satisfying:

[0232] Therefore, for x(t):

[0233] For y(t):

[0234] S53. Calculate the partial derivatives:

[0235]

[0236] in:

[0237]

[0238] then, The final expression of is:

[0239]

[0240] Similarly:

[0241]

[0242] in:

[0243]

[0244] then, The final expression of is:

[0245]

[0246] S54. Calculate the time derivative of the velocity related term:

[0247]

[0248] S55. Substitute the calculated terms in S54 into the Euler-Lagrange equation to obtain the differential equation: For the x direction:

[0249]

[0250] For the y direction:

[0251]

[0252] S56. For given boundary conditions:

[0253] Initial position: x(0)=0, y(0)=0;

[0254] End position: x(T)=1000, y(T)=1000, T is the total running time;

[0255] Speed ​​Constraints:

[0256] S57. Solve the differential equations:

[0257] Can get and The expression is:

[0258]

[0259] Where θ(t) is obtained by solving the above differential equations;

[0260] The actual running speed of the intelligent sanitation vehicle a for:

[0261]

[0262] For example, the value range of the Lagrange multiplier λ is set to [0.1, 10], λ1 is set to 0.1 for the first time, and λ1=0.1, v m =10Substitute into the Lagrangian function L formula:

[0263]

[0264] According to the Euler-Lagrange equation, we get:

[0265]

[0266] Calculated at the starting point (0,0), when t→0:

[0267]

[0268] We need to take the limit of t:

[0269]

[0270] therefore,

[0271] Substituting into the Euler-Lagrange equation we get:

[0272]

[0273] Similarly for the y direction:

[0274] Solve the equations of motion: get get

[0275] Considering the boundary conditions: (0,0) to (1000,1000), time T = 148.6s, we get:

[0276]

[0277] The actual running speed of the intelligent sanitation vehicle a for:

[0278]

[0279] The calculation results show that v a1The speed limit of 10 m / s is exceeded, indicating that the constraint is too weak when λ1 = 0.1.

[0280] Furthermore, the method of integrating the odor concentration distribution function and the population density distribution function to obtain the objective function and calculating the value of the objective function to calculate the impact of the route of the intelligent sanitation vehicle on the surrounding environment when performing the garbage collection task includes:

[0281] S61. Define the objective function:

[0282]

[0283] Among them, C(x, y, z, t) is the odor concentration distribution function, P(x, y, z) is the population density distribution function, Ω is the spatial calculation domain, which represents the entire calculation area, such as a block or urban area, and T is the total operation time; J reflects the impact of the garbage collection route of the intelligent sanitation vehicle on the surrounding environment. The smaller the J value, the better the route;

[0284] From the objective function, it can be concluded that ΔJ = C·P·Δt;

[0285] S62. Calculate the value of the objective function J:

[0286] In the total time T of the intelligent sanitation vehicle performing the garbage removal task, 5 time points are selected, namely t1~t5. The calculation results are as follows: Δx = v·cos(θ)·Δt, Δy = v·sin(θ)·Δt, and the coordinate values ​​of the key points corresponding to the five time points are obtained (x1, y1) to (x5, y5);

[0287] Substitute the known parameters t1~t5, (x1, y1)~(x5, y5) into the formulas C(x, y, t) and P(x, y) to obtain C1~C5 and P1~P5; substitute C1~C5 and P1~P5 into ΔJ=C·P·Δt to obtain ΔJ1~ΔJ5; when λ is known, according to the summation formula J=∑ΔJ i Calculate the value of J.

[0288] For example, λ1=0.1, v a1 =10.8, the coordinate positions of the sanitation vehicle at 5 time points on the route coordinates are: t=0s: (0,0); t=30s: (240,216); t=60s: (480,432); t=90s: (720,648); t=120s: (960,864);

[0289] Calculate the contribution of the time point to the objective function, substitute the five coordinate data into C(x,y,t),P(x,y),ΔJ=C·P·Δt, and get:

[0290] t=0s, ΔJ1=0; t=30s, ΔJ2=2.876×10 ―3 ;t=60s, ΔJ3=2.245×10-3; t=90s, ΔJ4

[0291] =1.987×10-3; t=120s, ΔJ5=1.765×10-3; J1=ΔJ1+ΔJ2+ΔJ3+ΔJ4+ΔJ5

[0292] =8.873×10-3, indicating that the route has a greater impact on residents, mainly because the speed is too fast (10.8>10m / s). The route is close to densely populated areas and needs to increase λ to strengthen speed constraints.

[0293] Furthermore, the objective function calculation result is compared and verified with the speed condition, and then the Lagrange multiplier is iteratively solved for the objective function value at logarithmic intervals until the optimal cleaning route condition is met, and the method for sending the optimal cleaning route to the intelligent sanitation vehicle includes:

[0294] S71, define the optimal cleaning route condition as: satisfying the speed constraint condition, and the actual running speed of the intelligent sanitation vehicle is less than the expected speed v m , the deviation between the two is less than Δv, Δv is the speed deviation, which can be defined according to the actual situation; the objective function J is the smallest, and further increasing or decreasing λ will not reduce J;

[0295] S72, set the Lagrange multiplier λ iteration condition: use logarithmic interval to take values ​​in the range of [0.1,10]; calculate the actual running speed v of the intelligent sanitation vehicle a and the value of the objective function J, iterate λ and compare it with the optimal cleaning route conditions. If it is not met, the current λ value continues to iterate until the optimal cleaning route conditions are met and the optimal cleaning route is sent to the intelligent sanitation vehicle.

[0296] For example, the speed deviation Δv is defined as 0.1, when v a >v m +0.1=10.1m / s, λ needs to be increased; when v a <v m ―0.1=9.9m / s, it needs to be reduced; when λ1=0.1, v a1 =10.8, J1 = 8.873×10-3, so the value of λ needs to be increased. Use the logarithmic interval to select the value of λ in the range of [0.1,10]. The calculation results are as follows:

[0297] λ2=0.3,v a2 =10.6m / s, J2=7.654×10 ―3 ;

[0298] λ3=0.4,v a3 =10.5m / s, J3=6.987×10 ―3 ;

[0299] λ4=0.48,v a4 =10.45m / s, J4=6.234×10 ―3 ;

[0300] λ5=0.534,v a5 =10.4m / s, J5=5.12×10 ―3 ;

[0301] λ6=0.82,v a6 =10.3m / s, J6=4.876×10 -3 ;

[0302] λ7=0.95,v a7 =10.25m / s, J7=4.543×10 -3 ;

[0303] λ8=1.21,v a8 =10.2m / s, J8=4.15×10 -3 ;

[0304] λ9=1.45,v a9 =10.15m / s, J9=3.876×10 ―3 ;

[0305] l 10 =1.78,va 10 =10.1m / s, J 10 =3.654×10 ―3 ;

[0306] l 11 =2.1, v a11 =10.05m / s, J 11 =3.432×10 -3 ;

[0307] l 12 =2.34, v a12 =10m / s, J 12 =3.24×10 -3 ;

[0308] l 13 =2.86, v a13 =9.51m / s, J 13 =3.015×10 -3 ;

[0309] The results show that after 12 iterations, λ reaches the expected speed v m =10m / s, and the value of J reaches the minimum; iterate once more to verify, λ 13 The actual running speed v of the intelligent sanitation vehicle a13 >v m +0.1, does not meet the speed constraint condition, so λ 12 =2.34, v a12 When =10, the curve drawn by the fitted coordinate values ​​through the formula Δx=v·cos(θ)·Δt, Δy=v·sin(θ)·Δt is the optimal transportation route.

[0310] Embodiment 2: Based on the same inventive concept, Figure 2 As shown, this embodiment also provides a municipal garbage collection vehicle route planning system, the system comprising:

[0311] The data collection module is used to obtain the meteorological data, intelligent sanitation vehicle operation data and block data of the block where the garbage collection route is located, and send the meteorological data, intelligent sanitation vehicle operation data and block data to the model calculation module; the meteorological data includes ambient temperature, relative humidity, and dominant wind direction data; the intelligent sanitation vehicle operation data includes vehicle operation speed; the block data includes residential type, block area, and block center population density;

[0312] The first calculation module is used to establish a garbage decomposition rate model for the block, and to modify the garbage decomposition rate model by combining the relative humidity correction factor. The meteorological data is substituted into the modified garbage decomposition rate model for the block to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions, so as to evaluate the urgency of garbage removal in the block.

[0313] The second calculation module is used to establish a propagation model of the odor in the air at the garbage source of the block, set initial conditions and boundary conditions for the location of the garbage source, perform Fourier transform on the diffusion equation to obtain the second equation, transform each term of the quadratic equation, obtain the time derivative term, the convection term, and the diffusion term in turn, combine all the transformed terms to obtain the third equation in the transformation domain, solve the third equation to obtain the fourth equation, perform inverse Fourier transform on the fourth equation to obtain the fifth equation, perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtain the garbage odor concentration function model;

[0314] The third calculation module is used to construct a block population density distribution function. On the basis of considering the garbage odor concentration function and the block population density distribution function, the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle is introduced to obtain the Lagrange function used to optimize the path. The Lagrange function is differentiated and substituted into the Euler-Lagrange equation to obtain the differential equation, and then the differential equation is solved to obtain the actual running speed of the intelligent sanitation vehicle;

[0315] The route optimization module is used to integrate the odor concentration distribution function and the population density distribution function to obtain the objective function. The value of the objective function is used to calculate the impact of the route on the surrounding environment when the intelligent sanitation vehicle performs the garbage collection task. The objective function calculation result is compared and verified with the speed condition, and then the Lagrange multiplier is iteratively solved at logarithmic intervals until the optimal collection route conditions are met, and the optimal collection route is sent to the intelligent sanitation vehicle.

[0316] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0317] Finally, it should be noted that: Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for planning a route for a municipal garbage collection vehicle, characterized in that: The method comprises the following steps: S1, obtains the meteorological data, intelligent sanitation vehicle operation data and block data of the block where the garbage collection route is located, and sends the meteorological data, intelligent sanitation vehicle operation data and block data to the model calculation module; the meteorological data includes ambient temperature, relative humidity, and dominant wind direction data; the intelligent sanitation vehicle operation data includes vehicle operation speed; the block data includes residential type, block area, and block center population density; S2, establish a garbage decomposition rate model for the block, modify the garbage decomposition rate model by combining the relative humidity correction factor, substitute the meteorological data into the modified garbage decomposition rate model for the block to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions, and evaluate the urgency of garbage removal in the block; S3, establish a propagation model of the odor in the air at the garbage source in the block, set the initial conditions and boundary conditions for the location of the garbage source, perform Fourier transform on the diffusion equation to obtain the second equation, transform each term of the quadratic equation, obtain the time derivative term, convection term, and diffusion term in turn, combine all the transformed terms to obtain the third equation in the transformation domain, solve the third equation to obtain the fourth equation, perform inverse Fourier transform on the fourth equation to obtain the fifth equation, perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtain the garbage odor concentration function model; S4, constructing a block population density distribution function, and introducing the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle on the basis of considering the garbage odor concentration function and the block population density distribution function, obtaining the Lagrange function used to optimize the path, taking the derivative of each term of the Lagrange function and substituting it into the Euler-Lagrange equation to obtain the differential equation, and then solving the differential equation to obtain the actual running speed of the intelligent sanitation vehicle; S5, integrate the odor concentration distribution function and the population density distribution function to obtain the objective function, calculate the value of the objective function to measure the impact of the route of the intelligent sanitation vehicle on the surrounding environment when performing the garbage collection task, compare and verify the objective function calculation result with the speed limit condition, and then iterate and solve the objective function value by increasing the Lagrange multiplier at logarithmic intervals until the optimal collection route conditions are met, and send the optimal collection route to the intelligent sanitation vehicle.

2. A municipal garbage removal vehicle route planning method according to claim 1, characterized in that: The method for establishing a block garbage decomposition rate model comprises: k=Yes -Ea / RT ; Among them, k is the decomposition rate constant, A is the pre-exponential factor, which represents the frequency of molecular collisions and reflects the number of attempts to react per unit time, Ea is the activation energy, R is the gas constant, and T is the absolute temperature.

3. A municipal garbage removal vehicle route planning method according to claim 2, characterized in that: The method of correcting the garbage decomposition rate model by combining the relative humidity correction factor, substituting meteorological data into the corrected block garbage decomposition rate model to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions to evaluate the urgency of block garbage removal includes: Modified garbage decomposition rate k a for: k a =k·f(RH); Among them, f(RH) is the humidity correction function, the value range is 0-1, RH is the relative humidity, when the relative humidity RH is less than the appropriate humidity RH opt hour, When the relative humidity RH is equal to the optimum humidity RH opt When the relative humidity RH is greater than the suitable humidity RH, f(RH) = 1; opt hour, RH opt For suitable humidity; The time required for garbage removal is the garbage decomposition time, and the garbage decomposition time t is: t=1 / k a ; Based on the humidity of different blocks, the garbage decomposition time of different blocks is calculated to evaluate the urgency of garbage removal. The shorter the garbage decomposition time, the higher the urgency of garbage removal. The alarm with the minimum garbage decomposition time is taken, and smart sanitation vehicles are arranged for garbage removal first.

4. A method for planning a route for a municipal garbage collection vehicle according to claim 3, characterized in that: The method of establishing a propagation model of odor in the air at a garbage source in a block, setting initial conditions and boundary conditions for the location of the garbage source, performing Fourier transform on the diffusion equation to obtain a second equation, transforming each term of the second equation, sequentially obtaining a time derivative term, a convection term, and a diffusion term, combining all the transformed terms to obtain a third equation in the transformation domain, solving the third equation to obtain a fourth equation, performing inverse Fourier transform on the fourth equation to obtain a fifth equation, performing Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtaining a garbage odor concentration function model includes: S41. Set the diffusion equation of odor propagation to: Where C is the odor concentration, x, y, z are the positions in three directions of the spatial coordinates, u, v, w are the wind speed components in the x, y, z directions respectively, and D is the diffusion coefficient of the odor substance; S42. Assume that C(x, y, z, t) represents the odor concentration at the position (x, y, z) at time t, and set the initial conditions and boundary conditions for the location of the garbage source: The initial conditions are: C(x,y,z,0)=Qδ(x-x0)δ(y-y0)δ(z-z0); Where C(x, y, z, 0) represents the odor concentration at the coordinate (x, y, z) at time t = 0, x0, y0, z0 are the positions of the initial source, and Q is the intensity of the garbage source; The boundary conditions are: S43, introduce Fourier transform to get the second equation: Forward transformation: Inverse transformation: S44, transform the terms of the second equation to obtain the time derivative term, convection term, and diffusion term in sequence: Since t is independent of the spatial variables, the time derivative term is: Using the derivative properties of the Fourier transform Get the convection term: Use the second derivative property of the Fourier transform: Get the diffusion term: S45. Combine all transformed terms to obtain the third equation in the transformed domain: Transform the formula to get: S46. Solve the equation in the transform domain to obtain the fourth equation: make Then the equation becomes: Solving the ordinary differential equation, we obtain: Where A is determined by the initial conditions; S47. Confirm the initial conditions. The initial conditions for Fourier transform are: therefore, A(k x ,k y ,k z )=Qexp(-i(k x x0+k y y0+k z z0)); S48. Perform inverse Fourier transform on the formula to obtain the fifth equation: The complete inverse transform expression is: Recombination index term: For the x direction, merge k x Item: For the y direction, merge with k y Item: For the z direction, merge k z Item: S49. Perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation: Compute the Gaussian integral, using the integral formula for each direction: Evaluate the triple integral step by step: First k x integral: The y and z directions are handled similarly; The final garbage odor concentration function can be expressed as: Where x0, y0, z0 are the three coordinate positions of the initial source, all defined as 0, and z is 0. The garbage odor concentration function can be simplified as:

5. A method for planning a route for a municipal garbage collection vehicle according to claim 4, characterized in that: The method for constructing a block population density distribution function comprises: The block population density distribution function P(x, y, z) representing the relative population density is set as: Among them, P0 is the population density of the block center, x, y, z represent the spatial coordinate position, z is 0, and the population density distribution function can be simplified as:

6. A method for planning a route for a municipal garbage collection vehicle according to claim 5, characterized in that: The method of introducing the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle on the basis of considering the garbage odor concentration function and the block population density distribution function, obtaining the Lagrange function for optimizing the path, performing derivative operations on each term of the Lagrange function, substituting the derivatives into the Euler-Lagrange equation to obtain the differential equation, and then solving the differential equation to obtain the actual running speed of the intelligent sanitation vehicle includes: S51. First, construct the Lagrangian function L: Where λ(t) is the Lagrange multiplier used to ensure that the path satisfies the speed constraint, v m is the expected speed; S52. Based on the Euler-Lagrange equation, for the path r(t) = [x(t), y(t)], the z direction is 0, satisfying: Therefore, for x(t): For y(t): S53. Calculate the partial derivatives: in: then, The final expression of is: Similarly: in: then, The final expression of is: S54. Calculate the time derivative of the velocity related term: S55. Substitute the calculated terms in S54 into the Euler-Lagrange equation to obtain the differential equation: For the x direction: For the y direction: S56. For given boundary conditions: Initial position: x(0)=0, y(0)=0; End position: x(T)=1000, y(T)=1000, T is the total running time; Speed ​​Constraints: S57. Solve the differential equations: Can get and The expression is: Where θ(t) is obtained by solving the above differential equations; The actual running speed of the intelligent sanitation vehicle a for:

7. A method for planning a route for a municipal garbage collection vehicle according to claim 6, characterized in that: The method of integrating the odor concentration distribution function and the population density distribution function to obtain the objective function and calculating the value of the objective function to use for the impact of the route of the intelligent sanitation vehicle on the surrounding environment when performing the garbage removal task includes: S61. Define the objective function: Among them, C(x, y, z, t) is the odor concentration distribution function, P(x, y, z) is the population density distribution function, Ω is the spatial calculation domain, which represents the entire calculation area, such as a block or urban area, and T is the total operation time; J reflects the impact of the garbage collection route of the intelligent sanitation vehicle on the surrounding environment. The smaller the J value, the better the route; From the objective function, it can be concluded that ΔJ = C·P·Δt; S62. Calculate the value of the objective function J: In the total time T of the intelligent sanitation vehicle performing the garbage removal task, 5 time points are selected, namely t1~t5. Calculation results: Through the formula Δx=v·cos(θ)·Δt, Δy=v·sin(θ)·Δt, we get the coordinate values ​​of the key points (x1, y1)~(x5, y5) corresponding to the five time points; Substitute the known parameters t1~t5, (x1, y1)~(x5, y5) into the formulas C(x, y, t) and P(x, y) to obtain C1~C5 and P1~P5 respectively; Substitute C1~C5 and P1~P5 into ΔJ=C·P·Δt to obtain ΔJ1~ΔJ5.

8. A method for planning a route for a municipal garbage collection vehicle according to claim 7, characterized in that: The method of comparing and verifying the objective function calculation result with the speed condition, and then iteratively solving the objective function value by increasing the Lagrange multiplier at logarithmic intervals until the optimal cleaning route condition is met, and sending the optimal cleaning route to the intelligent sanitation vehicle includes: S71, define the optimal cleaning route condition as: satisfying the speed constraint condition, and the actual running speed of the intelligent sanitation vehicle is less than the expected speed v m , the deviation between the two is less than Δv, Δv is the speed deviation, which can be defined according to the actual situation; the objective function J is the smallest, and further increasing λ will not reduce J; S72, set the Lagrange multiplier λ iteration condition: use logarithmic interval to take values ​​in the range of [0.1, 10]; calculate the actual running speed v of the intelligent sanitation vehicle a and the value of the objective function J, iterate λ and compare it with the optimal cleaning route conditions. If it is not met, the current λ value continues to iterate until the optimal cleaning route conditions are met and the optimal cleaning route is sent to the intelligent sanitation vehicle.

9. A municipal garbage collection vehicle route planning system, characterized in that: The system comprises: The data collection module is used to obtain the meteorological data, intelligent sanitation vehicle operation data and block data of the block where the garbage collection route is located, and send the meteorological data, intelligent sanitation vehicle operation data and block data to the model calculation module; the meteorological data includes ambient temperature, relative humidity, and dominant wind direction data; the intelligent sanitation vehicle operation data includes vehicle operation speed; the block data includes residential type, block area, and block center population density; The first calculation module is used to establish a garbage decomposition rate model for the block, and to modify the garbage decomposition rate model by combining the relative humidity correction factor. The meteorological data is substituted into the modified garbage decomposition rate model for the block to calculate the garbage decomposition rate and garbage decomposition time under different environmental conditions, so as to evaluate the urgency of garbage removal in the block. The second calculation module is used to establish a propagation model of the odor in the air at the garbage source of the block, set initial conditions and boundary conditions for the location of the garbage source, perform Fourier transform on the diffusion equation to obtain the second equation, transform each term of the quadratic equation, obtain the time derivative term, the convection term, and the diffusion term in turn, combine all the transformed terms to obtain the third equation in the transformation domain, solve the third equation to obtain the fourth equation, perform inverse Fourier transform on the fourth equation to obtain the fifth equation, perform Gaussian integral calculation and triple integral calculation on each direction of the fifth equation, and finally obtain the garbage odor concentration function model; The third calculation module is used to construct a block population density distribution function. On the basis of considering the garbage odor concentration function and the block population density distribution function, the Lagrange multiplier of the speed constraint condition of the intelligent sanitation vehicle is introduced to obtain the Lagrange function used to optimize the path. The Lagrange function is differentiated and substituted into the Euler-Lagrange equation to obtain the differential equation, and then the differential equation is solved to obtain the actual running speed of the intelligent sanitation vehicle; The route optimization module is used to integrate the odor concentration distribution function and the population density distribution function to obtain the objective function. The value of the objective function is used to calculate the impact of the route on the surrounding environment when the intelligent sanitation vehicle performs the garbage collection task. The objective function calculation result is compared and verified with the speed condition, and then the Lagrange multiplier is iteratively solved at logarithmic intervals until the optimal collection route conditions are met, and the optimal collection route is sent to the intelligent sanitation vehicle.

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