An Optimization Method for the Illuminance Uniformity of the Projection Image of an Intelligent Self-Closed-Loop Vehicle Light Carpet

Abstract

The present invention discloses an optimization method for the illuminance uniformity of the projection image of an intelligent self-closed-loop vehicle headlight light carpet, belonging to the technical field of intelligent vehicle headlights. It includes the following steps: Step S1, define the parameters of the projection system as a particle swarm, and initialize the position and velocity of the particles; Step S2, define the fitness evaluation function of each particle; Step S3, update the velocity and position of each particle according to the particle swarm optimization algorithm formula; Step S4, calculate the fitness value of the particle according to the updated position vector of the particle; Step S5, determine whether the iteration termination condition is satisfied. If the iteration termination condition is satisfied, output the optimal projection system parameters. If the iteration termination condition is not satisfied, jump to Step S3. The present invention provides an optimization method for the illuminance uniformity of the projection image of an intelligent self-closed-loop vehicle headlight light carpet, effectively improving the illuminance uniformity of the projection image, significantly enhancing the quality and adaptability of the light carpet projection, and improving the visual effect of the light carpet projection.

Description

Technical Field

[0001] The present invention relates to an optimization method for the illuminance uniformity of the projected image of an intelligent self-closed-loop vehicle light carpet, belonging to the technical field of intelligent vehicle lights. Background Art

[0002] At present, with the rapid advancement of cutting-edge technologies such as autonomous driving and intelligent networking, intelligent vehicle lights have evolved from simple lighting tools into key interfaces for complex interactions between vehicles and the outside world. The optimization of vehicle light performance and the improvement of the intelligent level not only directly relate to the safety of vehicles in complex traffic environments but also profoundly affect the overall experience of drivers and passengers. Against this background, the vehicle light carpet projection technology, as an extremely innovative lighting and interaction means, is gradually emerging. By projecting images or digital information onto the ground, it realizes effective communication between vehicles and between vehicles and people.

[0003] Although the vehicle light carpet projection technology shows great application potential and market prospects, its current development still faces a series of technical and implementation challenges. One of the most prominent problems is the uneven illuminance distribution of the projected image. During the projection process, due to the limitations of the light source intensity, lens design, and image processing algorithms, there are significant differences in the brightness of the projected image, with some areas being too bright or too dark, which in turn affects the clarity and readability of the information. This not only reduces the efficiency of information transmission but also may cause misunderstandings or confusion, undoubtedly increasing the potential safety risks for traffic participants who rely on this information for quick decision-making. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide an optimization method for the illuminance uniformity of the projected image of an intelligent self-closed-loop vehicle light carpet, which realizes the parameter optimization of the vehicle light carpet projection system, effectively improves the illuminance uniformity of the projected image, significantly enhances the quality and adaptability of the vehicle light carpet projection, improves the visual effect and user experience of the vehicle light carpet projection, has the advantages of high computational efficiency and fast convergence speed, and provides a safer, more efficient, and more comfortable lighting and interaction solution for vehicles.

[0005] To solve the above technical problems, the technical solution of the present invention is as follows:

[0006] The present invention provides an optimization method for the illuminance uniformity of the projected image of an intelligent self-closed-loop vehicle light carpet, which includes the following steps:

[0007] Step S1: Define the parameters of the projection system as a particle swarm, and initialize the position and velocity of the particles. The parameters of the projection system include the light source position, lens focal length, projection angle, and projection brightness;

[0008] Step S2: Define the fitness evaluation function for each particle according to the components of the particle position vector in the horizontal and vertical directions and the uniformity of the headlight projection illumination.

[0009] Step S3: Update the velocity and position of each particle according to the velocity and position update formulas of the particle swarm optimization algorithm.

[0010] Step S4: Calculate the fitness value of the particle according to the position vector of the updated particle.

[0011] Step S5: Determine whether the iteration termination condition is satisfied. The iteration termination condition is that the preset maximum number of iterations is reached or the fitness value of the particle satisfies the preset condition. If the iteration termination condition is satisfied, output the optimal projection system parameters; if the iteration termination condition is not satisfied, jump to Step S3.

[0012] Furthermore, in Step S1, define the parameters of the projection system as a particle swarm, and initialize the position and velocity of the particle, which specifically includes the following steps:

[0013] Step S11: Define all the parameters of the projection system as a particle swarm, and each particle in the particle swarm represents a set of projection system parameters.

[0014] Step S12: Set the position vector and velocity vector of each particle, and the velocity vector and position vector of each particle have the same number of components.

[0015] Step S13: Randomly initialize the position and velocity of the particle.

[0016] Furthermore, in Step S12, the calculation formula for the position vector of each particle is as follows:

[0017] ;

[0018] where and are the coordinate positions of the central axis of the light source projection module;

[0019] is the focal length of the projection lens;

[0020] is the headlight projection angle;

[0021] is the headlight projection brightness adjustment coefficient;

[0022] The calculation formula for the velocity vector of each particle is as follows:

[0023] ;

[0024] where is the velocity vector component of the light source projection module in the X direction;

[0025] is the velocity vector component of the light source projection module in the Y direction;

[0026] is the velocity vector component based on the focal length of the projection lens;

[0027] is the velocity vector component based on the projection angle of the vehicle headlight;

[0028] is the velocity vector component based on the brightness adjustment coefficient.

[0029] Further, in step S13, the positions and velocities of the particles are randomly initialized, which specifically includes the following steps:

[0030] Randomly select the initial value of each component of the particle position vector within the feasible position range of the parameters corresponding to each component of the particle position vector to complete the random initialization of the particle position;

[0031] Randomly select the initial value of each component of the particle velocity vector within the feasible velocity range of the parameters corresponding to each component of the particle velocity vector, and multiply it by a scaling factor to complete the random initialization of the particle velocity.

[0032] Further, the step of randomly selecting the initial value of each component of the particle position vector within the feasible position range of the parameters corresponding to each component of the particle position vector to complete the random initialization of the particle position specifically includes the following steps:

[0033] The calculation formula for the initial value of the coordinate position of the central axis of the light source projection module is as follows:

[0034] ;

[0035] ;

[0036] The calculation formula for the initial value of the focal length of the projection lens is as follows:

[0037] ;

[0038] The calculation formula for the initial value of the projection angle of the vehicle headlight is as follows:

[0039] ;

[0040] The calculation formula for the initial value of the projection brightness adjustment coefficient of the vehicle headlight is as follows:

[0041] ;

[0042] Among them, is a function for generating random numbers;

[0043] and are respectively the minimum and maximum values of the physical limit in the X - direction of the headlight installation position;

[0044] and are respectively the minimum and maximum values of the physical limit in the Y - direction of the headlight installation position;

[0045] and are respectively the minimum and maximum values of the projection lens focal length designed for the lens of the projection lens;

[0046] and are respectively the minimum and maximum values of the adjustable projection angle of the projection module.

[0047] Furthermore, the initial value of each component of the particle velocity vector includes the initial value of the velocity vector component in the X - direction of the light source projection module, the initial value of the velocity vector component in the Y - direction of the light source projection module, the initial value of the velocity vector component based on the projection lens focal length, the initial value of the velocity vector component based on the headlight projection angle, and the initial value of the velocity vector component based on the brightness adjustment coefficient.

[0048] Furthermore, the calculation formula for the initial value of the velocity vector component in the X - direction of the light source projection module is as follows:

[0049] ;

[0050] The calculation formula for the initial value of the velocity vector component in the Y - direction of the light source projection module is as follows:

[0051] ;

[0052] The calculation formula for the initial value of the velocity vector component based on the projection lens focal length is as follows:

[0053] ;

[0054] The calculation formula for the initial value of the velocity vector component based on the headlight projection angle is as follows:

[0055] ;

[0056] The calculation formula for the initial value of the velocity vector component based on the brightness adjustment coefficient is as follows:

[0057] ;

[0058] Among them, 、 and are scaling factors set according to actual requirements;

[0059] is a function for generating random numbers.

[0060] Furthermore, in the step S2, the calculation formula of the fitness evaluation function is as follows:

[0061] ;

[0062] Among them, is the horizontal component of the particle position vector;

[0063] is the vertical component of the particle position vector;

[0064] Uniformity Ratio of Illuminance is the percentage of the uniformity of the headlight projection illuminance;

[0065] and are weight coefficients.

[0066] Furthermore, in the step S3, the velocity and position update formulas of the particle swarm optimization algorithm are as follows:

[0067] ;

[0068] ;

[0069] Among them, is the velocity of particle i at time t;

[0070] is the velocity of particle i at time;

[0071] is the position of particle i at time t;

[0072] is the position of particle i at time;

[0073] is the inertia coefficient;

[0074] and are acceleration coefficients;

[0075] is a random number between 0 and 1;

[0076] is the historical optimal position of particle i;

[0077] is the global optimal position of the entire particle swarm.

[0078] Furthermore, in step S4, according to the updated position vector of the particle, the fitness value of the particle is calculated, which specifically includes the following steps:

[0079] Substitute the horizontal component and the vertical component of the updated position vector of the particle into the fitness evaluation function respectively to calculate the fitness value of the particle.

[0080] Adopting the above technical solution, the present invention has the following beneficial effects:

[0081] Introduce the particle swarm optimization algorithm into the vehicle light carpet projection technology, utilize the global search ability of the particle swarm optimization algorithm to iteratively optimize the key parameters of the projection system, and gradually approach the optimal projection system parameters, which is beneficial to minimizing the problem of uneven illuminance of the projection image and maximizing the projection efficiency and projection clarity. During the process of gradually approaching the optimal projection system parameters, the fitness evaluation function is used to evaluate the pros and cons of the projection system parameters, significantly improving the quality and adaptability of the vehicle light carpet projection, enhancing the visual effect and user experience of the vehicle light carpet projection, providing a safer, more efficient and comfortable lighting and interaction solution for the vehicle, and having the advantages of high calculation efficiency and fast convergence speed. This technology is expected to be widely applied in intelligent connected vehicles, autonomous driving vehicles and smart city traffic systems, promoting the innovation and development of automotive lighting technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 is the flowchart of the optimization method for the illuminance uniformity of the intelligent self-closed-loop vehicle light carpet projection image of the present invention;

[0083] Figure 2 is the flowchart of the method for defining the parameters of the projection system as a particle swarm and initializing the position and velocity of the particles of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0084] In order to make the content of the present invention easier to be clearly understood, the present invention will be further described in detail below according to specific embodiments in conjunction with the accompanying drawings.

[0085] As Figure 1 shown, this embodiment provides an optimization method for the illuminance uniformity of an intelligent self-closed-loop vehicle light carpet projection image, which includes the following steps:

[0086] Step S1: Define the parameters of the projection system as a particle swarm, and initialize the position and velocity of the particles. Among them, the parameters of the projection system include the light source position, lens focal length, projection angle, and projection brightness. The position of a particle refers to the coordinate or parameter value of the particle in the search space, and the velocity of the particle refers to the moving direction and step size of the particle in the search space;

[0087] As Figure 2 shown, step S1 of this embodiment specifically includes the following steps:

[0088] Step S11: Define all the parameters of the projection system as a particle swarm, set the number of particles in the particle swarm to N, and each particle in the particle swarm represents a set of projection system parameters;

[0089] Specifically, the selection and setting of the number of particles N are generally determined according to the complexity of the problem and computing resources. For the optimization problem of the vehicle headlight carpet projection image, N is considered to be set to a moderate value to balance the comprehensiveness of the algorithm search and the computing efficiency. In particular, for example, N = 30, which means that the algorithm will process 30 different combinations of projection system parameters simultaneously;

[0090] Step S12: Set the position vector and velocity vector of each particle, and the velocity vector and position vector of each particle have the same number of components, so as to update the value of each parameter during the iteration process;

[0091] The calculation formula for the position vector of each particle in this embodiment is as follows:

[0092] ;

[0093] Among them, and are the coordinate positions of the central axis of the light source projection module;

[0094] is the focal length of the projection lens;

[0095] is the headlight projection angle;

[0096] is the headlight projection brightness adjustment coefficient.

[0097] The calculation formula for the velocity vector of each particle in this embodiment is as follows:

[0098] ;

[0099] Among them, is the velocity vector component of the light source projection module in the X direction;

[0100] is the velocity vector component of the light source projection module in the Y direction;

[0101] is the velocity vector component based on the focal length of the projection lens;

[0102] is the velocity vector component based on the projection angle of the vehicle headlight;

[0103] is the velocity vector component based on the brightness adjustment coefficient.

[0104] Step S13: Randomly initialize the position and velocity of the particles to ensure that the algorithm can explore the entire search space, which specifically includes the following steps:

[0105] Randomly select the initial value of each component of the particle position vector within the feasible position range of the parameters corresponding to each component of the particle position vector to complete the random initialization of the particle position, which specifically includes the following steps:

[0106] Randomly select the initial value of the coordinate position of the central axis of the light source projection module within the physical limit values in the X and Y directions of the vehicle headlight installation position. The calculation formula for the initial value of the coordinate position of the central axis of the light source projection module is as follows:

[0107] ;

[0108] ;

[0109] Randomly select the initial value of the focal length of the projection lens within the design range corresponding to the lens of the projection lens. The calculation formula for the initial value of the focal length of the projection lens is as follows:

[0110] ;

[0111] Randomly select the initial value of the projection angle of the vehicle headlight within the adjustable angle range of the projection module. The calculation formula for the initial value of the projection angle of the vehicle headlight is as follows:

[0112] ;

[0113] Randomly select the initial value of the brightness adjustment coefficient of the vehicle headlight projection between 0 and 1. The calculation formula for the initial value of the brightness adjustment coefficient of the vehicle headlight projection is as follows:

[0114] ;

[0115] where is the function to generate random numbers;

[0116] and The minimum and maximum physical limit values in the X direction of the headlight installation position, respectively;

[0117] and The minimum and maximum physical limit values in the Y direction of the headlight installation position, respectively;

[0118] and The minimum and maximum values of the projection lens focal length designed for the lens of the projection lens, respectively;

[0119] and The minimum and maximum values of the adjustable projection angle of the projection module, respectively.

[0120] Randomly select the initial value of each component of the particle velocity vector within the feasible velocity range of the parameters corresponding to each component of the particle velocity vector, and multiply by a scaling factor to ensure that the initial velocity is moderate, and complete the random initialization of the particle velocity;

[0121] Specifically, the initial value of each component of the particle velocity vector in this embodiment includes the initial value of the velocity vector component of the light source projection module in the X direction, the initial value of the velocity vector component of the light source projection module in the Y direction, the initial value of the velocity vector component based on the projection lens focal length, the initial value of the velocity vector component based on the headlight projection angle, and the initial value of the velocity vector component based on the brightness adjustment coefficient;

[0122] The calculation formula for the initial value of the velocity vector component of the light source projection module in the X direction is as follows:

[0123] ;

[0124] The calculation formula for the initial value of the velocity vector component of the light source projection module in the Y direction is as follows:

[0125] ;

[0126] The calculation formula for the initial value of the velocity vector component based on the projection lens focal length is as follows:

[0127] ;

[0128] The calculation formula for the initial value of the velocity vector component based on the headlight projection angle is as follows:

[0129] ;

[0130] The calculation formula for the initial value of the velocity vector component based on the brightness adjustment coefficient is as follows:

[0131] ;

[0132] Among them, , and are scaling factors set according to actual requirements and are used to control the magnitude of the initial velocity;

[0133] is a function for generating random numbers.

[0134] Step S2: Define the fitness evaluation function for each particle according to the components of the particle position vector in the horizontal and vertical directions and the uniformity of the headlight projection illuminance. The calculation formula of the fitness evaluation function is as follows:

[0135] ;

[0136] Among them, is the component of the particle position vector in the horizontal direction;

[0137] is the component of the particle position vector in the vertical direction;

[0138] Uniformity Ratio of Illuminance is the percentage of the uniformity of the headlight projection illuminance. In an actual LED lighting system, a measuring tool such as an illuminometer can be used to measure the illuminance values at different positions, and then based on the measured data, the percentage of the illuminance uniformity can be calculated;

[0139] and are weight coefficients and are used to adjust the influence of the projection system parameters and the illuminance uniformity on the fitness value.

[0140] Step S3: Update the velocity and position of each particle according to the velocity and position update formulas of the particle swarm optimization algorithm to gradually approach the optimal solution of the projection system parameters;

[0141] Specifically, each position vector at time step will be updated according to the velocity vector of the control input. The velocity and position update formulas of the particle swarm optimization algorithm are as follows:

[0142] ;

[0143] ;

[0144] Among them, is the velocity of particle i at time t;

[0145] is particle i at Velocity at a moment;

[0146] is the position of particle i at time t;

[0147] is the position of particle i at moment;

[0148] is the inertia coefficient;

[0149] and are acceleration coefficients;

[0150] is a random number between 0 and 1;

[0151] is the historical best position of particle i;

[0152] is the global best position of the entire particle swarm.

[0153] Step S4: According to the updated position vector of the particle, calculate the fitness value of the particle, and evaluate the pros and cons of the projection system parameters through the fitness value. The specific steps are as follows:

[0154] Substitute the horizontal and vertical components of the updated position vector of the particle into the fitness evaluation function respectively, and calculate the fitness value of the particle.

[0155] Step S5: Determine whether the iteration termination condition is satisfied. The iteration termination condition is to reach the preset maximum number of iterations or the fitness value of the particle satisfies the preset condition; if the iteration termination condition is satisfied, output the optimal projection system parameters, and if the iteration termination condition is not satisfied, jump to step S3.

[0156] The working principle of the present invention is as follows:

[0157] Define the parameters of the projection system as a particle swarm, and initialize the position and velocity of the particles; define the fitness evaluation function of each particle according to the horizontal and vertical components of the particle position vector and the uniformity of the headlight projection illuminance; update the velocity and position of each particle according to the velocity and position update formulas of the particle swarm optimization algorithm; calculate the fitness value of the particle according to the updated position vector of the particle; determine whether the iteration termination condition is satisfied. If the iteration termination condition is satisfied, output the optimal projection system parameters, and if the iteration termination condition is not satisfied, continue to update the velocity and position of each particle.

[0158] Introduce the particle swarm optimization algorithm into the vehicle light carpet projection technology. Utilize the global search ability of the particle swarm optimization algorithm to iteratively optimize the key parameters of the projection system, so as to gradually approach the optimal projection system parameters. This is conducive to minimizing the problem of uneven illuminance of the projection image and maximizing the projection efficiency and projection clarity. During the process of gradually approaching the optimal projection system parameters, evaluate the quality of the projection system parameters through the fitness evaluation function, significantly improving the quality and adaptability of the vehicle light carpet projection, enhancing the visual effect and user experience of the vehicle light carpet projection, providing a safer, more efficient, and more comfortable lighting and interaction solution for the vehicle, and having the advantages of high computational efficiency and fast convergence speed. This technology is expected to be widely applied in intelligent connected vehicles, autonomous driving vehicles, and smart city traffic systems, promoting the innovation and development of automotive lighting technology.

[0159] The specific embodiments described above further elaborate on the technical problems solved, technical solutions, and beneficial effects of the present invention. It should be understood that the above description is only specific embodiments of the present invention and is not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for optimizing the uniformity of illumination of an image projected by an intelligent self-closed-loop vehicle light blanket, characterized in that: It includes the following steps: Step S1, defining the parameters of the projection system as a particle group, and initializing the position and velocity of the particles, wherein the parameters of the projection system include the light source position, lens focal length, projection angle, and projection brightness; Step S2, defining a fitness evaluation function for each particle according to the components of the particle position vector in the horizontal and vertical directions and the uniformity of the illumination of the vehicle headlight projection; Step S3, updating the speed and position of each particle according to the speed and position update formula of the particle swarm optimization algorithm; Step S4, calculating the fitness value of the particle according to the updated position vector of the particle; Step S5, judging whether an iteration termination condition is satisfied, wherein the iteration termination condition is that a preset maximum number of iterations is reached or the fitness value of the particle satisfies a preset condition; If the iteration termination condition is met, the optimal projection system parameters are output; if the iteration termination condition is not met, the process jumps to step S3; In step S1, the parameters of the projection system are defined as a particle group, and the position and velocity of the particles are initialized, which specifically includes the following steps: Step S11, defining all parameters of the projection system as a particle group, wherein each particle in the particle group represents a set of projection system parameters; Step S12, setting the position vector and velocity vector of each particle, and the velocity vector and position vector of each particle have the same number of components; Step S13, randomly initializing the position and velocity of the particle; In step S13, the position and velocity of the particle are randomly initialized, which specifically includes the following steps: Randomly select the initial value of each component of the particle position vector within the feasible position range of the parameter corresponding to each component of the particle position vector to complete the random initialization of the particle position; The initial value of each component of the particle velocity vector is randomly selected within the feasible velocity range of the parameter corresponding to each component of the particle velocity vector, and multiplied by a scaling factor to complete the random initialization of the particle velocity.

2. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 1 is characterized in that: In step S12, the calculation formula of the position vector of each particle is as follows: ； in, and is the coordinate position of the central axis of the light source projection module; is the focal length of the projection lens; is the projection angle of the headlight; is the headlight projection brightness adjustment coefficient; The calculation formula of the velocity vector of each particle is as follows: ； in, is the velocity vector component of the light source projection module in the X direction; is the velocity vector component of the light source projection module in the Y direction; is the velocity vector component based on the focal length of the projection lens; is the velocity vector component based on the projection angle of the headlight; is the velocity vector component based on the brightness adjustment coefficient.

3. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 2 is characterized in that: The step of randomly selecting the initial value of each component of the particle position vector within the feasible position range of the parameter corresponding to each component of the particle position vector to complete the random initialization of the particle position specifically includes the following steps: The calculation formula of the initial value of the coordinate position of the axis of the light source projection module is as follows: ； ； The calculation formula of the initial value of the focal length of the projection lens is as follows: ； The calculation formula of the initial value of the headlight projection angle is as follows: ； The calculation formula of the initial value of the headlight projection brightness adjustment coefficient is as follows: ； in, A function for generating random numbers; and They are the minimum and maximum values ​​of the physical limits in the X direction of the lamp installation position; and They are the minimum and maximum values ​​of the physical limits in the Y direction of the lamp installation position; and The minimum and maximum values ​​of the focal lengths of the projection lenses designed for the lenses of the projection lenses, respectively; and They are respectively the minimum and maximum values ​​of the adjustable projection angle of the projection module.

4. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 3 is characterized in that: The initial value of each component of the particle velocity vector includes the initial value of the velocity vector component of the light source projection module in the X direction, the initial value of the velocity vector component of the light source projection module in the Y direction, the initial value of the velocity vector component based on the focal length of the projection lens, the initial value of the velocity vector component based on the projection angle of the car light, and the initial value of the velocity vector component based on the brightness adjustment coefficient.

5. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 4 is characterized in that: The calculation formula of the initial value of the velocity vector component of the light source projection module in the X direction is as follows: ； The calculation formula of the initial value of the velocity vector component of the light source projection module in the Y direction is as follows: ； The calculation formula of the initial value of the velocity vector component based on the focal length of the projection lens is as follows: ； The calculation formula of the initial value of the velocity vector component based on the projection angle of the headlight is as follows: ； The calculation formula of the initial value of the velocity vector component based on the brightness adjustment coefficient is as follows: ； in, , and is the scaling factor set according to actual needs; A function that generates random numbers.

6. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 5 is characterized in that: In step S2, the calculation formula of the fitness evaluation function is as follows: ； in, is the component of the particle position vector in the horizontal direction; is the component of the particle position vector in the vertical direction; Uniformity Ratio of Illuminance is the percentage of illumination uniformity of the headlight projection; and is the weight coefficient.

7. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 6 is characterized in that: In step S3, the speed and position update formula of the particle swarm optimization algorithm is as follows: ； ； in, is the velocity of particle i at time t; For particle i The speed of the moment; is the position of particle i at time t; For particle i The location at the moment; is the coefficient of inertia; and is the acceleration factor; is a random number between 0 and 1; is the historical optimal position of particle i; is the global optimal position of the entire particle swarm.

8. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 7 is characterized in that: In step S4, the fitness value of the particle is calculated according to the updated position vector of the particle, which specifically includes the following steps: Substitute the horizontal and vertical components of the updated particle's position vector into the fitness evaluation function to calculate the particle's fitness value.

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