Optimization method for illumination uniformity of projection image of intelligent self-closed-loop vehicle lamp light blanket

Abstract

The invention discloses an intelligent self-closed-loop car lamp light blanket projection image illumination uniformity optimization method, and belongs to the technical field of intelligent car lamps. The method comprises the following steps: S1, defining parameters of a projection system as a particle swarm, and initializing positions and speeds of particles; s2, defining a fitness evaluation function of each particle; s3, updating the speed and the position of each particle according to a particle swarm optimization algorithm formula; s4, calculating fitness values of the particles according to the updated position vectors of the particles; and S5, judging whether an iteration termination condition is met or not, if the iteration termination condition is met, outputting the optimal projection system parameters, and if the iteration termination condition is not met, skipping to the step S3. According to the intelligent self-closed-loop optimization method for the illumination uniformity of the projected image of the vehicle lamp light blanket, the illumination uniformity of the projected image is effectively improved, the quality and adaptability of light blanket projection are remarkably improved, and the visual effect of light blanket projection is improved.

Description

Technical Field

[0001] The invention relates to a method for optimizing the uniformity of illumination of an image projected by an intelligent self-closed-loop vehicle light blanket, and belongs 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, smart car lights have evolved from simple lighting tools to key interfaces for complex interactions between vehicles and the outside world. The optimization of car light performance and the improvement of the level of intelligence are not only directly related to the safety of vehicles in complex traffic environments, but also have a profound impact on the overall experience of drivers and passengers. Against this background, car light blanket projection technology, as a highly innovative lighting and interactive means, is gradually emerging, realizing effective communication between cars and cars, and cars and people by projecting images or digital information onto the ground.

[0003] Although the car light carpet projection technology has shown great application potential and market prospects, its current development still faces a series of technical and implementation challenges, one of the most prominent of which is the uneven distribution of illumination of the projected image. During the projection process, due to the limitations of light source intensity, lens design, and image processing algorithms, the projected image has significant differences in brightness, with some areas being too bright or too dark, which in turn affects the clarity and readability of the information, reducing the efficiency of information transmission and possibly causing misunderstandings or confusion. This undoubtedly increases potential safety risks for traffic participants who rely on this information to make quick decisions. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide an intelligent self-closed-loop method for optimizing the illumination uniformity of a car light blanket projection image, thereby realizing parameter optimization of a car light blanket projection system, effectively improving the illumination uniformity of the projection image, significantly improving the quality and adaptability of the car light blanket projection, improving the visual effect and user experience of the car light blanket projection, having the advantages of high computational efficiency and fast convergence speed, and providing vehicles with a safer, more efficient and comfortable lighting and interaction solution.

[0005] In order to solve the above technical problems, the technical solution of the present invention is: The present invention provides a method for optimizing the uniformity of illumination of an image projected by an intelligent self-closed-loop vehicle light blanket, which comprises 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 the iteration termination condition is met, wherein the iteration termination condition is that a preset maximum number of iterations is reached or the fitness value of the particle meets a preset condition; if the iteration termination condition is met, outputting the optimal projection system parameters, if not, jumping to step S3.

[0006] Furthermore, 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 initialize the position and velocity of the particle.

[0007] Furthermore, 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.

[0008] Furthermore, 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.

[0009] Furthermore, the step of randomly selecting an 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 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.

[0010] Furthermore, 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.

[0011] Furthermore, 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.

[0012] Furthermore, 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.

[0013] Furthermore, 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 inertia coefficient; 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.

[0014] Furthermore, 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.

[0015] By adopting the above technical solution, the present invention has the following beneficial effects: The particle swarm optimization algorithm is introduced into the car light blanket projection technology. The global search capability of the particle swarm optimization algorithm is used to iteratively optimize the key parameters of the projection system to gradually approach the optimal projection system parameters, which is conducive to minimizing the problem of uneven illumination of the projection image and maximizing the projection efficiency and projection clarity. In the process of gradually approaching the optimal projection system parameters, the fitness evaluation function is used to evaluate the advantages and disadvantages of the projection system parameters, which significantly improves the quality and adaptability of the car light blanket projection, improves the visual effect and user experience of the car light blanket projection, and provides a safer, more efficient and comfortable lighting and interactive solution for vehicles, with the advantages of high computational efficiency and fast convergence speed. This technology is expected to be widely used in intelligent connected vehicles, autonomous driving vehicles and smart city transportation systems, promoting the innovation and development of automotive lighting technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a method for optimizing the uniformity of illumination of an image projected by an intelligent self-closed-loop vehicle light blanket of the present invention; Figure 2This is a flow chart of a method for defining parameters of a projection system as a particle group and initializing the position and velocity of the particles according to the present invention. DETAILED DESCRIPTION

[0017] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments in conjunction with the accompanying drawings.

[0018] like Figure 1 As shown, this embodiment provides a method for optimizing the uniformity of illumination of an image projected by an intelligent self-closed-loop vehicle light blanket, which comprises the following steps: Step S1, defining the parameters of the projection system as a particle swarm, and initializing the position and velocity of the particles, wherein the parameters of the projection system include the position of the light source, the focal length of the lens, the projection angle, and the projection brightness; the position of the particle refers to the coordinates or parameter value of the particle in the search space; and the velocity of the particle refers to the moving direction and step length of the particle in the search space; like Figure 2 As shown, step S1 of this embodiment specifically includes the following steps: Step S11, defining all parameters of the projection system as a particle group, setting the number of particles in the particle group to N, and each particle in the particle group represents a set of projection system parameters; Specifically, the selection and setting of the number of particles N is generally determined according to the complexity of the problem and the computing resources. For the headlight blanket projection image optimization problem, 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 means that the algorithm will process 30 different projection system parameter combinations at the same time; 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, so as to update the value of each parameter in the iterative process; The calculation formula of the position vector of each particle in this embodiment 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; It is the adjustment coefficient of the headlight projection brightness.

[0019] The calculation formula of the velocity vector of each particle in this embodiment 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.

[0020] Step S13: Randomly initialize the position and velocity of the particle to ensure that the algorithm can explore the entire search space, specifically including the following steps: The initial value of each component of the particle position vector is randomly selected 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, which specifically includes the following steps: The initial value of the coordinate position of the central axis of the light source projection module is randomly selected within the physical limit values ​​of the X direction and the Y direction of the lamp installation position. The calculation formula of the initial value of the coordinate position of the central axis of the light source projection module is as follows: ; ; An initial value of the focal length of the projection lens is randomly selected 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: ; The initial value of the headlight projection angle is randomly selected within the adjustable angle range of the projection module. The calculation formula of the initial value of the headlight projection angle is as follows: ; The initial value of the headlight projection brightness adjustment coefficient is randomly selected between 0 and 1. 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.

[0021] Randomly select the initial value of each component of the particle velocity vector within the feasible velocity range of the parameter corresponding to each component of the particle velocity vector, and multiply it by a scaling factor to ensure that the initial velocity is moderate, thus completing the random initialization of the particle velocity; Specifically, the initial value of each component of the particle velocity vector of 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 focal length of the projection lens, the initial value of the velocity vector component based on the projection angle of the headlight, and the initial value of the velocity vector component based on the brightness adjustment coefficient; 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: ; 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: ; The calculation formula for the initial value of the velocity vector component based on the focal length of the projection lens is as follows: ; The calculation formula for the initial value of the velocity vector component based on the projection angle of the headlight is as follows: ; The calculation formula for the initial value of the velocity vector component based on the brightness adjustment coefficient is as follows: ; in, , and It is a scaling factor set according to actual needs, used to control the size of the initial velocity; A function that generates random numbers.

[0022] Step S2: Define the fitness evaluation function of 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. 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. In the actual LED lighting system, the illumination values ​​at different positions can be measured using measurement tools such as illuminance meters, and then the illumination uniformity percentage can be calculated based on the measurement data. and is the weight coefficient, which is used to adjust the impact of projection system parameters and illumination uniformity on the fitness value.

[0023] Step S3, according to the speed and position update formula of the particle swarm optimization algorithm, the speed and position of each particle are updated to gradually approach the optimal solution of the projection system parameters; Specifically, each position vector At time step When the speed vector of the control input is To update, the speed and position update formula of the particle swarm optimization algorithm are 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.

[0024] Step S4, according to the updated particle position vector, calculate the particle fitness value, and evaluate the quality of the projection system parameters by the fitness value, 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.

[0025] Step S5, judging whether the iteration termination condition is met, the iteration termination condition is that the preset maximum number of iterations is reached or the fitness value of the particle meets the preset condition; if the iteration termination condition is met, the optimal projection system parameters are output; if the iteration termination condition is not met, jumping to step S3.

[0026] The working principle of the present invention is as follows: The parameters of the projection system are defined as a particle swarm, and the position and speed of the particles are initialized; the fitness evaluation function of each particle is defined according to the components of the particle position vector in the horizontal and vertical directions and the uniformity of the headlight projection illumination; the speed and position of each particle are updated according to the speed and position update formula of the particle swarm optimization algorithm; the fitness value of the particle is calculated according to the updated particle position vector; it is determined whether the iteration termination condition is met. If the iteration termination condition is met, the optimal projection system parameters are output. If the iteration termination condition is not met, the speed and position of each particle continue to be updated.

[0027] The particle swarm optimization algorithm is introduced into the car light blanket projection technology. The global search capability of the particle swarm optimization algorithm is used to iteratively optimize the key parameters of the projection system to gradually approach the optimal projection system parameters, which is conducive to minimizing the problem of uneven illumination of the projection image and maximizing the projection efficiency and projection clarity. In the process of gradually approaching the optimal projection system parameters, the fitness evaluation function is used to evaluate the advantages and disadvantages of the projection system parameters, which significantly improves the quality and adaptability of the car light blanket projection, improves the visual effect and user experience of the car light blanket projection, and provides a safer, more efficient and comfortable lighting and interactive solution for vehicles, with the advantages of high computational efficiency and fast convergence speed. This technology is expected to be widely used in intelligent connected vehicles, autonomous driving vehicles and smart city transportation systems, promoting the innovation and development of automotive lighting technology.

[0028] The specific embodiments described above further illustrate the technical problems, technical solutions and beneficial effects solved by the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. 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 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.

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 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 initialize the position and velocity of the particle.

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: 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.

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: 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.

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 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.

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: 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.

7. The method for optimizing the uniformity of illumination of an image projected by an intelligent self-closed-loop vehicle light blanket according to claim 6, 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.

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 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.

9. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 8, 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.

10. The method for optimizing the uniformity of illumination of the projection image of the intelligent self-closed-loop vehicle light blanket according to claim 9, 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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