A method, device and computer equipment for controlling automobile ceiling lights

Abstract

The present application relates to a method, device and computer equipment for controlling a car ceiling light. The method comprises: upon detecting a touch signal of a vehicle object on the car ceiling light, obtaining physiological perception data of the vehicle object, and obtaining interior lighting data corresponding to the target vehicle; identifying the emotional state information of the vehicle object according to the physiological perception data; constructing an emotional state optimization objective function of the vehicle object according to the physiological perception data and the interior lighting data; solving the emotional state optimization objective function with the output value of the emotional state optimization objective function as the minimum value as the target condition, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle; wherein each brightness adjustment parameter and each color temperature adjustment parameter are used to adjust the corresponding lamp bead, and can be actively adjusted according to the current natural environment and human environment, thereby adjusting the emotions of each object in the car.

Description

Technical Field

[0001] The present application relates to the field of intelligent automobile technology, and in particular to a method, device and computer equipment for controlling automobile ceiling lights. Background Art

[0002] With the development of automobile functions, automobile ceiling light control technology has emerged. It is a technical solution for optimizing the operation of automobile interior ceiling lights. Through the reasonable design of hardware and control logic, the ceiling lights can be intelligently switched on and off and the brightness can be adjusted according to different trigger conditions. This method usually combines information such as door status, vehicle startup and shutdown, driver operation, and ambient light, collects data through sensors, and uses controllers for comprehensive analysis to achieve automatic opening, closing, delayed extinguishing or dimming functions of the ceiling lights. This not only improves driving comfort and user experience, but also effectively reduces energy consumption and extends the service life of lamps. However, the control of automobile ceiling lights in traditional technologies is limited to the status of the car and the active operation of the driver. It lacks the function of active adjustment according to the current natural environment and cultural environment, resulting in the inability to adjust the emotions of various objects in the car through automobile ceiling light control technology. Summary of the invention

[0003] Based on this, it is necessary to provide a car ceiling light control method, device, computer equipment, computer-readable storage medium and computer program product that can actively adjust according to the current natural environment and cultural environment, so as to adjust the emotions of various objects in the car through car ceiling light control technology, in order to solve the above technical problems.

[0004] In a first aspect, the present application provides a method for controlling a car ceiling light, comprising:

[0005] After detecting a touch signal of a vehicle object on a car ceiling light, physiological perception data of the vehicle object is acquired, and interior lighting data corresponding to the target vehicle is acquired;

[0006] identifying emotional state information of the vehicle object according to the physiological perception data;

[0007] Constructing an optimization objective function for the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data;

[0008] Taking the output value of the emotional state optimization objective function as the minimum value as the target condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle;

[0009] Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

[0010] In one embodiment, the output value of the emotional state optimization objective function is taken as the minimum value as the target condition, the emotional state optimization objective function is solved, and the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle are obtained, including:

[0011] According to the hardware continuous parameter characteristics of the automobile ceiling light, setting the brightness temperature adjustment constraint conditions corresponding to each of the lamp beads;

[0012] According to the hardware instantaneous parameter characteristics of the automobile ceiling light, setting the brightness temperature emergency adjustment conditions corresponding to each of the lamp beads;

[0013] The emotional state optimization objective function is solved with the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition as the solution range to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0014] In one embodiment, the output value of the emotional state optimization objective function is taken as the minimum value as the target condition, the emotional state optimization objective function is solved, and the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle are obtained, including:

[0015] According to the hardware continuous parameter characteristics of the automobile ceiling light, setting the brightness temperature adjustment constraint conditions corresponding to each of the lamp beads;

[0016] According to the hardware instantaneous parameter characteristics of the automobile ceiling light, setting the brightness temperature emergency adjustment conditions corresponding to each of the lamp beads;

[0017] The emotional state optimization objective function is solved with the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition as the solution range to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0018] In one embodiment, the brightness temperature emergency adjustment condition is used as the solution range, the emotional state optimization objective function is solved, and the brightness adjustment parameter and color temperature adjustment parameter of each lamp bead are obtained, including:

[0019] Determining an emergency solution mode of the emotional state optimization objective function according to the solution endpoint value of the objective function solution in the brightness temperature adjustment constraint condition;

[0020] According to the emergency solution mode, the value range of the brightness temperature emergency adjustment condition is adjusted to obtain a brightness emergency value range and a color temperature emergency value range;

[0021] The brightness emergency value range and the color temperature emergency value range are used as the solution range to solve the emotional state optimization objective function and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0022] In one embodiment, the method further comprises:

[0023] When the objective function solution result indicates that the output value of the emotional state optimization objective function converges within the brightness temperature adjustment constraint condition, partitioning each of the lamp beads to obtain partition information of each lamp bead;

[0024] According to the partition information of each lamp bead and the vehicle object, the lighting prediction control optimization is performed on the solution result of the objective function to obtain the brightness fine-grained optimization information and the color temperature fine-grained optimization information corresponding to each lamp bead;

[0025] According to the emotional state weight of each lamp bead and the system control weight, error correction is performed on the brightness fine-grained optimization information and the color temperature fine-grained optimization information to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0026] In one embodiment, the expression of the emotional state optimization objective function is:

[0027]

[0028] in, Optimize the output value of the objective function for the emotional state, To predict the time domain length, For at the moment Predicted future The emotional state information of the vehicle object at a moment, is the emotional state information of the desired vehicle object, is a positive definite symmetric matrix that weights the emotional states, For at the moment Predicted future The adjustment amount of the lamp bead brightness and lamp bead color temperature at each moment, is a positive definite symmetric matrix that weights the system control.

[0029] In one embodiment, the method further comprises:

[0030] Obtaining a vehicle acceleration change curve corresponding to the target vehicle;

[0031] Comparing the similarity between the object acceleration change curve and the vehicle acceleration change curve, and determining the object motion abnormality information of the vehicle object;

[0032] According to the abnormal object motion information, the car top light is controlled to flash to emit an abnormal alarm.

[0033] In one embodiment, comparing the similarity between the object acceleration change curve and the vehicle acceleration change curve to determine the object motion abnormality information of the vehicle object includes:

[0034] Continuously deriving the object acceleration change curve to obtain the object jerk change curve;

[0035] Continuously deriving the vehicle acceleration change curve to obtain a vehicle jerk change curve;

[0036] When the similarity between the object jerk change curve and the vehicle jerk change curve is lower than a threshold, comparing the direction information of the object acceleration and the vehicle acceleration corresponding to a plurality of moments;

[0037] In the case that the direction information of the object acceleration and the vehicle acceleration at any time is different, the object motion abnormality information is determined according to the object jerk change curve and the vehicle jerk change curve.

[0038] In a second aspect, the present application also provides a vehicle ceiling light control device, comprising:

[0039] The analysis data acquisition module is used to acquire physiological perception data of the vehicle object and interior lighting data corresponding to the target vehicle when a touch signal of the vehicle object on the car ceiling light is detected;

[0040] An emotional state recognition module, used to recognize emotional state information of the vehicle object according to the physiological perception data;

[0041] An objective function construction module, used to construct an objective function for optimizing the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data;

[0042] A lamp bead parameter adjustment module, used to solve the emotional state optimization objective function with the output value of the emotional state optimization objective function as the minimum value as the target condition, and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle;

[0043] Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

[0044] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0045] After detecting a touch signal of a vehicle object on a car ceiling light, physiological perception data of the vehicle object is acquired, and interior lighting data corresponding to the target vehicle is acquired;

[0046] identifying emotional state information of the vehicle object according to the physiological perception data;

[0047] Constructing an optimization objective function for the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data;

[0048] Taking the output value of the emotional state optimization objective function as the minimum value as the target condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle;

[0049] Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

[0050] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0051] After detecting a touch signal of a vehicle object on a car ceiling light, physiological perception data of the vehicle object is acquired, and interior lighting data corresponding to the target vehicle is acquired;

[0052] identifying emotional state information of the vehicle object according to the physiological perception data;

[0053] Constructing an optimization objective function for the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data;

[0054] Taking the output value of the emotional state optimization objective function as the minimum value as the target condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle;

[0055] Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

[0056] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0057] After detecting a touch signal of a vehicle object on a car ceiling light, physiological perception data of the vehicle object is acquired, and interior lighting data corresponding to the target vehicle is acquired;

[0058] identifying emotional state information of the vehicle object according to the physiological perception data;

[0059] Constructing an optimization objective function for the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data;

[0060] Taking the output value of the emotional state optimization objective function as the minimum value as the target condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle;

[0061] Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

[0062] The above-mentioned method, device, computer equipment, storage medium and computer program product for controlling a car ceiling light obtain physiological perception data of the vehicle object and interior lighting data corresponding to the target vehicle by detecting a touch signal of the vehicle object on the car ceiling light; identify the emotional state information of the vehicle object based on the physiological perception data; construct an emotional state optimization objective function for the vehicle object based on the physiological perception data and the interior lighting data; solve the emotional state optimization objective function with the output value of the emotional state optimization objective function being the minimum value as the target condition, and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle; wherein each brightness adjustment parameter and each color temperature adjustment parameter are used to adjust the corresponding lamp beads.

[0063] By integrating the physiological perception data of vehicle objects, touch pressure data, and interior lighting data of target vehicles, the emotional state of individuals can be accurately identified, and the optimization objective function based on the emotional state can be used to adjust the brightness and color temperature of the car ceiling light beads. This method can not only actively adjust according to the current natural environment and cultural environment, thereby adjusting the emotions of various objects in the car through the car ceiling light control technology, but also relieve fatigue and improve driving comfort. At the same time, by improving the visual and emotional environment, the driver's concentration and reaction ability are enhanced, thereby indirectly improving driving safety. In addition, the system demonstrates a high degree of intelligence and personalization, providing an important reference for the application of future smart transportation systems, and greatly improving the level of science and technology and humanity of the in-car environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0065] Figure 1A diagram showing an application environment of a method for controlling a car ceiling light in an embodiment;

[0066] Figure 2 A schematic diagram of a flow chart of a method for controlling a car ceiling light in one embodiment;

[0067] Figure 3 It is a flowchart of a method for obtaining a first brightness adjustment parameter and a color temperature adjustment parameter in one embodiment;

[0068] Figure 4 Schematic diagram of a flow chart of a method for obtaining a second brightness adjustment parameter and a color temperature adjustment parameter in an embodiment;

[0069] Figure 5 It is a flowchart of a method for obtaining a third brightness adjustment parameter and a color temperature adjustment parameter in one embodiment;

[0070] Figure 6 1 is a flow chart of a fourth method for obtaining brightness adjustment parameters and color temperature adjustment parameters in one embodiment;

[0071] Figure 7 A schematic diagram of a flow chart of a method for flashing an abnormal alarm in one embodiment;

[0072] Figure 8 It is a flowchart of a method for determining abnormal object motion information in one embodiment;

[0073] Fig. 9 is a structural block diagram of a car ceiling light control device in one embodiment;

[0074] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0075] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0076] The embodiment of the present application provides a method for controlling a car ceiling light, which can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The server 104 detects the touch signal of the vehicle object on the car ceiling light through the terminal 102, obtains the physiological perception data of the vehicle object, and obtains the interior lighting data corresponding to the target vehicle; according to the physiological perception data, the emotional state information of the vehicle object is identified; according to the physiological perception data and the interior lighting data, the emotional state optimization objective function of the vehicle object is constructed; the output value of the emotional state optimization objective function is taken as the minimum value as the target condition, and the emotional state optimization objective function is solved to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle; wherein each brightness adjustment parameter and each color temperature adjustment parameter are used to adjust the corresponding lamp beads. Among them, the server 104 can be implemented with an independent server or a server cluster composed of multiple servers.

[0077] In an exemplary embodiment, Figure 2 As shown, a method for controlling a car ceiling light is provided, and the method is applied to Figure 1 The server in the example is used to illustrate, including the following steps 202 to 208. Among them:

[0078] Step 202 , when a touch signal of a vehicle object on a car ceiling light is detected, physiological perception data of the vehicle object is acquired, and interior lighting data corresponding to the target vehicle is acquired.

[0079] Among them, the vehicle object can be the driver or passenger in the car, which is the core service target of the emotion regulation system.

[0080] Among them, the car ceiling light can be the main lighting device installed on the top of the car. It is usually composed of multiple independently controllable lamp beads, providing basic lighting and emotional light environment adjustment functions. It is one of the core executive components of the emotional regulation system.

[0081] Among them, the touch signal can be an electronic signal generated by a touch operation on a button or touch panel that controls the car's dome light. These signals may include information such as the touch position, time, and intensity. They are usually detected by capacitive, resistive, or ultrasonic touch technologies and used to control the response of the car's dome light.

[0082] Among them, physiological sensing data can be physiological characteristic signals of vehicle objects collected by sensors, such as heart rate, skin conductance, blood oxygen level and breathing rate.

[0083] Among them, the in-vehicle lighting data can be information about the in-vehicle light environment collected by the on-board environmental sensor, including light intensity (brightness), color temperature, light uniformity, and light source distribution characteristics.

[0084] Specifically, high-precision physiological monitoring sensors (such as photoelectric volumetric pulse wave sensors, skin conductance sensors, etc.) installed on the seats in the car are used to obtain physiological perception data such as heart rate variability, respiratory rate, and skin electrical response. In another case, the pressure sensor built into the touch screen or touch button will collect touch pressure data to analyze the size of the touch force, fluctuation trend, and duration of continuous pressing; as well as the on-board camera system and special sensing equipment, to collect emotional visual data such as facial expressions, eye movement trajectories, and head postures of vehicle objects in real time. In order to ensure the synchronization and integrity of the data, multimodal data acquisition technology is used to achieve time series alignment of physiological and touch pressure signals. In addition, the in-car environmental sensors are used to measure the current in-car lighting conditions, including brightness, color temperature, and spatial light distribution characteristics, to ensure that there is a direct correlation between the lighting parameter data and the physiological data, providing reliable basic information for subsequent optimization.

[0085] Step 204: Identify the emotional state information of the vehicle object based on the physiological perception data.

[0086] Among them, the emotional state information can be the analysis and fusion of physiological perception data, or the analysis and fusion of emotional visual data, physiological perception data and touch pressure data, and the current emotional data of the identified vehicle object (such as detailed data of anxiety, pleasure, fatigue, etc.) and its intensity.

[0087] Specifically, the collected physiological perception data (or physiological perception data, emotional visual data, and touch pressure data at the same time) are input into the multimodal emotion recognition model. Among them, the processing of emotional visual data is done by extracting micro-expressions and dynamic behavior features through a convolutional neural network (CNN); the physiological perception data is analyzed by a long short-term memory network (LSTM) to analyze the change of signals over time; the touch pressure data is evaluated by a pattern recognition algorithm to evaluate the touch behavior characteristics (such as high pressure and fast clicks may indicate anxiety or tension, low pressure and slow dragging may indicate relaxation). In the recognition process of the model, a high-quality data set containing multiple emotional state labels is used for recognition to improve the accuracy of emotion recognition. Through the output results of the deep learning algorithm of the physiological features corresponding to the pure physiological perception data, or the fusion vision corresponding to the emotional visual data, the physiological features corresponding to the physiological perception data, and the action pressure features corresponding to the touch pressure data, fine-grained emotional states such as anxiety, stress, and pleasure are identified, and finally the structured emotional state information describing the emotional state is output, including the type of emotion and its intensity.

[0088] Step 206: construct an objective function for optimizing the emotional state of the vehicle object based on the physiological perception data and the in-vehicle lighting data.

[0089] Among them, the emotional state optimization objective function can be to take the emotional comfort of the vehicle object as the optimization target, calculate the adjustment scheme of variables such as brightness and color temperature, so as to output the optimal lighting parameter combination to achieve the optimization of the emotional state.

[0090] Specifically, with the goal of alleviating the negative emotions of vehicle subjects and optimizing their emotional states, a psychological light environment model is designed to integrate basic information such as the weight of the influence of factors such as brightness, color temperature, and light distribution uniformity on emotional comfort, and to construct an emotional state optimization objective function by combining its current emotional state information and the actual information of the in-vehicle lighting data. The main output variables of the emotional state optimization objective function include the lamp bead brightness adjustment parameters, color temperature adjustment parameters, and their nonlinear expression of the influence on the degree of emotional relief. By introducing constraints in actual lighting (such as maximum light intensity limit and color temperature adjustment range), it is ensured that the optimization scheme strikes a balance between technical feasibility and user experience.

[0091] For the emotional state optimization objective function, its expression is:

[0092]

[0093] in, The output value of the emotion state optimization objective function is constructed according to the model predictive control theory and is used to measure the overall performance of the system in the future. It is set by the control system designer to balance the computational complexity and prediction accuracy in order to predict the time domain length. Usually, an appropriate value is selected based on the system dynamic characteristics and response speed. For at the moment Predicted future The emotional state information of the vehicle object at a certain moment, specifically predicting the future emotional state through the system model and the current state, and the prediction model can be based on a neural network or other dynamic models. The emotional state information of the desired vehicle object is comprehensively set by the system based on the passenger's historical needs, the passenger's current situation and the vehicle's driving safety, and can also be additionally set by the passenger through the terminal. is a positive definite symmetric matrix that weights the emotional states, The specific data is set by the control system designer, and weights are assigned according to the importance of different emotional dimensions. For at the moment Predicted future The adjustment amount of the lamp bead brightness and lamp bead color temperature at each moment is the control variable obtained through the optimization process, which is used to adjust the system to achieve the desired state. It is a positive definite symmetric matrix that weights system control and is set by the control system designer. It assigns weights to different control inputs (such as brightness adjustment and color temperature adjustment) according to their energy consumption or impact on passenger comfort.

[0094] Step 208, taking the output value of the emotional state optimization objective function as the minimum value as the target condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle.

[0095] Among them, lamp beads can be the basic unit of light source in car ceiling lights, usually LED light sources. Each lamp bead can independently adjust the brightness and color temperature, and the output of the lamp bead combination can be precisely controlled to achieve diversified and personalized lighting environment.

[0096] Among them, the brightness adjustment parameter can be a numerical value used to control the luminous intensity of the lamp beads, which is usually achieved by changing the input current or pulse width modulation (PWM). This parameter is used to set the brightness of the light environment in mood regulation.

[0097] Among them, the color temperature adjustment parameter can be a numerical value used to control the luminous tone of the lamp beads, usually to achieve the output of cold light or warm light. This parameter is used to optimize the lighting tone in the car during mood regulation.

[0098] Specifically, a variety of optimization algorithms (such as genetic algorithms, particle swarm optimization algorithms or deep reinforcement learning) are used to solve the emotional state optimization objective function and find the optimal parameter combination that minimizes the function value of the emotional state optimization objective function. During the solution process, if the information inside and outside the vehicle and the emotional state of the vehicle object change dynamically, it is necessary to input the emotional state information of the vehicle object in real time to update the data and dynamically adjust the function parameters and input variables in the optimization process. The algorithm design needs to consider the complexity of high-dimensional multivariable optimization and the requirement of fast convergence within a limited computing time. The final output includes the optimal solution of the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead, ensuring that the light environment inside the car can adapt to the emotional changes of the vehicle object in real time.

[0099] According to the optimized brightness adjustment parameters and color temperature adjustment parameters, the brightness of the lamp beads is accurately adjusted through PWM (pulse width modulation) control technology, and the color temperature of the light source is dynamically adjusted using adjustable color temperature LED chips and driver modules. During the adjustment process, the intelligent lighting system gradually optimizes the light environment in the car to ensure the uniformity and softness of the light and avoid abrupt changes that cause additional stimulation to the vehicle object. By adjusting specific optical parameters, such as reducing brightness and adjusting color temperature to warm white light, anxiety can be relieved; or by increasing light intensity and cool colors to improve concentration, the purpose of scientifically regulating the emotions of vehicle objects can be achieved. Ultimately, emotion regulation in the car is achieved in a non-sensitive, real-time and personalized manner, improving the overall driving and riding experience.

[0100] In the above-mentioned car ceiling light control method, by detecting the touch signal of the vehicle object on the car ceiling light, the physiological perception data of the vehicle object and the interior lighting data corresponding to the target vehicle are obtained; based on the physiological perception data, the emotional state information of the vehicle object is identified; based on the physiological perception data and the interior lighting data, an emotional state optimization objective function of the vehicle object is constructed; with the output value of the emotional state optimization objective function being the minimum value as the target condition, the emotional state optimization objective function is solved to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle; wherein each brightness adjustment parameter and each color temperature adjustment parameter are used to adjust the corresponding lamp beads.

[0101] By integrating the physiological perception data of vehicle objects, touch pressure data, and interior lighting data of target vehicles, the emotional state of individuals can be accurately identified, and the optimization objective function based on the emotional state can be used to adjust the brightness and color temperature of the car ceiling light beads. This method can not only actively adjust according to the current natural environment and cultural environment, thereby adjusting the emotions of various objects in the car through the car ceiling light control technology, but also relieve fatigue and improve driving comfort. At the same time, by improving the visual and emotional environment, the driver's concentration and reaction ability are enhanced, thereby indirectly improving driving safety. In addition, the system demonstrates a high degree of intelligence and personalization, providing an important reference for the application of future smart transportation systems, and greatly improving the level of science and technology and humanity of the in-car environment.

[0102] In an exemplary embodiment, Figure 3 As shown, the output value of the emotional state optimization objective function is the minimum value as the target condition, the emotional state optimization objective function is solved, and the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the car ceiling light of the target vehicle are obtained, including steps 302 to 306. Among them:

[0103] Step 302, according to the hardware continuous parameter characteristics of the automobile ceiling light, the brightness temperature adjustment constraint conditions corresponding to each lamp bead are set.

[0104] Among them, the hardware continuous parameter characteristics can be the performance indicators and physical limitations of the car ceiling light beads under long-term stable working conditions, including maximum rated power, luminous flux output range, thermal management capabilities, operating temperature range and expected life.

[0105] Among them, the brightness temperature adjustment constraints can be divided into brightness adjustment constraints and color temperature adjustment constraints. The brightness adjustment constraints can be the brightness adjustment range and change rate limit set based on the continuous parameter characteristics of the lamp bead hardware. Specifically, it includes the maximum and minimum values ​​of the brightness of each lamp bead (for example, 0%-100%), and the upper limit of the gradual change rate of brightness change; the color temperature adjustment constraints can be the color temperature adjustment range and change rate limit set according to the hardware characteristics of the lamp bead. The color temperature adjustment must be performed within the color temperature range allowed by the lamp bead (for example, 2500K-6500K), and ensure that the adjustment rate meets the gradual change requirements (such as no more than 500K per second).

[0106] Specifically, based on the hardware continuous parameter characteristics of the car ceiling light, the performance limitations of the lamp beads under long-term stable operation are deeply analyzed, including factors such as maximum rated power, luminous flux output range, heat dissipation efficiency and working life. Combined with the experimental data and production specifications before the car ceiling light leaves the factory, the brightness adjustment constraints of each lamp bead are determined, that is, the adjustable brightness range (such as 0%-100%), and the color temperature adjustment constraints, that is, the adjustable color temperature range (such as 2500K-6500K). In addition, the overall uniformity and visual comfort of the light environment must be considered, and a reasonable gradual upper limit on the adjustment rate must be set (such as the brightness change per second must not exceed 10%) to avoid discomfort or visual fatigue caused by too fast changes in brightness or color temperature. These constraints are formulated to form a mathematical constraint model, which is used to optimize the constraint input of the algorithm.

[0107] Step 304, according to the hardware instantaneous parameter characteristics of the automobile ceiling light, set the brightness temperature emergency adjustment conditions corresponding to each lamp bead.

[0108] Among them, the hardware transient parameter characteristics can be the performance limit of the car ceiling light beads when responding to rapidly changing demands in a short period of time, including emergency current carrying capacity, thermal stabilization time, LED response speed, and maximum emergency brightness and color temperature adjustment range.

[0109] Among them, the brightness temperature emergency adjustment conditions can be divided into brightness emergency adjustment conditions and color temperature emergency adjustment conditions. The brightness emergency adjustment conditions can be the lamp bead brightness adjustment rules set in special emergency situations to ensure that the lamp bead can quickly increase or decrease the brightness within a safe range and maintain continuous operation; the color temperature emergency adjustment conditions can be the safety rules set for the rapid adjustment of the lamp bead color temperature when an emergency occurs in the vehicle or environmental requirements, including the color temperature change range and adjustment limit value in emergency situations.

[0110] Specifically, for the hardware instantaneous parameter characteristics of the car ceiling light, combined with the data on the physical limits of the lamp beads of the car ceiling light before leaving the factory when responding to the rapid adjustment needs during emergency time, such as emergency current carrying capacity, thermal stability time and LED response speed. For example, when the vehicle object's emotions fluctuate violently (such as anxiety or anger rising rapidly) or the ambient light changes sharply (such as entering and exiting a tunnel or strong light interference from the opposite side at night), the lamp beads need to be able to quickly complete the adaptive adjustment of light intensity and color temperature. When setting emergency adjustment conditions, it is necessary to clarify the brightness emergency adjustment conditions and color temperature emergency adjustment conditions, that is, the maximum adjustment range of the brightness and color temperature of the lamp beads in emergency situations (such as the brightness emergency adjustment range does not exceed 150% of the rated maximum value, the color temperature emergency change shall not exceed 5000K per second and the upper limit shall not exceed 10000K) to ensure a balance between the adjustment response speed and hardware protection, and to ensure that emergency alarms can be continuously issued.

[0111] Step 306, using the emotion state optimization objective function within the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition as the solution range, solving the emotion state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0112] Specifically, the solution scope of the emotional state optimization objective function is strictly limited to the set brightness adjustment constraints, color temperature adjustment constraints, brightness emergency adjustment conditions and color temperature emergency adjustment conditions, and the emotional state optimization objective function is solved by a nonlinear optimization algorithm. First, the variable weights in the emotional state optimization objective function are dynamically updated through the real-time emotional data input of the vehicle object, for example, the weight of warm colors is increased in the anxious state to prioritize the optimization of color temperature. Then, a particle swarm optimization algorithm (PSO) or gradient descent method is selected to gradually approach the optimal solution according to the minimization conditions of the emotional state optimization objective function. During the algorithm iteration, the convergence of the objective function is monitored in real time to ensure that the output brightness adjustment parameters and color temperature adjustment parameters are balanced in terms of accuracy and calculation time. Finally, a set of brightness adjustment parameters and color temperature adjustment parameters of each lamp bead that meet the hardware characteristics, safety restrictions and can significantly improve the emotional state of the vehicle object are obtained, providing an accurate basis for the real-time regulation of the ceiling lamp bead.

[0113] In this embodiment, by setting the adjustment constraints of brightness and color temperature according to the hardware continuous parameter characteristics of the car ceiling light, and setting the emergency adjustment conditions based on the instantaneous parameter characteristics, the method realizes the safe, accurate and dynamic regulation of the brightness and color temperature of the lamp beads. With the emotional state optimization objective function as the core, by solving within the above constraints, the optimal brightness and color temperature adjustment parameters can be generated for each lamp bead, so as to accurately match the real-time emotional needs of the vehicle object. While ensuring the long-term safety and stability of the hardware, this method provides efficient emergency response capabilities, so that the interior light environment can quickly adapt under both normal adjustment and sudden emotional states, greatly improving the comfort and safety of the driving and riding experience, while extending the service life of the lamp bead hardware.

[0114] In an exemplary embodiment, Figure 4 As shown, the emotional state optimization objective function is solved within the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead, including steps 402 to 404. Among them:

[0115] Step 402, using the output value of the emotional state optimization objective function under the brightness temperature adjustment constraint as the solution range, solving the emotional state optimization objective function to obtain the objective function solution result.

[0116] The objective function solution result may be a set of specific output values ​​generated by the optimization algorithm in the process of solving the emotional state optimization objective function, and these output values ​​include the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0117] Specifically, since step 302 mentions that the brightness temperature adjustment constraint can be divided into brightness adjustment constraint and color temperature adjustment constraint, the solution range of the emotional state optimization objective function is constructed according to the current emotional state information of the vehicle object, combined with the preset brightness adjustment constraint and color temperature adjustment constraint. These brightness adjustment constraints and color temperature adjustment constraints clarify the limits of parameters such as the adjustable range of lamp bead brightness and color temperature, gradient rate, and illumination uniformity. In the process of solving the emotional state optimization objective function, a nonlinear optimization algorithm (such as the Lagrange multiplier method or the particle swarm optimization algorithm) is used to gradually approach the minimum value of the emotional state optimization objective function through iterative calculation. The algorithm will dynamically adjust the optimization path according to the different weights of the lamp bead brightness and color temperature on the emotional relief effect, and obtain the objective function solution result. At this stage, the priority goal of the objective function solution result is to ensure that the emotional state optimization objective function can converge within the normal hardware adjustment range, while maintaining the long-term stability and safety of the lamp bead hardware.

[0118] Step 404, when the output value of the objective function solution representing the emotional state optimization objective function fails to converge within the brightness temperature adjustment constraint condition, the brightness temperature emergency adjustment condition is used as the solution range to solve the emotional state optimization objective function and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0119] Specifically, under normal circumstances, the emotional state optimization objective function can be calculated and converged under the brightness adjustment constraint conditions and the color temperature adjustment constraint conditions to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead; however, when the optimization algorithm of the emotional state optimization objective function cannot find the convergence solution of the objective function within the brightness adjustment constraint conditions and the color temperature adjustment constraint conditions (for example, the vehicle or environment has unexpected changes, causing the occupants of the vehicle to be in danger), the system automatically switches to the emergency solution mode. In this mode, since step 304 mentions that the brightness and temperature emergency adjustment conditions can be divided into brightness emergency adjustment conditions and color temperature emergency adjustment conditions, the brightness emergency adjustment conditions and color temperature emergency adjustment conditions are used as the new solution range, and the emergency adjustment conditions allow a larger brightness and color temperature adjustment range and a faster adjustment speed. In the algorithm solution process, the lamp bead is allowed to be adjusted quickly beyond the normal range for a short time, but the emergency current carrying capacity, thermal management status and response speed of the lamp bead will be monitored in real time to ensure that the hardware safety can continue to alarm in emergency situations; at the same time, emergency optimization gives priority to quickly responding to user emotional needs to ensure real-time and effectiveness. Through the above-mentioned solving process of normal mode and emergency mode, the system finally outputs the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead to form a complete adjustment plan. In normal mode, the solving results strictly follow the limitations of hardware continuous parameters, and the optimization results take into account the long-term operation reliability of the lamp beads while ensuring emotional improvement; in emergency mode, the solving results quickly respond to emotional needs within the emergency adjustment range of brightness emergency adjustment conditions and color temperature emergency adjustment conditions, providing immediate emotional relief effects for vehicle objects. Both modes verify their feasibility through simulation operation after the results are generated to ensure that the adjustment effect meets the system design goals and achieves a balance between the optimization of emotional state and the protection of lamp bead hardware.

[0120] In this embodiment, efficient adjustment of the emotional state target is achieved through phased optimization: first, the emotional state optimization objective function is solved within the scope of the brightness adjustment constraint and the color temperature adjustment constraint to achieve high accuracy in normal emotional state adjustment; second, when the solution fails to converge, the system automatically switches to emergency mode and uses the brightness and color temperature emergency adjustment conditions for extended optimization to ensure that the adjustment parameters can still be quickly obtained under special or extreme emotional needs. This two-layer solution mechanism significantly improves the flexibility and reliability of emotional state adjustment while ensuring the safety of system operation and the protection of lamp bead hardware, ensuring that vehicle objects can obtain personalized light environment support under different emotional states and environmental conditions, and greatly improving the comfort and safety of driving and riding experience.

[0121] In an exemplary embodiment, Figure 5 As shown, the brightness temperature emergency adjustment condition is used as the solution range, the emotional state optimization objective function is solved, and the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead are obtained, including steps 502 to 506. Among them:

[0122] Step 502: Determine an emergency solution mode for the emotional state optimization objective function according to the solution endpoint value of the objective function solution in the brightness temperature adjustment constraint condition.

[0123] The endpoint value to be solved may be the result when the brightness and color temperature parameters of the lamp beads reach the boundary values ​​of their set constraint ranges (such as the brightness reaches 0% or 100%, and the color temperature reaches a minimum of 2500K or a maximum of 6500K) when optimizing the emotional state objective function.

[0124] Among them, the emergency solution mode can be a special solution mechanism triggered when the conventional adjustment range cannot meet the emotion optimization needs, which is used to deal with emergency situations in the vehicle.

[0125] Specifically, in an emergency situation, by extracting the process information of the emotion state optimization objective function in the solution result of the objective function, which indicates the solution of the brightness adjustment constraint and the color temperature adjustment constraint, it is determined that the emotion state optimization objective function triggers any endpoint of the brightness adjustment constraint or the color temperature adjustment constraint during the solution process, and further extracts the specific data of the triggered endpoint and the data of another constraint matching the triggered endpoint. If the emotion state optimization objective function triggers the minimum value of the color temperature adjustment constraint in the process of seeking the minimum solution, the minimum value is output and the output value corresponding to the brightness adjustment constraint when the minimum value is output is output at the same time. According to the data obtained in the case of the above-mentioned triggering endpoint, multiple preset emergency solution modes are compared, and an emergency solution mode that can meet the above situation is selected.

[0126] Step 504: According to the emergency solution mode, the value range of the brightness temperature emergency adjustment condition is adjusted to obtain the brightness emergency value range and the color temperature emergency value range.

[0127] Among them, the brightness emergency value range can be the adjustment range set by the system for the lamp bead brightness adjustment in the emergency solution mode. Compared with the conventional brightness adjustment range, it is more special and cannot be used for a long time.

[0128] Among them, the color temperature emergency value range can be the extended range set by the system for the lamp color temperature adjustment in the emergency solution mode, allowing the color temperature to exceed the normal adjustment range (such as 2500K-6500K) to reach the emergency range (such as 6500K-9000K).

[0129] Specifically, after entering the emergency solution mode, the system redefines the emergency value range of brightness and color temperature according to the optimization requirements of the solution endpoint value and the current emotional state. For example, if the emotional state requires more warm colors to relieve anxiety, that is, one of the endpoints of the color temperature adjustment constraint has been touched in the previous search range, the system can adjust the color temperature adjustment range, such as adjusting the allowable range from the conventional 2500K-6500K to 6500K-9000K, and obtain the color temperature emergency value range; for brightness, it can break through the conventional adjustment range and increase the brightness adjustment range in a short time while ensuring the emergency carrying capacity of the hardware (such as allowing the brightness to be increased to 120% of the rated maximum brightness). At the same time, the system dynamically sets the upper limit of the adjustment rate according to the emergency current carrying capacity, thermal stability and hardware protection mechanism of the lamp beads, ensuring that the emergency range meets the needs of rapid adjustment without overloading or damaging the lamp bead hardware, and obtains the brightness emergency value range.

[0130] Step 506, using the brightness emergency value range and the color temperature emergency value range as the solution range, solve the emotional state optimization objective function to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0131] Specifically, within the adjusted emergency value range of brightness and the emergency value range of color temperature, the system re-solves the emotional state optimization objective function through the optimization algorithm. Among them, the optimization algorithm (such as genetic algorithm or particle swarm optimization algorithm) quickly iterates within the new degree of freedom range, and combines the real-time updated emotional state information to calculate the brightness and color temperature adjustment parameter combination of each lamp bead within the emergency value range of brightness and the emergency value range of color temperature. This process gives priority to the immediate improvement needs of the emotional state, and at the same time introduces a hardware protection mechanism to monitor the thermal load, current state and light environment changes of the lamp beads in real time to ensure the safety of the adjustment process. Finally, the system generates a set of brightness adjustment parameters and color temperature adjustment parameters for each lamp bead in the emergency mode, and quickly adjusts the brightness and color temperature of the lamp beads to effectively alleviate the emotional state of the vehicle object, achieving the goal of emotional optimization while ensuring stable operation of the hardware.

[0132] In this embodiment, the precise optimization of the in-vehicle light environment under extreme or special emotional needs is achieved through the strategy of dynamically adjusting the solution range. According to the solution endpoint value in the objective function solution result, the emergency solution mode is triggered to effectively identify the insufficient adjustment ability of the system; the emergency value range of brightness and color temperature is further adjusted to expand the adjustment space of lamp bead parameters to cope with emergency emotional states or special environmental changes. Finally, the optimization algorithm is re-solved within the emergency range to generate the optimal brightness and color temperature adjustment parameters for each lamp bead. This method not only enhances the adaptability and responsiveness of the emotion regulation system in complex scenarios, but also provides a more personalized and efficient emotion relief solution while ensuring hardware safety and stable operation, significantly improving the intelligence of the in-vehicle light environment and user experience satisfaction.

[0133] In an exemplary embodiment, Figure 6 As shown, the method further includes steps 602 to 606. Among them:

[0134] Step 602, when the output value of the objective function optimized by the objective function solution representing the emotional state converges within the brightness temperature adjustment constraint, each lamp bead is partitioned to obtain the partition information of each lamp bead.

[0135] Among them, the lamp bead partition information can be a lamp bead data set formed after the lamp beads in the car ceiling light are divided based on their physical position, light distribution range and functional role.

[0136] Specifically, after the objective function solution results show that the emotional state optimization objective function has converged within the brightness adjustment constraints and the color temperature adjustment constraints, that is, the combination of brightness value and color temperature value is found to make the function output value of the emotional state optimization objective function the minimum value, the lamp beads are scientifically partitioned based on the physical layout of the car ceiling light, light distribution characteristics, functional requirements and emotional adjustment requirements of the vehicle object. The lamp bead partition is classified by analyzing its position, angle and illumination range. For example, the lamp beads are divided into direct lighting area (mainly providing concentrated light, directly affecting the emotional state of the vehicle object), indirect lighting area (used to improve the softness of the overall light environment) and auxiliary light source area (supplementary lighting in dark corners or special areas). At the same time, combined with the vehicle object's sitting posture, sight direction and activity area in the car, the weight of the role of the lamp beads in regulating the emotional state is dynamically marked, and the above partition results are adjusted to form accurate lamp bead partition information.

[0137] Step 604, according to the partition information of each lamp bead and the vehicle object, the lighting prediction control optimization is performed on the solution result of the objective function to obtain the fine-grained optimization information of brightness and color temperature corresponding to each lamp bead.

[0138] Among them, lighting prediction control optimization can be a process of adjusting the brightness and color temperature of the lamp beads through a predictive algorithm by utilizing the lamp bead partition information and the emotional state characteristics of the vehicle object.

[0139] Among them, the fine-grained brightness optimization information can be parameter data generated after accurately adjusting the brightness of each lamp bead based on the lamp bead partition information and emotional demand prediction results.

[0140] Among them, the color temperature fine-grained optimization information can be parameter data formed after fine-tuning the color temperature of each lamp bead, including specific color temperature values ​​and their dynamic adjustment methods.

[0141] Specifically, based on the lamp bead partition information and the current emotional state characteristics of the vehicle object, the predictive control algorithm is used to fine-grained optimize the objective function solution results, and calculate the brightness and color temperature adjustment scheme of the lamp beads in each partition. During the optimization process, the emotional fluctuations of the vehicle object are predicted through machine learning models (such as time series prediction models or reinforcement learning models) combined with historical data (such as the emotional state change trend of the vehicle object, common ambient light interference scenarios) and real-time input emotional state data, and the lamp bead parameters are adjusted in advance to match emotional needs. For example, if an increasing trend of driver fatigue is detected, the brightness of the lamp beads in the direct lighting area can be increased first, the color temperature can be adjusted to the cold color range, and the light uniformity of the lamp beads in the indirect lighting area can be optimized to prevent local light stimulation from causing discomfort. Finally, fine-grained brightness optimization information and color temperature fine-grained optimization information for each lamp bead are generated to ensure that the lighting adjustment meets the partition characteristics and emotional needs.

[0142] Step 606, according to the emotional state weight of each lamp bead and the system control weight, error correction is performed on the brightness fine-grained optimization information and the color temperature fine-grained optimization information to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

[0143] The emotional state weight can be a priority coefficient assigned by the lamp beads according to the importance of the emotional needs of the vehicle object, which is used to guide the priority and importance order of lighting adjustment. For example, the anxiety state may give a higher weight to warm light adjustment, while the fatigue state will increase the preference weight for cold light.

[0144] Among them, the system control weight can be the priority coefficient set for system requirements such as hardware protection, energy consumption optimization and light environment uniformity during the lighting adjustment process, which is used to balance emotional state optimization and system operation requirements to avoid excessive adjustment leading to hardware overload or excessive energy consumption.

[0145] Specifically, combined with the emotional state weight of each lamp bead for the vehicle object (such as the high priority for warm light when anxious or the preference for bright cold light when tired) and the system control weight (such as hardware protection, energy consumption optimization, light environment uniformity, etc.), comprehensive error correction is performed on the fine-grained brightness optimization information and color temperature fine-grained optimization information. The correction process is completed through a multi-objective weighted optimization formula. For example, a higher emotional state weight is set for the direct lighting area so that its brightness and color temperature adjustment are closer to the user's emotional needs, while the indirect lighting area and auxiliary light source area are more considered. System energy efficiency and light transition requirements are avoided. Over-adjustment causes increased energy consumption or hardware pressure. At the same time, the operating status of the hardware (such as lamp bead temperature and current load) is monitored in real time and the error correction range is dynamically adjusted to ensure that the final output of the lamp bead brightness adjustment parameters and color temperature adjustment parameters not only meet the emotional optimization goals, but also maintain the stability and sustainability of the system operation.

[0146] In this embodiment, the brightness and color temperature of the lamp beads in the car are finely adjusted through partition optimization, predictive control and weight correction. Initially, based on the convergence result of the objective function, the lamp beads are partitioned according to function and position, and the lamp bead partition information is generated to clarify the contribution of the lights in each area to the emotional state. Further combined with the emotional needs of the vehicle object, the lighting predictive control optimization is performed on the solution of the objective function to generate fine-grained optimization information of brightness and color temperature to improve the predictability and adaptability of the adjustment. Finally, through the combined effect of the emotional state weight and the system control weight, the fine-grained optimization information is error corrected to ensure that the final adjustment parameters of the lamp beads not only meet the personalized emotional needs, but also take into account the system safety, energy consumption optimization and uniformity of the light environment. This method realizes the dynamic intelligent control of the light environment in the car, significantly improving the emotional comfort of the vehicle object, the refinement of the in-car experience and the reliability of the system operation.

[0147] In an exemplary embodiment, Figure 7 As shown, the method further includes steps 702 to 706. Among them:

[0148] Step 702, obtaining an object acceleration change curve of a vehicle object, and obtaining a vehicle acceleration change curve corresponding to a target vehicle.

[0149] The object acceleration change curve may be a time series curve generated by monitoring acceleration sensor data of a vehicle object (such as a driver or a passenger), reflecting its acceleration change characteristics at different time points.

[0150] The vehicle acceleration change curve can be a curve generated by recording the acceleration data of the vehicle at different time points through the vehicle's inertial measurement unit (IMU) or acceleration sensor. It reflects the dynamic acceleration changes of the vehicle under operations such as starting, braking, and turning, and is used to describe the overall motion behavior of the vehicle.

[0151] Specifically, the acceleration change data of the vehicle object is captured in real time through the on-board acceleration sensor, inertial measurement unit (IMU) and wearable devices (such as bracelets, seat-embedded sensors, etc.). These data reflect the motion dynamics of the object in three-dimensional space (including linear acceleration and angular acceleration), and after filtering and denoising, an accurate object acceleration change curve is generated. At the same time, the acceleration change curve of the vehicle itself is collected by the sensor module of the vehicle control system, including the acceleration information of the vehicle during starting, braking, turning and other operations, to obtain the vehicle acceleration change curve corresponding to the target vehicle, and further synchronize the two sets of data through a unified timestamp and spatial coordinate system to ensure the alignment and accuracy of the curve.

[0152] Step 704 : comparing the similarity between the object acceleration change curve and the vehicle acceleration change curve to determine the object motion abnormality information of the vehicle object.

[0153] Among them, the object motion abnormality information can be abnormal data detected by comparing the dynamic characteristics of the object acceleration change curve with the vehicle acceleration change curve (such as jerkiness, directional consistency, etc.), including the time, amplitude and type of the abnormality (such as slipping, imbalance or sudden movement), which is used to mark the abnormal motion state of the vehicle object.

[0154] Specifically, a signal processing algorithm (such as dynamic time warping algorithm DTW, cross-correlation analysis or Fourier transform) is used to calculate the similarity between the object acceleration change curve and the vehicle acceleration change curve. Under normal circumstances, the two curves should have a high consistency in time and amplitude, reflecting the synchronous response behavior of the vehicle object when the vehicle accelerates, decelerates or turns. When the system detects obvious differences between the two curves, such as abrupt changes, nonlinear fluctuations or a trend of continuous deviation from the vehicle acceleration curve in the object acceleration curve, it can be judged that the vehicle object may have abnormal motion (such as sudden fall, slipping off the seat or abnormal posture change), and the object motion abnormality information is generated. The object motion abnormality information is structured by marking the time point, abnormal amplitude and its frequency and other data to provide an accurate basis for subsequent warnings.

[0155] Step 706, based on the abnormal motion information of the object, control the top light of the car to flash to issue an abnormal alarm.

[0156] Among them, the abnormal alarm flashing can be a warning signal sent by the car roof light through a preset flashing mode (such as frequency, color change, etc.) when abnormal movement of the vehicle object is detected.

[0157] Specifically, once the abnormal motion information of the object is detected, the system identifies the abnormal type and severity from the abnormal motion information of the object, and further triggers the alarm function of the car's top light according to the type and severity of the abnormality to control the car's top light to flash an abnormal alarm, wherein the alarm function selects a flashing mode that matches the abnormal type and severity from the set flashing mode of the top light through the control module to perform abnormal alarm flashing, including flashing frequency, brightness and color. For example, for minor abnormalities (such as short-term posture deviation), the top light may flash at a low frequency to prompt attention; for serious abnormalities (such as the object falling or being unresponsive for a long time), the top light flashes at a high frequency or changes color (such as a red warning light) to send a strong alarm signal. In addition, the system can link other vehicle-mounted alarm devices (such as sound alarms, seat vibrations or information prompt screens) to ensure that the vehicle object and other occupants can quickly perceive abnormal situations and take timely measures, effectively improving the level of safety protection in the car.

[0158] In this embodiment, by obtaining the acceleration change curves of the vehicle object and the target vehicle and accurately analyzing the similarity between the two, the rapid detection of abnormal motion of the vehicle object is achieved. When the motion behavior of the object deviates significantly from the normal dynamic characteristics of the vehicle, the system can generate motion abnormality information in real time and remind the occupants or drivers of potential risks by flashing the abnormal alarm of the car's top light. This process not only improves the intelligent level of in-vehicle safety management, but also provides timely visual alarms when the object has sudden abnormal motion (such as fainting, slipping or unexpected posture changes), which helps to quickly respond to and handle emergencies, thereby significantly improving the safety and riding experience during vehicle operation.

[0159] In an exemplary embodiment, Figure 8 As shown, comparing the similarity between the object acceleration change curve and the vehicle acceleration change curve to determine the object motion abnormality information of the vehicle object includes steps 802 to 806. Among them:

[0160] Step 802: Continuously derive the object acceleration change curve to obtain the object jerk change curve.

[0161] The object jerk change curve may be a time series curve obtained by continuously deriving the object acceleration change curve, reflecting the rate and severity of the object acceleration change.

[0162] Specifically, in order to improve the accuracy of the curve, a filtering algorithm (such as low-pass filtering or Kalman filtering) is applied to the acceleration change curve to eliminate noise and sensor errors, ensuring that the curve is smooth and truly reflects the trend of the dynamic change of the object's motion. The filtered object acceleration change curve of the vehicle object is further continuously differentiated to calculate the instantaneous acceleration change rate of each point of the object acceleration change curve, and the collected instantaneous acceleration change rate is processed using a numerical differentiation algorithm (such as the central difference method or the sliding window gradient method), thereby generating a curve reflecting the intensity of the vehicle object's motion as the jerk change curve. Among them, the significant peaks and rapidly changing areas in the jerk curve indicate that the object may have experienced sudden movement or drastic posture changes.

[0163] Step 804: Continuously derive the vehicle acceleration change curve to obtain the vehicle jerk change curve.

[0164] The vehicle jerk change curve may be a time series curve obtained by continuously deriving the vehicle acceleration change curve, reflecting the severity and frequency of acceleration changes during dynamic operations (such as braking, acceleration, and steering) of the vehicle, and describing the violent movement characteristics of the vehicle.

[0165] Specifically, since vehicle acceleration data usually comes from high-precision on-board sensors, its processing process first needs to be synchronized with the object acceleration curve, and the data must be uniformly filtered and normalized to eliminate device differences and signal offsets. Then, the vehicle acceleration change curve is continuously derived through the same numerical differentiation method to generate the vehicle jerk change curve. This curve represents the intensity and dynamic characteristics of the vehicle's movement caused by operations (such as acceleration, deceleration, or turning).

[0166] Step 806 : When the similarity between the object jerk change curve and the vehicle jerk change curve is lower than a threshold, compare the direction information of the object acceleration and the vehicle acceleration corresponding to several moments.

[0167] The direction information may be the direction data of the acceleration vector in three-dimensional space, which is usually represented by calculating the angle, cosine value or unit vector of the vector.

[0168] Specifically, the jerk change curve of the object is analyzed for similarity with the jerk change curve of the vehicle. The dynamic time warping (DTW) algorithm or the cross-correlation analysis method is usually used to calculate the time series matching degree of the curves. When the similarity is lower than the set threshold, it indicates that the dynamic behaviors of the two are not consistent in the overall trend. At this time, it is necessary to further compare the acceleration direction information of the two at multiple key moments. By extracting the acceleration vector direction at each moment (such as by calculating the angle or direction cosine of the three-dimensional vector), it is verified whether the movement direction of the object is consistent with that of the vehicle.

[0169] Step 808: When the direction information of the object acceleration and the vehicle acceleration are different at any time, the abnormal motion information of the object is determined according to the object jerk change curve and the vehicle jerk change curve.

[0170] Specifically, when the direction information of the object acceleration and the vehicle acceleration at any moment is different, the details of the object jerk change curve and the vehicle jerk change curve are further analyzed, including the peak amplitude, change rate and frequency distribution. When an abnormal deviation appears in the object jerk curve that exceeds the error bar of the curve (such as the jerk in certain periods far exceeds the corresponding value of the vehicle or presents an excessively high fluctuation frequency), the system determines that the vehicle object may have abnormal movement. For example, a sudden high jerk may indicate that the object has accidentally fallen, while a continuous low jerk may reflect an abnormal static state. Combined with the characteristic points and abnormal amplitude of the jerk curve, object motion abnormality information including abnormal type, time, characteristic parameters and abnormal duration is generated to provide an accurate basis for subsequent warning and control decisions. For example, when a vehicle collides, the object jerk change curve and the vehicle jerk change curve have differences at the same time, that is, the vehicle jerk change curve moves forward on the time axis relative to the object jerk change curve.

[0171] In this embodiment, the jerk change curve is generated by continuously deriving the acceleration change curves of the vehicle object and the target vehicle, so as to capture the dynamic characteristics of the acceleration change more finely. By analyzing the similarity of the two jerk change curves, when it is found that the similarity is lower than the set threshold, the acceleration direction information at each moment is further compared to accurately locate the deviation of the object and the vehicle movement. When the acceleration direction is inconsistent at any moment, the abnormal movement behavior of the object is quickly identified in combination with the characteristics of the jerk change curve. This method can effectively detect possible abnormal states of vehicle objects (such as sudden slippage, posture imbalance or abnormal movement) and generate abnormal information in a timely manner, which helps to improve the accuracy and response speed of in-vehicle safety monitoring and significantly improve the intelligence level and safety assurance capabilities of vehicle operation.

[0172] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0173] Based on the same inventive concept, the embodiment of the present application also provides a vehicle dome light control device for implementing the above-mentioned vehicle dome light control method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the vehicle dome light control device provided below can refer to the above-mentioned limitations on a vehicle dome light control method, and will not be repeated here.

[0174] In an exemplary embodiment, Fig. 9 As shown, a car ceiling light control device is provided, including: an analysis data acquisition module 902, an emotional state recognition module 904, an objective function construction module 906 and a lamp bead parameter adjustment module 908, wherein:

[0175] The analysis data acquisition module 902 is used to acquire physiological perception data of the vehicle object and interior lighting data corresponding to the target vehicle when a touch signal of the vehicle object on the car ceiling light is detected;

[0176] The emotional state recognition module 904 is used to recognize the emotional state information of the vehicle object according to the physiological perception data;

[0177] An objective function construction module 906 is used to construct an objective function for optimizing the emotional state of a vehicle object according to the physiological perception data and the in-vehicle lighting data;

[0178] The lamp bead parameter adjustment module 908 is used to solve the emotional state optimization objective function by taking the output value of the emotional state optimization objective function as the minimum value as the target condition, and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle;

[0179] Among them, each brightness adjustment parameter and each color temperature adjustment parameter are used to adjust the corresponding lamp beads.

[0180] Each module in the above-mentioned automobile ceiling light control device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0181] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.10 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the server. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for controlling a car ceiling light is implemented.

[0182] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0183] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0184] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0185] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-mentioned method embodiments.

[0186] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0187] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0188] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0189] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for controlling a car ceiling light, characterized in that: The method comprises: After detecting a touch signal of a vehicle object on a car ceiling light, physiological perception data of the vehicle object is acquired, and interior lighting data corresponding to the target vehicle is acquired; identifying emotional state information of the vehicle object according to the physiological perception data; Constructing an optimization objective function for the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data; The expression of the emotional state optimization objective function is: in, Optimize the output value of the objective function for the emotional state, To predict the time domain length, For at the moment Predicted future The emotional state information of the vehicle object at a moment, is the emotional state information of the desired vehicle object, is a positive definite symmetric matrix that weights the emotional states, For at the moment Predicted future The adjustment amount of the lamp bead brightness and lamp bead color temperature at each moment, is a positive definite symmetric matrix that weights the system control; Taking the output value of the emotional state optimization objective function as the minimum value as the target condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle, including: According to the hardware continuous parameter characteristics of the automobile ceiling light, setting the brightness temperature adjustment constraint conditions corresponding to each of the lamp beads; According to the hardware instantaneous parameter characteristics of the automobile ceiling light, setting the brightness temperature emergency adjustment conditions corresponding to each of the lamp beads; Taking the emotional state optimization objective function as the solution range within the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameter and the color temperature adjustment parameter of each of the lamp beads; Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

2. The method according to claim 1, characterized in that The method of solving the emotional state optimization objective function within the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition as the solution range, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead includes: Taking the output value of the emotional state optimization objective function under the brightness temperature adjustment constraint as the solution range, solving the emotional state optimization objective function to obtain the objective function solution result; When the objective function solution result indicates that the output value of the emotional state optimization objective function fails to converge within the brightness temperature adjustment constraint condition, the brightness temperature emergency adjustment condition is used as the solution range to solve the emotional state optimization objective function and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

3. The method according to claim 2, characterized in that The method of using the brightness temperature emergency adjustment condition as the solution range, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead includes: Determining an emergency solution mode of the emotional state optimization objective function according to the solution endpoint value of the objective function solution in the brightness temperature adjustment constraint condition; According to the emergency solution mode, the value range of the brightness temperature emergency adjustment condition is adjusted to obtain a brightness emergency value range and a color temperature emergency value range; The brightness emergency value range and the color temperature emergency value range are used as the solution range to solve the emotional state optimization objective function and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

4. The method according to claim 2, characterized in that: The method further comprises: When the objective function solution result indicates that the output value of the emotional state optimization objective function converges within the brightness temperature adjustment constraint condition, partitioning each of the lamp beads to obtain partition information of each lamp bead; According to the partition information of each lamp bead and the vehicle object, the lighting prediction control optimization is performed on the solution result of the objective function to obtain the brightness fine-grained optimization information and the color temperature fine-grained optimization information corresponding to each lamp bead; According to the emotional state weight of each lamp bead and the system control weight, error correction is performed on the brightness fine-grained optimization information and the color temperature fine-grained optimization information to obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead.

5. The method according to claim 1, characterized in that The method further comprises: Acquire an object acceleration change curve of the vehicle object, and acquire a vehicle acceleration change curve corresponding to the target vehicle; Comparing the similarity between the object acceleration change curve and the vehicle acceleration change curve, and determining the object motion abnormality information of the vehicle object; According to the abnormal object motion information, the car top light is controlled to flash to emit an abnormal alarm.

6. The method according to claim 5, characterized in that The comparing the similarity between the object acceleration change curve and the vehicle acceleration change curve to determine the object motion abnormality information of the vehicle object includes: Continuously deriving the object acceleration change curve to obtain the object jerk change curve; Continuously deriving the vehicle acceleration change curve to obtain a vehicle jerk change curve; When the similarity between the object jerk change curve and the vehicle jerk change curve is lower than a threshold, comparing the direction information of the object acceleration and the vehicle acceleration corresponding to a plurality of moments; In the case that the direction information of the object acceleration and the vehicle acceleration at any time is different, the object motion abnormality information is determined according to the object jerk change curve and the vehicle jerk change curve.

7. A car ceiling light control device, characterized in that: The device comprises: The analysis data acquisition module is used to acquire physiological perception data of the vehicle object and interior lighting data corresponding to the target vehicle when a touch signal of the vehicle object on the car ceiling light is detected; An emotional state recognition module, used to recognize emotional state information of the vehicle object according to the physiological perception data; An objective function construction module, used to construct an objective function for optimizing the emotional state of the vehicle object according to the physiological perception data and the in-vehicle lighting data; The expression of the emotional state optimization objective function is: in, Optimize the output value of the objective function for the emotional state, To predict the time domain length, For at the moment Predicted future The emotional state information of the vehicle object at a moment, is the emotional state information of the desired vehicle object, is a positive definite symmetric matrix that weights the emotional states, For at the moment Predicted future The adjustment amount of the lamp bead brightness and lamp bead color temperature at each moment, is a positive definite symmetric matrix that weights the system control; The lamp bead parameter adjustment module is used to solve the emotional state optimization objective function by taking the output value of the emotional state optimization objective function as the minimum value as the target condition, and obtain the brightness adjustment parameters and color temperature adjustment parameters of each lamp bead in the automobile ceiling light of the target vehicle, including: According to the hardware continuous parameter characteristics of the automobile ceiling light, setting the brightness temperature adjustment constraint conditions corresponding to each of the lamp beads; According to the hardware instantaneous parameter characteristics of the automobile ceiling light, setting the brightness temperature emergency adjustment conditions corresponding to each of the lamp beads; Taking the emotional state optimization objective function as the solution range within the brightness temperature adjustment constraint condition and the brightness temperature emergency adjustment condition, solving the emotional state optimization objective function, and obtaining the brightness adjustment parameter and the color temperature adjustment parameter of each of the lamp beads; Among them, each of the brightness adjustment parameters and each of the color temperature adjustment parameters are used to adjust the corresponding lamp beads.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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