A control method and control system for intelligent four-color motorcycle lights

Abstract

The present application discloses a control method and a control system for an intelligent four-color motorcycle lamp, which relate to the technical field of motorcycle lamps. The method comprises obtaining current driving environment information of a motorcycle, the current driving environment information including weather conditions, light intensity, road type and vehicle speed; determining the color and brightness of a required light source based on the current driving environment information; generating a light source control instruction, the light source control instruction being used to control the color and brightness of an LED light source of a lamp bead board of the four-color motorcycle lamp; sending the light source control instruction to a driver board, which controls the lighting of the LED light source; monitoring the temperature at the light source based on a built-in temperature sensor, and adjusting the speed of a cooling fan according to the temperature information; monitoring the humidity inside a lampshade of the motorcycle lamp based on a built-in humidity sensor, and adjusting the size of an air vent connected to the lampshade of the motorcycle lamp based on the humidity information; the present application improves the control efficiency of the four-color motorcycle lamp and realizes intelligent light source control.

Description

Technical Field

[0001] The present application relates to the technical field of motorcycle lights, and in particular to a control method and a control system for an intelligent four-color motorcycle light. Background Art

[0002] With the widespread use of motorcycles in daily life, night driving safety has become one of the important research directions. Although existing motorcycle lamps have adopted LED light sources, which have advantages such as energy saving and long life, they still have some shortcomings in different usage scenarios (such as foggy days, cloudy days, etc.) and personal preferences.

[0003] In order to solve the problem that LED lamps in the existing technology can only perform simple lighting tasks and cannot adjust the brightness of the light source or replace light sources with different penetration according to different usage scenarios (foggy days, cloudy days, etc.) and personal preferences, a four-color motorcycle lamp has appeared on the market. The four-color motorcycle lamp includes a base, a cooling fan, a connector line, a lamp bead board and a driver board. The base includes a heat-conducting outer shell and a heat-conducting inner shell. The heat-conducting inner shell is a hollow cylinder with an open end, and the heat-conducting outer shell is a hollow cylinder with open ends. The open ends of the two are fixedly connected, the lamp bead board and the driver board are snapped together, and a brightness-adjustable LED light source is fixed on the lamp bead board, and the LED light source is four different colors.

[0004] Although the existing intelligent four-color motorcycle lights have solved these problems to a certain extent, there is still room for improvement: although the existing intelligent four-color motorcycle lights can adjust the color and brightness of the light source through manual settings, there is a defect that the light source control is not intelligent enough. Although equipped with a cooling fan, the speed of the cooling fan cannot be adjusted, and the heat dissipation control is not fine enough. Therefore, there is a defect that the control efficiency of the four-color motorcycle lights is low and it is not intelligent enough, and there is room for improvement. Summary of the Invention

[0005] In order to improve the control efficiency of four-color motorcycle lights and realize intelligent light source control, the present application provides a control method and a control system for an intelligent four-color motorcycle light.

[0006] In the first aspect, the invention objectives of this application are achieved by adopting the following technical solutions:

[0007] A method for controlling an intelligent four-color motorcycle light, comprising:

[0008] Obtaining the current driving environment information of the motorcycle, including weather conditions, light intensity, road type, and vehicle speed;

[0009] Determining the color and brightness of the required light source based on the current driving environment information;

[0010] Generate a light source control instruction, the light source control instruction is used to control the color and brightness of the LED light source of the lamp bead board of the four-color motorcycle light; send the light source control instruction to the driver board, and the driver board controls the LED light source to light up according to the light source control instruction;

[0011] Based on the built-in temperature sensor, the temperature at the light source is monitored, and the speed of the cooling fan is adjusted according to the temperature information; based on the built-in humidity sensor, the humidity inside the lampshade of the motorcycle light is monitored, and the size of the vent connected to the lampshade of the motorcycle light is adjusted according to the humidity information.

[0012] By adopting the above technical solution, the safety and driving experience of motorcycle driving at night are improved, and the control efficiency of four-color motorcycle lights is improved. Through on-board sensors, photosensors, GPS modules, speed sensors and other devices, the current driving environment information of the motorcycle is obtained in real time, including weather conditions, light intensity, road type and vehicle speed; based on the obtained driving environment information, the required light source color and brightness are intelligently determined. For example, an ice-blue light source is selected in foggy weather to improve penetration, and the light source brightness is increased to improve the lighting effect at night or in dim light conditions. The dynamic adjustment function enables the motorcycle lights to better adapt to different driving conditions; according to the monitored temperature information, the speed of the cooling fan is dynamically adjusted. When the temperature exceeds the preset threshold, the speed of the cooling fan is increased to quickly dissipate heat; when the temperature is below the preset threshold, the speed of the cooling fan is reduced to save energy. This refined heat dissipation management not only improves the heat dissipation effect, but also extends the service life of the lamp. According to the monitored humidity information, the size of the vent connected to the lampshade is dynamically adjusted. When the humidity exceeds the preset threshold, the size of the vent is increased to increase ventilation and prevent moisture condensation inside the lampshade. When the humidity is lower than the preset threshold, the size of the vent is reduced to reduce dust entry. The humidity management measures effectively prevent moisture condensation inside the lampshade and improve the reliability and life of the light source.

[0013] In a preferred example of the present application, before determining the color and brightness of the required light source based on the current driving environment information, the method further includes:

[0014] Obtaining driving environment information and lamp setting parameters of a motorcycle lamp, and determining a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is traveling at a low speed based on the driving environment information and the lamp setting parameters;

[0015] generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand;

[0016] Obtaining a lamp brightness change reference range representing a lamp brightness change threshold, and generating a motorcycle lamp brightness control model based on the lamp brightness change reference range and the lamp brightness comparison table;

[0017] The acquired current driving state information is input into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp.

[0018] By adopting the above technical solution, by comprehensively considering the current driving environment information of the motorcycle (such as weather conditions, light intensity, road type and vehicle speed) and the lamp setting parameters (such as the maximum brightness, minimum brightness and color change rate of the lamp), it is possible to intelligently predict the lighting needs of the motorcycle under different driving conditions, and generate a lamp brightness comparison table and a brightness control model based on this. By adjusting the color and brightness of the motorcycle lights in real time, it is ensured that the driver can be provided with the best field of view in various driving environments, thereby improving driving safety and comfort. Adjusting the lamp brightness according to actual needs avoids unnecessary energy waste, helps to extend the lamp life and improve energy utilization efficiency, thereby achieving the purpose of enhancing safety and energy saving and efficiency.

[0019] In a preferred example of the present application, the step of obtaining driving environment information and lamp setting parameters of a motorcycle lamp, and determining a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is traveling at a low speed based on the driving environment information and the lamp setting parameters, specifically includes:

[0020] Acquiring motorcycle driving environment information and lamp setting parameters of the motorcycle lamp, wherein the lamp setting parameters include maximum brightness, minimum brightness, and color change rate of the lamp;

[0021] determining a first predicted lighting requirement of the motorcycle under normal driving conditions based on the weather conditions, light intensity, and road conditions;

[0022] A second predicted lighting requirement of the motorcycle when traveling at a low speed is determined according to the traveling speed of the motorcycle, the weather conditions, and the road conditions.

[0023] By adopting the above technical solution, detailed information about the motorcycle's driving environment and lamp setting parameters are obtained, and based on this information, the motorcycle's lighting needs under different driving conditions are determined. Specifically, this includes obtaining the motorcycle's driving environment information and lamp setting parameters, determining the motorcycle's first predicted lighting needs under normal driving conditions based on weather conditions, light intensity, and road conditions. This ensures that the lamps provide the most suitable lighting effects in various weather conditions such as sunny days, rainy days, and nighttime, and on different road surfaces such as urban roads and rural roads, thereby improving driving safety and comfort. Furthermore, the second predicted lighting needs of the motorcycle when driving at low speeds are determined based on the motorcycle's driving speed, weather conditions, and road conditions. This avoids using excessive brightness at low speeds, reduces interference to the driver and other traffic participants, and ensures sufficient lighting effects to improve safety.

[0024] In a preferred example of the present application, generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp based on the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand specifically includes:

[0025] determining target brightness values ​​of the lamp under different driving conditions according to the maximum brightness and minimum brightness of the lamp of the motorcycle, and the first predicted lighting demand and the second predicted lighting demand;

[0026] Calculating a demand difference between the first predicted lighting demand and the second predicted lighting demand to obtain a rate of change for adjusting the brightness of the lamp;

[0027] Obtaining a brightness adjustment strategy for determining the actual brightness of the lamp according to the target brightness value and the change rate;

[0028] In combination with the color change rate of the lamp and the brightness adjustment strategy, a lamp brightness comparison table for comparing the brightness of motorcycle lamps is generated.

[0029] By adopting the above technical solution, the system comprehensively considers the maximum and minimum brightness of the lamp, as well as the first predicted lighting demand and the second predicted lighting demand, and can set appropriate target brightness values ​​for the lamp under different driving conditions; by calculating the demand difference between the first predicted lighting demand and the second predicted lighting demand, the change rate of adjusting the lamp brightness is obtained, making the brightness change smoother and avoiding sudden brightness changes from disturbing the driver; the brightness adjustment strategy is combined with the color change rate of the lamp, so that the system can quickly and accurately adjust the color and brightness of the lamp under different driving conditions, improve energy efficiency, and through smooth brightness changes and appropriate color changes, the system can provide the driver with a more comfortable driving experience and reduce eye fatigue.

[0030] In a preferred example of the present application, before determining the first predicted lighting requirement of the motorcycle under normal driving conditions based on the weather conditions, light intensity, and road conditions, the method further includes:

[0031] Obtaining the sensitivity of a light sensor of a motorcycle lamp, and determining an initial lighting requirement of the motorcycle lamp according to the weather condition and the sensitivity of the light sensor;

[0032] Obtaining a correction coefficient for adjusting a first predicted lighting demand according to an initial lighting demand of the motorcycle lamp;

[0033] The determining, based on the weather conditions, light intensity, and road conditions, of a first predicted lighting requirement of the motorcycle under normal driving conditions specifically includes:

[0034] A first predicted lighting requirement of the motorcycle under normal driving conditions is determined based on the correction coefficient, the weather conditions, the light intensity and the road conditions.

[0035] By adopting the above technical solution, the sensitivity of the light sensor of the motorcycle lamp is obtained, and combined with the weather conditions, the system can more accurately judge the initial lighting requirements of the motorcycle lamp. The correction coefficient obtained based on the initial lighting requirements can be used to make more precise adjustments to the first predicted lighting requirements, thereby improving the accuracy of the prediction. By introducing the correction coefficient, the system can dynamically adjust the brightness of the lamp according to the actual driving environment, ensuring that the most appropriate lighting effect can be provided in various situations.

[0036] In a preferred example of the present application, the step of inputting the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp specifically includes:

[0037] Obtaining current driving state information of the motorcycle, inputting the current driving state information into a motorcycle lamp brightness control model, and obtaining a lamp brightness adjustment instruction;

[0038] The brightness of the motorcycle lamp is adjusted according to the lamp brightness adjustment instruction.

[0039] By adopting the above technical solution, the latest driving environment information can be obtained in a timely manner, providing accurate data support for subsequent brightness adjustment. The application of the correction coefficient makes the first predicted lighting demand more in line with actual needs, thereby improving the adaptability and accuracy of the system.

[0040] In the second aspect, the invention objective of this application is achieved by adopting the following technical solutions:

[0041] A control system for an intelligent four-color motorcycle light is applied to the control method for an intelligent four-color motorcycle light as described above. The system comprises:

[0042] A driving environment information acquisition module is used to obtain the current driving environment information of the motorcycle, including weather conditions, light intensity, road type and vehicle speed;

[0043] a light source requirement determination module, configured to determine the color and brightness of the required light source based on the current driving environment information;

[0044] A light source instruction generation module, used to generate light source control instructions, wherein the light source control instructions are used to control the color and brightness of the LED light source of the lamp bead board of the four-color motorcycle light;

[0045] A drive control module, configured to receive the light source control instruction and control the LED light source to light up according to the light source control instruction;

[0046] Temperature monitoring module, with a built-in temperature sensor, is used to monitor the temperature at the light source and adjust the speed of the cooling fan based on the temperature information;

[0047] The humidity monitoring module has a built-in humidity sensor for monitoring the humidity inside the lampshade of the motorcycle light and adjusting the size of the vent connected to the lampshade of the motorcycle light according to the humidity information.

[0048] By adopting the above technical solution, the driving environment information acquisition module can obtain real-time information about the motorcycle's current driving environment, including weather conditions, light intensity, road type, and vehicle speed. This information provides accurate data support for the system, enabling it to adjust the color and brightness of the lamps based on the actual environment. The light source requirement determination module determines the required light source color and brightness based on the current driving environment information. The light source instruction generation module generates corresponding light source control instructions, and the drive control module controls the lighting of the LED light source based on these instructions. Intelligent adjustment ensures that the lamps provide optimal lighting effects in different weather and road conditions, improving the driver's field of view and thus enhancing driving safety. The system can smoothly adjust the lamp brightness according to the driving status, avoiding sudden brightness changes that may cause interference to the driver, further improving safety.

[0049] In a preferred embodiment of the present application, the system includes:

[0050] a lighting demand prediction module, configured to obtain driving environment information and lamp setting parameters of a motorcycle lamp, and determine, based on the driving environment information and the lamp setting parameters, a first predicted lighting demand of the motorcycle under different driving conditions and a second predicted lighting demand when the motorcycle is traveling at a low speed;

[0051] a lamp brightness comparison table generation module, connected to the lighting demand prediction module, for generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand;

[0052] a brightness control model generation module, connected to the lamp brightness comparison table generation module, for obtaining a lamp brightness change reference range representing a lamp brightness change threshold, and generating a motorcycle lamp brightness control model based on the lamp brightness change reference range and the lamp brightness comparison table;

[0053] The current state information processing module is connected to the brightness control model generating module and is used to input the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp.

[0054] In summary, this application includes at least one of the following beneficial technical effects:

[0055] 1. Real-time acquisition of the motorcycle's current driving environment information, including weather conditions, light intensity, road type, and vehicle speed. Based on the acquired driving environment information, the required light source color and brightness are intelligently determined. For example, an ice-blue light source is selected in foggy weather to improve penetration, and the light source brightness is increased to improve the lighting effect at night or in low light conditions. The dynamic adjustment function enables the motorcycle lights to better adapt to different driving conditions. The cooling fan speed is dynamically adjusted based on the monitored temperature information. When the temperature exceeds the preset threshold, the cooling fan speed is increased to quickly dissipate heat. When the temperature is below the preset threshold, the cooling fan speed is reduced to save energy. This refined heat dissipation management not only improves the heat dissipation effect but also extends the service life of the lamp. The size of the vent connected to the lampshade is dynamically adjusted based on the monitored humidity information. When the humidity exceeds the preset threshold, the vent size is increased to increase ventilation and prevent moisture condensation inside the lampshade. When the humidity is below the preset threshold, the vent size is reduced to reduce dust intrusion. The humidity management measures effectively prevent moisture condensation inside the lampshade and improve the reliability and life of the light source.

[0056] 2. By comprehensively considering the maximum and minimum brightness of the lamp, as well as the first and second predicted light demands, the system can set appropriate target brightness values ​​for the lamp under different driving conditions. By calculating the demand difference between the first and second predicted light demands, the system determines the rate of change for adjusting the lamp brightness, making brightness changes smoother and avoiding sudden brightness changes that may cause interference to the driver. The brightness adjustment strategy incorporates the lamp's color change rate, allowing the system to quickly and accurately adjust the lamp's color and brightness under different driving conditions, thereby improving energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of a method for controlling an intelligent four-color motorcycle light in one embodiment of the present application;

[0058] Figure 2 This is a flow chart before step S2 in a method for controlling an intelligent four-color motorcycle light in one embodiment of the present application;

[0059] Figure 3 This is a flowchart of step S21 in a method for controlling an intelligent four-color motorcycle light in one embodiment of the present application. DETAILED DESCRIPTION

[0060] The present application is further described in detail below with reference to the accompanying drawings.

[0061] In one embodiment, if Figure 1 As shown, the present application discloses a method for controlling an intelligent four-color motorcycle light, which specifically includes the following steps:

[0062] S1: Acquire current driving environment information of the motorcycle, which includes weather conditions, light intensity, road type, and vehicle speed.

[0063] In this embodiment, the current weather condition information is obtained through the vehicle-mounted sensor, the light intensity of the current environment is obtained through the photosensor, the type of the current road is obtained through the GPS module, and the current vehicle speed is obtained through the speed sensor.

[0064] S2: Based on the current driving environment information, determine the color and brightness of the required light source.

[0065] In this embodiment, a suitable light source color is selected according to weather conditions. For example, if the weather condition is foggy, an ice blue light source is selected. The brightness of the light source is adjusted according to the light intensity and road type. For example, if the current light intensity is low and the vehicle is traveling on a highway, a high-brightness light source is selected.

[0066] S3: Generate a light source control instruction, which is used to control the color and brightness of the LED light source of the lamp bead board of the four-color motorcycle light; send the light source control instruction to the driver board, and the driver board controls the LED light source to light up according to the light source control instruction.

[0067] In this embodiment, the controller generates corresponding control instructions based on the determined light source color and brightness, and transmits the control instructions to the driver board through the connector line. The driver board controls the LED light source on the lamp bead board to light up according to the specified color and brightness based on the received control instructions.

[0068] S4: Monitor the temperature of the light source based on the built-in temperature sensor and adjust the speed of the cooling fan according to the temperature information; monitor the humidity inside the lampshade of the motorcycle light based on the built-in humidity sensor and adjust the size of the vent connected to the lampshade of the motorcycle light according to the humidity information.

[0069] In this embodiment, the speed of the cooling fan is dynamically adjusted according to the temperature information. For example, if the temperature exceeds 40 degrees Celsius, the speed of the cooling fan is increased. The size of the vent is dynamically adjusted according to the humidity information. For example, if the humidity exceeds 70%, the size of the vent is increased.

[0070] For example, the temperature sensor detects that the temperature at the light source is 35 degrees Celsius. Since the temperature does not exceed the preset threshold (for example, 40 degrees Celsius), the cooling fan maintains its current speed. The humidity sensor detects that the humidity inside the lampshade is 60%. Since the humidity does not exceed the preset threshold (for example, 70%), the vent maintains its current size.

[0071] In one embodiment, if Figure 2 As shown, before step S2, a method for controlling an intelligent four-color motorcycle light further includes:

[0072] S21: Acquire driving environment information and lamp setting parameters of the motorcycle lamp, and determine a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is driving at a low speed based on the driving environment information and the lamp setting parameters.

[0073] In this embodiment, the lamp setting parameters include the maximum brightness, minimum brightness, characteristic parameters of light sources of different colors, etc. The lighting requirements of the motorcycle under different driving conditions are predicted based on weather conditions, light intensity, road type and vehicle speed. For example, high-brightness and high-penetration light sources are required when driving at high speeds, and moderate brightness and comfortable light sources are required when driving on urban roads. In particular, the lighting requirements when driving at low speeds are predicted. For example, soft brightness and light sources of specific colors are required when parking or driving slowly to improve safety.

[0074] S22: generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand.

[0075] In this embodiment, the first predicted lighting demand is to predict the lighting demand of the motorcycle under different driving conditions (such as high-speed driving, urban road driving, etc.) based on the driving environment information and the lamp setting parameters; the second predicted lighting demand is specifically predicted for the lighting demand when the motorcycle is driving at low speed, such as the brightness and color required when parking or driving slowly.

[0076] Specifically, a comparison table is generated according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand. The comparison table may be a multi-dimensional table, for example:

[0077] Travel: different driving conditions (high speed, city road, low speed)

[0078] Columns: Different weather conditions (sunny, rainy, foggy)

[0079] Cell: Recommended brightness and color settings.

[0080] S23: Obtain a lamp brightness change reference range representing a lamp brightness change threshold, and generate a motorcycle lamp brightness control model according to the lamp brightness change reference range and a lamp brightness comparison table.

[0081] In this embodiment, the lamp brightness change reference range defines a threshold range of lamp brightness change, which is used to determine whether the lamp brightness needs to be adjusted.

[0082] Specifically, define the threshold range of lamp brightness change, for example, when the brightness change exceeds 10%, adjustment is required, and set the upper and lower limits of the brightness change, for example, the brightness change range is 30% to 70%.

[0083] S24: Inputting the acquired current driving state information into a motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp.

[0084] In this embodiment, a brightness control instruction is generated according to the output result of the model, and the brightness control instruction is transmitted to the driver board through the connector line. The driver board adjusts the brightness of the LED light source on the lamp bead board according to the received brightness control instruction.

[0085] In one embodiment, if Figure 3 As shown, in step S21, the driving environment information and the lamp setting parameters of the motorcycle lamp are obtained, and the first predicted lighting demand of the motorcycle in different driving states and the second predicted lighting demand when the motorcycle is driving at a low speed are determined based on the driving environment information and the lamp setting parameters, which specifically includes:

[0086] S211: Acquire motorcycle driving environment information and lamp setting parameters of the motorcycle lamp, where the lamp setting parameters include maximum brightness, minimum brightness, and color change rate of the lamp.

[0087] Specifically, the maximum brightness and minimum brightness of the lamp are part of the lamp setting parameters, and are used to limit the brightness range of the lamp.

[0088] S212: Determine a first predicted lighting requirement of the motorcycle under normal driving conditions based on weather conditions, light intensity, and road conditions.

[0089] Specifically, the first predicted lighting demand is to judge the lighting demand of the motorcycle under normal driving conditions based on weather conditions, light intensity and road conditions. For example, if the weather condition is sunny, choose a warm white light source, and if it is foggy, choose an ice blue light source. When the light intensity is strong, choose a lower brightness, and when the light is weak, choose a higher brightness. When the road condition is a city road, choose constant brightness, and when the road condition is a highway, choose high brightness. As long as any driving environment information determines that higher brightness is required, a higher brightness will be uniformly selected.

[0090] S213: Determine a second predicted lighting requirement of the motorcycle when traveling at a low speed based on the traveling speed of the motorcycle, weather conditions, and road conditions.

[0091] In this embodiment, the second predicted lighting demand is to determine the lighting demand of the motorcycle when it is traveling at a low speed based on the traveling speed of the motorcycle, weather conditions, and road conditions.

[0092] For example, based on the consideration of driving speed, choose a light source with soft brightness and specific color when driving at low speed or parking; based on the consideration of weather conditions, choose a light source with high brightness and high penetration when driving at low speed on rainy days; based on the consideration of road conditions, choose a light source with moderate brightness and comfortable color when driving at low speed on rural roads.

[0093] In one embodiment, in step S22, a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp is generated based on the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand, specifically including:

[0094] S221: Determine target brightness values ​​of the lamp under different driving conditions according to the maximum brightness and the minimum brightness of the lamp of the motorcycle, and the first predicted lighting demand and the second predicted lighting demand.

[0095] Specifically, the target brightness value is determined according to the first predicted lighting demand and the second predicted lighting demand, combined with the maximum brightness and the minimum brightness, to determine the target brightness value under different driving conditions.

[0096] S222: Calculate the demand difference between the first predicted lighting demand and the second predicted lighting demand to obtain a change rate for adjusting the brightness of the lamp.

[0097] Specifically, the rate of change of the lamp brightness is calculated based on the demand difference value to ensure smooth and rapid brightness adjustment.

[0098] S223: Obtain a brightness adjustment strategy for determining the actual brightness of the lamp according to the target brightness value and the change rate.

[0099] In this embodiment, the color change rate refers to the speed at which the lamp switches between different colors.

[0100] S224: Generate a lamp brightness comparison table for comparing the brightness of the motorcycle lamps based on the color change rate and brightness adjustment strategy of the lamps.

[0101] For example, the maximum brightness and minimum brightness of the lamp are obtained, for example, the maximum brightness is 100% and the minimum brightness is 20%, and the target brightness values ​​under different driving conditions are determined according to the first predicted lighting demand (for example, an ice blue light source with a brightness of 80% is required for normal driving in foggy weather) and the second predicted lighting demand (for example, an ice blue light source with a brightness of 50% is required for low-speed driving in foggy weather); in step S223, the demand difference between the first predicted lighting demand (80%) and the second predicted lighting demand (50%) is calculated, that is, 80%-50%=30%, and the change rate of adjusting the brightness of the lamp is calculated according to the demand difference, for example, the change rate is 5% brightness adjustment per second, for example, adjusting from 50% to 80%: for example, increasing the brightness by 5% per second until it reaches 80%, for example, adjusting from 80% to 50%: reducing the brightness by 5% per second until it reaches 50%.

[0102] In step S224, the color change rate of the lamp is obtained, for example, a color change rate of 1 second per second. The brightness adjustment strategy and the color change rate are combined to generate a lamp brightness comparison table. The comparison table contains recommended brightness and color settings for different driving conditions, as well as the adjustment rate.

[0103] In one embodiment, before step S2, a method for controlling an intelligent four-color motorcycle light further includes:

[0104] S201: Obtain the sensitivity of the light sensor of the motorcycle lamp, and determine the initial lighting requirement of the motorcycle lamp according to the weather conditions and the sensitivity of the light sensor.

[0105] In this embodiment, the sensitivity of the light sensor refers to the sensitivity of the light sensor to changes in ambient light.

[0106] For example, based on weather conditions (such as sunny, rainy, and foggy) and the sensitivity of the light sensor, the initial lighting requirements of the motorcycle lamps are preliminarily determined. For example, on sunny days, the initial lighting requirement is low, such as 50% brightness; on rainy days, the initial lighting requirement is high, such as 70% brightness; on foggy days, the initial lighting requirement is the highest, such as 80% brightness.

[0107] S202: Obtaining a correction coefficient for adjusting a first predicted lighting demand according to an initial lighting demand of the motorcycle lamp.

[0108] Specifically, the correction coefficient is a factor used to adjust the first predicted lighting demand and is calculated based on the initial lighting demand.

[0109] For example, the initial light requirement is low: the correction factor might be 1.2.

[0110] Initial light requirements are high: the correction factor might be 1.0.

[0111] Initial light requirements are highest: a correction factor of perhaps 0.8 is possible.

[0112] In step S212, the first predicted lighting requirement of the motorcycle under normal driving conditions is determined based on weather conditions, light intensity, and road conditions, specifically including:

[0113] S2121: Determine the first predicted lighting requirement of the motorcycle under normal driving conditions based on the correction coefficient, weather conditions, light intensity, and road conditions.

[0114] Specifically, the road condition refers to the type of road surface currently being traveled, such as urban roads, highways, rural roads, etc.; for example, if the initial lighting requirement is 80% and the correction coefficient is 0.8, the final first predicted lighting requirement is 80%*0.8=64%.

[0115] In this embodiment, when the corrected first predicted lighting demand is added, 80%*0.8=64% brightness, ice blue light source, the controller generates a control instruction including 64% brightness and ice blue, and transmits the control instruction to the driver board through the connector line. The driver board adjusts the brightness and color of the LED light source on the lamp bead board according to the received control instruction to achieve 64% brightness and ice blue.

[0116] In one embodiment, in step S24, the acquired current driving state information is input into a motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp, specifically including:

[0117] S241: Acquire current driving state information of the motorcycle, input the current driving state information into a motorcycle lamp brightness control model, and obtain a lamp brightness adjustment instruction.

[0118] In this embodiment, the acquired current driving state information (weather conditions, light intensity, road conditions, driving speed) is input into the motorcycle lamp brightness control model, and the motorcycle lamp brightness control model generates corresponding brightness adjustment instructions based on the current driving state information and a pre-set comparison table.

[0119] Specifically, the process of generating a luminaire brightness control model involves multiple steps, including data collection, parameter setting, model construction, and verification. The following is a detailed generation process and technical details:

[0120] (1) Data Collection:

[0121] Driving environment data, weather conditions, light intensity, road conditions, and driving speed.

[0122] Lamp parameter data:

[0123] Maximum brightness, minimum brightness, color change rate, and light sensor sensitivity.

[0124] (2) Parameter setting

[0125] Initial lighting requirements:

[0126] Based on weather conditions and light sensor sensitivity, the initial lighting requirements of motorcycle lamps are preliminarily determined. For example, the initial lighting requirement on foggy days is 80%, and the initial lighting requirement on sunny days is 50%.

[0127] Correction factor:

[0128] Based on the initial light requirement, a correction factor is calculated. For example, if the initial light requirement is 80%, the correction factor might be 0.8.

[0129] (3) Model construction

[0130] Feature extraction:

[0131] Weather conditions: categorical variables, such as sunny, rainy, and foggy.

[0132] Light intensity: continuous variable, unit is lux.

[0133] Road conditions: categorical variables, such as urban roads, highways, and rural roads.

[0134] Driving speed: continuous variable, unit is km / h.

[0135] Target variable:

[0136] Target brightness: continuous variable, unit is percentage.

[0137] Target color: categorical variable, such as warm white, ice blue, red, gold.

[0138] Model selection:

[0139] Regression model: used to predict target brightness values, such as decision tree regression and random forest regression.

[0140] Classification model: used to predict target color, such as logistic regression, decision tree classification, random forest classification, etc.

[0141] Model training: Use a historical dataset to train the model. The historical dataset should contain brightness and color settings under various driving environments.

[0142] For example, a training dataset might include the following fields:

[0143] Weather conditions, light intensity, road conditions, driving speed, actual brightness, actual color

[0144] Model validation: Use cross-validation to evaluate the performance of the model and ensure the model's prediction accuracy under different driving conditions.

[0145] Evaluation indicators can include mean square error (MSE), accuracy, F1 score, etc.

[0146] The model generation steps include:

[0147] Data preprocessing: Continuous variables (such as light intensity and driving speed) are normalized to be within the same range.

[0148] Encoding: Encode categorical variables (such as weather conditions, road conditions, and target colors).

[0149] Feature Engineering:

[0150] First, select the features that have the greatest impact on the target variable, such as using correlation analysis or feature importance assessment, and then create new features, such as combining light intensity and driving speed into a new feature.

[0151] Model training:

[0152] Select a model: Select an appropriate model based on the problem type. For example, use a random forest regression model to predict target brightness and a random forest classification model to predict target color.

[0153] Train the model: Use the training dataset to train the model and adjust the model parameters to optimize performance.

[0154] (IV) Model Validation

[0155] Cross-validation: Use cross-validation to evaluate the performance of the model and ensure the generalization ability of the model in different driving environments.

[0156] Performance evaluation: Calculate the model's mean square error (MSE), accuracy, F1 score, and other indicators to evaluate the model's prediction accuracy.

[0157] S242: Adjust the brightness of the motorcycle lamp according to the lamp brightness adjustment instruction.

[0158] Specifically, a control signal is generated according to the brightness adjustment instruction output by the model, and the control signal is transmitted to the driver board through the connector line. The driver board adjusts the brightness of the LED light source on the lamp bead board according to the received control signal.

[0159] It should be understood that the serial numbers of the steps in the above embodiments do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0160] In one embodiment, a control system for an intelligent four-color motorcycle light is provided. The control system for the intelligent four-color motorcycle light corresponds to the control method for the intelligent four-color motorcycle light in the above embodiment.

[0161] An intelligent four-color motorcycle light control system includes modules A, B, C, and D. The detailed description of each functional module is as follows:

[0162] A driving environment information acquisition module is used to obtain the current driving environment information of the motorcycle, including weather conditions, light intensity, road type and vehicle speed;

[0163] A light source requirement determination module is used to determine the color and brightness of the required light source based on the current driving environment information;

[0164] A light source instruction generation module is used to generate light source control instructions, which are used to control the color and brightness of the LED light source of the lamp bead board of the four-color motorcycle light;

[0165] The drive control module is used to receive the light source control instruction and control the LED light source to light up according to the light source control instruction;

[0166] Temperature monitoring module, with a built-in temperature sensor, is used to monitor the temperature at the light source and adjust the speed of the cooling fan based on the temperature information;

[0167] The humidity monitoring module has a built-in humidity sensor for monitoring the humidity inside the lampshade of the motorcycle light and adjusting the size of the vent connected to the lampshade of the motorcycle light according to the humidity information.

[0168] Optionally, a control system for an intelligent four-color motorcycle light also includes:

[0169] a lighting demand prediction module, configured to obtain driving environment information and lamp setting parameters of a motorcycle lamp, and determine a first predicted lighting demand of the motorcycle under different driving conditions and a second predicted lighting demand when the motorcycle is traveling at a low speed based on the driving environment information and the lamp setting parameters;

[0170] a lamp brightness comparison table generation module, connected to the light demand prediction module, for generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted light demand, and the second predicted light demand;

[0171] a brightness control model generation module, connected to the lamp brightness comparison table generation module, for obtaining a lamp brightness change reference range representing a lamp brightness change threshold, and generating a motorcycle lamp brightness control model based on the lamp brightness change reference range and the lamp brightness comparison table;

[0172] The current state information processing module is connected to the brightness control model generating module and is used to input the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp.

[0173] Regarding the specific limitations of the control system of the intelligent four-color motorcycle light, please refer to the limitations of the control method of an intelligent four-color motorcycle light above, and will not be repeated here; the various modules in the above-mentioned intelligent four-color motorcycle light control system can be implemented in whole or in part through software, hardware, or a combination thereof; the above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above-mentioned modules.

[0174] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for controlling an intelligent four-color motorcycle light, characterized in that: include: Obtaining the current driving environment information of the motorcycle, including weather conditions, light intensity, road type, and vehicle speed; Determining the color and brightness of the required light source based on the current driving environment information; Generate a light source control instruction, the light source control instruction is used to control the color and brightness of the LED light source of the lamp bead board of the four-color motorcycle light; send the light source control instruction to the driver board, and the driver board controls the LED light source to light up according to the light source control instruction; The built-in temperature sensor monitors the temperature at the light source and adjusts the speed of the cooling fan based on the temperature information. The built-in humidity sensor monitors the humidity inside the lampshade of the motorcycle light and adjusts the size of the vent connected to the lampshade based on the humidity information. Before determining the color and brightness of the required light source based on the current driving environment information, the method further includes: Obtaining driving environment information and lamp setting parameters of a motorcycle lamp, and determining a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is traveling at a low speed based on the driving environment information and the lamp setting parameters; generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand; Obtaining a lamp brightness change reference range representing a lamp brightness change threshold, and generating a motorcycle lamp brightness control model based on the lamp brightness change reference range and the lamp brightness comparison table; Inputting the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp; The obtaining of driving environment information and lamp setting parameters of a motorcycle lamp, and determining, based on the driving environment information and the lamp setting parameters, a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is traveling at a low speed, specifically includes: Acquiring motorcycle driving environment information and lamp setting parameters of the motorcycle lamp, wherein the lamp setting parameters include maximum brightness, minimum brightness, and color change rate of the lamp; determining a first predicted lighting requirement of the motorcycle under normal driving conditions based on the weather conditions, light intensity, and road conditions; determining a second predicted lighting requirement of the motorcycle when traveling at a low speed based on the traveling speed of the motorcycle, the weather conditions, and the road conditions; Before determining the first predicted lighting requirement of the motorcycle under normal driving conditions based on the weather conditions, light intensity, and road conditions, the method further includes: Obtaining the sensitivity of a light sensor of a motorcycle lamp, and determining an initial lighting requirement of the motorcycle lamp according to the weather condition and the sensitivity of the light sensor; Obtaining a correction coefficient for adjusting a first predicted lighting demand according to the initial lighting demand of the motorcycle lamp; The determining, based on the weather conditions, light intensity, and road conditions, of a first predicted lighting requirement of the motorcycle under normal driving conditions specifically includes: A first predicted lighting requirement of the motorcycle under normal driving conditions is determined based on the correction coefficient, the weather conditions, the light intensity and the road conditions.

2. The method for controlling an intelligent four-color motorcycle light according to claim 1, characterized in that: The generating, according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand, a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp specifically includes: determining target brightness values ​​of the lamp under different driving conditions according to the maximum brightness and minimum brightness of the lamp of the motorcycle, and the first predicted lighting demand and the second predicted lighting demand; Calculating a demand difference between the first predicted lighting demand and the second predicted lighting demand to obtain a rate of change for adjusting the brightness of the lamp; Obtaining a brightness adjustment strategy for determining the actual brightness of the lamp according to the target brightness value and the change rate; In combination with the color change rate of the lamp and the brightness adjustment strategy, a lamp brightness comparison table for comparing the brightness of motorcycle lamps is generated.

3. The control method of an intelligent four-color motorcycle light according to claim 1, characterized in that: The step of inputting the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp specifically includes: Obtaining current driving state information of the motorcycle, inputting the current driving state information into a motorcycle lamp brightness control model, and obtaining a lamp brightness adjustment instruction; The brightness of the motorcycle lamp is adjusted according to the lamp brightness adjustment instruction.

4. An intelligent four-color motorcycle light control system, characterized in that: The method for controlling an intelligent four-color motorcycle light according to any one of claims 1 to 3 comprises: A driving environment information acquisition module is used to obtain the current driving environment information of the motorcycle, including weather conditions, light intensity, road type and vehicle speed; a light source requirement determination module, configured to determine the color and brightness of the required light source based on the current driving environment information; A light source instruction generation module, used to generate light source control instructions, wherein the light source control instructions are used to control the color and brightness of the LED light source of the lamp bead board of the four-color motorcycle light; A drive control module, configured to receive the light source control instruction and control the LED light source to light up according to the light source control instruction; Temperature monitoring module, with a built-in temperature sensor, is used to monitor the temperature at the light source and adjust the speed of the cooling fan based on the temperature information; The humidity monitoring module has a built-in humidity sensor for monitoring the humidity inside the lampshade of the motorcycle light and adjusting the size of the vent connected to the lampshade of the motorcycle light according to the humidity information.

5. The intelligent four-color motorcycle light control system according to claim 4, characterized in that: The system comprises: a lighting demand prediction module, configured to obtain driving environment information and lamp setting parameters of a motorcycle lamp, and determine, based on the driving environment information and the lamp setting parameters, a first predicted lighting demand of the motorcycle under different driving conditions and a second predicted lighting demand when the motorcycle is traveling at a low speed; a lamp brightness comparison table generation module, connected to the lighting demand prediction module, for generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand; a brightness control model generation module, connected to the lamp brightness comparison table generation module, for obtaining a lamp brightness change reference range representing a lamp brightness change threshold, and generating a motorcycle lamp brightness control model based on the lamp brightness change reference range and the lamp brightness comparison table; a current state information processing module, connected to the brightness control model generating module, for inputting the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp; Before determining the color and brightness of the required light source based on the current driving environment information, the method further includes: Obtaining driving environment information and lamp setting parameters of a motorcycle lamp, and determining a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is traveling at a low speed based on the driving environment information and the lamp setting parameters; generating a lamp brightness comparison table for adjusting the brightness of the motorcycle lamp according to the lamp setting parameters, the first predicted lighting demand, and the second predicted lighting demand; Obtaining a lamp brightness change reference range representing a lamp brightness change threshold, and generating a motorcycle lamp brightness control model based on the lamp brightness change reference range and the lamp brightness comparison table; Inputting the acquired current driving state information into the motorcycle lamp brightness control model to adjust the brightness of the motorcycle lamp; The obtaining of driving environment information and lamp setting parameters of a motorcycle lamp, and determining, based on the driving environment information and the lamp setting parameters, a first predicted lighting requirement of the motorcycle under different driving conditions and a second predicted lighting requirement when the motorcycle is traveling at a low speed, specifically includes: Acquiring motorcycle driving environment information and lamp setting parameters of the motorcycle lamp, wherein the lamp setting parameters include maximum brightness, minimum brightness, and color change rate of the lamp; determining a first predicted lighting requirement of the motorcycle under normal driving conditions based on the weather conditions, light intensity, and road conditions; determining a second predicted lighting requirement of the motorcycle when traveling at a low speed based on the traveling speed of the motorcycle, the weather conditions, and the road conditions; Before determining the first predicted lighting requirement of the motorcycle under normal driving conditions according to the weather conditions, light intensity, and road conditions, the method further includes: Obtaining the sensitivity of a light sensor of a motorcycle lamp, and determining an initial lighting requirement of the motorcycle lamp according to the weather condition and the sensitivity of the light sensor; Obtaining a correction coefficient for adjusting a first predicted lighting demand according to the initial lighting demand of the motorcycle lamp; The determining, based on the weather conditions, light intensity, and road conditions, of a first predicted lighting requirement of the motorcycle under normal driving conditions specifically includes: A first predicted lighting requirement of the motorcycle under normal driving conditions is determined based on the correction coefficient, the weather conditions, the light intensity and the road conditions.

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