Vehicle alarm prompting method, device and equipment based on reading light language, storage medium and computer program product

Abstract

The invention relates to the technical field of electric vehicles, in particular to a vehicle alarm prompting method, device and equipment based on a reading light language, a storage medium and a computer program product. According to the method, when an in-vehicle alarm signal is obtained, the current alarm type of the in-vehicle alarm signal is determined based on a preset alarm classification strategy, and the alarm type of the in-vehicle alarm signal comprises a child leaving prompt, a vehicle door risk prompt, a temperature abnormity prompt, an air abnormity prompt and a cleaning prompt; determining a target illumination mode of the reading lamp according to a mapping relation strategy between the current alarm type and alarm illumination; the reading lamp is controlled to be turned on and execute the target lighting mode, and the vehicle safety is improved.

Description

Technical Field

[0001] The present application relates to the technical field of electric vehicles, and in particular to a vehicle warning prompt method, device, equipment, storage medium and computer program product based on reading light language. Background Art

[0002] Existing vehicle lighting languages ​​are mostly used in the external environment, such as high and low beam lights, turn signals, brake lights, etc., and are mainly used for communication between the driver and the outside world. However, in the in-car prompt scenario, it currently mainly relies on the dashboard, voice prompts or central control screen. These methods have the following problems: information cannot be transmitted when the owner is not in the car, such as being unable to remind children or pets left behind after locking the car; the driver's attention is distracted during driving, and visual prompts may increase the driver's burden; the prompts are not intuitive enough and it is difficult to quickly attract the attention of the passengers. As a traditional lighting device, the roof reading light has adjustable functions of multiple brightness and modes, but its application is still limited to lighting needs and has not been fully developed as an interactive tool. Therefore, how to apply reading lights to in-car warning prompts to improve vehicle safety has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] The main purpose of this application is to provide a vehicle warning prompt method, device, equipment, storage medium and computer program product based on reading light language, aiming to solve the technical problem of how to improve vehicle safety.

[0004] To achieve the above purpose, the present application provides a vehicle warning prompt method based on reading light language, the method comprising the following steps:

[0005] When an in-vehicle alarm signal is obtained, the current alarm type of the in-vehicle alarm signal is determined based on a preset alarm classification strategy, wherein the alarm types of the in-vehicle alarm signal include a child left behind reminder, a door risk reminder, a temperature abnormality reminder, an air abnormality reminder, and a cleaning reminder;

[0006] Determining a target lighting mode of a reading light according to the current alarm type and alarm lighting mapping relationship strategy;

[0007] The reading lamp is controlled to turn on and execute the target lighting mode.

[0008] In one embodiment, before the step of determining the target lighting mode of the reading light according to the current alarm type and the alarm lighting mapping relationship strategy, the step further includes:

[0009] Respectively associating the child left behind reminder with the first lighting mode, the door risk reminder with the second lighting mode, the temperature abnormality reminder with the third lighting mode, the air abnormality reminder with the fourth lighting mode, and the cleaning reminder with the fifth lighting mode;

[0010] Based on the association result, the warning lighting mapping relationship strategy is generated.

[0011] In one embodiment, before the step of determining the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy when the in-vehicle alarm signal is acquired, the method further includes:

[0012] Acquire seat pressure data, door radar data, in-vehicle temperature data, in-vehicle air quality data, and camera data as data to be processed;

[0013] Comparing the data to be processed with preset standard data;

[0014] Based on the comparison result, it is determined whether to issue the in-vehicle warning signal.

[0015] In one embodiment, when the in-vehicle alarm signal is acquired, the step of determining the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy includes:

[0016] When the in-vehicle alarm signal is obtained, classification matching is performed based on the preset alarm classification strategy, the data source of the in-vehicle alarm signal, and the data features of the in-vehicle alarm signal;

[0017] If the classification matches multiple results, the multiple results are deduplicated and merged based on the preset priority order to obtain the current alarm type.

[0018] In one embodiment, after the step of determining the target lighting mode of the reading light according to the current alarm type and the alarm lighting mapping relationship strategy, the step further includes:

[0019] Acquire target lighting information corresponding to the target lighting mode, the target lighting information including target brightness level, target flickering frequency, target duration, and target special effect;

[0020] A control instruction is generated based on the target brightness level, the target flickering frequency, the target duration, and the target special effect.

[0021] In one embodiment, the step of controlling the reading light to turn on and execute the target lighting mode includes:

[0022] Obtaining the control instruction;

[0023] Determining whether the reading light is in a standby state;

[0024] If so, the reading light is controlled to turn on, and based on the control instruction, the reading light is adjusted to the target brightness level, the target flashing frequency, the target duration, and the target special effect.

[0025] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle warning prompt device based on reading light language, and the vehicle warning prompt device based on reading light language includes:

[0026] An alarm type determination module is used to determine the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy when an in-vehicle alarm signal is obtained, wherein the alarm types of the in-vehicle alarm signal include a child left behind reminder, a door risk reminder, a temperature abnormality reminder, an air abnormality reminder, and a cleaning reminder;

[0027] A lighting mode determination module, used to determine a target lighting mode of a reading light according to the current alarm type and alarm lighting mapping relationship strategy;

[0028] The target module is used to control the reading light to turn on and execute the target lighting mode.

[0029] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle warning prompt device based on reading light language, the device comprising: a memory, a processor, and a vehicle warning prompt program based on reading light language stored on the memory and executable on the processor, the vehicle warning prompt program based on reading light language being configured to implement the steps of the vehicle warning prompt method based on reading light language as described above.

[0030] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, on which a vehicle warning prompt program based on reading light language is stored. When the vehicle warning prompt program based on reading light language is executed by a processor, the steps of the vehicle warning prompt method based on reading light language as described above are implemented.

[0031] In addition, to achieve the above-mentioned purpose, the present application also proposes a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the vehicle warning prompt method based on reading light language as described above.

[0032] When the in-car alarm signal is obtained, the present application determines the current alarm type of the in-car alarm signal based on the preset alarm classification strategy, wherein the alarm types of the in-car alarm signal include child left behind reminder, door risk reminder, temperature abnormality reminder, air abnormality reminder and cleaning reminder; determines the target lighting mode of the reading light according to the current alarm type and alarm lighting mapping relationship strategy; controls the reading light to turn on and execute the target lighting mode. The present application accurately determines the type of in-car alarm signal based on the preset alarm classification strategy, and realizes intuitive and efficient light alarm prompts through the linkage of the target lighting mode and the reading light. Compared with traditional voice or screen prompts, light prompts can quickly attract the attention of passengers while reducing interference to the driver, effectively improving the safety of the in-car environment. This method makes full use of the existing hardware resources of the reading light without the need for additional equipment, expands the function of the reading light, and improves vehicle safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of the first embodiment of the vehicle warning prompt method based on reading light language of the present application;

[0034] Figure 2 This is a schematic diagram of a sub-flow in the second embodiment of the vehicle warning prompt method based on reading light language of this application;

[0035] Figure 3 This is a schematic diagram of a sub-flow in the third embodiment of the vehicle warning prompt method based on reading light language of this application;

[0036] Figure 4 This is a schematic diagram of the module structure of a vehicle warning prompt device based on reading light language according to an embodiment of the present application;

[0037] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the vehicle warning prompt method based on reading light language in the embodiment of the present application.

[0038] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0039] 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.

[0040] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0041] It should be noted that the existing vehicle lighting language is mostly used in the external environment, such as high and low beam lights, turn signals, brake lights, etc., and is mainly used for communication between the driver and the outside world. However, in the in-car prompt scene, it currently mainly relies on the dashboard, voice prompts or central control screen. These methods have the following problems: information cannot be transmitted when the owner is not in the car, such as being unable to remind children or pets left behind after locking the car; the driver's attention is distracted during driving, and visual prompts may increase the driver's burden; the prompts are not intuitive enough and it is difficult to quickly attract the attention of the passengers. As a traditional lighting device, the roof reading light has adjustable functions of multiple brightness and modes, but its application is still limited to lighting needs and has not been fully developed as an interactive tool. Therefore, how to apply reading lights to in-car warning prompts to improve vehicle safety has become a technical problem that needs to be solved urgently.

[0042] The main solution of the present application is: when an in-vehicle alarm signal is obtained, based on a preset alarm classification strategy, the current alarm type of the in-vehicle alarm signal is determined, wherein the alarm types of the in-vehicle alarm signal include child left behind reminder, door risk reminder, temperature abnormality reminder, air abnormality reminder and cleaning reminder; according to the current alarm type and the alarm lighting mapping relationship strategy, the target lighting mode of the reading light is determined; the reading light is controlled to turn on and execute the target lighting mode.

[0043] This application accurately determines the type of in-vehicle warning signal based on a preset warning classification strategy, and realizes intuitive and efficient light warning prompts through the linkage of target lighting mode and reading lights. Compared with traditional voice or screen prompts, light prompts can quickly attract passengers' attention while reducing interference to drivers, effectively improving the safety of the in-vehicle environment. This method makes full use of the existing hardware resources of reading lights, does not require additional equipment, expands the functions of reading lights, and improves vehicle safety.

[0044] It should be noted that the execution subject of the method of this embodiment can be a computing service device with data processing, network communication and program running functions, or it can be the above-mentioned vehicle warning prompt device based on reading light language with the same or similar functions. This embodiment and the following embodiments will be described by taking the vehicle warning prompt device based on reading light language as an example.

[0045] Based on this, the first embodiment of the vehicle warning prompt method based on reading light language of this application is proposed, please refer to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle warning prompt method based on reading light language of the present application.

[0046] In this embodiment, the vehicle warning prompt method based on reading light language includes the following steps:

[0047] S1: when an in-vehicle alarm signal is obtained, based on a preset alarm classification strategy, determining a current alarm type of the in-vehicle alarm signal, wherein the alarm types of the in-vehicle alarm signal include a child left behind reminder, a door risk reminder, a temperature abnormality reminder, an air abnormality reminder, and a cleaning reminder;

[0048] It should be noted that the in-vehicle warning signal is an abnormal state signal detected by the vehicle sensor or control system that may affect the in-vehicle environment or the safety of the occupants, such as the seat sensor detecting that a child is left behind, or the radar sensor detecting that there is a risk object near the door. The preset warning classification strategy is a set of pre-set classification algorithms or logic based on the vehicle's preset rules, which is used to classify and identify the detected warning signals and determine their specific warning types. The current warning type is a specific warning category determined according to the warning classification strategy, such as child left behind reminder, door risk reminder, etc., which is a clear description of the warning signal. The child left behind reminder refers to the reminder signal generated when the vehicle is locked and a child is still detected in the vehicle, which is used to prevent children from being forgotten in the vehicle. The door risk reminder refers to the reminder signal when the vehicle detects that there is an approaching moving object (such as a vehicle, bicycle, etc.) outside the door when the passenger opens the door to avoid potential collision risks. The temperature abnormality reminder refers to the signal generated by the in-vehicle temperature sensor when the in-vehicle temperature exceeds the set safety range (such as above 40℃ or below 0℃), which is used to ensure the safety and comfort of the occupants. The abnormal air warning refers to the warning signal generated when the air quality sensor in the car detects that the concentration of carbon dioxide or other harmful gases exceeds the standard, reminding the user to take measures such as ventilation to improve the air quality. The cleaning warning is a warning signal generated based on the vehicle's visual sensor or user settings to remind the user to clean the dirty areas in the car.

[0049] Specifically, the vehicle continuously monitors the in-vehicle environment or occupant behavior through built-in sensors and system modules (such as seat pressure sensors, radars, temperature sensors, air quality sensors, etc.). Once abnormal data is detected (such as weight on the seat but no one operates the vehicle after it is locked, the temperature in the vehicle is too high, etc.), the system generates a corresponding in-vehicle alarm signal. At this point, the signal is only in a preliminary state without classification and needs further processing and classification.

[0050] Furthermore, based on the preset alarm classification strategy, the collected alarm signals are analyzed and matched. For example: when the seat pressure sensor and infrared sensor are combined to confirm that there is biological activity in the car and no one returns after the car is locked, it is classified as a child left behind reminder; when the radar detects a moving object outside the door and determines that the safety distance is insufficient, it is classified as a door risk reminder; when the temperature sensor or air quality sensor exceeds the safety threshold, it is classified as a temperature abnormality reminder or an air abnormality reminder respectively. Through strategy rules and multi-sensor data fusion, the system finally determines the current alarm type corresponding to the signal for use in subsequent steps.

[0051] By presetting the alarm classification strategy, the system can quickly and accurately identify the type of in-car alarms based on multiple sensor inputs, effectively avoiding false alarms or missed alarms. For example, the risk of children being left behind or door collisions can be significantly reduced through child abandonment reminders and door risk reminders. Based on multi-sensor data (such as pressure, infrared, radar, air quality, etc.) and classification strategies, accurate judgment of complex environments can be achieved. For example, by combining temperature sensors and air quality sensors, users can be reminded to adjust the temperature and ventilate at the same time to improve the quality of the in-car environment. The application of classification strategies reduces redundant alarm information and only transmits clear alarm types, making the prompts more intuitive and easier for users to understand, avoiding the interference of multiple invalid reminders on users. At the same time, this step provides accurate alarm basis for subsequent light reminder modes, realizing a smarter in-car interactive experience. By classifying and processing complex signals in the car, the accuracy and safety of vehicle alarms are improved, and the foundation for the execution of intelligent light language is laid.

[0052] S2: Determine a target lighting mode of the reading light according to the current alarm type and the alarm lighting mapping relationship strategy;

[0053] It should be noted that the warning lighting mapping relationship strategy is a preset rule or logic that matches each warning type with a specific reading light lighting mode, which is used to intuitively convey warning information. For example: Child left behind reminder → high brightness low frequency flashing; door risk reminder → high brightness high frequency flashing. The target lighting mode is the final operating mode of the reading light determined according to the mapping relationship strategy, including brightness level, flashing frequency, special effect mode (such as breathing light), etc., which is used to express specific warning information.

[0054] Specifically, when the system identifies the current alarm type, it queries the target lighting mode corresponding to the type based on the vehicle's built-in mapping relationship strategy. For example, if the current alarm type is "children left behind reminder", the system determines that the target lighting mode is "high brightness low frequency flashing" by looking up the mapping table. If the current alarm type is "door risk reminder", the system sets the target lighting mode to "high brightness high frequency flashing". The mapping relationship table is pre-defined by the vehicle manufacturer or customized by the user through the vehicle system or mobile phone app to ensure flexibility and adaptability.

[0055] Furthermore, after finding the target mode, the system further decomposes its parameters and generates executable hardware control instructions. These parameters include: Brightness level: such as high brightness and low brightness. Flashing frequency: such as low frequency (1 time / second) or high frequency (2 times / second). Special effect mode: such as breathing light (gradually bright and dim) or intermittent flashing (bright for a period of time, then off and then bright again). Duration: The running time of the target mode, such as 10 seconds, 30 seconds or indefinitely, until the alarm state is lifted. Through the above process, the complex alarm logic is converted into specific lighting control parameters to complete the determination of the target lighting mode.

[0056] Each warning type corresponds to a unique target lighting mode, and users can quickly understand the warning content through the lighting effects without complicated interpretation. For example, high-frequency flashing can convey emergency information, and breathing lights can express milder prompts. Converting warning information into light modes is more intuitive than voice or screen prompts, and will not significantly interfere with the driver's attention. It is especially suitable for transmitting non-emergency information (such as air abnormality prompts) during driving. Through flexible mapping strategies, users can customize lighting modes according to their preferences, increase the personalization and controllability of the system, and improve the intelligence of the vehicle. Using existing reading light hardware to implement warning information prompts, there is no need to add additional equipment, reducing system complexity and cost. By combining the current warning type with the warning lighting mapping strategy, an accurate and intuitive light prompt function is achieved, which not only improves the efficiency of warning information transmission, but also enhances the safety and user experience of the vehicle.

[0057] S3: Control the reading light to turn on and execute the target lighting mode.

[0058] It should be noted that the reading light is a lighting device installed on the roof of the vehicle, usually used to illuminate the local space of the occupants. In this step, the reading light is used to perform the warning prompt function. Control refers to sending specific hardware execution instructions to the reading light through the vehicle control system to make it operate according to the target lighting mode.

[0059] Specifically, the target lighting mode is parsed into hardware executable control parameters, and a start command is sent to the reading light module through the vehicle control bus (such as the CAN bus). These commands include: Turn on command: activate the reading light module and start the target mode. Parameter loading: pass specific operating parameters to the light drive unit, such as brightness level (high brightness or low brightness), flashing frequency (such as high frequency 2 times / second or low frequency 1 time / second), special effect mode (such as breathing light).

[0060] Furthermore, after receiving the control instruction, the reading light module operates according to the target mode: Brightness control: adjust the light current or voltage to achieve the target brightness. Flashing mode: control the switching frequency of the light through the PWM (pulse width modulation) signal to achieve a high-frequency or low-frequency flashing effect. Special effects mode: control the lighting effect according to a specific algorithm. For example, the "breathing light" creates a soft prompt effect through a gradual brightening and dimming cycle. Duration: Controls the length of time the light mode runs, and automatically turns off or switches to the default mode after reaching the set value. If the alarm status is updated (such as the alarm is lifted or upgraded), the system can dynamically adjust the reading light operation mode. For example: switch from low-brightness intermittent flashing to high-brightness high-frequency flashing.

[0061] By precisely controlling the brightness and mode of the reading lights, the system can quickly and intuitively convey warning information to the occupants. For example, high-frequency flashing lights can quickly attract attention and respond to emergency situations such as door risk warnings. Using existing reading light equipment to implement warning prompts, no additional hardware investment is required, which significantly reduces system complexity and cost, while giving full play to the multi-functional potential of reading lights. The light prompt form does not rely on voice or screen to avoid distracting the driver's attention, while providing visual and intuitive warnings to the occupants, especially for prompting scenarios such as children left behind or abnormal air in the car. Adjust the light mode in real time according to the changes in the alarm, such as switching from the low-brightness long-brightness of the "cleaning prompt" to the high-brightness high-frequency flashing of the "door risk prompt", to ensure the flexibility and efficiency of the alarm response. Through the precise control and mode execution of the reading lights, this step realizes a low-cost and efficient in-vehicle alarm prompt method, effectively improving vehicle safety and user experience.

[0062] When the in-vehicle alarm signal is obtained, this embodiment determines the current alarm type of the in-vehicle alarm signal based on the preset alarm classification strategy, wherein the alarm types of the in-vehicle alarm signal include child left behind reminder, door risk reminder, temperature abnormality reminder, air abnormality reminder and cleaning reminder; determines the target lighting mode of the reading light according to the current alarm type and alarm lighting mapping relationship strategy; controls the reading light to turn on and execute the target lighting mode. This embodiment accurately determines the type of in-vehicle alarm signal based on the preset alarm classification strategy, and realizes intuitive and efficient light alarm prompts through the linkage of the target lighting mode and the reading light. Compared with traditional voice or screen prompts, light prompts can quickly attract the attention of passengers while reducing interference to the driver, effectively improving the safety of the in-vehicle environment. This method makes full use of the existing hardware resources of the reading light without the need for additional equipment, expands the function of the reading light, and improves vehicle safety.

[0063] Based on the above first embodiment, a second embodiment of the vehicle warning prompt method based on reading light language is proposed. Figure 2 , Figure 2This is a schematic diagram of a sub-process in the second embodiment of the vehicle warning prompt method based on reading light language of the present application.

[0064] like Figure 2 As shown, in this embodiment, before step S2, the following is further included:

[0065] S2a: respectively associating the child left behind reminder with the first lighting mode, the door risk reminder with the second lighting mode, the temperature abnormality reminder with the third lighting mode, the air abnormality reminder with the fourth lighting mode, and the cleaning reminder with the fifth lighting mode;

[0066] S2b: Based on the association result, generate the warning lighting mapping relationship strategy.

[0067] It should be noted that the first to fifth lighting modes refer to the reading light operation modes defined according to the prompt type, including brightness, flashing frequency, special effect mode (such as breathing light, long light, intermittent flashing, etc.), and each mode corresponds to a specific prompt type. The alarm lighting mapping relationship strategy refers to a set of rules that associate a specific alarm type with its corresponding reading light lighting mode, ensuring a clear correspondence between the prompt type and the lighting performance for subsequent prompt execution.

[0068] Specifically, according to the safety and interaction requirements of the vehicle, a specific lighting mode is predefined for each warning type. For example: the child left behind reminder is associated with the first lighting mode (such as high brightness and low frequency flashing), making the prompt intuitive and easy to attract attention. The door risk warning is associated with the second lighting mode (such as high brightness and high frequency flashing) to emphasize urgency and danger warnings. The temperature abnormality prompt is associated with the third lighting mode (such as low brightness and intermittent flashing) to reflect the continuous prompt of non-emergency status. The air abnormality prompt is associated with the fourth lighting mode (such as low brightness breathing light), which gently prompts to improve the environmental quality. The cleaning prompt is associated with the fifth lighting mode (such as low brightness and long light) to express the nature of a regular reminder. Through these associations, the one-to-one correspondence between each warning type and the reading light lighting mode is clarified, forming a preliminary lighting mapping rule.

[0069] Furthermore, after completing the association between the above-mentioned warning types and lighting modes, a complete mapping strategy is generated based on these relationships. The structure of the mapping strategy contains a correspondence table between the warning types and the target modes, which records the specific lighting mode parameters (such as brightness, frequency, and special effects mode) associated with each warning type. The mapping strategy can be adjusted through the vehicle system or mobile phone App. For example, users can change the "children left behind reminder" from "high brightness and low frequency flashing" to "high brightness and long light" according to their preferences to meet personalized needs. The generated mapping strategy is stored in the vehicle control system for subsequent reminder function calls to ensure efficient linkage between light prompts and warning types.

[0070] Each warning type is associated with a specific lighting mode one by one, so that the warning information is presented intuitively through lights. Users can quickly understand the prompt content without additional interpretation, which helps to improve the efficiency of information transmission. Different prompt types (such as emergency warnings and regular prompts) use differentiated lighting expressions, which helps users quickly distinguish information priorities in various scenarios. For example, high-brightness and high-frequency flashing is suitable for door risk prompts, while low-brightness breathing lights are more suitable for air abnormality prompts. Through the flexible adjustment of mapping strategies, users can customize the correspondence between warnings and lighting modes, such as setting lighting effects that are more in line with their preferences, further enhancing the personalization and intelligent functions of the vehicle. Using existing reading light hardware to implement multiple prompt functions, and realizing logically clear and function-rich lighting interactions through mapping relationship strategies, the cost of new hardware is reduced, and the design and maintenance of the prompt system are simplified. By associating warning types with lighting modes and generating warning lighting mapping relationship strategies, the modular design and efficient interaction of light prompt functions are realized, which significantly improves the safety, intelligence and user experience of vehicles.

[0071] Based on the first embodiment above, in this embodiment, before step S1, the following is further included:

[0072] S1a: Acquire seat pressure data, door radar data, in-vehicle temperature data, in-vehicle air quality data, and camera data as data to be processed;

[0073] S1b: comparing the data to be processed with preset standard data;

[0074] S1c: Based on the comparison result, determine whether to issue the in-vehicle alarm signal.

[0075] It should be noted that the seat pressure data is the seat load information detected by the seat pressure sensor in the car, which is used to determine whether there are passengers (such as children) left in the seat. The door radar data is the surrounding environment data obtained by the millimeter-wave radar or ultrasonic sensor installed near the door, which is used to determine whether there are moving objects (such as vehicles or pedestrians) approaching outside the door. The in-car temperature data is the temperature value in the car cabin monitored in real time by the in-car temperature sensor, which is used to detect whether there are abnormal temperatures (such as too high or too low). The in-car air quality data is the in-car air pollutant concentration data collected by the air quality sensor (such as carbon dioxide sensor, PM2.5 detector), which is used to determine whether the air in the car meets the standard. The camera data is the image or video data collected by the camera in the car or near the door, which is used to assist in identifying the remains, dangerous objects or the cleaning status of the car. The preset standard data refers to the pre-set safety thresholds or reference values ​​of various environmental or state parameters, which are used to compare with the data to be processed collected by the sensor.

[0076] Specifically, environmental data inside and outside the vehicle are collected in real time through a variety of sensors and devices, including: Seat pressure sensor: detects the pressure value of the seat to determine whether there are any objects or organisms left on the seat. Door radar sensor: monitors moving objects around the door to obtain their distance and movement trajectory. In-car temperature sensor: detects the temperature inside the car to determine whether it is within the set comfort range. Air quality sensor: measures the concentration of pollutants in the air inside the car to determine whether it exceeds safety standards. Camera: captures images inside or outside the car to identify special situations (such as objects left behind or damaged areas). The collected data forms a data set to be processed, which includes multiple types of sensor data to provide basic information for subsequent processing.

[0077] Furthermore, the collected data to be processed is compared and analyzed with the preset standard data. If the seat pressure value is higher than a certain threshold and the vehicle is in a locked state, a child may be left behind, and the system marks it as abnormal. If the distance of the object detected outside the door is less than the safe distance, it is determined that there is a door risk. If the temperature inside the car exceeds the set range (such as higher than 40°C), it is marked as a temperature abnormality. If the carbon dioxide concentration or PM2.5 concentration exceeds the preset upper limit, the system marks it as an air abnormality. The image recognition algorithm is used to determine whether there are leftovers, dangerous objects or contaminated areas. Based on the comparison results, the system determines whether to trigger an alarm signal: if any comparison exceeds the threshold, a corresponding in-car alarm signal is generated and associated with a specific alarm type. If all data are within the standard range, it is determined that the state inside the car is normal and there is no need to issue an alarm signal.

[0078] By integrating multiple sensor data (such as pressure, radar, temperature, air quality, etc.), the in-vehicle environment and occupant status can be fully monitored to avoid misjudgment or missed judgment caused by a single data source. Real-time comparison of the data to be processed with the preset standard data enables rapid identification and real-time response to abnormal conditions, such as automatically triggering a child left behind reminder in a high-temperature car to effectively prevent potential dangers. According to vehicle configuration and usage requirements, the preset standard data can be dynamically adjusted or new sensor support can be added (such as expansion to humidity detection) to achieve a wider range of abnormal detection scenarios. Automated data collection and alarm signal generation reduce the need for user participation, making the vehicle more intelligent and friendly, and improving the overall interactive experience. Through the above steps, efficient monitoring of the in-vehicle environment and abnormal conditions is achieved, providing an accurate trigger basis for the subsequent light prompt function, while significantly improving the intelligence and safety of the vehicle.

[0079] When the in-vehicle alarm signal is obtained, this embodiment determines the current alarm type of the in-vehicle alarm signal based on the preset alarm classification strategy, wherein the alarm types of the in-vehicle alarm signal include child left behind reminder, door risk reminder, temperature abnormality reminder, air abnormality reminder and cleaning reminder; determines the target lighting mode of the reading light according to the current alarm type and alarm lighting mapping relationship strategy; controls the reading light to turn on and execute the target lighting mode. This embodiment accurately determines the type of in-vehicle alarm signal based on the preset alarm classification strategy, and realizes intuitive and efficient light alarm prompts through the linkage of the target lighting mode and the reading light. Compared with traditional voice or screen prompts, light prompts can quickly attract the attention of passengers while reducing interference to the driver, effectively improving the safety of the in-vehicle environment. This method makes full use of the existing hardware resources of the reading light without the need for additional equipment, expands the function of the reading light, and improves vehicle safety.

[0080] Based on the above second embodiment, a third embodiment of the vehicle warning prompt method based on reading light language is proposed. Figure 3 , Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the vehicle warning prompt method based on reading light language of the present application.

[0081] In this embodiment, step S1 includes:

[0082] S11: when the in-vehicle alarm signal is acquired, classification matching is performed based on the preset alarm classification strategy, the data source of the in-vehicle alarm signal, and the data feature of the in-vehicle alarm signal;

[0083] S12: If the classification matches multiple results, the multiple results are deduplicated and merged based on a preset priority order to obtain the current alarm type.

[0084] It should be noted that the data source refers to the sensor or module that generates the alarm signal, such as seat pressure sensor, door radar, air quality sensor, etc., which is used to identify the physical source of the signal. Data characteristics: Specific information contained in the alarm signal, such as pressure value, temperature value or air pollution concentration, is used for classification judgment. Classification matching refers to matching the alarm signal with the specific alarm type according to the preset classification strategy. The preset priority sorting is the priority order defined for different alarm types based on safety or urgency, and is used to determine the final priority alarm type among multiple classification results. Deduplication and merging refers to when the same alarm signal matches multiple results, redundancy is removed through logical merging or filtering, and a unique alarm type is finally output.

[0085] Specifically, when an alarm signal is detected in the vehicle, the system performs classification and matching based on the following logic: Based on the data source: first identify the source sensor of the signal, for example, the seat pressure signal may match the child left behind reminder, and the radar signal may match the door risk reminder. Based on data features: analyze the specific data value or change pattern of the signal, for example: the pressure sensor data is higher than the threshold and the vehicle is in a locked state, which may match the "child left behind reminder". If the radar sensor detects that the distance of the moving object is less than the safe distance, it will match the "door risk reminder". Based on a preset classification strategy: the alarm signal is matched to one or more alarm types through a rule matching algorithm (such as conditional judgment or machine learning model).

[0086] Furthermore, if the classification matching results correspond to multiple alarm types, the results are processed according to the preset priority: Priority sorting: Arrange the alarm types according to the degree of urgency. For example, "Door risk warning" takes precedence over "Cleaning reminder". If multiple results come from the same signal source but have overlapping features, the system will remove redundant results. For example, air quality data may trigger "Air abnormality prompt" and "Temperature abnormality prompt" at the same time, in which case the system merges them into a more comprehensive "Environmental abnormality prompt". Merge: When the results involve different signal sources, the system combines multiple alarm types into a comprehensive prompt based on priority and relevance. For example, "Children left behind prompt" and "High temperature in car prompt" may be merged into "Children left behind high temperature prompt". Finally, a unique current alarm type is output to provide clear instructions for subsequent light reminders or other actions.

[0087] Classification and matching based on data sources and data features can effectively reduce misjudgments and ensure that the alarm type accurately reflects the actual situation in the car. For example, the "child left behind reminder" is jointly judged by seat pressure and car lock status to avoid false alarms caused by single data. Through classification strategies and priority sorting, the system can process multiple signals at the same time to ensure that important alarms are delivered first while taking into account secondary information. For example, when "door risk" and "air abnormality" coexist, safety-related risk information is given priority. The deduplication and merging mechanism reduces redundant prompts, ensuring that the warning information received by the user is concise and easy to understand, and will not be confused by repeated or unnecessary prompts. Priority sorting ensures that emergency situations (such as door risks) can be handled quickly, which helps reduce accidents and improve the safety performance of the vehicle. Classification strategies and priorities can be adjusted according to actual usage scenarios to adapt to different vehicles and user needs, enhancing the flexibility and adaptability of the system. Through this step, the ability to accurately extract and determine the unique alarm type from multi-source signals is realized, providing a reliable basis for subsequent light prompts or other responses, while greatly improving the intelligence and safety of the vehicle.

[0088] Based on the above second embodiment, in this embodiment, after step S2, the following is further included:

[0089] S2a: Acquire target lighting information corresponding to the target lighting mode, wherein the target lighting information includes a target brightness level, a target flickering frequency, a target duration, and a target special effect;

[0090] S2b: Generate a control instruction based on the target brightness level, the target flickering frequency, the target duration, and the target special effect.

[0091] It should be noted that the target lighting mode is a reading light operating mode determined based on the mapping relationship between the alarm type and the alarm lighting, and includes a set of specific lighting parameters (brightness, flashing frequency, duration, special effects) to intuitively convey alarm information. The target lighting information is a set of parameters that describe the specific operating details of the target lighting mode, including: target brightness level: the light intensity of the reading light, which can be divided into high brightness, low brightness, etc.; target flashing frequency: the switching speed of the light, such as high-frequency flashing (2 times / second), low-frequency flashing (1 time / second); target duration: the operating duration of the light mode, such as 10 seconds, 30 seconds or indefinite duration; target special effects: additional dynamic performance of the light, such as breathing light (gradually bright and dim cycle) or long light (continuous lighting); control instructions: a specific set of instructions for operating the reading light hardware, including light brightness, current, voltage, pulse width modulation (PWM) signal, etc., to guide the reading light to execute the target lighting mode.

[0092] Specifically, after determining the target lighting mode, the specific parameters related to the mode are extracted from the internal mapping relationship table to generate the target lighting information. Including: target brightness level: extract the brightness setting of the light, for example, "high brightness" corresponds to high current output, "low brightness" corresponds to low current output; target flashing frequency: determine the flashing speed of the light, for example, "high frequency" corresponds to flashing twice per second, "low frequency" corresponds to flashing once per second; target duration: extract the running time of the light mode, for example, "10 seconds" means that the mode will automatically turn off or switch after 10 seconds; target special effect: determine whether there is an additional dynamic effect, for example, "breathing light" requires the light intensity to change from low to high and then from high to low in a certain period. The target lighting information is stored as a parameter set for the next step of generating control instructions.

[0093] Furthermore, specific hardware control instructions are generated based on the target lighting information. These include: brightness instructions: convert the target brightness level into specific current or voltage parameters. For example, the highlight mode corresponds to a high current output instruction; flickering instructions: use PWM (pulse width modulation) technology to control the flickering frequency, and achieve high-frequency or low-frequency flickering effects by setting the switching cycle; time control instructions: load the target duration parameters, and use the timer module to control the running time of the mode; special effect instructions: call special effect algorithms (such as breathing lights) to generate dynamically changing brightness curves, and convert them into continuous current adjustment instructions; the generated control instructions are passed to the reading light driver module to instruct the hardware to execute the target mode.

[0094] Through the combination of brightness, flashing frequency, duration and special effects, the system can accurately display the warning information. For example, high-frequency flashing transmits emergency information, and breathing lights transmit soft prompts, which improves the efficiency of warning transmission and the user's perception effect. Through the separation design of target lighting information and control instructions, the system can flexibly adapt to different lighting hardware and user needs. For example, users can adjust the brightness or flashing frequency without modifying the core logic. By parsing the target lighting information and generating control instructions, the system realizes diversified prompt functions based on the existing hardware, avoiding additional hardware investment and reducing system costs. The control instructions are generated based on real-time target lighting information and can quickly switch modes according to the changes in the alarm. For example, switching from high-brightness flashing to breathing lights can adapt to changes in the urgency of the alarm. The control instructions are formatted as standard hardware interface signals to ensure compatibility with the reading light driver module, which is convenient for system expansion and maintenance. By obtaining target lighting information and generating control instructions, the system realizes an efficient closed loop from alarm type to lighting hardware control, significantly improving the intelligence and user experience of the vehicle, while enhancing the transmission effect of the alarm information.

[0095] Based on the above second embodiment, in this embodiment, step S3 includes:

[0096] S31: Obtain the control instruction;

[0097] S32: Determine whether the reading light is in a standby state;

[0098] S33: If yes, control the reading light to turn on, and based on the control instruction, adjust the reading light to the target brightness level, the target flashing frequency, the target duration, and the target special effect.

[0099] It should be noted that the standby state refers to the default working state of the reading light. At this time, the reading light is not lit, but is in a ready state to receive control instructions at any time.

[0100] Specifically, obtain the control instruction: the control instruction generated in the previous step contains parameters such as target brightness level, flashing frequency, duration and special effects. The instruction is passed to the hardware control module as the execution parameter of the reading light. Determine the status of the reading light: Detect whether the reading light is in standby state through the hardware status monitoring module: Standby state: The reading light is not activated and is ready to receive new instructions. Non-standby state: The reading light may be in operation or fault state, and exception handling is required (such as interrupting the current mode or restoring the default state).

[0101] Furthermore, turn on the reading light: if the reading light is in standby mode, the system sends an "on" signal to activate the reading light hardware module. Adjust to the target mode: According to the specific parameters of the control instruction, gradually adjust the reading light to the target mode: Adjust the brightness: control the current or voltage to the target brightness level, such as setting a high current output to achieve high brightness. Set the flashing frequency: Use PWM (pulse width modulation) technology to set the flashing cycle according to the instruction to achieve high or low frequency flashing. Control duration: Call the timer module to ensure that the target mode automatically stops or switches after running for a set time. Execute special effects: If the instruction contains dynamic changes (such as breathing lights), the system adjusts the brightness curve through an algorithm to achieve a cyclic change of gradually brightening and dimming during operation. Dynamic adjustment: If a new alarm signal or instruction (such as an alarm upgrade) is received during the operation of the mode, the system can update the control instruction in real time and switch to a new target mode.

[0102] By detecting the standby state of the reading light, the failure of command execution due to device operation conflicts or failures can be avoided, ensuring the smoothness and reliability of mode switching. By adjusting the brightness, flashing frequency and special effects, the reading light can intuitively display different warning information, helping users to quickly understand and respond, and improving the efficiency and accuracy of prompts. It supports real-time update of instructions during operation, such as switching from "low-brightness intermittent flashing" to "high-brightness high-frequency flashing", which can adapt to changes in alarm priorities or upgrades in emergency situations. By separating the design of state judgment, control instructions and hardware execution, the system can easily adapt to different types of reading light hardware and achieve high scalability. By monitoring the standby state and controlling the duration, the false triggering or long-term operation of the light can be avoided, energy consumption can be optimized and the life of the device can be extended. By obtaining control instructions, judging the state of the reading light and executing the target mode, this step realizes an efficient closed loop from logic signals to hardware control, ensuring the accuracy and real-time nature of the warning prompts, while improving the safety of the vehicle and user experience.

[0103] When the in-vehicle alarm signal is obtained, this embodiment determines the current alarm type of the in-vehicle alarm signal based on the preset alarm classification strategy, wherein the alarm types of the in-vehicle alarm signal include child left behind reminder, door risk reminder, temperature abnormality reminder, air abnormality reminder and cleaning reminder; determines the target lighting mode of the reading light according to the current alarm type and alarm lighting mapping relationship strategy; controls the reading light to turn on and execute the target lighting mode. This embodiment accurately determines the type of in-vehicle alarm signal based on the preset alarm classification strategy, and realizes intuitive and efficient light alarm prompts through the linkage of the target lighting mode and the reading light. Compared with traditional voice or screen prompts, light prompts can quickly attract the attention of passengers while reducing interference to the driver, effectively improving the safety of the in-vehicle environment. This method makes full use of the existing hardware resources of the reading light without the need for additional equipment, expands the function of the reading light, and improves vehicle safety.

[0104] The present application also provides a vehicle warning prompt device based on reading light language, please refer to Figure 4 , Figure 4 The module structure diagram of the vehicle warning prompt device based on reading light language in the embodiment of the present application is as follows:

[0105] The alarm type determination module 401 is used to determine the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy when an in-vehicle alarm signal is obtained, wherein the alarm types of the in-vehicle alarm signal include a child left behind reminder, a door risk reminder, a temperature abnormality reminder, an air abnormality reminder, and a cleaning reminder;

[0106] The lighting mode determination module 402 is used to determine the target lighting mode of the reading light according to the current alarm type and alarm lighting mapping relationship strategy;

[0107] The target module 403 is used to control the reading light to turn on and execute the target lighting mode.

[0108] The vehicle warning prompt device based on reading light language provided in the embodiment of the present application adopts the vehicle warning prompt method based on reading light language in the above embodiment, which can solve the technical problem of how to improve vehicle safety. Compared with the prior art, the beneficial effects of the vehicle warning prompt device based on reading light language provided in the embodiment of the present application are the same as the beneficial effects of the vehicle warning prompt method based on reading light language provided in the above embodiment, and the other technical features of the vehicle warning prompt device based on reading light language are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0109] The present application provides a vehicle warning prompt device based on reading light language, and the vehicle warning prompt device based on reading light language includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle warning prompt method based on reading light language in the above-mentioned embodiment.

[0110] Reference below Figure 5 , Figure 5 The device structure diagram of the hardware operating environment involved in the vehicle warning prompt method based on reading light language in the embodiment of the present application shows a structural diagram of a vehicle warning prompt device based on reading light language suitable for implementing the embodiment of the present application. The vehicle warning prompt device based on reading light language in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The vehicle warning prompt device based on reading light language shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0111] like Figure 5As shown, the vehicle warning prompt device based on reading light language may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in a read-only memory (ROM: Read Only Memory) 1002 or the program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the vehicle warning prompt device based on reading light language are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the vehicle warning prompt device based on the reading light language to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a vehicle warning prompt device based on the reading light language with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0112] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0113] The vehicle warning prompt device based on reading light language provided by the present application adopts the vehicle warning prompt method based on reading light language in the above embodiment, which can solve the technical problem of how to improve vehicle safety. Compared with the prior art, the beneficial effects of the vehicle warning prompt device based on reading light language provided by the present application are the same as the beneficial effects of the vehicle warning prompt method based on reading light language provided by the above embodiment, and the other technical features of the vehicle warning prompt device based on reading light language are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0114] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0115] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0116] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the vehicle warning prompt method based on reading light language in the above-mentioned embodiment.

[0117] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0118] The computer-readable storage medium may be included in the vehicle warning prompt device based on the reading light language; or may exist independently without being assembled into the vehicle warning prompt device based on the reading light language.

[0119] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the vehicle warning prompt device based on the reading light language, the vehicle warning prompt device based on the reading light language: when the in-vehicle warning signal is obtained, based on the preset warning classification strategy, determine the current warning type of the in-vehicle warning signal, wherein the warning type of the in-vehicle warning signal includes a child left behind prompt, a door risk prompt, a temperature abnormality prompt, an air abnormality prompt, and a cleaning prompt; determine the target lighting mode of the reading light according to the current warning type and the warning lighting mapping relationship strategy; control the reading light to turn on and execute the target lighting mode. The computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, and the programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or it can be connected to an external computer (for example, through the Internet using an Internet service provider).

[0120] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0121] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0122] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle warning prompt method based on reading light language, and can solve the technical problem of how to improve vehicle safety. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the vehicle warning prompt method based on reading light language provided by the above-mentioned embodiment, and will not be repeated here.

[0123] An embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned vehicle warning prompt method based on reading light language.

[0124] The computer program product provided by the present application can solve the technical problem of how to improve vehicle safety. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as the beneficial effects of the vehicle warning prompt method based on reading light language provided by the above embodiment, which will not be repeated here.

[0125] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A vehicle warning prompt method based on reading light language, characterized in that: The method comprises: When an in-vehicle alarm signal is obtained, the current alarm type of the in-vehicle alarm signal is determined based on a preset alarm classification strategy, wherein the alarm types of the in-vehicle alarm signal include a child left behind reminder, a door risk reminder, a temperature abnormality reminder, an air abnormality reminder, and a cleaning reminder; Determining a target lighting mode of a reading light according to the current alarm type and alarm lighting mapping relationship strategy; The reading lamp is controlled to turn on and execute the target lighting mode.

2. The method according to claim 1, characterized in that Before the step of determining the target lighting mode of the reading lamp according to the current alarm type and the alarm lighting mapping relationship strategy, the method further includes: Respectively associating the child left behind reminder with the first lighting mode, the door risk reminder with the second lighting mode, the temperature abnormality reminder with the third lighting mode, the air abnormality reminder with the fourth lighting mode, and the cleaning reminder with the fifth lighting mode; Based on the association result, the warning lighting mapping relationship strategy is generated.

3. The method according to claim 1, characterized in that Before the step of determining the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy when the in-vehicle alarm signal is acquired, the method further includes: Acquire seat pressure data, door radar data, in-vehicle temperature data, in-vehicle air quality data, and camera data as data to be processed; Comparing the data to be processed with preset standard data; Based on the comparison result, it is determined whether to issue the in-vehicle warning signal.

4. The method according to claim 1, characterized in that The step of determining the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy when the in-vehicle alarm signal is acquired includes: When the in-vehicle alarm signal is obtained, classification matching is performed based on the preset alarm classification strategy, the data source of the in-vehicle alarm signal, and the data features of the in-vehicle alarm signal; If the classification matches multiple results, the multiple results are deduplicated and merged based on the preset priority order to obtain the current alarm type.

5. The method according to claim 1, characterized in that After the step of determining the target lighting mode of the reading light according to the current alarm type and the alarm lighting mapping relationship strategy, the method further includes: Acquire target lighting information corresponding to the target lighting mode, the target lighting information including target brightness level, target flickering frequency, target duration, and target special effect; A control instruction is generated based on the target brightness level, the target flickering frequency, the target duration, and the target special effect.

6. The method according to claim 5, characterized in that The step of controlling the reading light to turn on and execute the target lighting mode comprises: Obtaining the control instruction; Determining whether the reading light is in a standby state; If so, the reading light is controlled to turn on, and based on the control instruction, the reading light is adjusted to the target brightness level, the target flashing frequency, the target duration, and the target special effect.

7. A vehicle warning prompt device based on reading light language, characterized in that: The device comprises: An alarm type determination module is used to determine the current alarm type of the in-vehicle alarm signal based on a preset alarm classification strategy when an in-vehicle alarm signal is obtained, wherein the alarm types of the in-vehicle alarm signal include a child left behind reminder, a door risk reminder, a temperature abnormality reminder, an air abnormality reminder, and a cleaning reminder; A lighting mode determination module, used to determine a target lighting mode of a reading light according to the current alarm type and alarm lighting mapping relationship strategy; The target module is used to control the reading light to turn on and execute the target lighting mode.

8. A computer device, characterized in that: The device includes: a memory, a processor, and a vehicle warning prompt program based on reading light language stored in the memory and executable on the processor, wherein the vehicle warning prompt program based on reading light language is configured to implement the steps of the vehicle warning prompt method based on reading light language as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a vehicle warning prompt program based on reading light language, and when the vehicle warning prompt program based on reading light language is executed by the processor, the steps of the vehicle warning prompt method based on reading light language as described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the vehicle warning prompt method based on reading light language as claimed in any one of claims 1 to 6 are implemented.

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