Vehicle atmosphere lamp control method and vehicle

Abstract

The application provides a control method of a vehicle atmosphere lamp and a vehicle; the method is applied to a first vehicle, and the method comprises the following steps: in response to receiving an emotional semantic signal sent by a second vehicle through wireless communication, analyzing the emotional semantic signal to obtain emotional intention information of the second vehicle; determining a first light control parameter based on the emotional intention information; and controlling an atmosphere lamp of the first vehicle based on the first light control parameter. The application analyzes the emotional semantic signal sent by the second vehicle to obtain emotional intention information, and then controls the atmosphere lamp of the first vehicle based on the emotional intention information, so as to realize emotional semantic interaction between vehicles based on light, and make the receiving vehicle able to perceive the emotional expression of the sending vehicle through the dynamic change of the atmosphere lamp, thereby enriching the expression mode of inter-vehicle social interaction.

Description

Technical Field

[0001] This application relates to vehicle technology, and more particularly to a method for controlling vehicle ambient lighting and a vehicle. Background Technology

[0002] The existing vehicle ambient lighting operates independently for each vehicle, and can only adjust the lighting or atmosphere based on the interior environment or occupant instructions. Communication between vehicles relies solely on standard signal lights such as turn signals and hazard lights for simple physical status indications, lacking the ability to interact with emotions through lighting. Summary of the Invention

[0003] This application provides a method for controlling vehicle ambient lighting and a vehicle, which enables emotional and semantic interaction between vehicles based on lighting. This allows the receiving vehicle to perceive the emotional expression of the sending vehicle through the dynamic changes in ambient lighting, thus enriching the ways of expressing inter-vehicle social interaction.

[0004] The technical solution of this application embodiment is implemented as follows: This application provides a method for controlling vehicle ambient lighting, applied to a first vehicle, the method comprising: In response to receiving an emotional semantic signal transmitted by the second vehicle via wireless communication, the emotional semantic signal is parsed to obtain the emotional intention information of the second vehicle; Based on the emotional intent information, the first lighting control parameters are determined; Based on the first lighting control parameters, the ambient lighting of the first vehicle is controlled.

[0005] This application provides a vehicle, the vehicle comprising: Memory is used to store executable instructions or computer programs. The processor, when executing computer-executable instructions or computer programs stored in the memory, implements the vehicle ambient lighting control method provided in the embodiments of this application.

[0006] The embodiments of this application have the following beneficial effects: In response to receiving an emotional semantic signal transmitted wirelessly by a second vehicle, the system first parses the signal to obtain the emotional intent information of the second vehicle. Then, based on this emotional intent information, it determines first lighting control parameters and subsequently controls the ambient lighting of the first vehicle based on these parameters. This overcomes the limitations of related technologies where ambient lighting is restricted to independent single-vehicle operation and lacks inter-vehicle emotional interaction capabilities. It enables vehicle-to-vehicle emotional semantic interaction based on lighting, allowing the receiving vehicle to perceive the sending vehicle's emotional expression through dynamic changes in ambient lighting, thus enriching the ways in which inter-vehicle social interaction is expressed. Attached Figure Description

[0007] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application. Obviously, the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0008] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0009] Figure 1 This is one of the flowcharts illustrating a method for controlling vehicle ambient lighting according to an embodiment of this application; Figure 2 This is a second schematic flowchart of a vehicle ambient lighting control method provided in an embodiment of this application; Figure 3 This is the third flowchart illustrating a method for controlling vehicle ambient lighting provided in this application embodiment; Figure 4 This is the fourth flowchart illustrating a method for controlling vehicle ambient lighting according to an embodiment of this application; Figure 5 This is the fifth flowchart illustrating a method for controlling vehicle ambient lighting according to an embodiment of this application; Figure 6 This is a schematic diagram of the architecture of a vehicle ambient lighting control system provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a vehicle ambient light control device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the specific technical solutions of this application will be further described in detail below with reference to the accompanying drawings of the embodiments of this application. The following embodiments are used to illustrate this application, but are not intended to limit the scope of this application.

[0011] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit the scope of this application.

[0012] In the following description, references to "some embodiments," "this embodiment," "this application embodiment," and examples, etc., describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subset of all possible embodiments and may be combined with each other without conflict.

[0013] The terms "first," "second," and "third" appearing in the embodiments of this application do not have a specific meaning (e.g., there is no order, nor does it indicate a special limitation on the number of devices in the embodiments of this application), but are merely for the purpose of clearly describing the embodiments of this application and do not constitute any limitation on the embodiments of this application. The term "multiple" appearing in the embodiments of this application refers to two or more integers.

[0014] To facilitate understanding of the technical solutions of the embodiments of this application, the relevant technologies or terms of the embodiments of this application are described below. The following related technologies or related terms are optional solutions and can be combined with the technical solutions of the embodiments of this application in any way, and all of them fall within the protection scope of the embodiments of this application.

[0015] Current automotive ambient lighting technology has gradually evolved from basic decorative lighting to intelligent and emotional interactive stages. The mainstream technology directions in the industry include: music rhythm control based on audio feature extraction, emotion response control based on voice or image recognition, multimodal immersive control that integrates ambient light and audio-visual signals, and single-vehicle ambient lighting adjustment solutions that integrate biometric features.

[0016] The inventors of this application discovered during their research and analysis that existing in-vehicle ambient lighting technology has significant technical defects in practical applications, failing to meet the advanced interaction and health management needs of smart cockpits. These defects include at least the following: (1) The inter-vehicle social interaction function is completely missing. The existing ambient lights are all operated independently by a single vehicle, and can only realize in-vehicle lighting and emotional response. They lack the ability to interact with emotional information between vehicles, and cannot complete the visual transmission of abstract emotional intentions through lighting. They only support physical status prompts such as turn signals and hazard lights, and there is no standardized inter-vehicle lighting semantic system.

[0017] (2) Health healing is an open-loop passive response without closed-loop regulation capability. Existing lighting adjustment schemes based on physiological signals can only achieve one-time open-loop control of "abnormal physiological signal detection → fixed lighting action execution". There is no real-time physiological feedback, dynamic parameter adjustment and steady-state maintenance mechanism. The phototherapy system is not constructed in conjunction with medical evidence-based basis, and it is impossible to achieve a complete health intervention closed loop of "perception-analysis-healing-feedback".

[0018] (3) The multi-occupant collaborative control mechanism is missing, and there is no vehicle-specific arbitration logic. Existing multi-user lighting control schemes simply adopt the driver priority rule or are based on static emotional state weighting, without integrating multi-dimensional factors such as driving safety, occupant health status, passenger role, and fairness of use. They cannot resolve multi-occupant lighting preference conflicts and are not adapted to the rigid safety constraints of vehicle scenarios.

[0019] (4) Environmental adaptation is a passive and delayed adjustment, without predictive adaptation capability. Existing ambient lights can only switch scenes based on the vehicle's current location and instantaneous ambient light. They do not combine navigation trip planning, destination information, and future weather changes to achieve predictive pre-adjustment. They cannot achieve intelligent adaptation of light changes before arrival, and scene switching is abrupt and the experience is poor.

[0020] In order to solve at least one of the above-mentioned problems in the related technologies, this application provides a method for controlling vehicle ambient lighting. This method breaks through the limitation of ambient lighting in the related technologies, which is limited to the independent operation of a single vehicle and lacks the ability of inter-vehicle emotional interaction. It realizes emotional semantic interaction between vehicles based on lighting, so that the receiving vehicle can perceive the emotional expression of the sending vehicle through the dynamic changes of ambient lighting, thus enriching the expression of inter-vehicle social interaction.

[0021] The control method for vehicle ambient lighting provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0022] Figure 1 This is one of the flowcharts illustrating a method for controlling vehicle ambient lighting according to an embodiment of this application. The method is applied to a first vehicle. Figure 1 As shown, the method may include the following steps 101 to 103: Step 101: In response to receiving the emotional semantic signal sent by the second vehicle via wireless communication, the emotional semantic signal is parsed to obtain the emotional intention information of the second vehicle.

[0023] In this embodiment, the first vehicle acts as the executing entity, and its onboard control system can receive wireless signals transmitted from the second vehicle via an integrated wireless communication module. This wireless communication can be implemented using technologies such as cellular networks (e.g., 5G), Dedicated Short-Range Communication (DSRC), or Cellular Vehicle-to-Everything (C-V2X) to ensure low-latency, highly reliable data transmission. The emotional semantic signal refers to a digital data packet generated and broadcast by the second vehicle's onboard system to express abstract emotional intentions. This data packet contains standardized encoded emotional tags (e.g., friendliness, joy, tension) and is transmitted after encapsulation using lightweight protocol frames.

[0024] In some embodiments, the specific structure of the emotional semantic signal can be a 7-byte standardized V2X protocol frame, where the frame header is fixed at 0xAA to identify the start of the data packet; the message type field occupies 1 byte, defining the category of emotional intent, such as 0x01 for greeting, 0x02 for gratitude, and 0x03 for warning; the vehicle anonymous ID occupies 4 bytes, which is a temporary anonymous identifier for the sender's vehicle identifier after hashing, ensuring privacy and security; and the emotion tag occupies 1 byte, used to refine the emotional state, such as 0x10 for friendliness, 0x20 for joy, and 0x30 for tension. This emotional semantic signal protocol frame design is lightweight and efficient, suitable for real-time interaction in a vehicle-to-everything (V2X) environment.

[0025] In some embodiments, when the wireless communication module of the first vehicle receives the emotional semantic signal, it first performs frame verification (such as Cyclic Redundancy Check (CRC)) to ensure data integrity. Then, it parses the content of each field, extracts the message type and emotional tag, and combines them to form a composite semantic key. For example, if the received message type is 0x02 (gratitude) and the emotional tag is 0x20 (joy), the parsing result includes a message type of gratitude and an emotional intent of joy. The parsing process of this emotional semantic signal can be completed through embedded software logic or a dedicated decoding chip, supporting millisecond-level response.

[0026] In some embodiments, the first vehicle continuously listens to the emotional semantic signals broadcast by the surrounding second vehicle through a wireless communication module. Once a valid data packet is detected, a parsing process is initiated to obtain the emotional intent information of the second vehicle.

[0027] Step 102: Determine the first lighting control parameters based on the emotional intent information.

[0028] It should be noted that the first lighting control parameters refer to a set of instruction parameters used to control the specific performance of the ambient lighting in the first vehicle, including but not limited to light color (RGB value), light intensity (brightness), dynamic effects (such as breathing, flowing water, pulse), frequency (rate of change), and duration. The above lighting control parameters collectively determine the final visual effect of the ambient lighting, thereby achieving a visual mapping of emotional intent information.

[0029] In some embodiments, the first vehicle has a predefined emotional-lighting narrative template library that maps different emotional intentions to specific lighting effects. For example, for the emotional intention of friendliness, the first vehicle's control system matches a light blue breathing light effect with a wavelength range of 460-480nm, a light intensity of 50cd, a frequency of 0.5Hz, and a duration of 4 seconds; for the emotional intention of joy, the first vehicle's control system matches a warm gold flowing light effect that flows from the front to the rear of the vehicle with a light intensity of 80cd and a duration of 3 seconds; for the emotional intention of tension, the first vehicle's control system matches a red pulse light effect with a frequency of 2Hz, a light intensity of 120cd, and a duration of 5 seconds.

[0030] It should be noted that the emotional-lighting narrative template library can be customized and expanded according to user preferences or scene requirements. For example, you can add a rainbow gradient light effect for excitement, or a soft purple flashing light effect for apology.

[0031] In some embodiments, based on the emotional intent information parsed in step 101, the corresponding lighting effect can be searched in the emotional-lighting narrative template library, and a specific first lighting control parameter can be generated.

[0032] It is understood that the embodiments of this application realize the precise conversion from abstract emotional intention information to concrete lighting expression, enabling vehicles to respond to external social signals in a unified, standardized and expressive manner, build a vehicle-to-vehicle lighting social network, and improve the emotional level and social experience of human-vehicle interaction.

[0033] Step 103: Control the ambient lighting of the first vehicle based on the first lighting control parameters.

[0034] It should be noted that the ambient lighting of the first vehicle can be composed of distributed LED light strips, covering areas such as the dashboard, door panels, floor, and ceiling, and supports independent control of multiple areas and linkage with the whole vehicle.

[0035] In some embodiments, the ambient lighting system of the first vehicle can send the first lighting control parameters to each LED driver module via the Controller Area Network (CAN) bus or the Local Interconnect Network (LIN) bus, and each LED driver module adjusts its own luminous characteristics according to the received first lighting control parameters.

[0036] In some embodiments, light intensity can be adjusted using pulse width modulation (PWM), color changes can be achieved through RGB three-channel current adjustment, and the rhythm and timing of dynamic effects can be controlled by a timer. For example, for the first lighting control parameter corresponding to the emotional intention of joy, LED beads from the front to the rear of the car can be lit sequentially, with each LED bead lighting up at a time interval of 0.1 seconds to create a sense of flow; for the first lighting control parameter corresponding to the emotional intention of tension, the LED beads can be controlled to flash rapidly using a high-frequency switch, with the frequency set to 2Hz and lasting for 5 seconds.

[0037] In some embodiments, certain constraints can be set to ensure the safety and comfort of lighting control. For example, during driving, if the dynamic lighting effect corresponding to the first lighting control parameter is too intense (e.g., frequency higher than 3Hz), it will automatically downgrade to static light or low-frequency breathing light; if the current interior lighting is too dim, the lighting control system will appropriately increase the light intensity to ensure visibility; when an occupant is using sleep mode, the lighting control system will ignore emotional semantic signals from the outside to maintain a quiet lighting environment.

[0038] In this embodiment of the application, the first vehicle can precisely drive the ambient lights to perform the specified lighting effects based on the first lighting control parameters determined in step 102, so as to achieve immediate, intuitive and beautiful visual feedback on external emotional intention information.

[0039] In this embodiment, in response to receiving an emotional semantic signal transmitted wirelessly by a second vehicle, the signal is first parsed to obtain the emotional intent information of the second vehicle. Then, based on this emotional intent information, a first lighting control parameter is determined, and subsequently, the ambient lighting of the first vehicle is controlled based on this first lighting control parameter. This overcomes the limitations of related technologies where ambient lighting is limited to independent operation of a single vehicle and lacks inter-vehicle emotional interaction capabilities. It enables vehicle-to-vehicle emotional semantic interaction based on lighting, allowing the receiving vehicle to perceive the emotional expression of the sending vehicle through the dynamic changes in the ambient lighting, thus enriching the expression methods of inter-vehicle social interaction.

[0040] In some embodiments, such as Figure 2As shown, step 102 may further include: Step 1021: Obtain the message type carried in the emotional semantic signal; the message type represents the type of social interaction between the second vehicle and the first vehicle.

[0041] It should be noted that message type refers to the type of social interaction between the second vehicle and the first vehicle during vehicle-to-vehicle emotional semantic interaction, that is, the specific category of the social intention conveyed by the second vehicle to the first vehicle. Message type can be encoded and transmitted through standardized V2X communication protocol frames. For example, message types include greeting, thanks, and warning, corresponding to message type field values ​​0x01, 0x02, and 0x03 in the protocol frame, respectively. For instance, when the driver of the second vehicle triggers a thank-you intention via voice or shortcut key, the system maps the intention to message type 0x02 and encapsulates it in a V2X communication protocol frame for broadcast. As a core classification dimension of emotional semantics, message type determines the direction of subsequent selection of the first lighting control parameters. For example, thanks can be mapped to a warm gold light appearance determined by the first lighting control parameters, while warnings can be mapped to a red light appearance determined by the first lighting control parameters.

[0042] In this application, the first vehicle can extract the message type field by parsing the received V2X communication protocol frame, thereby identifying the social intent type of the second vehicle, that is, the type of social interaction between the second vehicle and the first vehicle.

[0043] It should be noted that the message type and emotional intent information together constitute a composite semantic key-value pair, used to query the predefined mapping rules of the first lighting control parameters. For example, in congested urban areas, when a vehicle triggers a thank-you message type by yielding, the warm golden light display corresponding to this thank-you message type, determined by the first lighting control parameters, not only expresses gratitude but also visually alleviates the tension caused by traffic pressure.

[0044] Step 1022: Determine the first lighting control parameters based on the message type and the emotional intent information.

[0045] In this embodiment, there is a logical combination relationship between emotional intent information and message type. The message type and emotional intent information together determine the final first lighting control parameters, such as wavelength, light intensity, pulse frequency, etc.

[0046] In some embodiments, a first lighting control parameter mapping rule can be established based on the message type, and then the parameters in the mapping rule can be fine-tuned by combining emotional intent information. For example, if the message type is a greeting and the emotional intent is friendliness, a light blue breathing light (0.5Hz) determined by the first lighting control parameter can be used. If the message type is a greeting but the emotional intent is tension, it can be adjusted to a low-frequency flashing light with a slight purple tint, determined by the first lighting control parameter, to reflect different emotional tones. This two-dimensional matching mechanism improves the subtlety and emotional authenticity of the expression of the first lighting control parameter, avoiding the monotony of expression caused by a single dimension.

[0047] In some embodiments, the first vehicle has a predefined emotional-light narrative template library that maps different message types and emotional intent information to specific lighting effects. For example, for the combination of greeting and friendliness, the first vehicle's control system matches a light blue breathing light effect with a wavelength range of 460-480nm, a light intensity of 50cd, a frequency of 0.5Hz, and a duration of 4 seconds; for the combination of gratitude and joy, the first vehicle's control system matches a warm gold flowing light effect that flows from the front to the rear of the vehicle with a light intensity of 80cd and a duration of 3 seconds; for the combination of warning and tension, the first vehicle's control system matches a red pulse light effect with a frequency of 2Hz, a light intensity of 120cd, and a duration of 5 seconds.

[0048] It should be noted that the emotional-lighting narrative template library can be customized and expanded according to user preferences or scene requirements. For example, a rainbow gradient light effect can be added to the combination of celebration and excitement, or a soft purple flashing light effect can be added to the combination of apology and remorse.

[0049] It is understood that the embodiments of this application extract message type and emotional intent information from emotional semantic signals, and map abstract emotions into specific lighting effect parameters, such as specific colors, frequencies, durations, etc., thereby achieving accurate conversion of emotional semantics into lighting expression. This avoids the problem in related technologies that can only transmit physical states or lack standardized mapping, and enhances the emotional richness and comprehensibility of lighting expression.

[0050] In some embodiments, the second vehicle includes multiple vehicles; such as Figure 3 As shown, step 101 may further include: Step 1011: In response to receiving emotional semantic signals transmitted by multiple second vehicles via wireless communication, determine the target signal from the multiple emotional semantic signals according to a preset arbitration rule.

[0051] The pre-defined arbitration rules include at least one of the following: The first arbitration rule for the target signal is determined according to the priority of the message type carried by the emotional semantic signal; The second arbitration rule for determining the target signal is based on the distance between the second vehicle and the first vehicle; The third arbitration rule for determining the target signal is based on the chronological order in which the emotional semantic signals are received.

[0052] It should be noted that the preset arbitration rules refer to a set of logical rules used to determine which signal to process first when the first vehicle simultaneously receives emotional semantic signals from multiple second vehicles. The preset arbitration rules include at least one of the following: a first arbitration rule that determines the target signal based on message type priority (e.g., warning > thanks > greeting); a second arbitration rule that determines the target signal based on the distance between the second and first vehicles (closer distance, higher priority); and a third arbitration rule that determines the target signal based on the order of reception (first received, first processed). These rules work together to ensure that in multi-vehicle concurrent emotional interaction scenarios, the first vehicle can select the most urgent, relevant, or first-arriving signal as the processing target, avoiding conflicts or confusion in lighting effects and improving the rationality of the interaction and the user experience.

[0053] It should be noted that the target signal refers to the signal ultimately selected from multiple emotional semantic signals according to a preset arbitration rule and used for subsequent analysis. The target signal represents the emotional intent that should be prioritized in the current context. For example, when multiple vehicles simultaneously send thank-you and warning signals, the vehicle will prioritize the warning signal as the target signal. The selection process of the target signal enables intelligent filtering in complex inter-vehicle social environments, ensuring the timeliness and accuracy of the light response.

[0054] For example, a first vehicle is driving in a congested traffic area and simultaneously receives emotional semantic signals from three surrounding second vehicles: one sends gratitude (message type) + joy (emotional intent) due to yielding, one sends a warning (message type) + tension (emotional intent) due to emergency braking, and the other sends a greeting (message type) + friendliness (emotional intent) as a gesture of goodwill. The first vehicle first prioritizes the warning signal based on message type. If multiple warning signals exist, the distance between the second and first vehicles is compared, and the closest second vehicle is selected. If the distances are the same, the signals are sorted by reception time. The final selected signal triggers a corresponding lighting effect, such as a red pulse light, to alert the driver to potential risks.

[0055] It is understood that this application embodiment introduces preset arbitration rules to prioritize and select target signals from the emotional semantic signals sent by multiple target vehicles. This effectively solves the signal conflict problem during concurrent emotional interaction between multiple vehicles, thereby ensuring the accuracy and timeliness of light responses, and ultimately improving the intelligence level and driving safety of inter-vehicle emotional semantic interaction.

[0056] Step 1012: Analyze the target signal to obtain the emotional intent information of the second vehicle that sent the target signal.

[0057] In this embodiment, the first vehicle can parse the target signal determined in step 1011 to obtain the emotional intent information of the second vehicle that sent the target signal. For example, when the first vehicle parses the emotional intent information of the second vehicle that sent the target signal as tense, it can query the emotion-lighting narrative template library to obtain the corresponding lighting parameters: red, frequency 2Hz, duration 5 seconds, and activate the entire vehicle's LED light strip to execute the lighting effect. Simultaneously, the first vehicle can record this emotional intent information in a log or upload it to the cloud for subsequent data analysis or user feedback optimization. Furthermore, different vehicle models or user preferences can be configured through mapping rules in the emotion-lighting narrative template library to achieve personalized lighting narrative styles.

[0058] It is understandable that when multiple emotional semantic signals from second vehicles are received simultaneously, this application embodiment arbitrates the multiple emotional semantic signals by setting priority rules, selects a target signal for parsing and executes the corresponding lighting control, improves the defects of multi-vehicle interaction signal conflict, ensures the rationality and safety of lighting response, and avoids lighting chaos or misoperation caused by multiple signals being triggered simultaneously.

[0059] In some embodiments, such as Figure 4 As shown, the vehicle ambient lighting control method provided in this application embodiment further includes: Step 104: Obtain the physiological signals of each occupant in the first vehicle.

[0060] It should be noted that physiological signals refer to quantifiable bioelectrical or physical signals that reflect the physiological state of the human body, mainly including indicators such as heart rate (HR), heart rate variability (HRV), and skin conductance level (SCL).

[0061] In some embodiments, biosensor modules integrated into the seat headrests, steering wheel, and armrests can collect physiological signals of each occupant in real time. These signals are then filtered and pre-processed for noise reduction before being used for emotion recognition. For example, high heart rate variability typically indicates a relaxed state, while elevated skin conductance may indicate stress or tension. In practical applications, the emotion recognition system can automatically activate sensors after vehicle startup or occupant boarding, continuously monitoring the physiological data of each occupant and converting the raw physiological signals into feature parameters that can be used for subsequent analysis. Different sensor types, such as photoplethysmography (PPG) sensors and electrode-type skin conductance sensors, can be flexibly deployed according to the vehicle's spatial layout and cost requirements.

[0062] Step 105: Based on the physiological signals of each passenger, generate a three-dimensional emotion vector including stress index dimension, fatigue index dimension and relaxation index dimension.

[0063] It should be noted that the three-dimensional emotion vector can be a normalized triple. The three dimensions are used to characterize the current emotional state of the passengers. They correspond to the stress index, fatigue index, and relaxation index, respectively, and all have values ​​ranging from [0,1] and satisfying the following conditions: .

[0064] In some embodiments, a three-dimensional emotion vector can be generated based on the analysis results of feature parameters in physiological signals by a pre-trained deep learning model. For example, when an occupant has a high heart rate and low HRV, the system can determine that the occupant is in a state of high stress, thereby improving [their emotional state]. Value; if skin conductance is stable but heart rate is slow, it can be judged as a state of fatigue, and the level should be increased. value.

[0065] Step 106: Determine the second lighting control parameters based on the three-dimensional emotion vectors corresponding to each occupant.

[0066] It should be noted that the second lighting control parameter refers to a set of instruction parameters used to drive the ambient light to perform a specific lighting effect, including but not limited to wavelength ( ), light intensity ( ), optical pulse frequency ( )wait.

[0067] In some embodiments, a single proportional-integral-derivative (PID) multi-channel mapping control algorithm can be used to dynamically generate second lighting control parameters based on a three-dimensional emotion vector.

[0068] Step 107: Control the ambient lighting of the first vehicle based on the second lighting control parameters.

[0069] In some embodiments, the ambient lighting system of the first vehicle can send the second lighting control parameters to each LED driver module via a CAN bus or LIN bus, and each LED driver module adjusts its own luminous characteristics according to the received second lighting control parameters.

[0070] It is understood that this application embodiment acquires the physiological signals of each occupant in the vehicle, generates a three-dimensional emotion vector, and dynamically determines the second lighting control parameters based on the three-dimensional emotion vector, thereby controlling the ambient lighting. In this way, it is possible to achieve accurate perception and scientific intervention of the occupants' emotional state, thereby constructing a complete health phototherapy closed loop of perception-analysis-healing-feedback, and thus improving the emotional interaction experience and health management capabilities of the intelligent cockpit.

[0071] In some embodiments, step 106 may further include: Based on the three-dimensional emotion vectors corresponding to each occupant, the third lighting control parameters corresponding to each occupant are determined. Using the relaxation index of each occupant as the control target, a closed-loop control algorithm is used to adjust the third lighting control parameters corresponding to each occupant to obtain the fourth lighting control parameters corresponding to each occupant. The second lighting control parameter is determined based on the fourth lighting control parameter corresponding to each occupant.

[0072] It should be noted that the third lighting control parameters refer to the set of basic light parameters initially generated based on the occupant's current emotional state (represented by a three-dimensional emotion vector) and used to adjust the ambient lighting. These parameters may include wavelength, light intensity, and light pulse frequency, serving as the initial input values ​​for subsequent closed-loop control. For example, when an occupant is under high stress, the system can set the third lighting control parameters to blue light wavelength, medium light intensity, and a low-frequency breathing effect; when the occupant is fatigued, it can be set to warm yellow light, higher light intensity, and a medium-frequency pulse effect. The determination of the third lighting control parameters is based on initial light prescription rules from a medical evidence-based database, ensuring the scientific validity and effectiveness of the initial lighting settings.

[0073] In some embodiments, a three-dimensional emotion vector can be extracted using a deep learning model. Based on the preset mapping rules, the third lighting control parameters for each occupant are directly output.

[0074] It should be noted that the relaxation index is a component of the three-dimensional emotion vector, with a value range of [0,1], representing the current psychological relaxation level of the occupant; a higher value indicates greater relaxation. As the controlled variable in the closed-loop control system, the goal is to stabilize the relaxation index within an ideal range (e.g., [0.4, 0.6]) to achieve the purpose of health and healing. In this embodiment, the closed-loop control algorithm can be a single-PID multi-channel mapping control algorithm, that is, using a single error signal e(t) = target relaxation index - current relaxation index to drive three independent control channels. The wavelength channel uses only the proportional coefficient. The adjustment involves using a complete proportional-integral-derivative control structure for the light intensity channel, while the pulse channel uses only the derivative coefficients. Triggering. In this way, the phototherapy control system can sense changes in relaxation level in real time and dynamically adjust light parameters, forming a complete closed loop of perception-regulation-feedback. For example, when the system detects that the occupant's relaxation level is lower than the target value, it increases the blue light component and light intensity, and may trigger a short-term high-purity light pulse for rapid intervention. The final output fourth light control parameter is a precise light parameter value after closed-loop adjustment. Compared with the third light control parameter, the fourth light control parameter is closer to the occupant's current physiological needs, achieving precise, dynamic, and continuous phototherapy intervention. In actual vehicle operation, the single PID multi-channel mapping control algorithm performs multiple iterations per second to ensure timely and smooth light response, effectively relieving occupant stress or fatigue and improving ride comfort and safety.

[0075] It should be noted that the second lighting control parameter in this embodiment is the result obtained after comprehensively considering the fourth lighting control parameter after closed-loop adjustment for all occupants in a multi-occupant scenario. For example, the second lighting control parameter is obtained by fusing the fourth lighting control parameters corresponding to each occupant.

[0076] It should be noted that there is no strict timing restriction between steps 101 to 103 and steps 104 to 107, and they can be executed in parallel.

[0077] It is understood that the embodiments of this application determine the third lighting control parameter based on the three-dimensional emotion vector corresponding to each occupant, then use a closed-loop control algorithm with the relaxation index as the control target to dynamically adjust and obtain the fourth lighting control parameter, and finally integrate the fourth lighting control parameters of all occupants to determine the second lighting control parameter. In this way, it is possible to achieve accurate identification of the emotional state of each occupant and personalized light therapy intervention, thereby constructing a complete health intervention closed loop of perception-analysis-healing-feedback, which can improve the intelligence level of the in-vehicle ambient lighting system and the user's physical and mental health management capabilities.

[0078] In some embodiments, determining the second lighting control parameter based on the fourth lighting control parameter corresponding to each occupant includes: Based on the target factor, determine the fusion weight corresponding to each crew member; Based on the fusion weights corresponding to each occupant, the fourth lighting control parameters corresponding to each occupant are weighted and fused to obtain the second lighting control parameters. The target factor includes at least one of the following: The first factor characterizing the degree of influence of each occupant on the driving behavior of the first vehicle; The second factor characterizing the stress index of each occupant; A third factor characterizing the seating position of each occupant within the first vehicle; The fourth factor characterizes the cumulative duration during which each occupant's lighting preferences were not responded to.

[0079] It should be noted that the target factors refer to a set of quantitative indicators used to assess the influence of each occupant on lighting control decisions in the current vehicle environment. The role of the target factors is to allocate different voices to different occupants, thereby achieving fair, safe, and health-oriented coordinated lighting control. The target factors include at least one of the following: a first factor characterizing the degree of influence of each occupant on the driving behavior of the first vehicle; a second factor characterizing the stress index of each occupant; a third factor characterizing the seating position of each occupant in the first vehicle; and a fourth factor characterizing the cumulative duration during which each occupant's lighting preferences were not responded to.

[0080] The first factor characterizes the degree of influence of each occupant on the driving behavior of the first vehicle. It primarily targets the driver and occupants who may interfere with driving. For example, when the driver is in control, their influence is highest, and they are given the greatest weight. When a front passenger or rear passenger engages in disruptive behaviors such as frequently operating the central control screen or speaking loudly, the system can temporarily increase the first factor value for that passenger to ensure driving safety. The primary function of the first factor is to ensure driving safety and prevent driver distraction caused by conflicting lighting preferences.

[0081] The second factor represents the stress index of each passenger. It is derived from physiological signals such as heart rate and skin conductance collected by biosensors, and processed by a deep learning model to obtain a normalized stress value. Passengers with high stress indices require a more soothing lighting environment and therefore should be given a higher weight. For example, when a passenger's stress index exceeds 0.7, the system automatically increases the weight of that passenger's second factor, prioritizing their relaxation needs. The role of the second factor is to achieve health-oriented lighting adjustments, promoting relaxation for all passengers.

[0082] The third factor represents the seating position of each occupant within the vehicle. This third factor is a static role weight that can be preset to a fixed value. For example, the driver is assigned a weight of 1.0, the front passenger 0.8, and rear passengers 0.5. The purpose of the third factor is to reflect the differences in the importance of roles within the vehicle, ensuring that key occupants such as the driver have basic control priority in lighting control.

[0083] The fourth factor represents the cumulative duration for which each passenger's lighting preferences are not responded to, and it is used to ensure fairness in usage. When a passenger's lighting preferences are not adopted for an extended period, that passenger's fourth factor value increases over time, and the system gradually increases that passenger's weight, preventing the long-term neglect of specific passengers' needs. For example, if a rear-seat passenger does not receive a lighting preference response for 30 consecutive minutes, that passenger's fourth factor value increases to above 0.3, significantly increasing that passenger's influence. The role of the fourth factor is to balance fairness among multiple passengers and prevent a minority from dominating lighting settings for extended periods.

[0084] The fusion weight refers to a normalized value calculated based on the aforementioned target factors, reflecting the real-time voice of each occupant, and is used for subsequent weighted fusion calculations. The dynamic change of the fusion weight ensures that lighting control decisions can respond in real-time to changes in occupant status, achieving intelligent arbitration.

[0085] In this embodiment, after calculating the fusion weight corresponding to each occupant based on the target factor, the fourth lighting control parameters corresponding to each occupant can be weighted and fused based on these fusion weights to obtain the second lighting control parameters. The obtained second lighting control parameters take into account driving safety, occupant health, role status, and fairness of use.

[0086] It is understood that the embodiments of this application introduce a target factor and dynamically calculate the fusion weight of each occupant based on the target factor, and then perform weighted fusion on the fourth lighting control parameters corresponding to each occupant, thereby obtaining a second lighting control parameter that comprehensively considers safety, health, role, and fairness. In this way, intelligent coordination of lighting preferences among multiple occupants can be achieved, avoiding a decline in experience due to preference conflicts, thereby improving the intelligence level and user experience of the in-vehicle ambient lighting system.

[0087] In some embodiments, the target factor includes at least two of the first factor, the second factor, the third factor, and the fourth factor; The determination of the fusion weights for each passenger based on the target factor includes: The various factors in the target factor are weighted to obtain the fusion weights corresponding to each crew member.

[0088] In this embodiment, the factors in the target factor can be weighted, that is, each factor can be linearly combined according to a preset weight coefficient to obtain the fusion weight corresponding to each passenger. This fusion weight ensures that the lighting effect meets the preferences of the majority of passengers while not completely ignoring the needs of the minority of passengers.

[0089] It is understood that the embodiments of this application introduce target factors including at least two of the first, second, third, and fourth factors, and perform weighted calculations on each factor to obtain the fusion weight corresponding to each occupant. This allows for comprehensive consideration of multiple dimensions such as driving safety, occupant health status, role positioning, and fairness of use, thereby achieving more intelligent, user-friendly, and safe multi-occupant lighting coordination control. This effectively solves the problem of conflicting lighting preferences among multiple users in existing related technologies, improving the overall interactive experience and ride comfort of the smart cockpit.

[0090] In some embodiments, the method further includes: Monitor the rate of change in relaxation level of each crew member; If the rate of change in the relaxation level of any occupant is less than a first preset threshold, the weighting coefficients corresponding to each factor in the target factor are adjusted.

[0091] It should be noted that the relaxation degree change rate refers to the rate of change of the occupant's relaxation degree index per unit time, used to quantify the dynamic response trend of the occupant's physiological state during phototherapy intervention. The relaxation degree change rate is calculated by real-time acquisition of physiological signals such as occupant heart rate variability (HRV) and skin conductance level (SCL), and then extracting a three-dimensional emotion vector using a deep learning model. The formula is as follows: ,in The sampling period is (e.g., 1 minute). The rate of change in relaxation level is an important indicator for evaluating the effectiveness of the current phototherapy regimen. A positive rate of change indicates that relaxation level is improving, while a negative rate of change indicates that the intervention is not effective or has a reverse effect.

[0092] In some embodiments, physiological data of each occupant can be continuously collected, with relaxation level values ​​updated every minute, and the difference between adjacent time points calculated to obtain the relaxation level change rate. For example, if an occupant's relaxation level is 0.45 at the 10th minute and 0.42 at the 11th minute, then that occupant's relaxation level change rate is -0.03 / minute. The system can aggregate the relaxation level change rates of all occupants to the central decision-making unit as input conditions for weight adjustment.

[0093] It should be noted that the first preset threshold is a critical standard for determining the effectiveness of phototherapy intervention, used to trigger the weight adjustment mechanism. Based on medical evidence-based research and experimental verification, the first preset threshold can be set to 0.05 / minute. That is, when the rate of change in relaxation is lower than the first preset threshold, it is considered that the current phototherapy plan has failed to effectively promote relaxation, and a dynamic weight adjustment strategy needs to be activated. The first preset threshold can be adaptively configured according to different user groups (such as drivers and passengers) or specific scenarios (such as long-distance driving and night driving), and this application embodiment does not specifically limit it in this way.

[0094] In some embodiments, when the rate of change in a certain occupant's relaxation level is detected to be less than a first preset threshold, the weighting coefficient of the second factor representing the occupant's stress index can be temporarily increased by 20% (e.g., from the default 0.3 to 0.36), while the weighting coefficients of the other factors are proportionally reduced to maintain the normalization of the total weight, thereby prioritizing the satisfaction of the occupant's health needs.

[0095] It should be noted that the monitoring of the relaxation rate of each occupant and the control of the second lighting control parameters can be performed in parallel. That is, while controlling the vehicle ambient lights based on the second lighting control parameters, the relaxation rate of each occupant can be continuously monitored to dynamically adjust the weighting coefficient.

[0096] It is understood that, by monitoring the rate of change of occupant relaxation in real time, this application embodiment dynamically adjusts the weighting coefficients of various factors when it is found that the relaxation of a certain occupant is improving slowly (i.e., the rate of change of the occupant's relaxation is less than a first preset threshold), thereby achieving personalized, closed-loop health phototherapy regulation and significantly improving the health management capabilities of the smart cockpit.

[0097] In some embodiments, such as Figure 5 As shown, the method further includes: Step 108: Obtain the destination information of the first vehicle; the destination information includes at least one of the following: destination type information and destination weather information.

[0098] It's important to note that destination information refers to comprehensive attribute data about the vehicle's upcoming destination provided by the vehicle's navigation system or external data sources. This destination information supports the intelligent cockpit system in anticipating environmental characteristics and making predictive lighting adjustments. Destination type information refers to the functional category of the target location, such as residential areas, office areas, medical centers, and commercial complexes. Different types of locations correspond to different atmosphere requirements; for example, residential areas require relaxing and warm lighting, while office areas may need bright and focused lighting. Destination weather information refers to the weather conditions at the target location over a future period, including sunny, cloudy, rainy, snowy, and foggy conditions. These weather conditions directly affect the passengers' mood and visual comfort, thus requiring compensation or adaptation through lighting. For example, in rainy or foggy weather, the system can automatically adjust the light color temperature to a warmer tone, improving the perceived brightness inside the vehicle and alleviating feelings of oppression; in sunny weather, cool white light can be used to enhance alertness.

[0099] In some embodiments, destination information is obtained by the in-vehicle navigation module in conjunction with real-time map services and linked with a third-party weather API interface for dynamic updates. The headlight adjustment system continuously monitors changes in destination information to ensure that the headlight adjustment strategy remains consistent with the latest destination information. For example, when the navigation system detects that the navigation route will enter a commercial area and the weather forecast indicates light rain, the headlight adjustment system can activate the business rainy day headlight mode in advance, using soft warm white light with a low-frequency pulse effect to create a professional yet comfortable riding experience.

[0100] It is understood that this application embodiment achieves forward perception of the vehicle's future environment by obtaining destination type information and destination weather information. In this way, lighting adjustment strategies can be planned in advance, thereby avoiding the problem of abrupt switching of lighting adjustment strategies due to sudden changes in the vehicle's future environment, and thus improving the passenger's riding comfort and emotional experience.

[0101] Step 109: Determine the fifth lighting control parameter based on the destination information.

[0102] In this embodiment, the fifth lighting control parameter refers to a set of instruction parameters customized based on destination information, including but not limited to configuration parameters across multiple dimensions such as wavelength, light intensity, light pulse frequency, and dynamic effect mode. The fifth lighting control parameter is not a fixed value but is dynamically generated based on the type of destination and its weather information. For example, for a residential area on a sunny day, the system can generate a "Homecoming Mode" using 4000K warm white light, low intensity, and a slow breathing effect; for a medical center on a cloudy day, a "Healing Mode" is generated using 590nm warm yellow light, medium intensity, and stable constant brightness, synchronized with soothing music.

[0103] Step 110: Monitor the remaining time for the first vehicle to reach its destination, and in response to the remaining time being equal to or less than a second preset threshold, switch the first lighting control parameter to the fifth lighting control parameter, so as to control the ambient lighting of the first vehicle based on the fifth lighting control parameter.

[0104] It should be noted that the remaining time refers to the time required for the vehicle to reach its destination from the current moment. This remaining time can be dynamically calculated based on factors such as real-time vehicle speed, navigation route length, and traffic conditions. The second preset threshold is the critical point at which the headlights switch is triggered. It can be set to 10-30 seconds, depending on the duration required for a smooth headlight transition in actual applications. This embodiment does not impose a specific limitation on this setting. When the remaining time is less than or equal to the second preset threshold, the system determines that the vehicle is about to enter a new scene and initiates a smooth transition mechanism, gradually bringing the current headlight parameters closer to the fifth headlight control parameter to avoid abrupt switching that could affect the driving experience.

[0105] In some embodiments, the system updates the remaining duration every second and compares it with a second preset threshold. When the switching conditions are met, a gradual light adjustment is performed. For example, in the last 10 seconds, the light color temperature linearly transitions from 6500K to 4000K, the brightness decreases from 80% to 60%, and a slight breathing effect is introduced to achieve a seamless transition.

[0106] It is understood that in this embodiment, the fifth lighting control parameter is determined based on destination information, and switching is performed when the remaining duration is equal to or less than the second preset threshold, thus achieving predictive adaptive control of the lighting system. This method allows for advance adaptation to lighting scenarios, avoiding discomfort caused by sudden changes in lighting after the vehicle arrives at its destination, thereby achieving a smart cockpit experience where the lighting changes before arrival.

[0107] In some embodiments, when multiple lighting control parameters are obtained simultaneously, such as when at least two of the first lighting control parameters, the second lighting control parameters, and the fifth lighting control parameters in the above embodiments are obtained simultaneously, one of the following strategies can be used to make a unified decision to obtain the final lighting control parameters, and finally, based on the final lighting control parameters, the ambient lights of the first vehicle are controlled.

[0108] Strategy 1: Priority Strategy. The execution order of various lighting control parameters is determined according to preset priority rules, executing them sequentially from highest to lowest priority. These preset priority rules include, but are not limited to: the first lighting control parameter has the highest priority and is executed first; the second lighting control parameter has the second highest priority and is executed after the lighting effect corresponding to the first lighting control parameter has been displayed; the fifth lighting control parameter is a conditionally triggered parameter, and when the remaining duration is equal to or less than a second preset threshold, the currently executing first or second lighting control parameter is immediately paused, and the fifth lighting control parameter is executed; after the lighting scene corresponding to the fifth lighting control parameter has been adapted, the paused lighting control parameter is resumed.

[0109] Strategy Two: Weighted Fusion Strategy. Based on the source of each lighting control parameter, determine the fusion weight of each parameter. Then, weight the parameters to obtain the fused lighting control parameters. These fused parameters are used as the final lighting control parameters. For example, the first lighting control parameter originates from the emotional semantic signal sent by the second vehicle. When the emotional semantic signal is "warning," the fusion weight of the first lighting control parameter is 0.7; when the emotional semantic signal is "thank you" or "greeting," the fusion weight is 0.3. The second lighting control parameter originates from the physiological signals of the occupants inside the first vehicle. Its fusion weight is determined by the deviation of the occupant relaxation index from the target range; the greater the deviation, the higher the fusion weight of the second lighting control parameter, with a value range between 0.2 and 0.6. The fifth lighting control parameter is derived from the destination information, and its fusion weight is determined by the remaining time to reach the destination. The shorter the remaining time, the higher the fusion weight of the fifth lighting control parameter. The value range is between 0.1 and 0.5. When the remaining time is greater than the second preset threshold, the fusion weight of the fifth lighting control parameter is zero.

[0110] For example, when the first vehicle receives a "thank you" sentiment signal from the second vehicle (the fusion weight of the first lighting control parameter is 0.3), the current occupant relaxation index deviates little from the target range (the fusion weight of the second lighting control parameter is 0.3), and the remaining time to reach the destination is greater than a second preset threshold (the fusion weight of the fifth lighting control parameter is 0), the normalized fusion weights are 0.5, 0.5, and 0, respectively. When the remaining time to reach the destination decreases to the second preset threshold, the fusion weight of the fifth lighting control parameter increases to 0.4, and the normalized fusion weights are adjusted to 0.3, 0.3, and 0.4. Finally, the first, second, and fifth lighting control parameters are weighted and fused according to these fusion weights to obtain the final lighting control parameters.

[0111] The following examples illustrate possible implementation schemes of the vehicle ambient lighting control method described in one or more of the above embodiments.

[0112] This solution aims to construct an in-vehicle ambient lighting system that integrates inter-vehicle emotional semantic interaction, evidence-based closed-loop health phototherapy, multi-occupant dynamic weight arbitration, and predictive environmental adaptation, overcoming the limitations of related technologies. The solution includes the following inventive concepts: (1) Construct an inter-vehicle emotional semantic network. Define a lightweight V2X communication protocol frame to realize the standardized encoding, transmission and decoding of abstract emotional intentions such as greetings, thanks and warnings between vehicles. Combine the emotional-lighting narrative template library to complete the visual expression and establish an exclusive lighting social system between vehicles.

[0113] (2) Build a closed-loop phototherapy algorithm engine. With the occupant's relaxation level as the only controlled variable, a single PID multi-channel mapping control algorithm is adopted to independently map the PID proportional term, integral term, and derivative term to the three optical parameter dimensions of wavelength, light intensity, and light pulse frequency, respectively. Combined with a medical evidence-based database, a dynamic phototherapy prescription is generated to achieve precise closed-loop health intervention driven by physiological signals.

[0114] (3) Design a multi-dimensional weighted dynamic game arbitration model. Integrate safety factors (i.e., the first factor in the above embodiments), health factors (i.e., the second factor in the above embodiments), role factors (i.e., the third factor in the above embodiments), and fairness factors (i.e., the fourth factor in the above embodiments) to construct a vehicle-specific occupant discourse power model (i.e., a multi-dimensional weighted dynamic game arbitration model). The fusion of multi-occupant lighting preferences is completed through RGB color vector weighted normalization, taking into account driving safety, the health of all occupants, and fairness of use.

[0115] (4) Achieve predictive environment adaptive control: Combine navigation destination, remaining driving distance, real-time vehicle speed and future weather information to dynamically calculate the timing of light pre-adjustment, and complete the smooth transition of the lighting scene before the vehicle arrives at the destination, so as to achieve active intelligent adaptation.

[0116] For example, Figure 6 This is a schematic diagram of the architecture of a vehicle ambient lighting control system provided in an embodiment of this application, as shown below. Figure 6 As shown, the system includes a vehicle-to-vehicle social interaction module 610, an environmental perception module 620, a lighting execution module 630, a biosensor module 640, a closed-loop phototherapy algorithm engine 650, and a multi-occupant collaborative arbitration module 660. Among them: The vehicle-to-vehicle social interaction module 610 can be based on the V2X vehicle-to-everything communication unit to encode, broadcast, receive and parse emotional semantic protocol frames, complete the emotional intention interaction between vehicles, and output lighting narrative commands; The environmental perception module 620 can integrate information from the vehicle navigation system, weather data, ambient light sensor, and real-time vehicle speed data to achieve predictive adaptation to driving scenarios. The lighting actuator module 630 can drive all the LED light strips in the vehicle to execute lighting control commands; The biosensor module 640 can be integrated into the headrest, steering wheel, and armrest of a vehicle seat to collect physiological signals such as occupant heart rate, heart rate variability (HRV), and skin conductance level (SCL) in real time, and complete signal preprocessing and feature extraction. The closed-loop phototherapy algorithm engine 650 can achieve multi-dimensional emotion recognition based on physiological signals, generate an initial phototherapy prescription based on medical evidence, achieve closed-loop control of multi-dimensional phototherapy parameters through a single PID multi-channel mapping algorithm, and finally output personalized phototherapy instructions. The multi-occupant collaborative arbitration module 660 can calculate the real-time voice of each occupant based on a four-dimensional weight model, weight and fuse the preferences of each occupant, and output unified lighting control commands.

[0117] Next, the specific implementation of the above scheme will be described in detail. First, for the vehicle-to-vehicle emotional semantic interaction part, the system defines a 7-byte standardized lightweight protocol frame to achieve anonymized and highly reliable vehicle-to-vehicle emotional transmission. The frame structure is shown in Table 1 below: Table 1

[0118] After passengers can trigger social intentions via steering wheel shortcut keys or voice commands, the system maps the intentions to a combination of corresponding message types and emotional tags, encapsulates them into a protocol frame structure as shown in Table 1, and broadcasts them to surrounding vehicles through the V2X communication unit.

[0119] After receiving the protocol frame, the receiving vehicle completes frame verification and data parsing, extracts message type and sentiment tag to generate composite semantic key value; queries the predefined sentiment-lighting narrative template library, and maps abstract semantics to dynamic lighting effects.

[0120] For example, a compound semantic key value of "greeting" and "friendliness" corresponds to a light blue breathing light effect with a frequency of 0.5Hz for 4 seconds. Another example is a compound semantic key value of "gratitude" and "joy," which corresponds to a warm gold flowing light effect that moves from the front to the rear of the car for 3 seconds. Yet another example is a compound semantic key value of "warning" and "tension," which corresponds to a red pulse light effect with a frequency of 2Hz for 5 seconds.

[0121] When receiving emotional semantic commands from multiple surrounding vehicles simultaneously, arbitration can be completed according to the following priority: 1. Message type priority: Alerts > Thanks > Greetings; 2. Vehicle distance priority: The closer the vehicle is to this vehicle, the higher the priority; 3. Commands with the same priority: displayed in the order of receipt time, with a single light effect display interval of 2 seconds.

[0122] Subsequently, the health and wellness control process begins. The physiological signals collected by the biosensor module 640 are filtered and preprocessed for noise reduction. Time-frequency domain feature parameters are then extracted, input into a pre-trained deep learning model, and a normalized three-dimensional emotion vector is output. ,in, Indicates the stress index. Indicates fatigue index, This represents the relaxation level index. The values ​​of each parameter range from [0,1] and satisfy the following conditions: .

[0123] The system incorporates a medical evidence-based database integrating phototherapy research, and selects initial light parameter benchmarks based on the dominant emotion in the three-dimensional emotion vector. : 1. High-pressure state ( ): =470nm high-purity blue light, =50cd, =0.5Hz; 2. High fatigue state ( ): =590nm warm yellow light, =150cd, =1.0Hz; 3. Normal state ( and ): =4500K neutral white light, =100cd, =0Hz.

[0124] in, Indicates the reference wavelength. Indicates the reference illuminance. This indicates the reference pulse frequency.

[0125] Relaxation Index Let be the controlled variable, and set the target steady-state interval [0.4, 0.6], with the target value being... Define the error signal These are used to adjust system parameters in different dimensions, enabling uncoupled and precise control of the degree of relaxation.

[0126] In the wavelength control channel, only the proportional term is used. The formula is: .in, As an emotional symbol, stress is dominant and takes +1 (shifting towards blue light), while fatigue is dominant and takes 1 (shifting towards yellow light).

[0127] In the light intensity control channel, a complete PID control is adopted, and the formula is: .

[0128] In the pulse control channel, only the differential term is used. The rules are as follows: When At time t, the frequency of the light pulse is set. equal Multiply And trigger a high-purity light pulse with a duration of 1 second and corresponding to a specific wavelength; otherwise, set It equals 0.

[0129] After the lighting is activated, the biosensor module 640 collects the occupant's physiological feedback data in real time. Based on the collected data, the system updates the three-dimensional emotion vector and error signal. The system continuously adjusts and iterates based on the updated parameters until the occupant's relaxation level stabilizes within the preset target range.

[0130] For multi-occupant collaborative control, the system defines a normalized real-time voice right for the i-th occupant in the vehicle, as shown in the following formula: .in, Default coefficient , , , The factors are defined as follows: 1. Safety Factor The driver's safety factor is always 1.0; when an occupant exhibits behavior that interferes with driving, the system temporarily adjusts the occupant's safety factor to 0.8 and maintains this value for 10 seconds. 2. Health factors : It is positively correlated with the occupant stress index, among which This indicates the maximum stress index among all occupants in the vehicle; 3. Role Factors : Preset fixed values: driver is 1.0, front passenger is 0.8, and rear passenger is 0.5; 4. Fairness Factor : ,in Indicates crew The cumulative duration for which lighting preferences were not adopted.

[0131] The final output light color is a weighted and normalized sum of the RGB preference vectors of all occupants, as shown in the formula: .

[0132] in, For the first The occupants' RGB color preference vectors enable smooth lighting transitions without hard switching.

[0133] When the rate of change in occupant relaxation If the current light therapy intervention is deemed ineffective, the health factor weighting coefficient of the current occupants will be temporarily adjusted. Increase by 20% until the occupant's relaxation level shows a positive trend.

[0134] In terms of adaptive environmental control, the system combines navigation information, real-time vehicle conditions, and weather data to calculate the start time for pre-adjusting lighting scenes. It can also adjust the start time based on real-time vehicle speed. and remaining distance Calculate the estimated arrival time, before the estimated arrival time (Light transition duration, default 10s) Start pre-adjustment to ensure that the lighting scene is fully adapted when the vehicle arrives at its destination.

[0135] The system can match corresponding lighting scenes based on the destination type (residential, office, medical, commercial) and the weather information for the next 15 minutes.

[0136] After the pre-adjustment is initiated, the light parameters are gradually adjusted to ensure that the lighting scene configuration is fully adapted when the vehicle arrives at its destination.

[0137] It can monitor road condition changes in real time, update the remaining arrival time of vehicles, and simultaneously correct the pre-adjustment start time to avoid pre-adjustment being too early or too late, ensuring accurate scene adaptation.

[0138] It is understood that this solution has at least the following advantages: (1) Pioneering a standardized interactive system for vehicle-to-vehicle emotional semantics: Breaking through the limitation that existing vehicle-to-vehicle lights can only transmit physical states, the system achieves the anonymous transmission of abstract emotions through a 7-byte lightweight V2X protocol frame, and completes the visual expression by combining lighting narrative templates, thus building an exclusive vehicle-to-vehicle lighting social network.

[0139] (2) By constructing an evidence-based single-PID multi-channel closed-loop phototherapy system, which is different from the existing open-loop passive adjustment method, the degree of relaxation is used as the controlled variable. The three parameters of proportional, integral and differential are independently mapped to three light parameter dimensions. Combined with the medical evidence database, precise steady-state regulation is achieved, forming a complete closed loop of perception-healing-feedback, ensuring that the intervention effect is stable and controllable.

[0140] (3) Construct a vehicle-specific multi-occupant four-dimensional arbitration model: Unlike the smart home multi-user control scheme, it integrates four-dimensional factors of safety, health, role and fairness, strictly follows the vehicle driving safety constraints, realizes intelligent coordination of multi-occupant lighting preferences, and takes into account safety, health and fairness.

[0141] (4) Achieve trip-driven predictive environment adaptation: Unlike existing passive position matching schemes, it combines navigation information, weather conditions and vehicle speed data to dynamically calculate the timing of pre-adjustment, complete the smooth transition of lighting scenes, and achieve a smart cockpit experience where the light changes before the arrival of the vehicle.

[0142] It should be noted that although the steps of the method in this application are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps; or steps from different embodiments may be combined into a new technical solution.

[0143] Based on the same inventive concept as the foregoing embodiments, this application provides a control device for vehicle ambient lighting.

[0144] Figure 7 This is a schematic diagram of a vehicle ambient lighting control device provided in an embodiment of this application. The device is applied to a first vehicle. Figure 7 As shown, the vehicle ambient lighting control device 700 includes: a parsing module 710, a determining module 720, and a control module 730; wherein: The parsing module 710 is used to parse the emotional semantic signal received by the second vehicle via wireless communication to obtain the emotional intention information of the second vehicle. The determining module 720 is used to determine the first lighting control parameters based on the emotional intention information; The control module 730 is used to control the ambient lights of the first vehicle based on the first lighting control parameters.

[0145] In some embodiments, the determining module 720 is further configured to: obtain the message type carried in the emotional semantic signal; the message type characterizes the type of social interaction between the second vehicle and the first vehicle; and determine the first lighting control parameter based on the message type and the emotional intent information.

[0146] In some embodiments, the second vehicle includes multiple vehicles, and the parsing module 710 is further configured to: in response to receiving emotional semantic signals transmitted by multiple second vehicles via wireless communication, determine a target signal from the multiple emotional semantic signals according to a preset arbitration rule; parse the target signal to obtain emotional intent information of the second vehicle that sent the target signal; the preset arbitration rule includes at least one of the following: a first arbitration rule for determining the target signal according to the priority of the message type carried by the emotional semantic signal; a second arbitration rule for determining the target signal according to the distance between the second vehicle and the first vehicle; and a third arbitration rule for determining the target signal according to the chronological order of receiving the emotional semantic signals.

[0147] In some embodiments, the vehicle ambient lighting control device 700 further includes: The acquisition module is used to acquire the physiological signals of each occupant in the first vehicle; The generation module is used to generate a three-dimensional emotion vector including stress index dimension, fatigue index dimension and relaxation index dimension based on the physiological signals of each occupant. The determining module 720 is further configured to: determine the second lighting control parameters based on the three-dimensional emotion vectors corresponding to each occupant; The control module 730 is also used to control the ambient lighting of the first vehicle based on the second lighting control parameters.

[0148] In some embodiments, the determining module 720 is further configured to: determine a third lighting control parameter corresponding to each occupant based on the three-dimensional emotion vector corresponding to each occupant; adjust the third lighting control parameter corresponding to each occupant using a closed-loop control algorithm with the relaxation index of each occupant as the control target, thereby obtaining a fourth lighting control parameter corresponding to each occupant; and determine a second lighting control parameter based on the fourth lighting control parameter corresponding to each occupant.

[0149] In some embodiments, the determining module 720 is further configured to: determine the fusion weight corresponding to each occupant based on the target factor; and perform weighted fusion of the fourth lighting control parameters corresponding to each occupant based on the fusion weight corresponding to each occupant to obtain the second lighting control parameters; the target factor includes at least one of the following: a first factor characterizing the degree of influence of each occupant on the driving behavior of the first vehicle; a second factor characterizing the stress index of each occupant; a third factor characterizing the seating position of each occupant in the first vehicle; and a fourth factor characterizing the cumulative duration for which the lighting preferences of each occupant have not been responded to.

[0150] In some embodiments, the target factor includes at least two factors selected from the first factor, the second factor, the third factor, and the fourth factor; the determining module 720 is further configured to: weight each factor in the target factor to obtain the fusion weight corresponding to each passenger.

[0151] In some embodiments, the vehicle ambient lighting control device 700 further includes: The monitoring module is used to monitor the rate of change in the relaxation level of each occupant; The adjustment module is used to adjust the weighting coefficients of each factor in the target factor when the rate of change of relaxation of any occupant is less than a first preset threshold.

[0152] In some embodiments, the acquisition module is further configured to: acquire destination information of the first vehicle; the destination information includes at least one of the following: destination type information, destination weather information; The determining module 720 is further configured to: determine the fifth lighting control parameter based on the destination information; The monitoring module is further configured to: monitor the remaining time for the first vehicle to reach its destination, and in response to the remaining time being equal to or less than a second preset threshold, switch the first lighting control parameter to the fifth lighting control parameter, so as to control the ambient lighting of the first vehicle based on the fifth lighting control parameter.

[0153] The descriptions of the above device embodiments are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0154] Based on the same inventive concept as the foregoing embodiments, this application provides a vehicle.

[0155] Figure 8 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Figure 8 The vehicle 800 shown includes a processor 801, which can call and run computer programs from memory to implement the methods in the embodiments of this application.

[0156] Optionally, such as Figure 8 As shown, the vehicle 800 may further include a memory 802. The processor 801 can retrieve and run computer programs from the memory 802 to implement the methods described in this embodiment.

[0157] The memory 802 can be a separate device independent of the processor 801, or it can be integrated into the processor 801.

[0158] Optionally, such as Figure 8 As shown, the vehicle 800 may also include a transceiver 803, which the processor 801 can control to communicate with other devices. Specifically, it can send information or data to other devices or receive information or data sent by other devices.

[0159] The transceiver 803 may include a transmitter and a receiver. The transceiver 803 may further include an antenna, and the number of antennas may be one or more.

[0160] This application also provides a computer-readable storage medium for storing computer programs.

[0161] Optionally, the computer-readable storage medium can be applied to the vehicle in the embodiments of this application, and the computer program causes the processor or vehicle to perform the various methods of the embodiments of this application, which will not be described in detail here for the sake of brevity.

[0162] This application also provides a computer program product, including computer program instructions.

[0163] Optionally, the computer program product can be applied to the vehicle in the embodiments of this application, and the computer program instructions cause the processor or vehicle to execute the various methods of the embodiments of this application. For the sake of brevity, they will not be described in detail here.

[0164] This application also provides a computer program.

[0165] Optionally, the computer program can be applied to the vehicle in the embodiments of this application. When the computer program runs on the processor or the vehicle, it causes the processor or the vehicle to execute the various methods of the embodiments of this application. For the sake of brevity, these will not be described in detail here.

[0166] It should be noted that the descriptions of the devices, storage media, computer program products, and computer program embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the device, storage media, computer program products, and computer program embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0167] It should be understood that the processor in the embodiments of this application may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0168] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0169] It should be understood that the above-described memory is exemplary and not a limiting description. For example, the memory in the embodiments of this application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DR RAM), etc. That is to say, the memory in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0170] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0171] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0172] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0173] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0174] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0175] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a vehicle to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0176] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling vehicle ambient lighting, characterized in that, Applied to a first vehicle, the method includes: In response to receiving an emotional semantic signal transmitted by the second vehicle via wireless communication, the emotional semantic signal is parsed to obtain the emotional intention information of the second vehicle; Based on the emotional intent information, the first lighting control parameters are determined; Based on the first lighting control parameters, the ambient lighting of the first vehicle is controlled.

2. The method according to claim 1, characterized in that, Determining the first lighting control parameters based on the emotional intent information includes: Obtain the message type carried in the emotional semantic signal; the message type represents the type of social interaction between the second vehicle and the first vehicle. Based on the message type and the emotional intent information, the first lighting control parameters are determined.

3. The method according to claim 1 or 2, characterized in that, The second vehicle includes multiple vehicles. The step of responding to receiving emotional semantic signals transmitted by the second vehicle via wireless communication, parsing the emotional semantic signals to obtain the emotional intent information of the second vehicle, includes: In response to receiving emotional semantic signals transmitted wirelessly by multiple second vehicles, a target signal is determined from the multiple emotional semantic signals according to a preset arbitration rule; The target signal is parsed to obtain the emotional intent information of the second vehicle that sent the target signal; The pre-defined arbitration rules include at least one of the following: The first arbitration rule for the target signal is determined according to the priority of the message type carried by the emotional semantic signal; The second arbitration rule for determining the target signal is based on the distance between the second vehicle and the first vehicle; The third arbitration rule for determining the target signal is based on the chronological order in which the emotional semantic signals are received.

4. The method according to claim 1, characterized in that, The method further includes: Acquire the physiological signals of each occupant in the first vehicle; Based on the physiological signals of each passenger, a three-dimensional emotion vector is generated, including the stress index dimension, fatigue index dimension, and relaxation index dimension. Based on the three-dimensional emotion vectors corresponding to each occupant, the second lighting control parameters are determined. The ambient lighting of the first vehicle is controlled based on the second lighting control parameters.

5. The method according to claim 4, characterized in that, The determination of the second lighting control parameters based on the three-dimensional emotion vectors corresponding to each occupant includes: Based on the three-dimensional emotion vectors corresponding to each occupant, the third lighting control parameters corresponding to each occupant are determined. Using the relaxation index of each occupant as the control target, a closed-loop control algorithm is used to adjust the third lighting control parameters corresponding to each occupant to obtain the fourth lighting control parameters corresponding to each occupant. The second lighting control parameter is determined based on the fourth lighting control parameter corresponding to each occupant.

6. The method according to claim 5, characterized in that, The determination of the second lighting control parameters based on the fourth lighting control parameters corresponding to each occupant includes: Based on the target factor, determine the fusion weight corresponding to each crew member; Based on the fusion weights corresponding to each occupant, the fourth lighting control parameters corresponding to each occupant are weighted and fused to obtain the second lighting control parameters. The target factor includes at least one of the following: The first factor characterizing the degree of influence of each occupant on the driving behavior of the first vehicle; The second factor characterizing the stress index of each occupant; A third factor characterizing the seating position of each occupant within the first vehicle; The fourth factor characterizes the cumulative duration during which each occupant's lighting preferences were not responded to.

7. The method according to claim 6, characterized in that, The target factor includes at least two factors selected from the first factor, the second factor, the third factor, and the fourth factor; The determination of the fusion weights for each passenger based on the target factor includes: The various factors in the target factor are weighted to obtain the fusion weights corresponding to each crew member.

8. The method according to claim 7, characterized in that, The method further includes: Monitor the rate of change in relaxation level of each crew member; If the rate of change in the relaxation level of any occupant is less than a first preset threshold, the weighting coefficients corresponding to each factor in the target factor are adjusted.

9. The method according to claim 1, characterized in that, The method further includes: Obtain the destination information of the first vehicle; the destination information includes at least one of the following: destination type information, destination weather information; Based on the destination information, the fifth lighting control parameter is determined; The remaining time for the first vehicle to reach its destination is monitored, and in response to the remaining time being equal to or less than a second preset threshold, the first lighting control parameter is switched to the fifth lighting control parameter, so as to control the ambient lighting of the first vehicle based on the fifth lighting control parameter.

10. A vehicle, characterized in that, include: Memory is used to store executable instructions or computer programs. A processor, when executing computer-executable instructions or computer programs stored in the memory, implements the method according to any one of claims 1 to 9.

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