Method for controlling an atmosphere lamp and vehicle

Abstract

The application discloses a kind of atmosphere lamp's regulation and control method and vehicle, it is related to intelligent cabin technical field, including: obtaining navigation information including navigation terminal point attribute information, vehicle current position and remaining journey, navigation path is divided into multiple continuous light effect control section, when vehicle enters next light effect control section, based on end attribute determines the light effect control parameter of adaptation, calculate the monotone increasing light effect preview intensity coefficient that reduces with remaining journey, intensity coefficient and light effect parameter are combined to generate and execute the atmosphere lamp regulation and control instruction of corresponding section.The application finds the light effect control parameter adapted to terminal attribute, realizes the strong association of light effect and travel purpose, and uses light effect preview intensity coefficient to decompose existing single full amplitude jump into multiple small amplitude segmented progressive change, solve the problem that light effect is constant throughout the journey, single full jump changes harshly and is irrelevant to travel purpose, improve user driving experience.

Description

Technical Field

[0001] This application relates to the technical field of intelligent cockpits, and particularly to a method for controlling ambient lights and a vehicle. Background Art

[0002] With the development of intelligent cockpit technology, vehicle ambient lights have gradually evolved from traditional decorative functions to interactive functions in the intelligent cockpit scenario. Existing technologies have achieved the linkage control of ambient lights and the navigation system. The mainstream solutions include triggering light effect prompts through navigation steering instructions, mapping corresponding light effects based on the current geographical location of the vehicle, and adjusting the light effect color according to the road traffic congestion conditions, so as to achieve the linkage of the ambient lights in the navigation scenario.

[0003] However, all existing linkage control solutions adopt a threshold-triggered discrete control logic, which can only control the instantaneous jump of the ambient light effect when the navigation information reaches the trigger node. For example, when the navigation prompts a turn, the ambient light on the turning side is controlled to jump from a green light effect to a red light effect, or when the navigation end point is set to the seaside, the ambient light is controlled to jump from the current color to a blue light effect and maintain this blue light effect until the navigation ends. This results in a decrease in the spatio-temporal correlation between the ambient light effect and the navigation journey, the inability to dynamically adjust the light effect, and the abrupt and rigid change of the light effect, seriously reducing the user experience. Summary of the Invention

[0004] In view of the above problems, this application provides a method for controlling ambient lights and a vehicle to achieve the purpose of improving the user experience. The specific solutions are as follows:

[0005] The first aspect of this application provides a method for controlling ambient lights, including: <00000- 19>

[0006] Obtain navigation information, where the navigation information includes: end point attribute information of the navigation end point, the current vehicle position, and the remaining journey information;

[0007] Divide the navigation path into multiple consecutive light effect control sections, and determine the light effect control section to which the current vehicle position belongs;

[0008] When the vehicle enters the second light effect control section from the first light effect control section, search for light effect control parameters adapted to the end point attribute information;

[0009] Calculate the light effect preview intensity coefficient of the second light effect control section based on the remaining journey information. The light effect preview intensity coefficient monotonically increases as the remaining journey information decreases, and the light effect preview intensity coefficient of the second light effect control section is greater than that of the first light effect control section;

[0010] Based on the light effect pre-simulation intensity coefficient and the light effect control parameters, an ambient light control command corresponding to the second light effect control section is generated and executed.

[0011] In one possible implementation, determining the light effect control section to which the current vehicle location belongs includes:

[0012] Perform semantic recognition on the endpoint attribute information to obtain the first semantic label of the navigation endpoint;

[0013] Find the light effect control parameters of each type corresponding to the first semantic tag. The types include at least one of hue value, saturation, light effect intensity, refresh rate, and light effect type.

[0014] One possible implementation also includes:

[0015] Obtain the weather information at the current sampling time, and perform semantic recognition on the weather information to obtain the second semantic label of the weather information;

[0016] Find each light effect adjustment parameter corresponding to the second semantic tag, and the type of the light effect adjustment parameter corresponds one-to-one with the type in the light effect control parameter;

[0017] The light effect control parameters are adjusted using the light effect adjustment parameters corresponding to the same type to obtain the adjusted light effect control parameters for each type.

[0018] In one possible implementation, determining the light effect control section to which the current vehicle location belongs includes:

[0019] Obtain the first light effect control road segment to which the vehicle belongs at the previous sampling time;

[0020] The current vehicle position is matched with the coordinate intervals corresponding to each of the light effect control road segments to determine the second light effect control road segment to which the vehicle belongs at the current sampling time;

[0021] If the second light effect control section is different from the first light effect control section, then the current vehicle position is determined to indicate that the vehicle has entered the second light effect control section from the first light effect control section.

[0022] One possible implementation also includes:

[0023] If the second light effect control segment is the same as the first light effect control segment, then the current vehicle position indicates that the vehicle is still in the first light effect control segment, and the ambient light is controlled to continuously output historical ambient light control commands in the first light effect control segment, the historical ambient light control commands corresponding to the first light effect control segment.

[0024] In one possible implementation, calculating the light effect pre-simulation intensity coefficient of the second light effect control section based on the remaining travel information includes:

[0025] The remaining travel information is input into a preset logarithmic nonlinear function, so that the preset logarithmic nonlinear function calculates the light effect pre-simulation intensity coefficient of the second light effect control section based on the remaining travel information, a preset attenuation constant, and a preset pre-simulation path length.

[0026] In one possible implementation, generating and executing the ambient light control command corresponding to the second light effect control section based on the light effect pre-simulation intensity coefficient and the light effect control parameters includes:

[0027] Using the light effect pre-simulation intensity coefficient as a modulation factor, the light effect control parameters are modulated using a preset progressive modulation algorithm to obtain the actual light effect control parameters corresponding to the second light effect control segment. The actual light effect control parameters are then encapsulated into the current ambient light control command corresponding to the second light effect control segment, and the current ambient light control command is executed.

[0028] In one possible implementation, the method for controlling the ambient light further includes:

[0029] If a change in navigation path is detected, obtain the target light effect control parameters corresponding to the attribute information of the changed navigation destination;

[0030] Based on the target light effect control parameters and the light effect control parameters before the change, a smooth transition parameter is calculated, wherein the smooth transition parameter includes at least one of transition duration and transition curve;

[0031] Based on the transition parameters, the ambient light is controlled to smoothly transition from the current lighting effect state to the lighting effect state corresponding to the target lighting effect control parameters.

[0032] In one possible implementation, the step of generating and executing the ambient light control command corresponding to the second light effect control section includes:

[0033] Obtain the current light effect control parameters and target light effect control parameters of the ambient light, wherein the target light effect control parameters are determined based on the light effect pre-simulation intensity coefficient and the light effect control parameters;

[0034] Calculate the parameter variation range between the current light effect control parameter and the target light effect control parameter;

[0035] Based on the parameter change amplitude and the preset maximum parameter change rate, the transition duration is calculated, and the transition duration is positively correlated with the parameter change amplitude.

[0036] According to the transition duration, the ambient light is controlled to smoothly transition from the current light effect control parameter to the target light effect control parameter.

[0037] A fourth aspect of this application provides a vehicle, including: an ambient lighting controller, the ambient lighting controller being configured to perform the ambient lighting control method as described in the first aspect or any implementation thereof.

[0038] The ambient light controller provided in the second aspect of this application.

[0039] By employing the aforementioned technical solution, the ambient lighting control method and vehicle provided in this application obtain the basic data required for subsequent ambient lighting control through the configured navigation information. Furthermore, by configuring the navigation path into multiple continuous light effect control segments and identifying the current vehicle position within its respective light effect control segment, this application decomposes the logic of existing technologies that only trigger corresponding control operations at trigger nodes into multiple light effect control segments that progress along the complete navigation path, fundamentally breaking the inherent logic of threshold-triggered discrete control. Subsequently, by configuring the system to find lighting effect control parameters that match the destination attribute information when a vehicle enters the second lighting effect control section from the first, the system calculates the lighting effect pre-simulation intensity coefficient for the second lighting effect control section based on the remaining travel information. Since the lighting effect pre-simulation intensity coefficient represents the degree to which the lighting effect control parameters monotonically increase as the remaining travel information decreases, and the lighting effect pre-simulation intensity coefficient for the second lighting effect control section is greater than that for the first, the system breaks down the abrupt, one-time lighting effect jump of existing technologies into multiple segments of gradual enhancement. This solves the problem of existing technologies where the lighting effect remains unchanged throughout the entire process after a jump and cannot be dynamically adjusted, while also avoiding the abrupt changes in lighting effect caused by a full-amplitude jump. It also establishes a one-to-one correspondence between lighting effect and lighting effect control sections. Finally, by configuring the generation and execution of the current ambient light control command based on the lighting effect pre-simulation intensity coefficient and lighting effect control parameters, the system avoids frequent jumps within a single lighting effect control section, ensuring a smooth transition of ambient light effects within that section. As can be seen, this application realizes dynamic and progressive light effect adjustment of ambient lighting according to the navigation route, which improves the user experience. Attached Figure Description

[0040] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0041] Figure 1 A flowchart illustrating a method for controlling ambient lighting provided in this application;

[0042] Figure 2 A schematic diagram of a light effect control section provided in this application;

[0043] Figure 3 A schematic diagram of a light effect control section provided in this application;

[0044] Figure 4 A flowchart illustrating a method for controlling ambient lighting provided in this application;

[0045] Figure 5 This is a schematic diagram of the structure of an ambient light controller provided in this application. Detailed Implementation

[0046] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0047] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0048] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0049] It should be noted that in the existing intelligent cockpit ambient lighting and navigation system linkage control, threshold-triggered discrete control logic is used. This results in the ambient lighting effect only being controlled to change instantaneously when navigation information reaches a trigger node. This leads to a lack of smooth transition in the light effect change, making dynamic adjustment impossible, and reducing the spatiotemporal correlation between the light effect and the navigation journey. Specifically, existing technology can only control the ambient lighting effect on the turning side to change to a prompt color for a short period when the navigation turning command is triggered, or control the ambient lighting effect to change from the current color to blue and maintain this state until the navigation ends when the navigation destination attribute is seaside. This causes the light effect to remain unchanged for a long period of the remaining journey, with abrupt changes only occurring at specific nodes, thus weakening the dynamic correspondence between the light effect and the progress of the navigation journey.

[0050] For example, in a scenario where a vehicle navigates to a seaside destination, when the remaining distance meets a preset threshold, the ambient lighting effect is directly switched from its current color to blue and maintained. Users cannot perceive the gradual change in lighting effect as the vehicle approaches its destination, resulting in a lack of continuity in the interactive experience. Furthermore, as the remaining distance gradually shortens, the lighting effect does not dynamically adjust with the distance, only abruptly changing as the destination nears, further diminishing the user experience.

[0051] If the aforementioned issues are not resolved, the instantaneous changes in ambient lighting effects will continue to affect users' perception of the intelligent cockpit's interactive functions, weakening the practicality of the intelligent cockpit scenario. Furthermore, the reduced correlation between lighting effects and navigation routes will prevent the effective use of interactive functions. Consequently, users' acceptance of the vehicle's level of intelligence will be affected, and the continuity of the intelligent cockpit's interactive experience cannot be guaranteed.

[0052] To address the aforementioned problems, the first aspect of this application provides a method for controlling ambient lighting, such as... Figure 1 The diagram shows a flowchart of an ambient light control method, which includes:

[0053] S101. Obtain navigation information, which includes: destination attribute information, current vehicle location, and remaining trip information.

[0054] It should be noted that in practical applications, the above navigation information can be obtained from the vehicle's navigation system or a navigation device that communicates with the vehicle, using a periodic polling method.

[0055] It should be noted that, in practical applications, the destination attribute information mentioned above can represent attributes such as the name, region, terrain, and type of the navigation destination. For example, assuming the navigation destination is Forest Park A in Province B, the destination attribute information could be one or more of "Forest Park A," "Province B," "hilly forest," or "tourist resort area." This destination attribute information can be input by the user or retrieved from the vehicle-side database or the cloud based on the semantic recognition results of the navigation destination.

[0056] It should be noted that in practical applications, the aforementioned current vehicle location refers to the vehicle's real-time geographic coordinates or location identifier at the current sampling moment. The aforementioned remaining travel information can be the remaining distance or remaining travel time from the current vehicle location to the navigation destination.

[0057] S102. Divide the navigation path into multiple continuous light effect control segments and determine the light effect control segment to which the current vehicle position belongs.

[0058] It should be noted that in practical application scenarios, the aforementioned light effect control road segments can be obtained after the user completes the navigation route setting, based on the preset number of light effect control road segments, or based on the preset light effect control path length after dividing the complete navigation route.

[0059] It should be noted that, in practical application scenarios, the determination of the light effect control segment to which the current vehicle position belongs can be based on the relationship between the spatial coordinates of the current vehicle position and the spatial coordinate intervals of each light effect control segment, as well as the identification result of the light effect control segment at the previous sampling time. Alternatively, it can be based on the distance between the current vehicle position and the control starting point, identifying the relationship between that distance and the corresponding distance intervals of each light effect control segment, as well as the identification result of the light effect control segment at the previous sampling time. This application provides an example of such a method:

[0060] like Figure 2 The diagram shows a schematic of a light effect control road segment, which includes three light effect control road segments connected in sequence. The spatial coordinate interval for light effect control segment A is [X1, X2), the spatial coordinate interval for light effect control segment B is [X2, X3), and the spatial coordinate interval for light effect control segment C is [X3, X4). Assume that the spatial coordinates of the current vehicle position collected at the current sampling time i are (X1, X2). i Y i ), then in X i ∈[X1, X2), determine that the current vehicle position belongs to the light effect control section A, if X i If the distance is ∈ [X3, X4), then the current vehicle position is determined to belong to the C light effect control segment. Further, assuming the current vehicle position belongs to the B light effect control segment, and the previous sampling time also indicated the current vehicle position as belonging to the B light effect control segment, then the current vehicle position is ultimately determined to represent that it is always within the B light effect control segment. If the previous sampling time indicated the current vehicle position belonged to the A light effect control segment, then the current vehicle position is ultimately determined to represent that the vehicle entered the B light effect control segment (i.e., the subsequent first light effect control segment) from the A light effect control segment (i.e., the subsequent second light effect control segment).

[0061] It should be noted that this application divides the navigation path into multiple continuous light effect control segments by configuring the current vehicle position to identify the light effect control segment to which it belongs. This allows the application to decompose the logic of the prior art, which only triggers the corresponding control operation at the trigger node, into multiple light effect control segments that proceed along the complete navigation path, thereby fundamentally breaking the inherent logic of threshold-triggered discrete control.

[0062] S103. When a vehicle enters the second light effect control section from the first light effect control section, search for light effect control parameters that match the destination attribute information.

[0063] It should be noted that in practical applications, the aforementioned first light effect control segment is a series of segments divided along the complete navigation path, adjacent to the second light effect control segment, and divided only earlier than the second light effect control segment. As described above... Figure 2 For example, if section A is the first lighting control section, then section B is the second lighting control section; if section B is the first lighting control section, then section C is the second lighting control section.

[0064] It should be noted that in practical applications, the above-mentioned light effect control parameters are used to control the display light effects of ambient lights. These parameters can be of various types, including but not limited to: hue value range, saturation, dynamic type, refresh rate, and special effects. These light effect control parameters can be pre-set and stored based on endpoint attribute information, or they can be set by the user.

[0065] It should be noted that in real-world applications, users may change their destination or adjust lighting effect control parameters while the vehicle is in motion. Therefore, this application configures the lighting effect control parameters to match the destination attribute information when the vehicle's current location indicates that it has moved from the first lighting effect control segment to the second lighting effect control segment. This allows the ambient lighting effect to dynamically adapt to the user's needs, avoiding the risk of a degraded user experience caused by the ambient lighting generating constant lighting effects or lighting effect control parameters that are incompatible with the user's needs.

[0066] It should be noted that, for the sake of understanding the above light effect control parameters, this paper will explain one possible implementation of this application: Assuming the navigation destination is Beach C, then its destination attribute information is beach and resort area. The light effect control parameters adapted to the beach include hue value range, saturation, dynamic type and refresh rate. The hue value range is: H=180°~210° (representing a gradual transition from cyan to sky blue), the saturation is: S=0.5~0.7 (representing high saturation), the dynamic type is flowing, and the refresh rate is 0.1~0.3Hz (simulating ocean waves).

[0067] S104. Calculate the light effect prediction intensity coefficient of the second light effect control section based on the remaining travel information. The light effect prediction intensity coefficient increases monotonically as the remaining travel information decreases. The light effect prediction intensity coefficient of the second light effect control section is greater than that of the first light effect control section.

[0068] It should be noted that, in practical applications, the aforementioned light effect pre-simulation intensity coefficient is a dimensionless factor used to adjust the ambient light effect intensity, salience, and / or dynamic update frequency. This application configures the system to find light effect control parameters that match the destination attribute information when a vehicle enters a second light effect control section from a first light effect control section. It then configures the calculation of the light effect pre-simulation intensity coefficient for the second light effect control section based on the remaining travel information. Since the light effect pre-simulation intensity coefficient represents the degree to which the light effect control parameters monotonically increase as the remaining travel information decreases, and the light effect pre-simulation intensity coefficient for the second light effect control section is greater than that for the first light effect control section, the abrupt, one-time light effect jump in existing technologies is broken down into multiple segments of gradual enhancement. This solves the problem of existing technologies where the light effect remains unchanged throughout the entire process after a jump and cannot be dynamically adjusted, while also avoiding abrupt and harsh changes in light effect. Simultaneously, it establishes a one-to-one correspondence between light effect and light effect control sections.

[0069] S105. Based on the light effect pre-simulation intensity coefficient and light effect control parameters, generate and execute the ambient light control command corresponding to the second light effect control section.

[0070] It should be noted that, in practical application scenarios, this application generates and executes the current ambient light control command for the second ambient light control section by configuring the light effect pre-simulation intensity coefficient and light effect control parameters. This avoids frequent and large jumps in ambient light effects within a light effect control section, ensuring a smooth transition of ambient light effects within the light effect control section and improving the user experience.

[0071] To facilitate understanding of the ambient light control method provided in the first aspect of this application, an example of a possible implementation of this application is described below:

[0072] Suppose user A is navigating to a destination called "Resort C," whose destination attribute is identified as "Relaxation / Nature." The total length of the complete navigation route is 100 kilometers.

[0073] At the current sampling time, the navigation system obtains navigation information, including the destination attribute information "Resort C" as "Relax / Nature", the current vehicle position as position X, and the remaining distance information between the current vehicle position and "Resort C" as 50 kilometers.

[0074] The current vehicle position is identified, and its corresponding light control segment is determined. The complete navigation path has been pre-divided into multiple light control segments, each 10 kilometers long. Position X is identified as being within a segment with a remaining distance of 40-50 kilometers; this segment is designated as the first light control segment. As the vehicle travels, when it enters a segment with a remaining distance of 30-40 kilometers, this segment is designated as the second light control segment.

[0075] When a vehicle moves from the first lighting control section to the second lighting control section, the system searches for lighting control parameters that match the "Relaxed / Natural" endpoint attribute information. For example, it retrieves a base hue value of 180 degrees, a saturation of 0.6, and a low-frequency pulsating pattern.

[0076] Based on the remaining travel information (e.g., 35 km within the second light effect control section), the light effect prediction intensity coefficient for the second light effect control section is calculated. For example, if the coefficient for the first light effect control section (40-50 km) is 0.2, then the coefficient for the second light effect control section (30-40 km) might be 0.4. This coefficient is designed to increase monotonically as the remaining distance decreases, ensuring a gradual enhancement of light effect.

[0077] Subsequently, based on the calculated light effect pre-simulation intensity coefficient (0.4) and the retrieved light effect control parameters (hue value of 180 degrees, saturation of 0.6, and low-frequency pulsation mode), the current ambient lighting control command corresponding to the second light effect control segment is generated. For example, this command might specify a hue value of 170 degrees, a saturation of 0.4, and a relatively small pulsation mode amplitude. The ambient lighting system then continuously outputs the light effect corresponding to this command throughout the second light effect control segment. As the vehicle passes through subsequent segments, the remaining travel information continuously decreases, and the light effect pre-simulation intensity coefficient continuously increases (e.g., 0.6, 0.8, 1.0). The generated ambient lighting control command will cause the light effect to gradually shift towards the complete "relaxed / natural" parameters (e.g., hue value approaching 180 degrees, saturation approaching 0.6, and the pulsation mode becoming more pronounced). This achieves a smooth, progressive change in the ambient lighting effect, rather than an instantaneous jump.

[0078] In one possible implementation, the above-mentioned method of controlling the ambient light to continuously output the light effect corresponding to the current ambient light control command in the second light effect control section can be:

[0079] After receiving the current ambient lighting control command, the ambient lighting controller parses it to obtain the corresponding current ambient lighting control command for each independent lighting zone (such as the left front door, right front door, left rear door, right rear door, dashboard, footwell, etc.). This current ambient lighting control command includes: target RGB value (calculated based on hue, saturation, and brightness), dynamic mode (static / breathing / flowing / flickering / gradient, etc.), dynamic parameters (period, frequency, flow direction, etc.), and transition duration (for smooth transitions during scene switching). Subsequently, the ambient lighting controller sends the corresponding current ambient lighting control command for each independent lighting zone to the respective independent driver IC in the form of a pulse width modulation (PWM) signal, enabling the independent driver IC to control the corresponding RGB-LED light strip output according to the specified conditions.

[0080] This application obtains navigation information through configuration, thereby acquiring the basic data required for subsequent ambient lighting control. Furthermore, by configuring the navigation path into multiple continuous light effect control segments and identifying the current vehicle position within its respective light effect control segment, this application breaks down the logic of existing technologies that only trigger corresponding control operations at trigger nodes into multiple light effect control segments that progress along the complete navigation path, fundamentally breaking the inherent logic of threshold-triggered discrete control. Subsequently, by configuring the system to find lighting effect control parameters that match the destination attribute information when a vehicle enters the second lighting effect control section from the first, the system calculates the lighting effect pre-simulation intensity coefficient for the second lighting effect control section based on the remaining travel information. Since the lighting effect pre-simulation intensity coefficient represents the degree to which the lighting effect control parameters monotonically increase as the remaining travel information decreases, and the lighting effect pre-simulation intensity coefficient for the second lighting effect control section is greater than that for the first, the system breaks down the abrupt, one-time lighting effect jump of existing technologies into multiple segments of gradual enhancement. This solves the problem of existing technologies where the lighting effect remains unchanged throughout the entire process after a jump and cannot be dynamically adjusted, while also avoiding the abrupt changes in lighting effect caused by a full-amplitude jump. It also establishes a one-to-one correspondence between lighting effect and lighting effect control sections. Finally, by configuring the generation and execution of the current ambient light control command based on the lighting effect pre-simulation intensity coefficient and lighting effect control parameters, the system avoids frequent jumps within a single lighting effect control section, ensuring a smooth transition of ambient light effects within that section. As can be seen, this application realizes dynamic and progressive light effect adjustment of ambient lighting according to the navigation route, which improves the user experience.

[0081] In one possible implementation, the light effect control parameters that match the endpoint attribute information are searched, including:

[0082] Semantic recognition is performed on the destination attribute information to obtain the first semantic label of the navigation destination;

[0083] Find the light effect control parameters of each type corresponding to the first semantic tag. The types include at least one of hue value, saturation, light effect intensity, refresh rate, and light effect type.

[0084] It should be noted that, in practical applications, the aforementioned first semantic tag can be a semantic tag pre-stored in the vehicle-side device and associated with the semantic recognition result, representing the deep semantic information of the navigation destination. Due to the limited computing power and storage resources of the vehicle-side device, and the large number of alternative navigation destinations, it is not feasible to customize and develop corresponding light effect control parameters for different navigation destinations, or to store the light effect control parameters of all navigation destinations in the vehicle-side device. Furthermore, undifferentiated light effect control parameters are difficult to adapt to users' personalized needs, leading to a decline in user experience. Therefore, this application identifies destination attribute information through configuration and obtains the first semantic tag of the navigation destination through semantic recognition results. This improves the adaptability and richness of light effect control parameters to different navigation destination scenarios under limited computing power and storage resources, avoiding the risk of a decline in user experience caused by undifferentiated light effect control parameters failing to meet users' personalized needs.

[0085] It should be noted that, in practical applications, the aforementioned first semantic label can be set after deep semantic analysis based on the Point of Interest (POI) information of different navigation endpoints. A Point of Interest is a data unit used in a geographic information system to mark a specific location, representing entities such as buildings, shops, and bus stops, and is one of the basic geospatial data types. Table 1 below provides an example of the correspondence between the first semantic label and the endpoint attribute information.

[0086] Table 1

[0087]

[0088] It should be noted that, in practical application scenarios, the above-mentioned search for various types of light effect control parameters corresponding to the first semantic tag can be to search for the light effect control parameters corresponding to each tag content in the first semantic tag.

[0089] Suppose a user sets their navigation destination to "Sanya Bay Beach". First, the system obtains the destination's attribute information, which may include descriptive text such as "Sanya Bay", "beach", and "tourist attraction". Next, it performs semantic recognition on this destination attribute information. For example, the system's internal semantic recognition module could be a rule-based and keyword-matching processor that identifies the core semantic term "beach" and converts it into a first semantic tag for the navigation destination, such as "beach". Subsequently, the system searches a pre-defined lighting effect parameter database based on this first semantic tag of "beach". This database stores various types of lighting effect control parameters corresponding to different semantic tags. For the semantic tag "beach," the system can find and obtain the following lighting effect control parameters: hue value, for example, set to blue (e.g., hue value range between 180-240 degrees) to simulate the color of the ocean; saturation, for example, set to medium-high saturation (e.g., 70%-90%) to make the blue appear vivid; light intensity, for example, set to medium intensity (e.g., 50%-70%) to create a comfortable feeling; refresh rate, for example, set to a low refresh rate (e.g., 0.5Hz-1Hz) to simulate the slow undulation of ocean waves; and light effect type, for example, set to "wave" light effect type to make the ambient light present a dynamic effect similar to the undulation of ocean waves. These found lighting effect control parameters will serve as the basis for generating ambient light adjustment commands, enabling the ambient light to present a highly adapted and immersive dynamic lighting effect according to the specific attributes of the navigation destination.

[0090] In one possible implementation, to further enhance the richness of light effect types and meet users' personalized needs, the aforementioned light effect types may also include special light effects, such as white wave embellishments, snow reflective flashes, and flowing light effects of traffic, which can be preset by users or selected based on the aforementioned first semantic tag matching.

[0091] It should be noted that, in practical applications, the semantic recognition of endpoint attribute information to obtain the first semantic label of the navigation endpoint can be performed using the navigation endpoint name or type with the first semantic label added as training data, and a preset navigation endpoint semantic recognition model trained using the above training data can be used for recognition. This preset navigation endpoint semantic recognition model can be of various types, including but not limited to: TextRecurrentNeural Network with Attention (TextRNN-Attention), TextConvolutionalNeural Network (TextCNN), Large Language Model (LLM), etc. This application does not impose further limitations or elaborate on the training process of the aforementioned preset navigation endpoint semantic recognition model.

[0092] In one possible implementation, the flowchart for obtaining the aforementioned light effect control parameters can be as follows: Figure 3 As shown, the following operation steps are included:

[0093] Step S301: Obtain the navigation destination. And trigger step S302.

[0094] Step S302: Use the POI knowledge base to identify the destination attribute information of the navigation destination and output the destination attribute information of the navigation destination. Then trigger step S303.

[0095] Step S303: Use a preset navigation endpoint semantic recognition model to perform semantic recognition on the endpoint attribute information to obtain the first semantic recognition label corresponding to the endpoint attribute information. Then trigger step S304.

[0096] Step S304: Based on the preset mapping relationship, find the light effect control parameters that have a mapping relationship with the first semantic recognition tag. And trigger step S305.

[0097] Step S305: The mapping relationship and the corresponding light effect control parameters of the chicken claw are summarized into structured data and stored in the cloud server or vehicle-side device.

[0098] One possible implementation also includes:

[0099] Obtain the weather information at the current sampling time, and perform semantic recognition on the weather information to obtain the second semantic label of the weather information;

[0100] Find the light effect adjustment parameters corresponding to the second semantic tag. The type of the light effect adjustment parameter corresponds one-to-one with the type in the light effect control parameter.

[0101] The light effect control parameters are adjusted using the corresponding light effect adjustment parameters of the same type to obtain the adjusted light effect control parameters for each type.

[0102] It should be noted that in practical applications, weather can affect user emotions. For example, rainy weather can cause feelings of depression, while sunny weather can cause feelings of joy. Therefore, continuously displaying cool colors when a user is feeling depressed will exacerbate that feeling, while using static lighting effects when a user is feeling joyful will be incompatible with that feeling. Thus, this application addresses this by configuring and searching for lighting effect adjustment parameters corresponding to the second semantic tag. The types of these adjustment parameters correspond one-to-one with the types in the lighting effect control parameters. By using the adjustment parameters of the same type to adjust the lighting effect control parameters, the adjusted lighting effect control parameters for each type are obtained. This allows for the analysis and quantification of external parameters affecting user experience, and the use of these quantified adjustment parameters to adjust the lighting effect control parameters. Ultimately, this improves the compatibility between the adjusted lighting effect control parameters and the user's personalized emotional needs, thereby enhancing the user experience.

[0103] It's important to clarify that, in practical applications, obtaining weather information at the current sampling time refers to acquiring environmental meteorological data related to the vehicle's current location and time. This can be achieved, for example, through real-time data collection by onboard environmental sensors (such as rain sensors, light sensors, and temperature sensors), or by obtaining data from external meteorological service platforms (such as internet meteorological APIs) via onboard communication modules, or even by connecting to mobile devices like smartphones to access data provided by their built-in meteorological applications. Semantic recognition of weather information to obtain secondary semantic tags refers to transforming raw, diverse weather data into structured, standardized classification tags. For example, the system can identify and map descriptions in sensor data or meteorological reports (such as "rainfall greater than X millimeters" or "temperature lower than Y degrees Celsius") into specific semantic tags, such as "sunny," "cloudy," "rainy," "snowy," and "smoggy," based on a pre-defined rule base or lookup table; alternatively, machine learning models can be used to analyze weather description text or sensor data to automatically generate these semantic tags. Finding the lighting effect adjustment parameters corresponding to the second semantic tag refers to obtaining the corresponding lighting effect adjustment values ​​from a preset parameter library or through an algorithm model based on the identified weather semantic tag. For example, when the second semantic tag is "rainy day," the system will search for a specific set of adjustment parameters associated with "rainy day." These parameters are designed to make the ambient lighting effects more suitable for the rainy weather atmosphere. The one-to-one correspondence between the types of lighting effect adjustment parameters and the types of lighting effect control parameters ensures that the parameters used for adjustment are consistent in type with the lighting effect control parameters to be adjusted. For example, if the lighting effect control parameters include hue value, saturation, and light intensity, then the lighting effect adjustment parameters should also include corresponding hue adjustment values, saturation adjustment values, and light intensity adjustment values ​​to ensure the effectiveness and compatibility of the adjustment. Adjusting the lighting effect control parameters using lighting effect adjustment parameters of the same type means applying weather-related adjustment parameters to the lighting effect control parameters determined based on the navigation destination attributes to achieve dynamic adjustment of the lighting effects. This can be done through methods such as weighted averaging, linear superposition, or nonlinear function mapping. For example, adding or subtracting the original hue value from the hue adjustment parameter, or multiplying or dividing the original luminous efficacy intensity from the luminous efficacy intensity adjustment parameter. The resulting set of luminous efficacy control parameters after adjustment, derived from weather information, will be used to generate ambient light control commands.

[0104] Furthermore, to avoid over-adjustment, the aforementioned light effect adjustment parameters can be positive or negative percentages. When adjusting the light effect control parameters using the same type of corresponding light effect adjustment parameters, the percentage corresponding to the corresponding type of light effect adjustment parameter can be added or removed from the light effect control parameters, thereby avoiding the risk of sudden changes in light effect caused by over-adjustment or incompatibility with the user's personalized emotional needs.

[0105] To facilitate understanding of the operational steps for adjusting the light effect control parameters using the same type of corresponding light effect adjustment parameters to obtain the adjusted light effect control parameters for each type, this article will specifically describe one possible implementation of this application:

[0106] Suppose a vehicle is navigating to a destination at the "seaside." Based on the destination's attribute information, the system identifies and determines a set of basic lighting control parameters, such as a blue hue, high saturation, moderate light intensity, and a refresh rate simulating waves. If the system detects that the current weather information is "light rain," it performs semantic recognition to obtain the second semantic label "rainy day." Next, the system finds the lighting adjustment parameters corresponding to "rainy day," such as a saturation adjustment parameter of -15% (reduced by 15%), a light intensity adjustment parameter of -20% (reduced by 20%), a hue adjustment parameter of +5% (fine-tuned towards a grayish-blue tone), and a refresh rate adjustment parameter of -10% (reduced refresh rate to simulate raindrops). Then, the system applies these adjustment parameters to the previously determined basic lighting control parameters; for example, reducing the saturation of the original blue tone by 15%, reducing the light intensity by 20%, fine-tuning the hue towards a grayish-blue tone, and reducing the refresh rate. Ultimately, a set of adjusted lighting control parameters was generated to control the ambient lighting output to produce a slightly muted, lower saturation, reduced intensity, and slower refresh rate blue wave effect, thus more accurately simulating the atmosphere of a rainy beach. Through this technical solution, the ambient lighting output can dynamically respond to current weather conditions, avoiding the problem of the lighting effect being out of sync with the actual environment. This makes the ambient lighting control more intelligent and user-friendly, significantly improving the user's driving experience and immersion under different weather conditions, and enhancing the adaptability and realism of the lighting effect.

[0107] In one possible implementation, determining the light effect control section to which the current vehicle's location belongs includes:

[0108] Obtain the first light-effect control segment to which the vehicle belonged at the previous sampling time;

[0109] Match the current vehicle location with the coordinate range corresponding to each light effect control segment to determine the second light effect control segment to which the vehicle belongs at the current sampling time;

[0110] If the second light effect control section is different from the first light effect control section, then the current vehicle position is determined to indicate that the vehicle has entered the second light effect control section from the first light effect control section.

[0111] It should be noted that the above method of matching the current vehicle position with the coordinate intervals corresponding to each light effect control segment to determine the second light effect control segment to which the vehicle belongs at the current sampling time carries the risk of failing to distinguish the actual distance. For example, in mountainous or hilly areas, spatial coordinates can only determine the distance between two points, but the actual distance traveled by the vehicle differs significantly from the distance determined by the spatial coordinates. Therefore, the coordinate interval can also be converted into a distance interval based on the distance control start point or navigation endpoint, and the distance between the current vehicle position and the corresponding point of the above-mentioned benchmark can be calculated and compared with the above-mentioned distance interval. For example, assuming the navigation endpoint is used as the benchmark, the coordinate interval corresponding to light effect control segment A is converted into a distance interval of [50kM, 40kM), the spatial coordinate interval corresponding to light effect control segment B is [40kM, 30kM), and the spatial coordinate interval corresponding to light effect control segment C is [30kM, 20kM). Further assuming that the distance between the current vehicle position and the navigation endpoint is 37kM, then the current vehicle indicates that the vehicle is in light effect control segment B.

[0112] It should be noted that, in practical applications, the above-described steps for determining the current vehicle's location within a specific lighting control segment are designed to accurately identify changes in the vehicle's location along the navigation path, thereby providing precise triggering timing for the dynamic adjustment of ambient lighting. First, the vehicle's real-time location is continuously tracked, and the segment information at the previous sampling time is recorded, i.e., the first lighting control segment. This historical information serves as a benchmark, providing continuity for subsequent segment change detection. Then, the currently acquired vehicle location information is compared and matched with the pre-defined geographical coordinate intervals of all lighting control segments to determine which segment the vehicle is actually located in at the current sampling time, i.e., the second lighting control segment. This precise matching ensures accurate real-time positioning of the vehicle on the navigation path. Next, by comparing the currently determined second lighting control segment with the previously recorded first lighting control segment, if they differ, it is determined that the vehicle has moved from the first lighting control segment into the second. This determination mechanism ensures that the subsequent ambient lighting effect adjustment logic is triggered only when the vehicle actually switches segments. In this way, the solution can accurately and timely detect road segment switching events of vehicles, providing reliable input for subsequent steps such as finding light effect control parameters based on navigation destination attribute information, calculating light effect pre-simulation intensity coefficients, and generating ambient light adjustment commands. This avoids problems such as inaccurate light effect adjustment or frequent light effect jumps caused by inaccurate location recognition or change detection delays, and significantly improves the spatiotemporal correlation between ambient light and navigation journey and user experience.

[0113] One possible implementation also includes:

[0114] If the second lighting effect control segment is the same as the first lighting effect control segment, then the current vehicle position is determined to indicate that the vehicle is still in the first lighting effect control segment, and the ambient lights are controlled to continuously output historical ambient light control commands in the first lighting effect control segment. The historical ambient light control commands correspond to the first lighting effect control segment.

[0115] It should be noted that, in practical application scenarios, this application, by configuring the second light effect control segment to be the same as the first light effect control segment, determines that the current vehicle position indicates that the vehicle is still in the first light effect control segment, and controls the ambient light to continuously output historical ambient light adjustment commands in the first light effect control segment. The historical ambient light adjustment commands correspond to the first light effect control segment, thereby avoiding frequent adjustments to the light effect in the same light effect control segment, ensuring the continuity and smoothness of the light effect in the same light effect control segment, and improving the user experience.

[0116] In one possible implementation, to avoid redundant use of computing and storage resources on the vehicle-side equipment, when the second light effect control segment is the same as the first light effect control segment, it can be determined by comparing the unique identifier or corresponding coordinate range of the light effect control segment identified at the current sampling time (i.e., the second light effect control segment) with the light effect control segment recorded at the previous sampling time (i.e., the first light effect control segment). If they are identical, the condition is met. For example, a state variable representing the current road segment where the vehicle is located can be maintained. After each road segment identification, the newly identified road segment is compared with this state variable; if they are the same, the condition is met.

[0117] In one possible implementation, determining the current vehicle position, indicating that the vehicle is still within the first light effect control segment, can be achieved by, when the aforementioned conditions are met, clarifying that the vehicle's current state has not changed segment, but rather continues to remain within the original light effect control segment. This can be achieved by setting an internal status flag (e.g., "segment not changed") and setting it to true, or by directly assigning the segment information identified at the current sampling time to a variable representing the "current vehicle's segment," ensuring its value remains consistent with the "first light effect control segment" at the previous sampling time.

[0118] In one possible implementation, the aforementioned control of ambient lighting by continuously outputting historical ambient lighting control commands in the first lighting effect control segment can ensure that the ambient lighting effect remains stable and continuous when the vehicle does not switch segments. For example, the most recently successfully generated ambient lighting control command for each lighting effect control segment can be stored as a "historical ambient lighting control command." When the vehicle is still in that segment, the stored command can be directly resent or maintained. Alternatively, after each successful generation and transmission of an ambient lighting control command, it can be cached. When the vehicle is detected to still be in the same segment, the command can be read from the cache and reapplied.

[0119] In one possible implementation, the correspondence between the aforementioned historical ambient lighting control commands and the first lighting effect control segment ensures that the continuously output ambient lighting control commands match the lighting effect control segment the vehicle is currently in. For example, a mapping table can be established to associate and store the unique identifier of each lighting effect control segment with the corresponding historical ambient lighting control commands. Alternatively, when generating ambient lighting control commands, the command and the identifier of the current segment can be packaged and stored together for subsequent retrieval of the corresponding command based on the segment identifier.

[0120] In one possible implementation, the light effect prediction intensity coefficient of the second light effect control section is calculated based on the remaining travel information, including:

[0121] The remaining travel information is input into a preset logarithmic nonlinear function so that the preset logarithmic nonlinear function can calculate the light effect pre-simulation intensity coefficient of the second light effect control section based on the remaining travel information, the preset attenuation constant and the preset pre-simulation path length.

[0122] It should be noted that, in practical applications, the aforementioned preset logarithmic linear function is a mathematical function used to calculate the light effect preview intensity coefficient while ensuring the smoothness of the light effect transition and changes. Its "logarithmic nonlinearity" characteristic means that the change in the light effect preview intensity coefficient is not a simple linear relationship with the remaining travel information, but rather changes slowly when the remaining travel information is large and accelerates when the remaining travel information is small, thus simulating a gradually enhanced perceptual effect. The formula for this preset logarithmic function can be: ,in, It is the light effect preview intensity coefficient. 0 represents no perception, 1 represents full perception, D is the remaining travel information, which can be the remaining mileage or remaining travel time between the current vehicle position and the navigation destination. Preferably, since the remaining travel time is affected by vehicle speed, the remaining mileage can be selected as the preferred calculation parameter. The above-mentioned D0 is a preset attenuation constant used to control the sensitivity to changes in light intensity, and can be set to a shorter distance such as 1km, 3km or 5km. max A preset pre-navigation path length is used to control the timing of light effect changes, preventing the light effect intensity from saturating before reaching the navigation endpoint due to an excessively long navigation path, thus affecting the user experience. The formula for the aforementioned preset logarithmic function can also be: ,in, Here, A is the light effect preview intensity coefficient, B is the preset attenuation constant, and L is the preset preview path length. remaining This is the remaining itinerary information.

[0123] It should be noted that, in practical application scenarios, this application configures the aforementioned preset logarithmic nonlinear function to achieve a slow increase in the light effect pre-show intensity coefficient during the initial stage of the pre-show (e.g., during the process of the remaining driving range from 30 km to 15 km), a rapid increase in the light effect pre-show intensity coefficient during the middle stage of the pre-show (e.g., during the process of the remaining driving range from 15 km to 3 km), and a light effect pre-show intensity coefficient approaching 1 during the later stage of the pre-show (e.g., during the process of the remaining driving range from 3 km to 1 km). This achieves a smooth and gradual enhancement of the light effect, avoids abrupt changes in the light effect, and ensures a progressive enhancement of the light effect display effect, thereby strengthening the user experience.

[0124] In one possible implementation, based on the light effect pre-simulation intensity coefficient and the light effect control parameters, an ambient light control command corresponding to the second light effect control section is generated and executed, including:

[0125] Using the light effect pre-simulation intensity coefficient as the modulation factor, the light effect control parameters are modulated using a preset progressive modulation algorithm to obtain the actual light effect control parameters corresponding to each light effect control segment in the second light effect control segment. The actual light effect control parameters are then encapsulated into the current ambient light control command corresponding to the second light effect control segment, and the current ambient light control command is executed.

[0126] It should be noted that, in practical applications, the aforementioned modulation factor refers to a variable used to change or influence the characteristics of the target parameter during signal or parameter adjustment. Here, the light effect prediction intensity coefficient, as a modulation factor, dynamically adjusts the degree or rate of change of the light effect control parameters based on the remaining travel information of the vehicle and the navigation destination. It can be directly applied as a multiplier to the light effect control parameters, affecting the final performance of the light effect in a linear or non-linear manner; alternatively, it can also be used as a weighting coefficient to distribute or balance among multiple light effect parameters, thereby achieving more precise light effect adjustment.

[0127] It should be noted that in practical applications, the aforementioned pre-defined progressive modulation algorithm is a calculation method designed to achieve smooth and continuous parameter changes. Its core principle is to avoid instantaneous jumps in parameters, instead using a series of small, continuous adjustments to gradually transition the parameters from one state to another. This algorithm can take various forms, including but not limited to: Linear Interpolation (LERP) algorithm, Exponential Decay algorithm, and S-Curve Progressive Modulation algorithm. Among these, the aforementioned linear interpolation based on time or distance ensures uniform changes in luminous efficacy parameters across the entire road segment; exponential decay or S-curve functions can also be used to accelerate or decelerate changes in luminous efficacy at specific stages, simulating a more natural visual effect.

[0128] It should be noted that in practical applications, the aforementioned actual light effect control parameters refer to the final parameter values ​​used to directly control the ambient light output after processing by a progressive modulation algorithm. These parameters form the basis for the actual light effect presented by the ambient light in the current light effect control section. They can include at least one of hue value, saturation, luminous intensity (brightness), refresh rate, and light effect type. The combination of these parameters determines the final visual effect of the ambient light. Encapsulation refers to the process of combining multiple related data or parameters into a single, structured data unit. Ambient light control commands are instructions used to tell the ambient light controller how to output light effects. Through encapsulation, the modulated hue, saturation, brightness, and other actual light effect control parameters can be integrated into a complete instruction package, facilitating parsing and execution by the ambient light controller. This encapsulation can be a data packet in a specific format, sent to the ambient light controller through a communication interface; or it can be a call to a preset application programming interface (API), passing the parameters as input to the control module.

[0129] In one possible implementation, the specific implementation method for generating and executing the ambient light control command corresponding to the second light effect control segment based on the light effect pre-simulation intensity coefficient and the light effect control parameters can be:

[0130] When a vehicle enters the second lighting control section from the first, the system first determines the target lighting control parameters to be blue (e.g., hue value 240 degrees, saturation 80%, luminous intensity 70%) based on the navigation destination attribute information (e.g., the destination is "seaside"). Simultaneously, based on the current vehicle position and the remaining distance to the navigation destination (e.g., 5 kilometers remaining), the system calculates the lighting effect pre-simulation intensity coefficient (e.g., 0.6) for the current second lighting control section. To achieve a smooth transition in lighting effect, the system uses this pre-simulation intensity coefficient of 0.6 as a modulation factor. Next, a preset progressive modulation algorithm, such as a distance-based linear interpolation algorithm, is used to modulate the target lighting control parameters. Assuming the ambient lighting effect of the first lighting control section is green (hue value 120 degrees), the progressive modulation algorithm will calculate the current actual hue value, saturation, and luminous intensity for the transition from green to blue based on the pre-simulation intensity coefficient of 0.6. For example, the algorithm might calculate the current actual hue value as 180 degrees (between 120 and 240 degrees), saturation as 60%, and luminous efficacy as 50%. These calculated actual hue values, saturation, and luminous efficacy values ​​are the actual control parameters for each lighting effect in the second lighting effect control section. These actual control parameters are then encapsulated into a data packet containing information such as hue, saturation, and luminous efficacy, forming the current ambient light control command. This command is then sent to the ambient light controller, which, based on the command, continuously outputs a smoothly transitioning lighting effect in the second lighting effect control section, for example, gradually changing from green to cyan, and then to blue.

[0131] It should be noted that, as can be seen from the above specific implementation methods, this application solves the problem of abrupt and jarring changes in light effect in traditional ambient lighting control. By introducing a light effect pre-simulation intensity coefficient as a modulation factor and using a preset progressive modulation algorithm to modulate the light effect control parameters, a smooth and continuous transition of ambient lighting effects is achieved. This progressive change avoids instantaneous jumps in light effect, making the spatiotemporal correlation between light effect and navigation route stronger. When the vehicle moves from one light effect control segment to another, the user can feel a natural and smooth change in light effect, thus significantly improving the user experience and making the ambient lighting's interactive function more user-friendly and immersive. At the same time, encapsulating the modulated light effect actual control parameters into control commands also ensures that the ambient lighting controller can execute light effect changes efficiently and accurately, guaranteeing the stability and reliability of the system operation.

[0132] In one possible implementation, the ambient light control method provided in the first aspect of this application further includes:

[0133] If a change in navigation path is detected, obtain the target light effect control parameters corresponding to the attribute information of the changed navigation destination;

[0134] Based on the target light effect control parameters and the light effect control parameters before the change, calculate the smooth transition parameters, which include at least one of the transition duration and the transition curve.

[0135] Based on the transition parameters, the ambient light is controlled to smoothly transition from the current lighting effect state to the lighting effect state corresponding to the target lighting effect control parameters.

[0136] It should be noted that in real-world applications, navigation routes may change due to traffic congestion or altered user travel plans, such as changing the navigation destination or deviating from the original route. If the lighting effect abruptly changes from the current state to the new destination or route, the user experience will be negatively impacted (e.g., a sudden shift from a smooth blue light effect to a rapidly fluctuating red light effect). Therefore, this application configures the ambient light to obtain target lighting effect control parameters corresponding to the attribute information of the changed destination when a navigation route change is detected. Based on these parameters, a smooth transition parameter is calculated. This parameter then controls the ambient light to smoothly transition from the current state to the state corresponding to the target lighting effect control parameter, thus avoiding the risk of abrupt changes negatively impacting the user experience.

[0137] It should be noted that in practical applications, there are multiple ways to calculate the smooth transition parameters based on the target light effect control parameters and the light effect control parameters before the change. Two examples are provided here:

[0138] For ease of description, the light effect control parameters used in the following examples include: hue value, saturation, and light effect intensity.

[0139] Example 1: When the smooth transition parameter is the transition duration, calculate the difference between the same type of parameters in the target light effect control parameter and the light effect control parameter before the change; then, find the preset change rate of the light effect control parameter of the type corresponding to the difference, where the preset change rate is based on the maximum change rate that the human eye feels comfortable with for that type of parameter; finally, based on the quotient of the difference of the same type and the preset change rate, determine the transition duration corresponding to each type of parameter, and determine the maximum value of each transition duration as the aforementioned transition duration.

[0140] In Example 2, when the smooth transition parameter is a transition curve, the difference between the same type of parameters in the target light effect control parameter and the light effect control parameter before the change is calculated. Then, the target transition curve is determined based on the maximum value among the differences. For example, when the maximum value is not greater than a preset small change threshold (based on human eye comfort calibration), a preset linear transition curve is selected to ensure the timeliness of light effect changes. When the maximum value is greater than the preset small change threshold, a preset non-linear transition curve (such as a logistic curve) is selected to achieve a natural effect of slow start, fast transition, and slow finish, avoiding the abruptness of linear transitions during large changes. Based on the determined target transition curve, interpolation calculations are performed in real time to obtain the actual light effect control parameters at each moment during the transition process, and the ambient light is controlled to operate based on the real-time calculated parameters.

[0141] In one possible implementation, if Example 1 and Example 2 are executed simultaneously, the start and end times of the target transition curve are controlled as the transition time, and the curve steepness is adjusted adaptively, with the transition time as a constraint.

[0142] In one possible implementation, the characteristic is that generating and executing the ambient light control command corresponding to the second light effect control section includes:

[0143] Obtain the current and target light effect control parameters of the ambient light. The target light effect control parameters are determined based on the light effect pre-simulation intensity coefficient and the light effect control parameters.

[0144] Calculate the parameter variation between the current luminous efficacy control parameters and the target luminous efficacy control parameters;

[0145] The transition time is calculated based on the parameter change magnitude and the preset maximum parameter change rate. The transition time is positively correlated with the parameter change magnitude.

[0146] Based on the transition time, the ambient lighting is smoothly transitioned from the current lighting effect control parameters to the target lighting effect control parameters.

[0147] It should be noted that, in practical application scenarios, in order to avoid excessive changes in light effect during the switching between adjacent light effect control sections and reduce the user experience, this application calculates the parameter change range between the current light effect control parameters and the target light effect control parameters by configuring the calculation, and calculates the transition time based on the parameter change range and the preset maximum parameter change rate, thereby realizing a smooth transition of the ambient light control from the current light effect control parameters to the target light effect control parameters and avoiding excessive changes in light effect.

[0148] It should be noted that in actual application scenarios, the calculation method of the above transition duration is the same as the calculation method when the smooth transition parameter is the transition duration. The only difference is that the specific value of the light effect control parameter is the light effect control parameter of the adjacent light effect control road segment. This application will not elaborate on this further.

[0149] To facilitate understanding of the ambient light control method of the first aspect or any implementation thereof, a possible implementation of this application is described hereby:

[0150] like Figure 4 The diagram shows a flowchart of an ambient light control method. The specific operation steps are as follows:

[0151] Step S401: Obtain navigation information and weather information at the current sampling time. Then trigger step S402.

[0152] Step S402: Obtain the first light effect control segment to which the vehicle belonged at the previous sampling time. And trigger step S403.

[0153] Step S403: Match the current vehicle position in the navigation information with the coordinate intervals corresponding to each light effect control segment to determine the second light effect control segment to which the vehicle belongs at the current sampling time. Then trigger step S404.

[0154] Step S404: Determine whether the first light effect control segment and the second light effect control segment are the same. If yes, trigger step S405; otherwise, trigger step S406.

[0155] Step S405: Determine the current vehicle position, indicating that the vehicle is still in the first light effect control section. Then trigger step S407.

[0156] Step S406: Determine the current vehicle position, indicating that the vehicle has moved from the first light effect control section to the second light effect control section. Then, trigger step S408.

[0157] Step S407: Control the ambient light to continuously output historical ambient light control commands in the first light effect control section. The historical ambient light control commands correspond to the first light effect control section.

[0158] Step S408: Semantic recognition is performed on the destination attribute information of the navigation destination in the navigation information to obtain the first semantic label of the navigation destination. The corresponding types of light effect control parameters are then searched for. Semantic recognition is performed on the weather information to obtain the second semantic label of the weather information. The corresponding light effect adjustment parameters are then searched for. The types of the light effect adjustment parameters correspond one-to-one with the types in the light effect control parameters. Step S409 is then triggered.

[0159] Step S409: Adjust the light effect control parameters using the corresponding light effect adjustment parameters of the same type to obtain the adjusted light effect control parameters for each type. Then, step S410 is triggered.

[0160] Step S410: Input the remaining travel information into a preset logarithmic nonlinear function so that the preset logarithmic nonlinear function calculates the light effect prediction intensity coefficient of the second light effect control section based on the remaining travel information, the preset attenuation constant, and the preset prediction path length. Then trigger step S411.

[0161] Step S411: Using the light effect pre-simulation intensity coefficient as the modulation factor, the light effect control parameters are modulated using a preset progressive modulation algorithm to obtain the actual light effect control parameters corresponding to each light effect control segment in the second light effect control segment, and each actual light effect control parameter is encapsulated into the current ambient light control command corresponding to the second light effect control segment. Step S412 is then triggered.

[0162] Step S412: Control the ambient light to continuously output the light effect corresponding to the current ambient light control command in the second light effect control section.

[0163] It should be noted that, in practical application scenarios, steps S401 and S402 are possible implementations of step S101 of the first aspect. Steps S403 to S406 are possible implementations of step S102 of the first aspect. Steps S408 and S409 are possible implementations of step S103 of the first aspect. Step S410 is a possible implementation of step S104 of the first aspect. Steps S411 and S412 are possible implementations of step S105 of the first aspect.

[0164] A second aspect of this application provides a vehicle, including: an ambient light controller, which is used to perform an ambient light control method as provided in the first aspect or any implementation thereof.

[0165] A third aspect of this application provides an ambient light controller, including at least one processor and a memory connected to the processor, wherein:

[0166] Memory is used to store computer programs;

[0167] The processor is used to execute a computer program to enable the ambient light controller to implement the ambient light control method of the first aspect or any implementation thereof.

[0168] In one possible implementation, such as Figure 5The diagram illustrates a suitable structural schematic for implementing the ambient lighting controller in the embodiments of this application. The electronic devices in the embodiments of this application may include, but are not limited to, ECU (Electronic Control Unit), VCU (Vehicle Control Unit), MCU (Micro Controller Unit), etc. Figure 5 The ambient light controller shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0169] like Figure 5 As shown, the ambient light controller may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. When the ambient light controller is powered on, the RAM 503 also stores various programs and data required for the operation of the ambient light controller. The processing device 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0170] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, memory cards, hard drives, etc.; and communication devices 509. Communication device 509 allows the ambient light controller to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An ambient lighting controller with various devices is shown; however, it should be understood that implementation or having all of the devices shown is not required. More or fewer devices may be implemented alternatively.

[0171] The fourth aspect of this application provides a computer storage medium carrying one or more computer programs. When the one or more computer programs are executed by an ambient light controller, the ambient light controller is able to implement the ambient light control method of the first aspect or any implementation thereof.

[0172] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and 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 modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0173] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0174] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0175] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method for controlling ambient lighting, characterized in that, include: Obtain navigation information, which includes: destination attribute information of the navigation destination, current vehicle location, and remaining trip information; The navigation path is divided into multiple consecutive light effect control segments, and the light effect control segment to which the current vehicle position belongs is determined. When a vehicle enters the second light effect control section from the first light effect control section, the light effect control parameters that match the destination attribute information are searched. The light effect pre-simulation intensity coefficient of the second light effect control section is calculated based on the remaining travel information. The light effect pre-simulation intensity coefficient increases monotonically as the remaining travel information decreases. The light effect pre-simulation intensity coefficient of the second light effect control section is greater than that of the first light effect control section. Based on the light effect pre-simulation intensity coefficient and the light effect control parameters, an ambient light control command corresponding to the second light effect control section is generated and executed.

2. The method for controlling ambient lighting according to claim 1, characterized in that, Determining the light effect control section to which the current vehicle location belongs includes: Perform semantic recognition on the endpoint attribute information to obtain the first semantic label of the navigation endpoint; Find the light effect control parameters of each type corresponding to the first semantic tag. The types include at least one of hue value, saturation, light effect intensity, refresh rate, and light effect type.

3. The method for controlling ambient lighting according to claim 2, characterized in that, Also includes: Obtain the weather information at the current sampling time, and perform semantic recognition on the weather information to obtain the second semantic label of the weather information; Find each light effect adjustment parameter corresponding to the second semantic tag, and the type of the light effect adjustment parameter corresponds one-to-one with the type in the light effect control parameter; The light effect control parameters are adjusted using the light effect adjustment parameters corresponding to the same type to obtain the adjusted light effect control parameters for each type.

4. The method for controlling ambient lighting according to claim 1, characterized in that, Determining the light effect control section to which the current vehicle location belongs includes: Obtain the first light effect control road segment to which the vehicle belongs at the previous sampling time; The current vehicle position is matched with the coordinate intervals corresponding to each of the light effect control road segments to determine the second light effect control road segment to which the vehicle belongs at the current sampling time; If the second light effect control section is different from the first light effect control section, then the current vehicle position is determined to indicate that the vehicle has entered the second light effect control section from the first light effect control section.

5. The method for controlling ambient lighting according to claim 4, characterized in that, Also includes: If the second light effect control segment is the same as the first light effect control segment, then the current vehicle position indicates that the vehicle is still in the first light effect control segment, and the ambient light is controlled to continuously output historical ambient light control commands in the first light effect control segment, the historical ambient light control commands corresponding to the first light effect control segment.

6. The method for controlling ambient lighting according to claim 1, characterized in that, The calculation of the light effect pre-simulation intensity coefficient of the second light effect control section based on the remaining travel information includes: The remaining travel information is input into a preset logarithmic nonlinear function, so that the preset logarithmic nonlinear function calculates the light effect pre-simulation intensity coefficient of the second light effect control section based on the remaining travel information, a preset attenuation constant, and a preset pre-simulation path length.

7. The method for controlling ambient lighting according to any one of claims 1 to 3, characterized in that, The step of generating and executing ambient light control commands corresponding to the second light effect control section based on the light effect pre-simulation intensity coefficient and the light effect control parameters includes: Using the light effect pre-simulation intensity coefficient as a modulation factor, the light effect control parameters are modulated using a preset progressive modulation algorithm to obtain the actual light effect control parameters corresponding to the second light effect control segment. The actual light effect control parameters are then encapsulated into the current ambient light control command corresponding to the second light effect control segment, and the current ambient light control command is executed.

8. The method for controlling ambient lighting according to claim 1, characterized in that, The method for controlling the ambient light also includes: If a change in navigation path is detected, obtain the target light effect control parameters corresponding to the attribute information of the changed navigation destination; Based on the target light effect control parameters and the light effect control parameters before the change, a smooth transition parameter is calculated, wherein the smooth transition parameter includes at least one of transition duration and transition curve; Based on the transition parameters, the ambient light is controlled to smoothly transition from the current lighting effect state to the lighting effect state corresponding to the target lighting effect control parameters.

9. The method for controlling ambient lighting according to claim 1, characterized in that, The generation and execution of the ambient light control command corresponding to the second light effect control section includes: Obtain the current light effect control parameters and target light effect control parameters of the ambient light, wherein the target light effect control parameters are determined based on the light effect pre-simulation intensity coefficient and the light effect control parameters; Calculate the parameter variation range between the current light effect control parameter and the target light effect control parameter; Based on the parameter change amplitude and the preset maximum parameter change rate, the transition duration is calculated, and the transition duration is positively correlated with the parameter change amplitude. According to the transition duration, the ambient light is controlled to smoothly transition from the current light effect control parameter to the target light effect control parameter.

10. A vehicle, characterized in that, include: An ambient light controller, the ambient light controller being used to perform the ambient light control method as described in claims 1 to 9.

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