A roof lighting system based on adaptive adjustment of driving lighting needs

Abstract

This invention discloses a vehicle roof lighting system that adaptively adjusts based on driving lighting needs, belonging to the field of vehicle lighting technology. It includes a road condition recognition module, a vehicle status acquisition module, a central control module, a lighting execution module, an anti-glare coordination module, and a human-machine interaction module. The road condition recognition module acquires geological texture features, geometric contour information, and ambient light intensity within a preset range in front of the vehicle, generating a multi-dimensional semantic map. The vehicle status acquisition module monitors the vehicle's dynamic parameters and dynamic pose in real time, performs noise reduction preprocessing on the raw sensor data, and outputs vehicle driving posture parameters. Through a multi-sensor layout, Kalman filtering algorithm, and multi-degree-of-freedom mechanical actuators, it meets the urgent need for high-quality auxiliary lighting for off-road vehicles in complex and dynamic driving environments, significantly improving driver visibility safety. Simultaneously, through intelligent anti-glare coordination logic, it enhances road traffic safety.

Description

Technical Field

[0001] This invention relates to the field of vehicle lighting technology, and more particularly to a roof lighting system that adaptively adjusts based on driving lighting needs. Background Technology

[0002] With the increasing popularity of off-road driving, driving safety in outdoor off-road scenarios (such as deserts, mountain roads, mud, and forest trails) has become a core requirement. As a crucial auxiliary device for off-road driving, the lighting effect of in-vehicle outdoor lighting systems directly impacts the driver's field of vision and driving safety. Currently, most in-vehicle outdoor lighting devices on the market (such as roof-mounted spotlights and front bumper spotlights) use manual adjustment. Drivers must adjust the brightness, angle, and range of the light using manual switches and knobs based on their experience, lacking adaptive adjustment capabilities based on driving lighting needs.

[0003] Existing technologies for vehicle-mounted outdoor lighting still have significant limitations: First, manual adjustment requires frequent driver intervention during off-road driving, which can easily distract the driver in bumpy or complex road conditions, increasing driving safety risks. Second, different off-road environments have significantly different requirements for lighting parameters. For example, desert areas have strong reflected light interference, mountain roads have large undulations, and forests are dimly lit with numerous obstacles. Existing systems lack the ability to recognize specific road condition characteristics, resulting in poor matching of lighting parameters and potential problems such as blind spots, glare, or insufficient illuminance. Third, current lighting systems generally lack active sensing mechanisms for oncoming vehicles or pedestrians, making it difficult to adjust the beam intensity or direction in time when oncoming vehicles or pedestrians approach, potentially causing visual interference to the other party. Finally, most lighting devices operate independently and do not effectively link with the vehicle's driving status (such as speed, steering angle, and vehicle posture), limiting the dynamic adaptability and scene coverage of the lighting strategy. These factors collectively restrict the intelligence level and overall safety performance of vehicle-mounted outdoor lighting systems in complex off-road environments. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a roof lighting system that adaptively adjusts based on driving lighting needs. Through a multi-sensor layout, Kalman filtering algorithm, and multi-degree-of-freedom mechanical actuators, it meets the urgent need for high-quality auxiliary lighting for off-road vehicles in complex and dynamic driving environments, significantly improving driver visibility and safety. At the same time, through intelligent anti-glare collaborative logic, it enhances road traffic safety.

[0005] This invention provides a vehicle roof lighting system that adaptively adjusts based on driving lighting needs. The system includes a road condition recognition module, a vehicle status acquisition module, a central control module, a lighting execution module, an anti-glare coordination module, and a human-machine interaction module. The road condition recognition module acquires geological texture features, geometric contour information, and ambient light intensity within a preset range in front of the vehicle through a high-definition vehicle camera, millimeter-wave radar, and light sensor, and generates a multi-dimensional semantic map. The vehicle status acquisition module is used to monitor the vehicle's dynamic parameters and dynamic pose in real time, and to perform noise reduction preprocessing on the raw sensor data to output smooth vehicle driving posture parameters. The central control module has a built-in road condition lighting matching database, which is used to retrieve and generate target lighting adjustment instructions based on the multidimensional semantic map and vehicle driving posture parameters. The lighting execution module includes a roof-mounted LED spotlight and an adjustment drive mechanism, which is used to dynamically adjust the light field distribution, pointing angle and beam shape of the roof-mounted LED spotlight according to the target lighting adjustment command. The anti-glare coordination module is used to monitor the biothermal characteristics or reflective strip characteristics of oncoming vehicles and pedestrians, and after identification, it sends an interruption request to the central control module to execute the anti-glare light reduction strategy. The human-computer interaction module renders and displays the system's operating status in real time through a graphical interface, provides a control mode switching interface, and has a built-in fault self-diagnosis program.

[0006] Preferably, the road condition recognition module includes: A high-definition vehicle camera is installed on the upper inner side of the vehicle's windshield to collect raw image data of the area in front of the vehicle. The millimeter-wave radar, located at the geometric center of the front bumper, integrates a microstrip patch antenna array to assist in identifying the distance and outline of obstacles in road conditions, compensating for the recognition deficiencies of high-definition vehicle cameras in dim or dusty environments. The light sensor, located on the roof of the vehicle, is an integrated digital ambient light sensor with a surface covered by a high-transmittance UV-resistant filter, used to collect ambient light intensity. During the road condition feature extraction process, the central control module receives the raw image data from the high-definition vehicle camera and first performs noise reduction, distortion correction, and white balance processing. Then, it calls the convolutional neural network model to perform semantic segmentation and feature classification. Next, it spatially maps and fuses the geometric contour information of the millimeter-wave radar to generate a multi-dimensional semantic map.

[0007] Preferably, the vehicle status acquisition module includes a vehicle speed sensor, a steering angle sensor, a body roll sensor, and a gear position sensor; wherein, the vehicle speed sensor acquires the real-time vehicle speed through pulse signals from the wheel speed sensors of the four wheels; the steering angle sensor monitors the angular displacement of the steering wheel in real time through magnetic encoder technology and acquires the real-time steering angle of the vehicle's steering wheel; the body roll sensor calculates the vehicle's pitch angle around the lateral axis and roll angle around the longitudinal axis in real time through an inertial measurement unit, used to identify the vehicle's climbing, descending, and roll states; and the gear position sensor identifies the current power output state in real time through CAN messages from the transmission control unit.

[0008] Preferably, the vehicle state acquisition module uses a Kalman filter algorithm to eliminate mechanical noise interference during the data preprocessing stage, and its state update equation is: ; In the formula, for The optimal state estimate at time t. For Kalman gain, These are the actual measured values ​​from the sensor.

[0009] Preferably, the lighting execution module includes: The roof-mounted LED spotlights use multi-chip packaging technology, and the LED substrate uses aluminum nitride ceramic material with high thermal conductivity and is closely attached to the heat sink fins. The adjustment drive mechanism includes a stepper motor and a transmission gear set; wherein, the stepper motor supports 1 / 256 micro-step drive, which enables the roof LED spotlight to rotate on both horizontal and vertical axes. The lighting execution module also includes an electrically adjustable lens assembly; the electrically adjustable lens assembly is located inside the roof LED spotlight, and by changing the relative position between the lenses, it can switch between narrow beam, medium beam and wide beam.

[0010] Preferably, the central control module executes differentiated lighting control logic based on the road condition recognition result as follows: In desert conditions, if the ambient light intensity is greater than the preset background threshold, the central control module actively reduces the duty cycle of the pulse width modulation to adjust the brightness to the preset medium brightness mode, while controlling the motorized zoom lens group to switch to wide beam mode; if the ambient light intensity is less than the preset background threshold, the brightness is adjusted to the preset high brightness mode, while controlling the motorized zoom lens group to switch to medium beam mode. In mountainous road conditions, the system reads the pitch angle data from the vehicle body tilt sensor in real time. When the system detects that the vehicle is climbing, it calculates the compensation angle and controls the stepper motor to drive the roof LED spotlights to shift upward. The shift amount is directly proportional to the slope angle, ensuring that the beam center is always parallel to the slope or slightly higher than the far end of the road surface. When the system detects that the vehicle is going downhill, the light axis automatically shifts downward to eliminate the blind spot in front of the vehicle. In forest or continuous winding road conditions, the system receives data from the steering angle sensor in real time. When the steering wheel angular velocity exceeds a preset threshold, the system drives the roof LED spotlights to deflect synchronously to the steering side, achieving dynamic tracking of the optical axis to the tangent of the driving path. In addition, based on the density of trees on both sides detected by millimeter-wave radar, if it is determined that the vehicle is currently driving on a narrow path, the system switches the electric zoom lens group to narrow beam mode.

[0011] Preferably, the anti-glare coordination module includes an infrared sensor and an image processing unit; The infrared sensor uses a narrow-band infrared filter to capture specific band infrared features carried by the high beams or low beams of oncoming vehicles, as well as infrared signals from pedestrians; the image processing unit uses a specific target detection algorithm to scan the images from the high-definition vehicle camera in real time. When the biothermal features or reflective strip features of oncoming vehicles or pedestrians are detected within a preset range ahead, a high-priority interrupt request is immediately sent to the central control module, and an anti-glare reduction strategy is executed. The anti-glare and light reduction strategy is as follows: First, the PWM duty cycle of the driver's side spotlight is rapidly reduced to below 30%, and at the same time, the stepper motor is controlled to deflect the light axis to the outside of the vehicle, so that the strong light is avoided from the line of sight of oncoming drivers; when the oncoming target disappears, the original lighting parameters are restored to ensure the smoothness of the visual transition.

[0012] Compared with the prior art, the present invention has significant technical advantages: 1. By integrating multimodal road condition perception with vehicle dynamic status analysis, the lighting execution module is driven to achieve full-dimensional adaptive linkage adjustment of lighting parameters. This eliminates the traditional manual adjustment mode, avoids driver distraction in complex road conditions, and accurately matches the lighting needs of various off-road scenarios. It effectively suppresses glare, eliminates blind spots, and significantly improves the effective illuminance coverage of the road surface and driving visibility safety.

[0013] 2. The anti-glare coordination module identifies oncoming vehicles and pedestrians in real time, and links with the central control module to execute an anti-glare strategy of active beam avoidance and smooth recovery, effectively avoiding strong light interference with oncoming vehicles or pedestrians, while ensuring the visual comfort of the driver.

[0014] 3. The system's automatic calibration mechanism ensures long-term high precision in lighting adjustment. At the same time, the human-machine interaction module enables flexible switching between automatic and manual modes and personalized lighting parameter presets. While ensuring adaptive lighting capabilities across all scenarios, it also accommodates the personalized needs of drivers, improving the system's vehicle compatibility and operational flexibility. Attached Figure Description

[0015] Figure 1 This is a system block diagram of the roof lighting system provided by the present invention.

[0016] Figure 2 This is a flowchart illustrating the road condition recognition and control logic in this invention.

[0017] Figure 3 This is a schematic diagram illustrating the principle of beam angle adjustment under uphill conditions in this invention. Detailed Implementation

[0018] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention. It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0019] Example 1 Please see Figures 1-3 This invention provides a vehicle roof lighting system that adaptively adjusts based on driving lighting needs. Its overall architecture is logically rigorous and highly integrated, aiming to provide intelligent light field distribution for vehicles operating in off-road and complex conditions. The system includes a road condition recognition module, a vehicle status acquisition module, a central control module, a lighting execution module, an anti-glare coordination module, and a human-machine interaction module. Each module communicates bidirectionally with the central control module via a Controller Area Network (CAN) bus. In this embodiment, the CAN bus uses the high-speed CAN protocol with a communication rate set to 500kbps, and the transmission period for critical control messages is 10ms to ensure the real-time performance and synchronization of signal transmission within the system.

[0020] The road condition recognition module is used for multimodal digital reconstruction of the external physical environment; it includes a high-definition vehicle-mounted camera, a millimeter-wave radar, and a light sensor; wherein, the high-definition vehicle-mounted camera is installed on the upper inner side of the vehicle's windshield, with a horizontal field of view set to 120° and a vertical field of view set to 60°, for acquiring raw image data within a range of 3m to 150m ahead; the millimeter-wave radar is installed at the geometric center of the front bumper, employs 24GHz frequency modulated continuous wave (FMCW) technology, and integrates a microstrip patch antenna array internally; the detection range of this radar is set to... The distance is set to 0.5m to 50m, with a distance resolution better than 0.1m and an azimuth measurement range of ±60°. It is used to assist in identifying the distance and outline of obstacles (such as stones, trees, and potholes) in road conditions, and to make up for the recognition defects of high-definition vehicle cameras in dim and dusty environments. The light sensor is set on the roof of the vehicle and adopts an integrated digital ambient light sensor. Its surface is covered with a high-transmittance UV-resistant filter, and the dynamic detection range covers 0.1 lux to 10000 lux. It is used to collect ambient light intensity and distinguish between daytime, dusk, nighttime, and low-light scenes such as tunnels and forests. During the road condition feature extraction process, the high-definition vehicle camera transmits the raw image stream of the captured road conditions to the central control module through a low-voltage differential signal interface. After receiving the image stream, the central control module first performs noise reduction, distortion correction, and white balance processing. Then, it calls the built-in convolutional neural network (CNN) model to perform semantic segmentation and feature classification, thereby accurately identifying the geological texture features of the current driving surface (such as the sand texture of the desert, the undulating contours of the mountain road, the muddy texture of the muddy ground, and the distribution of trees in the forest). The millimeter-wave radar is responsible for compensating for the blind spots of the high-definition vehicle camera in low visibility environments such as sandstorms, strong light, dense fog, or heavy rain. The raw point cloud data generated by the millimeter-wave radar is processed by a spatial clustering algorithm to extract the geometric contour information of obstacles ahead. The light sensor is used to collect the ambient light intensity of the current vehicle, providing a reference for the system's brightness benchmark adjustment.

[0021] Furthermore, the central control module spatially maps and fuses the obstacle coordinate system fed back by the millimeter-wave radar with the pixel coordinate system of the high-definition vehicle camera to establish a unified vehicle coordinate system. It then uses an extended Kalman filter (EKF) to eliminate false alarms caused by drift from a single sensor, ultimately generating a multi-dimensional semantic map that includes road condition type, slope trend, obstacle distribution, and background light intensity. This multi-dimensional semantic map is updated 30 times per second and serves as a real-time base for lighting strategy formulation.

[0022] The vehicle status acquisition module is used to monitor the vehicle's dynamic parameters and dynamic posture in real time. It includes a vehicle speed sensor, a steering angle sensor, a body roll sensor, and a gear position sensor. The vehicle speed sensor calculates the real-time vehicle speed by reading the pulse signals from the wheel speed sensors of all four wheels. The steering angle sensor, mounted on the steering column, uses magnetic encoder technology to monitor the angular displacement of the steering wheel in real time, acquiring the real-time steering angle of the steering wheel to determine the vehicle's steering direction and steering amplitude. The body roll sensor is a key component in this system for adjusting the beam pitch. It calculates the vehicle's pitch angle around the lateral axis and roll angle around the longitudinal axis in real time using an inertial measurement unit, thereby identifying the vehicle's climbing, descending, and roll states. The gear position sensor reads CAN messages from the transmission control unit to identify the current power output state (forward, reverse, and neutral) in real time, coordinating with the lighting system's logical switching in different driving directions.

[0023] To eliminate noise interference from high-frequency mechanical vibrations generated by vehicles under complex off-road conditions (such as gravel roads and washboard roads) on the perceived data, this invention performs a Kalman filter program during the data preprocessing stage and sets the state vector to include position, velocity, and acceleration information. Its state update equation is described as follows: ; In the formula, for The optimal state estimate at time t. For Kalman gain, These are actual sensor measurements. Through this iterative algorithm, the system can extract smooth vehicle driving posture parameters from the raw signal mixed with a large amount of noise. For example, when the vehicle is violently bumpy, the filtered pitch angle data can maintain physical continuity, thereby avoiding meaningless high-frequency jitter in the lighting actuator module and extending the service life of the stepper motor.

[0024] The central control module uses an MCU microcontroller based on the ARM Cortex-M7 core and has a built-in road condition lighting matching database. The road condition lighting matching database stores a mapping matrix between different road condition feature vectors (such as surface reflectivity, slope value, turning rate, vehicle speed, illuminance) and optimal lighting parameter vectors (such as brightness PWM duty cycle, horizontal deflection angle, vertical offset angle, focal length step value). The central control module also includes a data fusion algorithm and a lighting parameter adjustment algorithm. The data fusion algorithm is used to fuse and analyze road condition data, obstacle data, and ambient light data transmitted by the road condition recognition module with driving status parameters transmitted by the vehicle status acquisition module to determine the lighting requirements of the current driving scenario. The lighting parameter adjustment algorithm is used to call the optimal lighting parameters from the road condition lighting matching database based on the fusion analysis results, generate a target lighting adjustment command, and generate an anti-glare control command in conjunction with the signal from the anti-glare coordination module. The command transmission delay does not exceed 100ms to ensure the real-time performance of lighting adjustment.

[0025] The lighting execution module is the terminal unit for realizing light field adjustment. It typically includes at least two sets of roof-mounted LED spotlights symmetrically arranged at the front edge of the roof and a matching adjustment drive mechanism. Each set of roof-mounted LED spotlights uses multi-chip packaging technology. To provide excellent penetration and contrast under complex weather conditions, its color temperature is set in the cool white light range of 6000K to 8000K. The LED chip substrate of the roof-mounted LED spotlights uses aluminum nitride ceramic material with high thermal conductivity and is closely attached to heat sink fins. The adjustment drive mechanism consists of a stepper motor with high microstepping drive capability and its transmission gear set. The stepper motor supports 1 / 256 microstep drive and can realize dual-axis rotation of the roof-mounted LED spotlights in the horizontal direction (-60° to +60°) and the vertical direction (-30° to +30°). In addition, the roof-mounted LED spotlights are also equipped with an electric zoom lens group. By driving a micro linear motor through a central control module to change the relative position between the lenses, smooth switching between narrow beam (long illumination distance), medium beam and wide beam (wide illumination range) can be achieved.

[0026] In practice, the central control module executes highly differentiated lighting schemes based on the recognition results of the road condition recognition module and the feedback from the vehicle status acquisition module to meet the needs of specific scenarios.

[0027] In desert conditions, due to the extremely high light reflectivity of sand particles, ordinary high-brightness lighting easily produces severe diffuse glare, leading to driver fatigue. In this situation, the central control module adjusts the brightness in real time based on the ambient light intensity obtained from the light sensor. If the ambient light intensity exceeds a preset background threshold, the central control module actively reduces the duty cycle of the pulse width modulation (PWM), and the brightness adjustment follows this functional relationship: ; In the formula, This is the equivalent average voltage across the LED spotlight on the roof. Peak supply voltage, In the periodic time The actual conduction time within the range, This refers to the duty cycle. By precisely controlling the conduction time, the brightness is adjusted to a preset medium brightness mode (e.g., 50% of maximum brightness); simultaneously, the motorized zoom lens group is switched to wide beam mode, increasing the light spot area to reduce the luminous flux per unit area, thereby effectively suppressing visual glare. If the ambient light intensity is less than a preset background threshold, the brightness is adjusted to a preset high brightness mode (e.g., greater than 90% of maximum brightness), while the motorized zoom lens group is switched to medium beam mode.

[0028] On mountain roads with significant terrain undulations, traditional fixed-angle spotlights would shine directly into the sky when climbing slopes, while their beam distance would be too short when descending. To address this, the central control module reads the pitch angle data from the vehicle's tilt sensor in real time. When the vehicle is detected climbing (i.e., pitch angle greater than +5°), the central control module calculates a compensation angle and controls a stepper motor to drive the roof-mounted LED spotlight upwards. The offset is directly proportional to the slope angle and takes vehicle speed compensation into account. This adjustment ensures that the beam center is always parallel to the slope or slightly above the far end of the road surface, greatly improving visibility at the top of the slope. Conversely, when descending (pitch angle less than -5°), the light axis automatically shifts downwards to eliminate blind spots in front of the vehicle.

[0029] In forested or winding road conditions, the central control module uses a CAN bus to synchronize with the steering angle sensor in real time. When the steering wheel angular speed exceeds a preset threshold, the central control module drives the roof-mounted LED spotlights to deflect synchronously towards the steering side, achieving dynamic tracking of the optical axis with the tangent of the driving path. Simultaneously, based on the density of trees on both sides detected by millimeter-wave radar, if it is determined that the vehicle is driving on a narrow path, the beam will automatically narrow, switching the electric zoom lens assembly to narrow beam mode. This effectively reduces unnecessary scattering light from tree edges, concentrating light energy more on the road surface and enhancing path recognition.

[0030] The anti-glare coordination module includes an infrared sensor and an image processing unit. The infrared sensor is symmetrically arranged on the side of the LED spotlight housing on the roof, using a narrow-band infrared filter to capture specific band infrared features carried by the high beams or low beams of oncoming vehicles, as well as infrared signals from pedestrians. The image processing unit uses a specific target detection algorithm to scan the image from the high-definition vehicle camera in real time. When the biothermal features or reflective strip features of oncoming vehicles or pedestrians are detected within a 50m range (this distance can be dynamically extended to 100m depending on vehicle speed), the anti-glare coordination module immediately sends a high-priority interrupt request to the central control module. The central control module executes an anti-glare reduction strategy: first, it rapidly reduces the PWM duty cycle of the spotlight on the corresponding side (usually the driver's side) to below 30%, and simultaneously controls the stepper motor to deflect the optical axis 15° outward from the vehicle, thereby avoiding the strong light from the oncoming driver's line of sight. When the anti-glare coordination module confirms that the oncoming target has disappeared, it immediately restores the original lighting parameters through a slow-start algorithm to ensure a smooth visual transition.

[0031] The human-machine interface module includes an in-vehicle LCD screen and physical buttons. The in-vehicle LCD screen renders the current road condition recognition results, real-time vehicle attitude data, and the real-time brightness percentage and pointing angle of the roof-mounted LED spotlights in real time through a graphical interface. The physical buttons are used to switch between automatic and manual modes with a single click. In automatic mode, the driver can preset a personalized brightness gain coefficient according to their visual preferences. In manual mode, the in-vehicle LCD screen provides a virtual slider, allowing the driver to adjust the angle of the stepper motor and the power of the roof-mounted LED spotlights via touch or a physical knob. Furthermore, the human-machine interface module is equipped with a fault self-diagnosis program that monitors the heartbeat messages of each module on the CAN bus in real time. Once abnormal sensor data, a CAN transceiver open circuit, or a stepper motor stall is detected, the system immediately displays a red error code in a prominent position on the in-vehicle LCD screen and triggers an in-vehicle buzzer for an audible and visual warning.

[0032] At the hardware protection level, the system is also equipped with a power management module and a physical protection structure. The power management module is connected to the vehicle's 12V DC main line and uses a multi-stage Buck-Boost step-down and step-up voltage regulator circuit to output a stable 5V (powering the MCU and logic circuits) and 12V (powering the LEDs and motors). This module is equipped with a high-energy pulse suppression circuit for off-road environments, including a varistor and transient voltage suppressor diode array, which can effectively absorb electromagnetic surges generated by generator overload or high-power electrical switching, preventing vehicle circuit fluctuations from damaging the system module.

[0033] The physical protection structure fully considers the harsh external environment and has been modified as follows: the roof LED spotlights and controller housings are made of ADC12 aluminum alloy high-pressure die casting, and the surface is treated with anodizing and anti-ultraviolet powder coating; all mechanical connections are fitted with fluororubber O-rings; in the light window section, high-strength tempered glass is used and coated with a hydrophobic nano-coating to reduce the adhesion of rainwater and mud; the overall protection level is not lower than IP67, and it has a mechanical strength with a vibration resistance G-value of not less than 10G, ensuring that the internal precision optical components and electronic control unit can still operate stably for a long time in deep wading, sandstorms or high-frequency bumpy environments.

[0034] The technical effects of the present invention will be quantitatively demonstrated through specific embodiments below.

[0035] Comparison Case 1: Uses conventional fixed high-power roof spotlights; control method is manual switch, no automatic brightness and angle adjustment; optical specifications are equal power (60W) LEDs, fixed illumination angle, fixed focus lens.

[0036] Comparison Case 2: An automatic system with only a single sensor for adjustment is used; the control core is a common 8-bit microcontroller; the sensor is only a light sensor; the actuator has brightness adjustment but no automatic horizontal and vertical angle compensation mechanism.

[0037] Experimental Environment Setup: A comprehensive off-road section was selected, including a steep slope (20° gradient), sharp turns (15m radius), dust-covered areas, and oncoming vehicles. Driving speed was maintained between 20-40 km / h. Recorded indicators included: effective road illuminance compliance rate (the percentage of the target area with illuminance above 30 lux), driver visual fatigue score (1-10 points, lower scores indicating greater fatigue), system response latency, and the success rate of anti-glare triggering by oncoming vehicles. Data comparison results are shown in Table 1 below: Table 1: Comparison of performance test data between embodiments of the present invention and comparative examples Analysis of the data in Table 1 shows that this embodiment significantly outperforms the comparative case under complex working conditions. On slopes, thanks to IMU-based active pitch angle compensation, the effective road surface illuminance compliance rate reached 94.5%, far exceeding the 42.1% of comparative case 1. On curves, thanks to the steering linkage function, this embodiment effectively covers blind spots, demonstrating significant advantages in multimodal sensor fusion, particularly in anti-glare success rate and recognition accuracy in dusty environments. Furthermore, through efficient PWM scheduling, this embodiment maintains high-quality lighting while consuming only 82% of the energy required for constant power illumination, showcasing excellent energy efficiency.

[0038] In practical engineering applications, the initial calibration of the system is equally crucial. When the system is first installed on a vehicle, the central control module automatically enters calibration mode. First, the gravity vector determined by the vehicle tilt sensor is used as the Z-axis zero reference. Then, a high-definition onboard camera identifies the vanishing point of the flat ground ahead, establishing the horizontal plane coordinates. Finally, the stepper motor performs a full-stroke self-check, recording the mechanical limit positions. All calibration parameters are stored in the EEPROM, ensuring the system maintains extremely high pointing accuracy every time it starts up.

[0039] For extreme cold or high temperature environments, this invention further optimizes the heat dissipation logic. The central control module reads the thermistor data integrated into the roof LED spotlight substrate in real time; when the substrate temperature exceeds 85°C, the system will activate a derating strategy, gradually reducing the PWM duty cycle in 5% increments until the temperature returns to a safe range; at the same time, the physical protection structure of the housing is designed with a waterproof and breathable valve (Gore-Tex interface), which balances the internal and external air pressure while ensuring IP67 protection level, preventing condensation caused by drastic temperature changes from accumulating on the inside of the lens, ensuring all-weather reliability.

[0040] In summary, the roof lighting system based on adaptive adjustment according to driving lighting needs provided by this invention, through high-precision sensor layout, rigorous Kalman filtering algorithm, and multi-degree-of-freedom mechanical actuator, successfully solves the urgent need for high-quality auxiliary lighting for off-road vehicles in complex and dynamic driving environments. It not only significantly improves the driver's visibility safety, but also takes into account the common safety of road traffic participants through intelligent anti-glare collaborative logic, and has extremely high engineering application value and market promotion prospects.

[0041] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A vehicle roof lighting system that adaptively adjusts based on driving lighting needs, characterized in that: The system includes a road condition recognition module, a vehicle status acquisition module, a central control module, a lighting execution module, an anti-glare coordination module, and a human-machine interaction module. The road condition recognition module acquires geological texture features, geometric contour information, and ambient light intensity within a preset range in front of the vehicle through a high-definition vehicle camera, millimeter-wave radar, and light sensor, and generates a multi-dimensional semantic map. The vehicle status acquisition module is used to monitor the vehicle's dynamic parameters and dynamic pose in real time, and to perform noise reduction preprocessing on the raw sensor data to output smooth vehicle driving posture parameters. The central control module has a built-in road condition lighting matching database, which is used to retrieve and generate target lighting adjustment instructions based on the multidimensional semantic map and vehicle driving posture parameters. The lighting execution module includes a roof-mounted LED spotlight and an adjustment drive mechanism, which is used to dynamically adjust the light field distribution, pointing angle and beam shape of the roof-mounted LED spotlight according to the target lighting adjustment command. The anti-glare coordination module is used to monitor the biothermal characteristics or reflective strip characteristics of oncoming vehicles and pedestrians, and after identification, it sends an interruption request to the central control module to execute the anti-glare light reduction strategy. The human-computer interaction module renders and displays the system's operating status in real time through a graphical interface, provides a control mode switching interface, and has a built-in fault self-diagnosis program.

2. The roof lighting system based on adaptive adjustment according to driving lighting needs as described in claim 1, characterized in that: The road condition recognition module includes: A high-definition vehicle camera is installed on the upper inner side of the vehicle's windshield to collect raw image data of the area in front of the vehicle. The millimeter-wave radar, located at the geometric center of the front bumper, integrates a microstrip patch antenna array to assist in identifying the distance and outline of obstacles in road conditions, compensating for the recognition deficiencies of high-definition vehicle cameras in dim or dusty environments. The light sensor, located on the roof of the vehicle, is an integrated digital ambient light sensor with a surface covered by a high-transmittance UV-resistant filter, used to collect ambient light intensity. During the road condition feature extraction process, the central control module receives the raw image data from the high-definition vehicle camera and first performs noise reduction, distortion correction, and white balance processing. Then, it calls the convolutional neural network model to perform semantic segmentation and feature classification. Next, it spatially maps and fuses the geometric contour information of the millimeter-wave radar to generate a multi-dimensional semantic map.

3. The roof lighting system based on adaptive adjustment according to driving lighting needs as described in claim 2, characterized in that: The vehicle status acquisition module includes a vehicle speed sensor, a steering angle sensor, a body roll sensor, and a gear position sensor. The vehicle speed sensor acquires the vehicle's real-time speed via pulse signals from the wheel speed sensors of all four wheels. The steering angle sensor monitors the angular displacement of the steering wheel in real-time using magnetic encoder technology and acquires the real-time steering angle of the steering wheel. The body roll sensor calculates the vehicle's pitch angle around the lateral axis and roll angle around the longitudinal axis in real-time using an inertial measurement unit to identify the vehicle's climbing, descending, and roll states. The gear position sensor identifies the current power output status in real-time via CAN messages from the transmission control unit.

4. The roof lighting system based on adaptive adjustment according to driving lighting needs as described in claim 3, characterized in that: The vehicle state acquisition module uses a Kalman filter algorithm to eliminate mechanical noise interference during the data preprocessing stage, and its state update equation is as follows: ； In the formula, for The optimal state estimate at time t. For Kalman gain, These are the actual measured values ​​from the sensor.

5. The roof lighting system based on adaptive adjustment according to driving lighting needs as described in claim 3, characterized in that: The lighting execution module includes: The roof-mounted LED spotlights use multi-chip packaging technology, and the LED substrate uses aluminum nitride ceramic material with high thermal conductivity and is closely attached to the heat sink fins. The adjustment drive mechanism includes a stepper motor and a transmission gear set; wherein, the stepper motor supports 1 / 256 micro-step drive, which enables the roof LED spotlight to rotate on both horizontal and vertical axes. The lighting execution module also includes an electrically adjustable lens assembly; the electrically adjustable lens assembly is located inside the roof LED spotlight, and by changing the relative position between the lenses, it can switch between narrow beam, medium beam and wide beam.

6. The roof lighting system based on adaptive adjustment according to driving lighting needs as described in claim 5, characterized in that: The central control module executes differentiated lighting control logic based on the road condition recognition results as follows: In desert conditions, if the ambient light intensity is greater than the preset background threshold, the central control module actively reduces the duty cycle of the pulse width modulation and adjusts the brightness to the preset medium brightness mode, while controlling the motorized zoom lens group to switch to wide beam mode. If the ambient light intensity is less than the preset background threshold, adjust the brightness to the preset high brightness mode, and at the same time control the motorized zoom lens group to switch to the medium beam mode; In mountainous road conditions, the system reads the pitch angle data from the vehicle body tilt sensor in real time. When the system detects that the vehicle is climbing, it calculates the compensation angle and controls the stepper motor to drive the roof LED spotlights to shift upward. The shift amount is directly proportional to the slope angle, ensuring that the beam center is always parallel to the slope or slightly higher than the far end of the road surface. When the system detects that the vehicle is going downhill, the light axis automatically shifts downward to eliminate the blind spot in front of the vehicle. In forest or on winding roads, data from the steering angle sensor is received in real time. When the steering wheel angular velocity exceeds a preset threshold, the roof LED spotlights are driven to deflect synchronously to the steering side, achieving dynamic tracking of the optical axis to the tangent of the driving path; in addition, based on the distribution density of trees on both sides detected by millimeter-wave radar, if it is determined that the vehicle is currently driving in a narrow path, the electric zoom lens group is switched to narrow beam mode.

7. The roof lighting system based on adaptive adjustment according to driving lighting needs as described in claim 6, characterized in that: The anti-glare collaborative module includes an infrared sensor and an image processing unit; The infrared sensor uses a narrow-band infrared filter to capture specific band infrared features carried by the high beams or low beams of oncoming vehicles, as well as infrared signals from pedestrians; the image processing unit uses a specific target detection algorithm to scan the images from the high-definition vehicle camera in real time. When the biothermal features or reflective strip features of oncoming vehicles or pedestrians are detected within a preset range ahead, a high-priority interrupt request is immediately sent to the central control module, and an anti-glare reduction strategy is executed. The anti-glare and light reduction strategy is as follows: First, the PWM duty cycle of the driver's side spotlight is rapidly reduced to below 30%, and at the same time, the stepper motor is controlled to deflect the light axis to the outside of the vehicle, so that the strong light is avoided from the line of sight of oncoming drivers; when the oncoming target disappears, the original lighting parameters are restored to ensure the smoothness of the visual transition.

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