Passenger sitting posture adaptive side curtain form adjusting system and method

Abstract

The embodiment of the present application relates to the technical field of side air curtain, and specifically discloses a side air curtain mode adjusting system and method based on occupant sitting posture self-adaptation.The present application collects seat pressure distribution data and occupant human body space data, synchronously processes, identifies the occupant sitting posture state, and determines a plurality of sitting posture key characteristic parameters;self-adaptively adjusts and plans a plurality of independent control areas of the side air curtain, generates a real-time adjusting strategy, and controls the inflation of the side air curtain when a dangerous vehicle collision occurs.The present application can collect seat pressure distribution data and occupant human body space data, identify the occupant sitting posture state, determine a plurality of sitting posture key characteristic parameters, self-adaptively adjust and plan a plurality of independent control areas of the side air curtain, and then control the inflation when a dangerous vehicle collision occurs, so as to self-adaptively adjust the side air curtain according to the occupant sitting posture, and effectively avoid the problems of insufficient protection or secondary injury.

Description

Technical Field

[0001] This invention belongs to the field of side curtain air technology, and particularly relates to a side curtain air shape adjustment system and method based on occupant seating posture adaptation. Background Technology

[0002] Side curtain airbags are an important restraint and protection device in a vehicle's passive safety system. They are mainly installed on the inner side of the vehicle's roof, above the side panel between the A-pillar and C-pillar (or D-pillar), corresponding to the side window area. In the event of a side collision, rollover, or partial frontal offset collision, they deploy instantly to form a flexible airbag barrier distributed along the window, providing effective cushioning and support for the occupants' head, neck, and upper body. This reduces the risk of injury caused by direct collisions between occupants and doors, side windows, pillars, or external objects, and is an indispensable and important component of modern automotive safety systems.

[0003] In existing technologies, automotive side curtain airbags typically employ a preset, single deployment configuration. Regardless of whether the occupant is in a standard sitting position, a reclining position, or a position close to the door, the coverage, thickness, and rigidity of the airbag remain unchanged. It cannot adaptively adjust the side curtain airbag according to the occupant's sitting position, which can easily lead to insufficient protection or secondary injuries. Summary of the Invention

[0004] The purpose of this invention is to provide a side curtain airbag morphology adjustment system and method based on occupant seating posture, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: A side curtain airbag morphology adjustment method based on occupant seating posture adaptation, the method specifically includes the following steps: When in the adjustment and wake-up state, data on seat pressure distribution and occupant human body space are collected; The seat pressure distribution data and the occupant human body space data are processed synchronously to identify the occupant's sitting posture and determine multiple key characteristic parameters of the sitting posture. Based on the occupant's sitting posture and multiple key characteristic parameters of the sitting posture, adaptive adjustment planning is performed on multiple independent control areas of the side curtain airbag to generate a real-time adjustment strategy. Vehicle collision monitoring is performed, and in the event of a dangerous vehicle collision, the side curtain airbags are inflated accordingly in accordance with the real-time adjustment strategy.

[0006] The side curtain airbag morphology adjustment system based on occupant seating posture adaptation includes a relevant data acquisition unit, a data processing and identification unit, an adaptive adjustment planning unit, and a collision inflation control unit, wherein: The relevant data acquisition unit is used to collect seat pressure distribution data and occupant human body space data when in the adjustment and wake-up state; The data processing and identification unit is used to synchronously process the seat pressure distribution data and the occupant human body space data, identify the occupant's sitting posture, and determine multiple key characteristic parameters of the sitting posture. An adaptive adjustment planning unit is used to adaptively adjust and plan multiple independent control areas of the side curtain airbag according to the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, and generate a real-time adjustment strategy. The collision inflation control unit is used to monitor vehicle collisions and, in the event of a dangerous vehicle collision, to control the inflation of the side curtain airbags according to the real-time adjustment strategy.

[0007] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention introduces an adjustment wake-up mechanism based on multi-source signal continuous stability judgment and personalized baseline learning. When the vehicle is stationary or driving smoothly and the occupant's posture is stable, the learning cycle is automatically started to collect and verify the generated occupant reference posture parameters, thereby ensuring that the system only wakes up under reliable operating conditions, providing a high-quality data starting point for subsequent processing.

[0008] 2. This invention normalizes the coordinate system of the optimized pressure distribution data and human body space data, and verifies and corrects the directional consistency of the trunk tilt feature calculated by the pressure distribution balance ratio against the spatial coordinates. Then, it performs collaborative compensation on the head lateral offset feature based on the corrected tilt angle, and finally extracts the key sitting posture feature parameters that are mutually verified and have consistent physical meaning, thus solving the error interference and parameter coupling problems in the fusion of multi-source sensor data.

[0009] 3. This invention integrates the compensated lateral head offset with the effective tilt angle into an offset risk assessment value, converts the torso rotation angle into a stiffness influence coefficient, and performs dual-path optimization adjustment on the trigger timing and basic inflation volume of each independent control area based on these two quantitative indicators. Then, it performs global conflict detection and coordination on the preliminary optimization parameters of all areas to generate optimized adjustment parameters that are internally coordinated in terms of timing and mechanics, thus achieving a leap from local parameter optimization to overall system coordination.

[0010] 4. This invention maps the occupant's sitting posture to a basic risk value and designs risk gain factors with different growth patterns for the compensated head lateral offset, effective tilt angle, and torso rotation angle. A comprehensive risk index is obtained by product fusion. The risk level is determined by querying a preset mapping table. A nonlinear dynamic risk assessment route that conforms to the principles of human biomechanics and collision dynamics is established, providing a quantitative basis for the accurate division of air curtain triggering priority. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0012] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0013] Figure 2 An application architecture diagram of the system provided in an embodiment of the present invention is shown. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0015] Understandably, in existing technologies, automotive side curtain airbags typically employ a preset, single deployment configuration. Regardless of whether the occupant is in a standard sitting position, a reclined sitting position, or a sitting position close to the door, the coverage area, thickness, and rigidity of the airbag remain unchanged. It cannot adaptively adjust the side curtain airbag according to the occupant's sitting position, which can easily lead to insufficient protection or secondary injuries.

[0016] To address the aforementioned issues, this invention collects seat pressure distribution data and occupant body space data; processes this data synchronously to identify the occupant's sitting posture and determine multiple key posture characteristic parameters; adaptively adjusts multiple independent control areas of the side curtain airbags according to the occupant's sitting posture and these key parameters, generating a real-time adjustment strategy; performs vehicle collision monitoring; and, in the event of a dangerous vehicle collision, controls the inflation of the side curtain airbags accordingly based on the real-time adjustment strategy. This invention effectively avoids insufficient protection or secondary injuries by collecting seat pressure distribution data and occupant body space data, identifying the occupant's sitting posture, determining multiple key posture characteristic parameters, adaptively adjusting multiple independent control areas of the side curtain airbags, and then controlling inflation accordingly in the event of a dangerous vehicle collision.

[0017] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0018] Specifically, the side curtain airbag morphology adjustment method based on occupant seating posture adaptively includes the following steps: Step S101: When in the adjustment wake-up state, collect seat pressure distribution data and occupant human body space data.

[0019] In this embodiment of the invention, by acquiring vehicle operation data and analyzing the status of the vehicle doors and seats based on the vehicle operation data, it is determined whether the vehicle is in an adjustment wake-up state. When the vehicle is in an adjustment wake-up state with the doors closed and the seats occupied, it is determined that the vehicle is in an adjustment wake-up state. At this time, a first acquisition instruction and a second acquisition instruction are generated. According to the first acquisition instruction, seat pressure distribution data are acquired, and according to the second acquisition instruction, occupant human body space data are acquired.

[0020] Understandably, seat pressure distribution data refers to the pressure values ​​of multiple areas of the car's seat cushion and backrest collected simultaneously; occupant human body space data refers to the three-dimensional spatial coordinates of the occupant's head, shoulders, and torso collected simultaneously.

[0021] In a preferred embodiment of the present invention, the process of collecting seat pressure distribution data and occupant human body space data while in the adjustment and wake-up state specifically includes the following steps: Step S1011: Obtain vehicle operating data; Step S1012: Based on the vehicle operation data, analyze the status of the vehicle doors and seats to determine whether they are in an adjustment wake-up state; Step S1013: When it is determined that the state is in the adjustment wake-up state, a first acquisition command and a second acquisition command are generated; Step S1014: Collect seat pressure distribution data according to the first acquisition instruction; Step S1015: Collect occupant human body space data according to the second acquisition instruction.

[0022] In a preferred embodiment of the present invention, analyzing the status of the car doors and seats based on the car's operating data to determine whether it is in an adjustment / awakening state specifically includes the following steps: Step S10121: Obtain vehicle operation data and extract door closing and locking signals, seat pressure continuous distribution signals, vehicle longitudinal acceleration signals and lateral acceleration signals with a duration longer than a first preset time. Step S10122: Based on the door closing and locking signal, confirm that the target door has been continuously closed and locked for more than a second preset time, and generate a door status confirmation signal; Step S10123: Based on the seat pressure continuous distribution signal, calculate the average change value between the pressure data collected by the seat pressure distribution sensor within the third preset time window; if the average change value is lower than the first preset threshold, determine that the occupant posture has entered a stable state and generate a posture stabilization signal. Step S10124: Based on the vehicle's longitudinal acceleration signal and lateral acceleration signal, calculate the longitudinal acceleration change amplitude and the lateral acceleration change amplitude respectively; perform weighted fusion calculation on the longitudinal acceleration change amplitude and the lateral acceleration change amplitude to obtain the vehicle interference quantization value; Step S10125: If the attitude stabilization signal is valid and the vehicle interference quantization value is lower than the second preset threshold, then generate an environment ready signal. Step S10126: When the door status confirmation signal and the environment ready signal are received simultaneously, the attitude baseline learning cycle is started, and seat pressure distribution data and occupant human body space data are collected within the attitude baseline learning cycle. Using the seat pressure distribution data and occupant human body space data, the baseline attitude parameters used to characterize the current normal sitting posture of the occupant are calculated. Step S10127: After the attitude baseline learning cycle ends, check whether each parameter value in the reference attitude parameters used to characterize the current occupant's normal sitting posture falls within the corresponding preset valid value range; if all parameter values ​​fall within the corresponding preset valid value range, the confidence verification is deemed to have passed and the occupant is officially determined to be in the adjustment wake-up state.

[0023] In this embodiment of the invention, by integrating three types of information—door locking status, occupant posture stability, and vehicle driving smoothness—a multi-level, multi-condition wake-up logic is established to ensure the system activates only under high-confidence conditions. Specifically, firstly, by detecting the long-term stability of the door's continuously closed locking signal and the seat pressure distribution, it is confirmed that the occupant is in position and in a relatively static state. Simultaneously, longitudinal and lateral acceleration signals of the vehicle are collected and weighted and fused to quantify the interference level of the current driving environment, ensuring that data collection is not affected by severe acceleration, deceleration, or bumps. When both conditions of stable occupant posture and smooth vehicle driving are met, the system initiates a posture baseline learning cycle. During this cycle, seat pressure and human body space data are collected, and baseline posture parameters are calculated. Finally, by verifying whether these parameters are within a reasonable physiological range, it is confirmed that the system has truly entered a reliable ready state. This avoids false wake-ups in unreliable scenarios such as frequent door opening and closing, frequent occupant posture adjustments, or bumpy vehicle driving, ensuring that the data source used for subsequent posture recognition and adjustment planning has sufficient accuracy and representativeness.

[0024] Furthermore, the side curtain airbag morphology adjustment method based on occupant seating posture also includes the following steps: Step S102: Synchronously process the seat pressure distribution data and the occupant human body space data to identify the occupant's sitting posture and determine multiple key characteristic parameters of the sitting posture.

[0025] In this embodiment of the invention, seat pressure distribution data and occupant human body space data are synchronized in time, and then anomalies in the seat pressure distribution data and occupant human body space data are identified and eliminated to generate optimized pressure distribution data and optimized human body space data. Then, the optimized pressure distribution data and optimized human body space data are used to identify sitting posture to determine the occupant's sitting posture state. Then, the optimized pressure distribution data and optimized human body space data are used to perform feature analysis to determine multiple key sitting posture feature parameters. Specifically, the multiple key sitting posture feature parameters include head lateral offset, tilt angle and torso rotation angle.

[0026] In a preferred embodiment of the present invention, the step of synchronously processing the seat pressure distribution data and the occupant human body space data to identify the occupant's sitting posture and determine multiple key sitting posture feature parameters specifically includes the following steps: Step S1021: Synchronize the seat pressure distribution data and the occupant human body space data in time; Step S1022: Anomalies are removed from the seat pressure distribution data and the occupant human body space data; Step S1023: Generate optimized pressure distribution data and optimized human body space data; Step S1024: Perform posture recognition on the optimized pressure distribution data and the optimized human body space data to determine the occupant's sitting posture. Step S1025: Perform feature analysis on the optimized pressure distribution data and the optimized human body space data to determine multiple key sitting posture feature parameters, including head lateral offset, tilt angle and torso rotation angle.

[0027] In a preferred embodiment of the present invention, the process of performing feature analysis on the optimized pressure distribution data and the optimized human body space data to determine multiple key characteristic parameters of sitting posture specifically includes the following steps: Step S10251: Based on the optimized human body space data, extract the spatial coordinates of the occupant's head, shoulders, and hips; Step S10252: Using the seat back plane corresponding to the optimized pressure distribution data as the reference plane, establish a posture analysis coordinate system, and transform the spatial coordinates of the occupant's head, shoulders, and hips to the posture analysis coordinate system to obtain normalized head coordinates, normalized shoulder coordinates, and normalized hip coordinates. Step S10253: Based on the normalized head coordinates and normalized shoulder coordinates, calculate the lateral distance of the occupant's head center point relative to the longitudinal central axis of the seat, as the head lateral offset feature. Step S10254: Based on the normalized shoulder coordinates and the normalized hip coordinates, calculate the angle between the line connecting the side profile of the torso and the perpendicular line of the reference plane, and use it as the torso tilt feature quantity. Step S10255: Analyze the ratio of the total pressure in the left side region of the seat back to the total pressure in the right side region in the optimized pressure distribution data to obtain the pressure distribution balance ratio. Step S10256: Use the pressure distribution equalization ratio to verify the directional consistency of the trunk tilt characteristic quantity. If the trunk tilt characteristic quantity indicates a leftward tilt and the pressure distribution equalization ratio is greater than a predetermined value, or if the trunk tilt characteristic quantity indicates a rightward tilt and the pressure distribution equalization ratio is less than a predetermined value, then the verification is deemed successful. If the verification is successful, the trunk tilt characteristic quantity is taken as the effective tilt angle. If the verification fails, the angle correction amount is calculated based on the numerical difference between the pressure distribution equalization ratio and the trunk tilt characteristic quantity. The trunk tilt characteristic quantity and the angle correction amount are added together to obtain the effective tilt angle. Step S10257: Perform numerical translation compensation on the head lateral offset feature based on the effective tilt angle to obtain the compensated head lateral offset. Step S10258: In the posture analysis coordinate system, the rotation angle of the torso around the vertical axis is calculated based on the spatial vector relationship between the normalized shoulder coordinates and the normalized hip coordinates, and is used as the torso rotation angle; the effective tilt angle, the compensated lateral head offset, and the torso rotation angle are used as key feature parameters for determining multiple sitting postures.

[0028] In this embodiment of the invention, a unified posture analysis coordinate system based on the seat back plane is established. Heterogeneous data from pressure distribution sensors and spatial positioning sensors are spatially normalized and fused for analysis, thereby extracting key parameters that accurately reflect the occupant's lateral posture characteristics. First, the spatial coordinates of the head, shoulders, and hips are transformed into this unified coordinate system, and the geometric features of the head's lateral offset and torso tilt are directly calculated. Then, the pressure information of the left and right sides of the seat back pressure distribution balance ratio is introduced to verify the directional consistency and correct the numerical value of the torso tilt angle calculated based on the spatial coordinates, solving the misjudgment problem that may occur when a single spatial sensor is obscured by clothing or in a specific posture. Finally, based on the corrected effective tilt angle, the head's lateral offset is compensated to eliminate the measurement error of the head's relative position caused by torso tilt, and the torso's rotation angle around the vertical axis is calculated independently. This process realizes the complementarity and mutual verification of multi-source sensor data. The final output of the head's lateral offset, tilt angle, and torso rotation angle is a set of highly reliable sitting posture feature parameters with clear physical meaning and logical consistency.

[0029] Furthermore, the side curtain airbag morphology adjustment method based on occupant seating posture also includes the following steps: Step S103: Based on the occupant's sitting posture and multiple key characteristic parameters of the sitting posture, adaptive adjustment planning is performed on multiple independent control areas of the side curtain airbag to generate a real-time adjustment strategy.

[0030] In this embodiment of the invention, multiple independent control zones of the side curtain airbag are determined. Then, based on the occupant's seating posture, the key coverage height and length of the side curtain airbag are determined. Basic adjustment planning is performed on the multiple independent control zones to generate multiple basic adjustment parameters. Subsequently, based on multiple key seating posture feature parameters, the multiple basic adjustment strategies are adaptively optimized to generate multiple optimized adjustment parameters. Combining the occupant's seating posture and multiple key seating posture feature parameters, a risk analysis of the driving posture is performed to determine the risk level. Based on the risk level, the trigger priority of the multiple independent control zones is determined. Then, based on the multiple trigger priorities, the response optimization of the multiple optimized adjustment parameters is performed to generate a real-time adjustment strategy.

[0031] It is understandable that the multiple basic adjustment parameters and multiple optimized adjustment parameters all contain parameter values ​​for inflation volume and support strength in multiple independent control areas.

[0032] In a preferred embodiment of the present invention, the step of adaptively adjusting and planning multiple independent control areas of the side curtain airbag according to the occupant's sitting posture and multiple key characteristic parameters of the sitting posture, and generating a real-time adjustment strategy, specifically includes the following steps: Step S1031: Determine multiple independent control zones for the side curtain airbags; Step S1032: Based on the occupant's sitting posture, perform basic adjustment planning for multiple independent control areas to generate multiple basic adjustment parameters; Step S1033: Adaptively optimize the multiple basic adjustment strategies according to the multiple key characteristic parameters of the sitting posture to generate multiple optimized adjustment parameters; Step S1034: Based on the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, optimize the response of multiple optimization adjustment parameters to generate a real-time adjustment strategy.

[0033] In a preferred embodiment of the present invention, the adaptive optimization of multiple basic adjustment strategies based on multiple key posture feature parameters to generate multiple optimized adjustment parameters specifically includes the following steps: Step S10331: The compensated lateral head offset and the effective roll angle are weighted and combined to calculate the risk assessment value of the occupant's head offset relative to each independent control area in a side collision. Step S10332: Convert the torso rotation angle into a stiffness influence coefficient for the support requirements of multiple independent control zones of the contralateral air curtain. Step S10333: Optimize and adjust the trigger timing parameters of each independent control area based on the offset risk assessment value. For areas where the offset risk assessment value is higher than the preset threshold, increase the trigger priority of the target area and advance the trigger time by a set duration. Optimize and adjust the basic inflation volume of each independent control area based on the stiffness influence coefficient. For areas where the stiffness influence coefficient is higher than the preset threshold, increase the basic inflation volume of the target area according to a preset ratio to obtain the preliminary optimization parameters for each independent control area. Step S10334: Perform global coordination verification on the preliminary optimization parameters of each independent control area. If the trigger time interval between adjacent areas is detected to be less than the preset minimum safety interval, the trigger time of the later triggered area is delayed until the preset minimum safety interval is met. If the inflation volume difference between adjacent areas is detected to exceed the preset maximum allowable pressure difference, the inflation volume of the area with higher inflation volume is appropriately reduced until the inflation volume difference between adjacent areas is less than the preset maximum allowable pressure difference, so as to obtain the set of intermediate optimization parameters for internal coordination, and use the intermediate optimization parameters in the set of intermediate optimization parameters for internal coordination as multiple optimization adjustment parameters.

[0034] In this embodiment of the invention, the head lateral offset and tilt angle, which characterize the occupant's posture space, are fused into an offset risk assessment value. The torso rotation angle, which characterizes the torso's orientation, is converted into a stiffness influence coefficient. This dual-path quantitative index drives the parameter optimization of each independent control area of ​​the side curtain airbag. Specifically, the triggering sequence of each area is dynamically adjusted based on the offset risk assessment value. Areas with high risk are triggered earlier to meet more urgent protection needs. The basic inflation volume of each area is adjusted based on the stiffness influence coefficient to provide airbag areas with higher stiffness for torso torso twisting postures that require more support. After completing the above preliminary optimization based on local risks, a global systemic coordination verification is further performed to check and adjust potential triggering sequence conflicts and excessive inflation pressure differences between adjacent areas. This ensures that the triggering of all areas is smoothly connected in time, and that the support surface formed after inflation has a smooth mechanical transition. This avoids uncoordinated overall airbag deployment or internal stress concentration caused by excessive local adjustments. Thus, the final control strategy is generated, from parameter optimization targeting local posture characteristics to ensuring the coordinated, safe, and effective deployment of the airbag as a whole system.

[0035] In a preferred embodiment of the present invention, the step of integrating the occupant's sitting posture state and multiple key posture feature parameters to optimize the response of multiple optimization adjustment parameters and generate a real-time adjustment strategy specifically includes the following steps: Step S10341: Based on the occupant's sitting posture and multiple key characteristic parameters of the sitting posture, a risk analysis of the driving posture is performed to determine the risk level; Step S10342: Determine the trigger priority of multiple independent control areas based on the risk level; Step S10343: Optimize the response of the multiple optimization adjustment parameters according to the multiple trigger priorities to generate a real-time adjustment strategy.

[0036] In a preferred embodiment of the present invention, the risk analysis of driving posture, which combines the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, to determine the risk level specifically includes: Step S103411: Map the occupant's sitting posture to a posture reference risk value; wherein, the mapping to a posture reference risk value includes: the standard sitting posture in the occupant's sitting posture corresponds to the low reference value in the reference risk value, the lateral sitting posture in the occupant's sitting posture corresponds to the medium reference value in the reference risk value, and the forward-leaning sitting posture in the occupant's sitting posture corresponds to the high reference value in the reference risk value. Step S103412: Calculate the head position risk gain factor based on the compensated lateral head offset; wherein, the calculation of the head position risk gain factor includes: for every preset unit offset increase in the compensated lateral head offset, the head position risk gain factor increases linearly by a preset unit gain value. Step S103413: Calculate the roll attitude risk gain factor based on the effective roll angle; wherein, the calculation of the roll attitude risk gain factor includes: for every preset unit angle increase in the effective roll angle, the roll attitude risk gain factor increases according to a preset nonlinear relationship curve. Step S103414: Calculate the trunk torsion risk gain factor based on the trunk rotation angle; wherein, the calculation of the trunk torsion risk gain factor includes: for every preset unit rotation angle increase in the trunk rotation angle, the trunk torsion risk gain factor increases according to a preset exponential relationship. Step S103415: Multiply and fuse the attitude baseline risk value with the head position risk gain factor, the tilt attitude risk gain factor, and the trunk torsion risk gain factor to obtain the comprehensive risk index. Step S103416: Input the comprehensive risk index into the preset risk level mapping table to obtain the final determined risk level.

[0037] In this embodiment of the invention, a baseline risk value is assigned to the occupant based on their sitting posture. Standard, tilted, and forward-leaning postures correspond to low, medium, and high baseline values, respectively. Subsequently, key characteristic parameters of each posture are processed. The compensated lateral head offset increases risk gain linearly, the effective tilt angle increases risk gain according to a preset non-linear curve, and the torso rotation angle increases risk gain exponentially. The baseline risk value is then multiplied consecutively by the three risk gain factors to obtain a comprehensive risk index. Finally, this index is compared with a preset risk level mapping table to determine the final risk level. This process transforms the sitting posture and multiple key parameters into a quantitative, graded risk assessment result, providing a direct basis for subsequently accurately defining the triggering priority of each independent control zone of the side curtain airbags.

[0038] Furthermore, the side curtain airbag morphology adjustment method based on occupant seating posture also includes the following steps: Step S104: Perform vehicle collision monitoring, and when a dangerous vehicle collision occurs, control the inflation of the side curtain airbags accordingly according to the real-time adjustment strategy.

[0039] In this embodiment of the invention, vehicle collision monitoring is performed to acquire collision monitoring data. By analyzing the collision monitoring data, it is determined whether a vehicle collision has occurred. If a vehicle collision is determined to have occurred, the vehicle collision intensity is determined and compared with a preset danger threshold intensity to determine whether a dangerous vehicle collision has occurred. If the vehicle collision intensity is greater than the preset danger threshold intensity, a dangerous vehicle collision is determined to have occurred. At this time, the side curtain airbags are inflated according to a real-time adjustment strategy to effectively avoid the problem of insufficient protection or secondary injury.

[0040] In a preferred embodiment of the present invention, the step of performing vehicle collision monitoring and, in the event of a dangerous vehicle collision, controlling the inflation of the side curtain airbags according to the real-time adjustment strategy specifically includes the following steps: Step S1041: Perform vehicle collision monitoring and obtain collision monitoring data; Step S1042: Analyze the collision monitoring data to determine whether a vehicle collision has occurred; Step S1043: When a vehicle collision is determined to have occurred, the intensity of the vehicle collision is determined. Step S1044: Compare the vehicle collision intensity with a preset danger threshold intensity to determine whether a dangerous vehicle collision has occurred. Step S1045: When a dangerous vehicle collision is determined to have occurred, the side curtain airbags are inflated in accordance with the real-time adjustment strategy.

[0041] Furthermore, Figure 2An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0042] In another preferred embodiment of the present invention, the side curtain airbag morphology adjustment system based on occupant seating posture adaptation includes: The relevant data acquisition unit 101 is used to collect seat pressure distribution data and occupant human body space data when it is in the adjustment wake-up state.

[0043] In this embodiment of the invention, the relevant data acquisition unit 101 acquires vehicle operation data and analyzes the status of the vehicle doors and seats based on the vehicle operation data to determine whether it is in an adjustment wake-up state. When the vehicle is in an adjustment wake-up state with the doors closed and the seats occupied, it is determined that it is in an adjustment wake-up state. At this time, a first acquisition instruction and a second acquisition instruction are generated. According to the first acquisition instruction, seat pressure distribution data are acquired, and according to the second acquisition instruction, occupant human body space data are acquired.

[0044] The data processing and identification unit 102 is used to synchronously process the seat pressure distribution data and the occupant human body space data, identify the occupant's sitting posture, and determine multiple key characteristic parameters of the sitting posture.

[0045] In this embodiment of the invention, the data processing and identification unit 102 synchronizes the seat pressure distribution data and the occupant human body space data in time, then identifies and removes anomalies in the seat pressure distribution data and the occupant human body space data, thereby generating optimized pressure distribution data and optimized human body space data. Subsequently, the optimized pressure distribution data and optimized human body space data are used to identify the sitting posture to determine the occupant's sitting posture state. Then, the optimized pressure distribution data and optimized human body space data are used to perform feature analysis to determine multiple key sitting posture feature parameters. Specifically, the multiple key sitting posture feature parameters include the head lateral offset, the tilt angle, and the torso rotation angle.

[0046] In a preferred embodiment of the present invention, the data processing and identification unit 102 specifically includes: Time synchronization module 1021 is used to synchronize the seat pressure distribution data and the occupant human body space data in time; An anomaly removal module 1022 is used to remove anomalies from the seat pressure distribution data and the occupant human body space data. The optimization generation module 1023 is used to generate optimized pressure distribution data and optimized human body space data; The posture recognition module 1024 is used to perform posture recognition on the optimized pressure distribution data and the optimized human body space data to determine the occupant's posture status. The feature analysis module 1025 is used to perform feature analysis on the optimized pressure distribution data and the optimized human body space data to determine multiple key feature parameters of sitting posture, including head lateral offset, tilt angle and torso rotation angle.

[0047] Furthermore, the side curtain airbag morphology adjustment system based on occupant seating posture adaptation also includes: The adaptive adjustment planning unit 103 is used to adaptively adjust and plan multiple independent control areas of the side curtain airbag according to the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, and generate a real-time adjustment strategy.

[0048] In this embodiment of the invention, the adaptive adjustment planning unit 103 determines multiple independent control areas of the side curtain airbag, and then determines the key coverage height and length of the side curtain airbag based on the occupant's sitting posture. It performs basic adjustment planning for the multiple independent control areas to generate multiple basic adjustment parameters. Then, according to multiple key characteristic parameters of the sitting posture, it adaptively optimizes the multiple basic adjustment strategies to generate multiple optimized adjustment parameters. Combining the occupant's sitting posture and multiple key characteristic parameters of the sitting posture, it performs a risk analysis of the driving posture to determine the risk level. Then, according to the risk level, it determines the trigger priority of the multiple independent control areas. Finally, according to the multiple trigger priorities, it performs response optimization of the multiple optimized adjustment parameters to generate a real-time adjustment strategy.

[0049] In a preferred embodiment of the present invention, the adaptive adjustment planning unit 103 specifically includes: The area determination module 1031 is used to determine multiple independent control areas of the side curtain airbag; The basic adjustment planning module 1032 is used to perform basic adjustment planning for multiple independent control areas based on the occupant's sitting posture, and generate multiple basic adjustment parameters. The adaptive optimization module 1033 is used to adaptively optimize the multiple basic adjustment strategies according to multiple key feature parameters of the sitting posture, and generate multiple optimized adjustment parameters. The response optimization module 1034 is used to integrate the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, and to optimize the response of multiple optimization adjustment parameters to generate a real-time adjustment strategy.

[0050] Furthermore, the side curtain airbag morphology adjustment system based on occupant seating posture adaptation also includes: The collision inflation control unit 104 is used to monitor vehicle collisions and, in the event of a dangerous vehicle collision, to control the inflation of the side curtain airbags according to the real-time adjustment strategy.

[0051] In this embodiment of the invention, the collision inflation control unit 104 performs vehicle collision monitoring, acquires collision monitoring data, analyzes the collision monitoring data to determine whether a vehicle collision has occurred, determines the vehicle collision intensity when a vehicle collision is determined, and compares the vehicle collision intensity with a preset danger threshold intensity to determine whether a dangerous vehicle collision has occurred. When the vehicle collision intensity is greater than the preset danger threshold intensity, a dangerous vehicle collision is determined. At this time, the side curtain airbags are inflated according to a real-time adjustment strategy to effectively avoid the problem of insufficient protection or secondary injury.

[0052] In a preferred embodiment of the present invention, the collision inflation control unit 104 specifically includes: The collision monitoring module 1041 is used to perform vehicle collision monitoring and acquire collision monitoring data. The collision occurrence determination module 1042 is used to analyze the collision monitoring data and determine whether a vehicle collision has occurred. The intensity determination module 1043 is used to determine the intensity of a vehicle collision when a vehicle collision is determined to have occurred. The dangerous collision judgment module 1044 is used to compare the vehicle collision intensity with a preset danger threshold intensity to determine whether a dangerous vehicle collision has occurred. The inflation control module 1045 is used to control the inflation of the side curtain airbags according to the real-time adjustment strategy when a dangerous vehicle collision is determined to have occurred.

[0053] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0054] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0055] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0056] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for adjusting the shape of a side curtain airbag based on the seating posture of an occupant, characterized by, The method specifically includes the following steps: When in the adjustment and wake-up state, data on seat pressure distribution and occupant human body space are collected; The seat pressure distribution data and the occupant human body space data are processed synchronously to identify the occupant's sitting posture and determine multiple key characteristic parameters of the sitting posture. Based on the occupant's sitting posture and multiple key characteristic parameters of the sitting posture, adaptive adjustment planning is performed on multiple independent control areas of the side curtain airbag to generate a real-time adjustment strategy. Vehicle collision monitoring is performed, and in the event of a dangerous vehicle collision, the side curtain airbags are inflated accordingly in accordance with the real-time adjustment strategy.

2. The method of claim 1, wherein the method is based on an occupant sitting posture. When in the adjustment and wake-up state, collecting seat pressure distribution data and occupant human body space data specifically includes the following steps: Obtain vehicle operating data; Based on the vehicle's operating data, analyze the status of the vehicle's doors and seats to determine whether they are in an adjustment / wake-up state. When it is determined that the system is in a state of adjustment and wake-up, a first acquisition command and a second acquisition command are generated. Collect seat pressure distribution data according to the first acquisition command; According to the second acquisition instruction, collect occupant human body space data. 3.The method of claim 2, wherein, Based on the vehicle's operating data, the status of the vehicle's doors and seats is analyzed to determine whether it is in an adjustment / awakening state. This specifically includes the following steps: Acquire vehicle operation data and extract door closing and locking signals, seat pressure distribution signals, vehicle longitudinal acceleration signals, and lateral acceleration signals with a duration longer than a first preset time; Based on the door closing and locking signal, confirm that the target door has been continuously closed and locked for more than a second preset time, and generate a door status confirmation signal; Based on the continuous distribution signal of seat pressure, the average change value between the pressure data collected by the seat pressure distribution sensor within the third preset time window is calculated; if the average change value is lower than the first preset threshold, it is determined that the occupant posture has entered a stable state and a posture stabilization signal is generated. Based on the vehicle's longitudinal acceleration signal and lateral acceleration signal, the longitudinal acceleration change amplitude and the lateral acceleration change amplitude are calculated respectively; the longitudinal acceleration change amplitude and the lateral acceleration change amplitude are weighted and fused to obtain the vehicle interference quantization value; If the attitude stabilization signal is valid and the vehicle interference quantization value is lower than the second preset threshold, then an environment ready signal is generated. When both the door status confirmation signal and the environment ready signal are received simultaneously, the posture baseline learning cycle is started, and seat pressure distribution data and occupant human body space data are collected within the posture baseline learning cycle. Using the seat pressure distribution data and occupant human body space data, the baseline posture parameters used to characterize the current normal sitting posture of the occupant are calculated. After the attitude baseline learning cycle ends, check whether each parameter value in the reference attitude parameters used to characterize the current occupant's normal sitting posture falls within the corresponding preset valid value range; if all parameter values ​​fall within the corresponding preset valid value range, the confidence check is deemed to have passed, and the occupant is officially deemed to be in the adjustment wake-up state.

4. The method of claim 3, wherein the method further comprises: The process of synchronously processing the seat pressure distribution data and the occupant human body space data to identify the occupant's sitting posture and determine multiple key posture feature parameters specifically includes the following steps: The seat pressure distribution data and the occupant human body space data are synchronized over time. Anomalies are removed from the seat pressure distribution data and the occupant body space data. Generate optimized pressure distribution data and optimized human body space data; The optimized pressure distribution data and the optimized human body space data are used to identify sitting postures and determine the occupant's sitting posture. Feature analysis is performed on the optimized pressure distribution data and the optimized human body space data to determine multiple key sitting posture feature parameters, including head lateral offset, tilt angle and trunk rotation angle.

5. The method of claim 4, wherein the method further comprises: The specific steps for performing feature analysis on the optimized pressure distribution data and the optimized human body space data to determine multiple key characteristic parameters of sitting posture include: Based on the optimized human body spatial data, the spatial coordinates of the occupant's head, shoulders, and hips are extracted. Using the seat back plane corresponding to the optimized pressure distribution data as a reference plane, a posture analysis coordinate system is established. The spatial coordinates of the occupant's head, shoulders, and hips are transformed into the posture analysis coordinate system to obtain normalized head coordinates, normalized shoulder coordinates, and normalized hip coordinates. Based on normalized head coordinates and normalized shoulder coordinates, the lateral distance between the occupant's head center point and the longitudinal central axis of the seat is calculated as the head lateral offset feature. Based on the normalized shoulder coordinates and the normalized hip coordinates, the angle between the line connecting the side profile of the torso and the perpendicular line of the reference plane is calculated as the torso tilt feature. By analyzing the optimized pressure distribution data, the ratio of the total pressure in the left side area of ​​the seat back to the total pressure in the right side area is obtained to obtain the pressure distribution balance ratio. The pressure distribution equalization ratio is used to verify the directional consistency of the trunk tilt characteristic. The verification is considered successful when the trunk tilt characteristic indicates a leftward tilt and the pressure distribution equalization ratio is greater than a predetermined value, or when the trunk tilt characteristic indicates a rightward tilt and the pressure distribution equalization ratio is less than a predetermined value. If the verification is successful, the trunk tilt characteristic is taken as the effective tilt angle. If the verification fails, the angle correction is calculated based on the numerical difference between the pressure distribution equalization ratio and the trunk tilt characteristic. The effective tilt angle is obtained by adding the trunk tilt characteristic and the angle correction. Numerical translation compensation is performed on the lateral head offset feature based on the effective tilt angle to obtain the compensated lateral head offset. In the posture analysis coordinate system, the rotation angle of the torso around the vertical axis is calculated based on the spatial vector relationship between the normalized shoulder coordinates and the normalized hip coordinates, and is used as the torso rotation angle; the effective tilt angle, the compensated lateral head offset, and the torso rotation angle are used as key feature parameters to determine multiple sitting postures. 6.The method of claim 5, wherein, Based on the occupant's seating posture and multiple key posture feature parameters, adaptive adjustment planning is performed on multiple independent control areas of the side curtain airbags to generate a real-time adjustment strategy, specifically including the following steps: Define multiple independent control zones for the side curtain airbags; Based on the occupant's sitting posture, basic adjustment planning is performed on multiple independent control areas to generate multiple basic adjustment parameters; Based on multiple key characteristic parameters of sitting posture, multiple basic adjustment strategies are adaptively optimized to generate multiple optimized adjustment parameters. Based on the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, the response to multiple optimization adjustment parameters is optimized to generate a real-time adjustment strategy. 7.The method of claim 6, wherein, Based on multiple key characteristic parameters of sitting posture, adaptive optimization of multiple basic adjustment strategies is performed to generate multiple optimized adjustment parameters, specifically including the following steps: The compensated lateral head offset and the effective roll angle are weighted and combined to calculate the risk assessment value of the occupant's head offset relative to each independent control area in a side collision. The torso rotation angle is converted into a stiffness influence coefficient for supporting multiple independent control zones of the contralateral air curtain. The trigger timing parameters of each independent control area are optimized and adjusted based on the offset risk assessment value. For areas where the offset risk assessment value is higher than the preset threshold, the trigger priority of the target area is increased and the trigger time is set in advance. The basic inflation volume of each independent control area is optimized and adjusted based on the stiffness influence coefficient. For areas where the stiffness influence coefficient is higher than the preset threshold, the basic inflation volume of the target area is increased according to the preset ratio to obtain the preliminary optimized parameters of each independent control area. The preliminary optimization parameters for each independent control area are globally coordinated and verified. If the triggering time interval between adjacent areas is found to be less than the preset minimum safety interval, the triggering time of the later-triggered area is delayed until the preset minimum safety interval is met. If the inflation volume difference between adjacent areas is found to exceed the preset maximum allowable pressure difference, the inflation volume of the area with higher inflation volume is appropriately reduced until the inflation volume difference between adjacent areas is less than the preset maximum allowable pressure difference, so as to obtain the intermediate optimization parameter set for internal coordination. The intermediate optimization parameters in the intermediate optimization parameter set for internal coordination are used as multiple optimization adjustment parameters. 8.The method of claim 7, wherein, Based on the occupant's sitting posture and multiple key posture feature parameters, the response optimization of multiple optimization adjustment parameters is performed to generate a real-time adjustment strategy, specifically including the following steps: Based on the occupant's seating posture and multiple key characteristic parameters of the seating posture, a risk analysis of the driving seating posture is conducted to determine the risk level; Based on the risk level, the triggering priority of multiple independent control areas is determined; Based on the multiple trigger priorities, the multiple optimization adjustment parameters are optimized in response to generate a real-time adjustment strategy. 9.The method of claim 8, wherein, Based on the occupant's seating posture and multiple key characteristic parameters of the seating posture, a risk analysis of the driving seating posture is conducted to determine the risk level, specifically including: The occupant's sitting posture is mapped to a posture reference risk value; wherein, the mapping to the posture reference risk value includes: the standard sitting posture in the occupant's sitting posture corresponds to the low reference value in the reference risk value, the lateral sitting posture in the occupant's sitting posture corresponds to the medium reference value in the reference risk value, and the forward-leaning sitting posture in the occupant's sitting posture corresponds to the high reference value in the reference risk value. Based on the compensated lateral head offset, calculate the head position risk gain factor; wherein, the calculation of the head position risk gain factor includes: for every preset unit offset increase in the compensated lateral head offset, the head position risk gain factor increases linearly by a preset unit gain value. Based on the effective roll angle, calculate the roll attitude risk gain factor; wherein, the calculation of the roll attitude risk gain factor includes: for every preset unit angle increase in the effective roll angle, the roll attitude risk gain factor increases according to a preset nonlinear relationship curve; The trunk torsion risk gain factor is calculated based on the trunk rotation angle. The calculation of the trunk torsion risk gain factor includes: for every preset unit rotation angle increase in the trunk rotation angle, the trunk torsion risk gain factor increases according to a preset exponential relationship. The attitude baseline risk value is multiplied and fused with the head position risk gain factor, the lateral posture risk gain factor, and the trunk torsion risk gain factor to obtain the comprehensive risk index. Input the comprehensive risk index into the preset risk level mapping table to obtain the final determined risk level.

10. The side curtain airbag morphology adjustment method based on occupant seating posture adaptation according to claim 9, characterized in that, The process of conducting vehicle collision monitoring and, in the event of a dangerous vehicle collision, controlling the inflation of the side curtain airbags according to the aforementioned real-time adjustment strategy specifically includes the following steps: Conduct vehicle collision monitoring and acquire collision monitoring data; The collision monitoring data is analyzed to determine whether a vehicle collision has occurred. When determining that a vehicle collision has occurred, the intensity of the collision must be determined. The vehicle collision intensity is compared with a preset danger threshold intensity to determine whether a dangerous vehicle collision has occurred. When a dangerous vehicle collision is determined to have occurred, the side curtain airbags are inflated accordingly in accordance with the real-time adjustment strategy described above.

11. A side curtain airbag morphology adjustment system based on occupant seating posture adaptation, characterized in that, The system employs the side curtain air morphology adjustment method based on occupant seating posture adaptation as described in any one of claims 1-10, and the system includes: The relevant data acquisition unit is used to collect seat pressure distribution data and occupant human body space data when in the adjustment and wake-up state; The data processing and identification unit is used to synchronously process the seat pressure distribution data and the occupant human body space data, identify the occupant's sitting posture, and determine multiple key characteristic parameters of the sitting posture. An adaptive adjustment planning unit is used to adaptively adjust and plan multiple independent control areas of the side curtain airbag according to the occupant's sitting posture state and multiple key characteristic parameters of the sitting posture, and generate a real-time adjustment strategy. The collision inflation control unit is used to monitor vehicle collisions and, in the event of a dangerous vehicle collision, to control the inflation of the side curtain airbags according to the real-time adjustment strategy.

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