A vehicle safety control method based on front passenger departure perception

Abstract

The present invention provides a vehicle safety control method based on front-seat occupant out-of-position sensing, comprising: step S11, establishing a seat base coordinate system; step S12, forming an occupant key coordinate system; step S13, establishing a front-seat occupant restraint system key geometric parameter model; step S14, building an active avoidance AEB / AES strategy model library; step S15, obtaining a comprehensive out-of-position parameter according to a first preset rule based on the front-seat occupant restraint system key geometric parameter model and the active avoidance AEB / AES strategy model library; step S16, generating a comprehensive out-of-position index according to a second preset rule based on the comprehensive out-of-position parameter; and step S17, generating an optimal intelligent restraint parameter based on the comprehensive out-of-position index to determine the vehicle safety control strategy. The present invention accurately obtains front-seat occupant position information, determines whether the occupant is in an out-of-position state, accurately assesses the out-of-position impact caused by AEB braking, and optimizes the vehicle safety control strategy.

Description

Technical Field

[0001] The present invention relates to the field of automobiles, and in particular to an automobile safety control method based on front-seat passenger out-of-position perception. Background Art

[0002] In recent years, the China New Car Assessment Program (CNCAP) has introduced AEB (Automatic Emergency Braking) technology into the automotive active safety arena. Its primary function is to reduce collision speed or avoid a collision in the event of a rear-end collision or with a pedestrian. Given the high frequency and proportion of accidents involving two-wheeled electric vehicles in China, the CNCAP has incorporated AEB active braking technology specifically for two-wheeled electric vehicles into its evaluation system. While AEB technology has a wide range of applications and has garnered widespread consumer acclaim, it can also cause occupants, particularly front-seat passengers, to move from their original seating positions and lean forward excessively during AEB braking. This can lead to inappropriate airbag contact timing and location, potentially exacerbating injuries. Consequently, the calibration of airbag firing timing and method under AEB has been a hot research topic.

[0003] With the rapid development of new energy vehicles and autonomous driving technology, smart cockpit technology has mushroomed and become a new and important development direction. Smart cockpit systems primarily consist of driver monitoring (DMS) and occupant monitoring (OMS). The former primarily monitors the driver, utilizing cameras positioned on the steering column or A-pillar; the latter primarily monitors passengers, typically using cameras positioned near the rearview mirror, and may also be supplemented by millimeter-wave radar. In addition to capturing information such as occupant occupancy, driver distraction, fatigue, and facial recognition, cameras also capture key parameters such as the distance between the driver and passenger from the steering wheel and instrument panel based on internal and external camera parameters. These parameters are crucial for evaluating comprehensive departure parameters after AEB intervention.

[0004] Existing technologies primarily use methods such as gaze tracking, facial features, and eye feature classification to monitor drivers for distraction, fatigue, drowsiness, or even coma due to sudden illness. However, algorithms for monitoring driver departure from their seat are nearly nonexistent. Furthermore, existing technologies fail to consider the possibility that front-seat passengers may have already left their seat before AEB initiates braking. Summary of the Invention

[0005] In response to the defects in the existing technology, the purpose of the present invention is to provide a vehicle safety control method based on front-seat passenger out-of-position perception, aiming to accurately obtain the front-seat passenger position information, determine whether the occupant is in an out-of-position state, accurately evaluate the out-of-position impact caused by AEB braking, and optimize the vehicle safety control strategy.

[0006] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solution:

[0007] The present invention provides a vehicle safety control method based on front-seat passenger out-of-position sensing, comprising:

[0008] Step S11: Determine whether the seat is occupied by someone using a seat pressure sensor, determine whether the driver or passenger is wearing a seat belt using a seat belt buckle sensor, and obtain position information using a seat horizontal displacement sensor, a seat vertical displacement sensor, and a seat back angle sensor; establish a seat basic coordinate system based on the information obtained from the seat pressure sensor, the seat belt buckle sensor, the seat horizontal displacement sensor, the seat vertical displacement sensor, and the seat back angle sensor;

[0009] Step S12: identifying key parameters through the OMS camera, including the occupant's seat status, seat belt wearing status, occupant's body shape, and key position information, to form a key coordinate system for the occupant;

[0010] Step S13, establishing a key geometric parameter model of the front occupant restraint system based on the seat basic coordinate system and the occupant key coordinate system;

[0011] Step S14: construct an active AEB / AES avoidance strategy model library through the following process:

[0012] In step S141, a occupant forward leaning basic model library is established;

[0013] In step S142, the vehicle ABS speed information is read from the vehicle chassis CAN bus;

[0014] In step S143, the vehicle pitch angle information is read from the vehicle chassis CAN bus;

[0015] In step S144, an active avoidance AEB / AES strategy model library is established based on the occupant forward leaning basic model library, the vehicle ABS speed information, and the vehicle pitch angle information;

[0016] Step S15, obtaining a comprehensive departure parameter according to a first preset rule based on the front occupant restraint system key geometric parameter model and the active avoidance AEB / AES strategy model library;

[0017] Step S16, generating a comprehensive out-of-position index according to the comprehensive out-of-position parameter and a second preset rule;

[0018] Step S17: forming optimal intelligent constraint parameters based on the comprehensive out-of-position index to determine a safety control strategy for the vehicle.

[0019] Preferably, in step S12:

[0020] Step S121, determining the occupant's seat occupancy status through the OMS combined with the seat pressure sensor information;

[0021] Determine the wearing status of seat belts by judging the seat belt position;

[0022] Identify the body shape of the occupants through body shape judgment;

[0023] Identify key position information, including the distance between the front of the occupant's nose and the steering wheel and instrument panel, as well as information on irregular driving behavior;

[0024] Based on the above judgment results, the occupant key coordinate system is formed.

[0025] Preferably, in step S141:

[0026] The occupant forward tilt basic model library is established based on the 5% percentile occupant forward tilt model library, the 50% percentile occupant forward tilt model library, and the 95% percentile occupant forward tilt model library.

[0027] Preferably, the first preset rule is: obtaining the initial position of the front occupant based on the key geometric parameter model of the front occupant restraint system, obtaining the AEB braking departure increment based on the active avoidance AEB / AES strategy model library, and generating a comprehensive departure parameter by superimposing the AEB braking departure increment on the initial position of the front occupant.

[0028] Preferably, the second preset rule is: the comprehensive out-of-position parameters obtained according to the first preset rule are used to form a comprehensive out-of-position index based at least on the principles of damage risk and characteristic zoning algorithm.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] By introducing OMS parameters, the present invention can more accurately determine the initial key geometric position parameters of the front-seat driver and passengers in a collision accident scenario. At the same time, by performing occupant departure assessment after AEB braking, it can accurately assess the front-seat driver and passenger departure parameters to determine the vehicle safety control strategy after system optimization to maximize the reduction of occupant injury value in the accident and protect the safety of the front-seat occupants. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0032] Figure 1 Schematic diagram of the process described in the embodiment;

[0033] Figure 2Schematic diagram of the process of steps S11-S13 of the method described in the embodiment;

[0034] Figure 3 Schematic diagram of the detailed process of step S14 of the method described in the embodiment DETAILED DESCRIPTION

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0036] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without making any creative efforts shall fall within the scope of protection of the present application.

[0037] It should be noted that similar reference numerals and letters denote similar items in the following figures. Therefore, once an item is defined in one figure, it does not require further definition or explanation in subsequent figures. Furthermore, all directional designations (such as up, down, left, right, front, back, bottom, etc.) in this application are intended only to explain the relative positional relationships and movement of components in a specific posture (as shown in the figures). If the specific posture changes, the directional designations will also change accordingly.

[0038] Example

[0039] This embodiment provides a vehicle safety control method based on front-seat passenger out-of-position perception. It fully utilizes the OMS to capture the front-seat passenger position information in real time, and updates, stores, and feedback key geometric parameters in real time to determine whether the passenger is in an out-of-position state. It also integrates the OMS to monitor the position parameters of the driver and passengers, evaluates the incremental out-of-position caused by AEB braking, and comprehensively optimizes the vehicle safety control strategy (such as the airbag deployment strategy).

[0040] like Figure 1 As shown, the main steps of this embodiment include:

[0041] S11: Obtain the position parameters of the electric seat, such as pressure, horizontal, vertical, backrest angle, and seat belt buckle, and establish the basic coordinate system of the seat. Specifically, Figure 2 As shown:

[0042] The seat pressure sensor is used to determine whether the seat is occupied, the seat belt buckle sensor is used to determine whether the driver and passenger are wearing seat belts, and the seat horizontal displacement sensor, seat vertical displacement sensor, and seat back angle sensor are used to obtain position information;

[0043] A basic seat coordinate system is established based on information from the seat pressure sensor, seatbelt buckle sensor, seat horizontal displacement sensor, seat vertical displacement sensor, and seat back angle sensor. This coordinate system enables more accurate identification of the driver and occupant's position.

[0044] S12: Identify key parameters through the OMS camera, including the occupant's seat status, seat belt wearing status, occupant's body characteristics, and key position information, to form an occupant's key coordinate system to evaluate the out-of-position parameters under different AEB braking strategies. Specifically, Figure 2 As shown:

[0045] The OMS combines information from the seat pressure sensor to determine the occupant's seat occupancy status, for example, whether the seat is occupied by a person, a pet, or a general heavy object.

[0046] The seat belt position is used to determine the seat belt wearing status.

[0047] By judging the body shape, the body shape characteristics of the occupants can be identified. It is further possible to determine whether the occupants' body shapes are close to the 5th percentile, 50th percentile, and 95th percentile population. This fully considers the forward leaning state of occupants of different body shapes, improves the evaluation accuracy of the method of this embodiment, and at the same time improves the evaluation efficiency.

[0048] Identify key position information, including the distance between the front of the occupant's nose and the steering wheel and instrument panel, as well as information on irregular driving behaviors, such as the seat being in a zero-gravity state and the feet being placed above the instrument panel. By identifying relevant information, the driver and occupant status can be taken into account to the greatest extent, making the subsequent model establishment more realistic.

[0049] Based on the above judgment results, the occupant key coordinate system is formed.

[0050] S13: Based on the seat basic coordinate system established in S11 and the occupant key coordinate system formed in S12, establish the key geometric parameter model of the front occupant restraint system, such as Figure 2 shown.

[0051] S14: Build an active avoidance AEB / AES strategy model library, which is implemented through the following process: Figure 3 As shown:

[0052] In step S141, a basic occupant forward tilt model library is established. Furthermore, a 5% percentile occupant forward tilt model library, a 50% percentile occupant forward tilt model library, and a 95% percentile occupant forward tilt model library may be established first. The basic occupant forward tilt model library is then established based on the established occupant forward tilt model libraries of different percentiles, thereby fully considering the forward tilt states of occupants of different body types and improving the assessment accuracy of the method of this embodiment.

[0053] In step S142, the vehicle ABS speed information is read from the vehicle chassis CAN bus;

[0054] In step S143, the vehicle pitch angle information is read from the vehicle chassis CAN bus;

[0055] In step S144, an active avoidance AEB / AES strategy model library is established based on the occupant forward lean basic model library, the vehicle ABS speed information, and the vehicle pitch angle information.

[0056] S15: Based on the front occupant restraint system key geometric parameter model and the active avoidance AEB / AES strategy model library, a comprehensive out-of-position parameter is obtained according to a first preset rule for accurately assessing the out-of-position impact caused by AEB braking. Specifically, the first preset rule is to obtain the front occupant's initial position based on the front occupant restraint system key geometric parameter model, obtain the AEB braking out-of-position increment based on the active avoidance AEB / AES strategy model library, and then superimpose the AEB braking out-of-position increment on the front occupant's initial position to generate a comprehensive out-of-position parameter. This allows for accurate and realistic assessment of occupant out-of-position after AEB braking.

[0057] S16: Generate a comprehensive out-of-position index based on the comprehensive out-of-position parameters according to a second preset rule. Furthermore, the second preset rule is: The comprehensive out-of-position index is generated based on the comprehensive out-of-position parameters obtained according to the first preset rule, at least based on the injury risk and characteristic zoning algorithm principles. It should be noted that the comprehensive out-of-position index may also be generated based on other algorithmic principles, and this embodiment is not limited thereto.

[0058] S17: Based on the comprehensive out-of-position index, optimal intelligent constraint parameters are formed to determine the vehicle's safety control strategy, such as the airbag deployment strategy.

[0059] Based on real-world collision scenarios, this embodiment introduces OMS parameters to more accurately determine the initial key geometric position parameters of front-seat occupants in a collision. This embodiment further utilizes these initial key parameters to perform post-AEB occupant departure assessment, resulting in a more accurate and realistic assessment. Based on this accurate assessment of front-seat occupant departure parameters, system-optimized vehicle safety control strategies (such as airbag deployment strategies) can minimize occupant injury in an accident and protect the safety of front-seat occupants.

[0060] The above describes the specific embodiments of the present invention. Based on the above description, relevant personnel can make various changes and modifications without departing from the scope of the technical concept of this invention.

Claims

1. A vehicle safety control method based on front passenger departure perception, characterized in that: include: Step S11: Determine whether the seat is occupied by someone using a seat pressure sensor, determine whether the driver or passenger is wearing a seat belt using a seat belt buckle sensor, and obtain position information using a seat horizontal displacement sensor, a seat vertical displacement sensor, and a seat back angle sensor; establish a seat basic coordinate system based on the information obtained from the seat pressure sensor, the seat belt buckle sensor, the seat horizontal displacement sensor, the seat vertical displacement sensor, and the seat back angle sensor; Step S12: identifying key parameters through the OMS camera, including the occupant's seat status, seat belt wearing status, occupant's body shape, and key position information, to form a key coordinate system for the occupant; Step S13, establishing a key geometric parameter model of the front occupant restraint system based on the seat basic coordinate system and the occupant key coordinate system; Step S14: construct an active AEB / AES avoidance strategy model library through the following process: In step S141, a occupant forward leaning basic model library is established; In step S142, the vehicle ABS speed information is read from the vehicle chassis CAN bus; In step S143, the vehicle pitch angle information is read from the vehicle chassis CAN bus; In step S144, an active avoidance AEB / AES strategy model library is established based on the occupant forward leaning basic model library, the vehicle ABS speed information, and the vehicle pitch angle information; Step S15, obtaining a comprehensive departure parameter according to a first preset rule based on the front occupant restraint system key geometric parameter model and the active avoidance AEB / AES strategy model library; Step S16, generating a comprehensive out-of-position index according to the comprehensive out-of-position parameter and a second preset rule; Step S17: forming optimal intelligent constraint parameters based on the comprehensive out-of-position index to determine a safety control strategy for the vehicle.

2. The automobile safety control method based on front-seat passenger departure sensing according to claim 1, characterized in that: In step S12: Step S121, determining the occupant's seat occupancy status through the OMS combined with the seat pressure sensor information; Determine the wearing status of seat belts by judging the seat belt position; Identify the body shape of the occupants through body shape judgment; Identify key position information, including the distance between the front of the occupant's nose and the steering wheel and instrument panel, as well as information on irregular driving behavior; Based on the above judgment results, the occupant key coordinate system is formed.

3. The automobile safety control method based on front passenger departure perception according to claim 1, characterized in that: In step S141: The occupant forward tilt basic model library is established based on the 5% percentile occupant forward tilt model library, the 50% percentile occupant forward tilt model library, and the 95% percentile occupant forward tilt model library.

4. The automobile safety control method based on front-seat passenger departure sensing according to claim 1, characterized in that: The first preset rule is: obtain the initial position of the front occupant based on the key geometric parameter model of the front occupant restraint system, obtain the AEB brake departure increment based on the active avoidance AEB / AES strategy model library, and generate a comprehensive departure parameter by superimposing the AEB brake departure increment on the initial position of the front occupant.

5. The automobile safety control method based on front-seat passenger departure sensing according to claim 1, characterized in that: The second preset rule is: the comprehensive out-of-position parameters obtained according to the first preset rule are used to form a comprehensive out-of-position index based on at least the damage risk and characteristic zoning algorithm principles.

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