The introduction of automated L5 driving technologies will revolutionise the design of vehicle interiors and seating configurations, improving occupant comfort and experience. It is foreseen that pre-crash emergency braking and swerving manoeuvres will affect occupant posture, which could lead to an interaction with a deploying airbag. This research addresses the urgent safety need of defining the occupant’s kinematics envelope during that pre-crash phase, considering rotated seat arrangements and different seatbelt configurations. The research used two different sets of volunteer tests experiencing L5 vehicle manoeuvres, based in the first instance on 22 50th percentile fit males wearing a lap-belt (OM4IS), while the other dataset is based on 87 volunteers with a BMI range of 19 to 67 kg/m2 wearing a 3-point belt (UMTRI). Unique biomechanics kinematics corridors were then defined, as a function of belt configuration and vehicle manoeuvre, to calibrate an Active Human Model (AHM) using a multi-objective optimisation coupled with a Correlation and Analysis (CORA) rating. The research improved the AHM omnidirectional kinematics response over current state of the art in a generic lap-belted environment. The AHM was then tested in a rotated seating arrangement under extreme braking, highlighting that maximum lateral and frontal motions are comparable, independent of the belt system, while the asymmetry of the 3-point belt increased the occupant’s motion towards the seatbelt buckle. It was observed that the frontal occupant kinematics decrease by 200 mm compared to a lap-belted configuration. This improved omnidirectional AHM is the first step towards designing safer future L5 vehicle interiors.
With the increasing use of Computer Aided Engineering, it has become vital to be able to evaluate the accuracy of numerical models. This research poses the problem of selection of the most accurate and relevant correlation solution to a set of corridor variations. Specific methods such as CORA, widely accepted in industry, are developed to objectively evaluate the correlation between monotonic functions, while the Minimum Area Discrepancy Method, or MADM, is the only method to address the correlation of non-injective mathematical variations, usually related to force/acceleration versus displacement problems. Often, it is not possible to differentiate objectively various solutions proposed by CORA, which this paper proposes to answer. This research is original, as it proposes a new innovative correlation optimisation framework, which can select the best CORA solution by including MADM as a subsequent process. The paper and the methods are rigorous, having used an industry standard driver airbag computer model, built virtual test corridors and compared the relationship between different CORA and MADM ratings from 100 Latin Hypercube samples. For the same CORA value of ‘1’ (perfect correlation), MADM was capable to objectively differentiate between 13 of them and provide the best correlation possible. The paper has recommended the MADM settings n = 1; m = 2 or n = 3; m = 2 for a congruent relationship with CORA. As MADM is performed subsequently, this new framework can be implemented in already existing industrial processes and provide automotive manufacturers and Original Equipment Manufacturers (OEM) with a new tool to generate more accurate computer models.
This research investigates a computational method, which can assist the development of occupants’ passive safety in future autonomous vehicles, more particularly in the definition of head kinematics in rotated seat arrangement during emergency braking. To capture these head motions, the methodology utilised an Active Human Model, whose head kinematics were validated in a previous work in three-point and lap-belt restraint configuration scenarios. A sled model was then built where the seat backrest angle (SBA) and the seat orientation, modelled by rotating the acceleration angle (AA), could be adjusted to represent various ‘living room’ seating conditions. A Design of Experiments study was then performed by varying AA from 0° to 360° in steps of 22.5° and SBA from 20° to 60° in steps of 8°. The responses were subsequently converted into a Reduced Order Model (ROM), which was then successfully validated through a comparison with the kinematic responses predicted with simulations. In terms of simulation time, it was found that the ROM was able to calculate the head kinematics in 3 s instead of the 1.5 h taken using Simcenter Madymo, without compromising predicted responses accuracy. This research has provided a unique method to define head kinematics corridors for seated occupants in autonomous vehicle interiors, including maximum head excursion, head kinematics as a function of time and define for the first time (a) the safe “or’ but not both head envelope within the cabin interior, and (b) capture the seated scenarios where head proximity to airbag systems could be of concern, following emergency braking.
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