## 1 Introduction
Occupants of autonomous vehicles might be seated farther back from the cockpit area due to the absence of a need for driving, which could potentially reduce the effectiveness of traditional restraint systems such as knee bolsters and knee airbags. In conventional vehicles, knee bolsters can help mitigate submarining in frontal crashes. Their position plays a critical role in controlling pelvis rotation and protecting the spine [22]. Crash analyses have shown that when knee bolsters are removed during a 56 km/h frontal crash, it is difficult to prevent submarining using conventional occupant restraint systems [20; 21]. Furthermore, in various unconventional seating positions, BPI seatbelts might not be practical, prompting the anticipated adoption of belt-in-seat (BIS) systems [23]. Therefore, to evaluate crash safety in autonomous vehicles, it is necessary to consider seat track positions farther from the instrument panel, where occupants are not restrained by knee bolsters, in conjunction with the implementation of BIS systems. To enable such investigations, simulation tools capable of capturing occupant behavior during both pre-crash and crash phases are essential. Active human body models accounting for muscle activity are used widely tools [24]. Various active human models are available, including finite element (FE) models (such as the Global Human Body Modeling Consortium v6.0 (GHBMC) [25], Total Human Model for Safety v6.1 (THUMS) [26], and SAFER Human Body Model v10 (SAFER) [27]) and multi-body (MB) models such as the MADYMO (Siemens, Munich, Germany) Active human body model (AHBM) [28]. FE human body models (HBMs) have the potential to achieve higher biofidelity than MB models because they can represent the human body in greater detail. However, this increased fidelity comes at a significantly higher computational cost, making them challenging to use in large-scale parametric studies. Some studies have found that automatic emergency braking (AEB) activation can alter occupants' injury risks during frontal and side-impact crashes using FE human body models. However, these studies were performed under limited crash or restraint conditions [29; 30]. Similarly, other studies have investigated the effects of seatback angle and seat position without considering occupant excursion due to emergency braking [20; 21; 31; 32]. In contrast, MB HBMs, such as the MADYMO AHBM, are computationally efficient and better suited for studies requiring a high number of simulations. Therefore, it would be meaningful to investigate the effect of emergency braking prior to a crash on the injury risk of occupants considering other autonomous vehicle relevant parameters such as seatback angle, seat track position, autonomous vehicle relevant crash conditions, and so on using computationally efficient MB HBMs. Considering these distinctive natures of autonomous vehicle crashes, e.g., occupant posture, pre-crash maneuver, and so on, there could be new vehicle crash test conditions that need to be included in vehicle crash safety test protocols. Currently, vehicle crash safety is mainly evaluated by physical tests due to limitations in terms of cost, repeatability, reproducibility, and standardization, which restrict the types of tests that can be conducted. These limitations will also apply when selecting crash safety evaluation conditions for autonomous vehicles. When selecting characteristics to consider in evaluating the crash safety of autonomous vehicles, it is beneficial to understand the relative importance of these characteristics in relation to occupants' injury risk. The objective of this study was to evaluate the effects of autonomous vehicle relevant parameters such as AEB activation, seatback angle, seat track position, and seat belt type on occupant injury risk as an effort to prioritize consideration of those potential parameters in either physical or virtual vehicle crash safety evaluations. First, biofidelity of the MB AHBM was validated for both pre-crash kinematics and injury risk prediction.