# A Review of Seatbelt Technologies and Their Role in Vehicle Safety
## 3 Results
### Autonomous Vehicles and Adaptive Seatbeltls  
Autonomous vehicles bring with them an increased degree of comfort, often achieved by rotating and tilting the occupant seats. Sometimes the occupants sit in uncomformable positions, defined in the specialized literature as OOP, out of position. Thus in [62], the authors conducted simulations, which can later be complemented by physical testing. In the study, they identified several parameters that have a greater influence on the level of injury. The simulation results suggest that both kinematics and injuries resulting from inclined configurations with a seatback at 40 degrees are sensitive to the pulse severity, seat pan, and pelvis angles. For a 15 degrees seat pan configuration and a belt restraint usingtwo pretensioners, the pelvis initial angle could lead to either a proper occupant restraint or submarining associated with significant injury risk. An analysis of the literature regarding disabled people who use wheelchairs in autonomous vehicles, emphasizing that it is necessary to secure the wheelchair to the vehicle and provide occupant protection with a Wheelchair Tiedown and Occupant Restraint System (WTORS), is made in [63]. For this population to use an autonomous vehicle, a WTORS must be crashworthy for use in smaller vehicles, able to be used independently, and adaptable for a wide range of wheelchair types. Currently available WTORS do not have these characteristics, but a universal docking interface geometry and prototype automatic seatbelt donning systems have been developed. The study presented in [64] was performed on a sled test rig using a 50 cc Hybrid III dummy according to a full factorial experiment. In addition, input factors were selected in order to verify a safe test condition for surrogate testing. The measured value was head acceleration, which was used for the calculation of a head injury criterion. What was found was an optimal seat angle of 117 degrees at which the head injury criteria had the lowest represented value. Moreover, preliminary body dynamics showed a danger of whiplash occurrence for occupants in a fully reclined seat. Experiments on cohorts of passengers of different ages, in vehicles performing obstacle avoidance maneuvers, were conducted in [65]. The study examined kinematics, muscle activity, and seatbelt load distribution. Children showed different neuromuscular control of head and trunk motion compared to older occupants. The transition to autonomous mobility demands a radical rethinking of seatbelt design and functionality. Integrating passive restraints with active vehicle intelligence systems is no longer optional; it is essential. Adaptive, AI-enhanced seatbelt systems capable of interpreting a wide array of sensory data offer a promising pathway to meet the complex safety demands of autonomous environments. However, further research, simulation, and interdisciplinary collaboration will be very important in ensuring these technologies are both effective and equitable. Recent advancements in vehicle safety systems have increasingly focused on the integration of artificial intelligence and multi-modal sensor fusion to enhance occupant protection--an approach highly relevant to adaptive seatbelt design in autonomous vehicles. Ref. [66] demonstrated the efficacy of multi-level sensor fusion in modeling driving behavior, where data from LIDAR, radar, and visual sensors were synthesized to predict and respond to vehicular dynamics. This methodological framework directly supports the feasibility of a sensor-rich seatbelt system capable of responding to real-time collision risks by modulating belt tension accordingly. Similarly, ref. [67] introduced a deep learning model--Gated Bi-directional Long Short-Term Memory with Part-to-Whole Attention (GBL-PA)--that effectively detects seatbelt usage using video data, underscoring the potential of AI in occupant behavior recognition.