CHILD SAFETY IN AUTONOMOUS VEHICLES: "LIVING ROOM" LAYOUT

Autonomous vehicles start to be introduced on our roads and will soon become a reality. Although fatal traffic accidents will be significantly reduced, remaining fatal passenger car crashes should be taken into account to ensure the safety of users. The new highly adaptable interior designs, with totally different layouts from the current ones, may significantly impact occupant safety, especially child passenger safety. Analyzing how these new vehicles affect child safety is a challenge that needs to be addressed. The "living room" layout (face-to-face seating position) is one of the preferences of families traveling with children. Young children need further support and supervision so the possibility of rotating seats to be able to be in front of the small children is a valuable feature for parents. Therefore, new seating orientations away from the forward facing position should be taken into account to ensure children protection. The objective of this study is to evaluate child occupant safety in a "living room" seating position (a possible option in full autonomous vehicles) versus the current forward facing position. Virtual testing methodology was used to perform this study. The virtual PIPER child human body model (HBM) was used. This model is one of the only HBMs developed and validated from child PMHS data (Paediatric Post-Mortem Human Surrogate). The two configurations were defined according with the EuroNCAP child occupant protection test protocol. It was found that the "living room" layout presents worse results according to the child's head injury patterns than in forward facing position. In conclusion, attending to the new seating orientations away from the forward facing position, it is necessary to adapt the restraint systems; otherwise children could suffer potentially dangerous situations.

Telehealth Applied to Deliver In-situ Behavioral Skills Training to Reduce Car Seat Misuse During the Covid-19 Pandemic

ObjectiveThe use of telehealth has been a common approach to deliver health education before and during the COVID-19 pandemic. However, its ability to apply behavioral skills training (BST) for CRS education has been undocumented. This study assessed the efficacy of telehealth to deliver in-situ behavioral skills training (BST) to teach expectant parents how to install and use their child restraint system (CRS) to reduce misuse and improve retention during the COVID-19 pandemic.MethodA repeated measures group design was used to evaluate 171 individual participants, in a 37-step CRS task analysis for baseline, BST, and follow-up. Performance across all participants was aggregated for each task analysis. Participants were recruited from National Highway Traffic Safety Administration car seat fitting stations during the Covid-19 pandemic between March through July, 2020.ResultsBaseline results identified significant critical misuse across participants. With BST, delivered with telehealth, misuse decreased by 97% among 37 task objectives. A 2-week follow-up evaluation concluded that 100% of participants retained the skills they mastered during BST.ConclusionsThis study suggests the use of telehealth, as a method of BST delivery for CRS education, is an effective approach to reduce CRS misuse and the burden of child occupant motor vehicle injury. It was found to empower participants and improve their self-confidence, while ensuring the safety of their child occupant. While it was found to be an effective approach for expectant parents during the COVID-19 pandemic, it also has broader child passenger safety program and train-the-trainer implications beyond the COVID-19 pandemic.

A Peak-Selection RBF Mesh Morphing Method for Subject-Specific Child Occupant Modeling

The mesh morphing method is widely applied in building subject-specific human finite element models. However, there are many problems yet to be resolved when applying the mesh morphing method in subject-specific modeling, such as calculation difficulties and low morphing accuracy. To solve these problems above, an efficient peak-selection RBF mesh morphing method is proposed in the paper. Firstly, by comparing different types of radial basis functions, an optimal kernel function is selected to improve morphing accuracy. Secondly, the landmarks are reduced by selecting multiple peak nodes from the object surfaces, so as to reduce iteration steps and improve the mesh generation efficiency. The proposed peak-selection Radial Basis Function (RBF) mesh morphing method is further demonstrated through a subject-specific child finite element modeling problem. This mesh morphing method has important significance for analyzing the occupant injury of different body features in motor vehicle crashes.