Vehicle Model Simplification for Efficient Pedestrian Safety Assessment

Pablo Lozano･Simona Roka･Lucia Vizuete (Applus IDIADA)･Xufeng Li (IDIADA China)･Andre Eggers (BASt)

Pedestrian accidents represent a persistent global public health challenge requiring continued attention. Current assessments employ advanced impactor systems; however, these standardized methods face inferior bio-fidelity in capturing biomechanical responses compared to HBM). HBMs offer superior anatomical accuracy but require substantial computational resources, limiting their practical application in safety evaluations. This research investigates a vehicle model simplification methodology to enhance computational efficiency while maintaining HBM accuracy. The study employs the open-source Nissan Rogue model with HBMs, alongside conventional impactor models, within the LS-DYNA simulation environment. The proposed simplification approach reduces computational burden while preserving kinematic fidelity, thereby enabling more extensive investigations.

AI-driven motorcycle risk analysis: Novel insights for safety development

Genis Mensa･Diego Martin･Pol Garriga (Applus IDIADA)

Building upon our published Exposure-Based Risk Index methodology, we present novel AI-driven analysis of 4+ million Spanish motorcycles revealing counterintuitive safety patterns. Key findings: newer motorcycles (0-5 years) show +15.4% accident overrepresentation despite comprising minority of fleet; middle-mileage vehicles (2,000-5,000 km/year) demonstrate peak risk in non-linear relationship; low engine motorcycles (≤125cc) can be more dangerous for serious injuries than high engine variants. IDIADA's integration of advanced data analytics with comprehensive physical and virtual crash testing capabilities enables motorcycle OEM partners to develop targeted, evidence-based safety strategies based on quantified real-world risk patterns.

Injury Analysis of Occupants in Reclining Seated Posture

Tomohiro Izumiyama (Mazda)･Norihiro Nishida (Department of Orthopedic Surgery at Yamaguchi University hospital)･Masahiro Koike (Department of Radiological Technology at Yamaguchi University hospital)

To reduce fatalities and serious injuries caused by traffic accidents, it is important to maintain proper seating posture and occupant restraint. The seating posture of occupants varies among individuals and affects the restraint provided by seatbelts. In this study, we analyzed the individual variabilities in potential occupant postures and predicted injury risks during collisions using human body models.

Analysis of the Effect of Restraint Devices on Maxillofacial Fractures in Frontal Collisions

Hitoshi Ida･Michihisa Asaoka･Masashi Aoki (TOYODA GOSEI)･Masahito Hitosugi (Shiga University of Medical Science)

Maxillofacial fractures require a prolonged treatment period and cause significant stress to the injured individuals due to postoperative pain and restricted mouth opening caused by intermaxillary fixation, among other factors. This study aims to analyze the incidence of maxillofacial fractures in motorvehicle collisions and their influencing factors using accident investigation databases, and to elucidate effective occupant protection technologies.