Taking SAFER HBM to the global arena; focusing the cervical and thoracic spine
Reference number | |
Coordinator | Volvo Personvagnar AB - Volvo Car Corporation |
Funding from Vinnova | SEK 4 109 000 |
Project duration | November 2022 - December 2024 |
Status | Ongoing |
Venture | Safe automated driving – FFI |
Call | Safe automated driving – FFI |
Purpose and goal
The purpose of the project is to make SAFER HBM a biofidelic, robust, competent, and attractive tool for the project partners’ needs, also including being available to the community. Specific goals include to further improve the model, with special attention on spinal kinematics and injury risk prediction, and to enable global use of the model by preparing it for Free-Access. The SAFER HBM will have capabilities to model the combined pre-crash and in-crash occupant in-crash response including muscle activation which is crucial for instance for prediction of cervical spine injuries.
Expected effects and result
Preparing the spine for detailed injury prediction will increase the ability of HBM to be used for cervical spine soft tissue injury prediction. By exchanging the remaining proprietary model parts from SAFER HBM and establishing the framework for providing the model as Free-Access, we establish the model as one a few potential HBMs to be used for future planned VT protocols by the consumer information organizations. This project will strengthen SAFER HBM as a global acknowledged tool, which benefits the Swedish industries to continue be leading in vehicle safety system development.
Planned approach and implementation
The spinal curvature of the updated SAFER HBM is defined based on a literature review, in addition to a study using volunteers seated in a vehicle seat. The cervicothoracic spine model is modelled, and the models of the spine, shoulders, femurs and knees are integrated into the whole body SAFER HBM, whereby the model will be improved and third party IP restrictions removed. In parallel, relevant spinal injury mechanisms and tissues are identified to become the foundation of injury risk prediction functions. In addition, a framework for sharing the model as Free-Access is developed.