The IFAS project set out to create an Injury Risk Model (IRM) that can predict the severity of passenger injuries for a wide range of seat positions and crash scenarios in future autonomous vehicles. The core scientific achievement was the construction of a matrix that links crash kinematics, seat geometry and occupant characteristics to injury metrics such as thoracic, head and neck injury risk. The matrix was populated with data from Hybrid‑III 50 % dummy tests and evaluated against the U.S. FMVSS 208 standard. The resulting tables were colour‑coded to provide an intuitive visual assessment of risk levels. To make the complex data set accessible, a demonstrator was built that displays the injury matrix in real time. The demonstrator uses a commercial stereo camera to locate the occupant in the seat; the camera data are only used for visualisation and seat‑position determination, while future production vehicles will rely on radar or automotive‑grade camera solutions. The demonstrator was presented at the Airbag 2022 conference, marking the first public showcase of the IRM.

Beyond the matrix, the project developed a simulation tool that interpolates between discrete crash types. The interpolation is driven by a pre‑crash safety monitor component, which was created with internal resources. By blending injury values from neighbouring crash scenarios, the tool can generate smooth transitions in risk assessment as the occupant moves through different seat positions. The seat demonstrator visualises these interpolated risks as trajectory sectors, allowing designers to see how small changes in seating geometry affect injury outcomes. The IRM also informs the selection of restraint systems: it can determine the minimum acceptable vehicle speed for a given seat position, the required sensor accuracy for occupant detection, and the optimal restraint configuration for each crash constellation. The project performed a generic hazard and risk analysis in line with ISO 26262 to ensure functional safety compliance for automotive applications.

The project’s financial footprint was dominated by personnel costs (€491 404,82) and external services from Continental Alzenau (€206 352,28), together covering 90 % and 87 % of the planned budget, respectively. Travel expenses were not incurred because pandemic restrictions prevented any trips. The funding came from the IFAS programme, a German initiative aimed at advancing vehicle safety research. The project’s partners included Continental, Indie Semiconductor FFO GmbH, Technische Hochschule Ingolstadt, Technische Universität Chemnitz and CMORE Automotive GmbH. Continental led the overall coordination and provided the core development platform, while the universities supplied research expertise in biomechanics and simulation. The semiconductor partner contributed sensor‑processing algorithms, and CMORE Automotive supplied vehicle integration expertise.

The IRM has already entered a production‑grade project commissioned by Continental, and a second series project is currently in the bidding phase. The demonstrator and simulation tools developed during IFAS are expected to accelerate the integration of adaptive restraint activation in future vehicles, supporting the industry’s goal of zero traffic fatalities. The project’s results demonstrate that a data‑driven injury risk assessment can guide the design of seat‑position‑aware safety systems, ensuring that new interior concepts do not compromise occupant protection while enabling the benefits of autonomous driving.