Current Analysis Methods
SAE J941: Current SAE recommendation is a drafting practice that establishes eye locations within a described range or population. The procedures manually test 95th and 99th eyellipses for a 50/50 adult gender mix audit user population.
SAE J1050: Current SAE recommendations are three drafting approximation methods for describing and measuring the driver’s direct and indirect obstructions within specific vision fields.
These SAE recommended methods are all completely manual, high-cost, complex to initiate, achieve low accuracy, and are proven to be extremely time-consuming.
Ocular3D Analysis Advantage
Ocular3D combines advanced computer-aided engineering (CAE) and virtual reality (VR) with advanced machine learning (ML) algorithms. These digital methods are specifically programmed to learn the product and provide optimizations specific to man-machine interfaces. Visualization Analysis™ becomes accurate, efficient, and effective.
Necessary Guidelines Ocular3D Meets
J941 analysis capabilities example:
Determines driver field of view or obstructions for a single pair of eye points. You can perform multiple iterations of those points in Ocular3D with a single click.
Determines driver field of view or obstructions using the SAE Eyellipses for a percentage of a described population. You can perform multiple iterations of populations in Ocular3D with a single click.
Determines driver field of view or obstructions for which the range of those specific points were arranged. You can perform multiple iterations of those specific points in Ocular3D with a single click.
For OEMs, the Benefits of Using Ocular3D for SAE J941/J1050 Analysis are Clear
- Meet regulatory compliance mandates for both domestic and export vehicles
- Demonstrate and illustrate proof of compliance for items captured in the Federal Registry (i.e. FMVSS101) to provide clear litigation avoidances
- Regularly meet or exceed specific regulatory certifications resulting in less certification withdrawals
- Advanced machine learning brings opportunity for direct and optimized learnings extracted (functions 1,2,3) for both virtual and physical test subjects
- Eliminate unnecessary production costs and enhance OEM best practices with advanced machine learning (ML) optimization