Sean Hubbard

Sean Hubbard is a research scientist at GCAPS. Prior to joining GCAPS, Hubbard spent more than six years studying the design of mechanisms to exploit linear and non-linear dynamics in aerospace, marine, and civil defense applications. He was responsible for the design and implementation of computational models of dynamic systems, model validation, design optimization and system identification. More recently he worked as a product development engineer for a manufacturer of industrial pneumatic machinery where he acted as the project manager for development projects and was responsible for engineering the design of new products.

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Presentation

Reduction of parameter space scenario testing via safety model

Reduction of the parameter space for synthetic scenario creation is conducted with a novel approach using the GCAPS safety model. Using real-world data from perception systems, CISS, or naturalistic driving data, the decomposition process of GCAPS creates a concrete scenario. The concrete scenario is parameterized, and ranges of the parameters are identified. The safety model uses the object trajectories, road path and informed statistics to determine several metrics such as conflict probability. Applying the safety model to the concrete scenario and parameter ranges segregates the parameter space by the safety model metrics, enabling a focused evaluation of the ADAS.