We present Omniverse, a set of configurable abstractions for efficient developments of complex driving events during simulated driving scenarios. The goal of Omniverse is to identify the inefficiency of existing scenario implementations and provide an alternative design for ease-of-implementations for simulated driving events. We first investigate the standard code base of driving scenarios and abstract their overlapped building blocks through mathematical models. Then, we design and implement a set of flexible and configurable abstractions as an external library, to allow further developments and adaptions for more generalized cases. Finally, we validate the correctness and examine the effectiveness of Omniverse through standard driving scenarios' implementations, and the results show that Omniverse can (1) save 42.7% development time, averaged across all participants; and (2) greatly improve the overall user experience via significantly improved readability and extendability of codes. The whole library of Omniverse is online at https:// github.com/unnc-ucc/Omniverse-OpenDS.
