We encourage you to read the Release Notes page about the many changes and enhancements from the latest release of RIDE, version 2023.3.
The Rapid Integration & Development Environment (RIDE) is a simulation environment that unites many DoD simulation efforts to provide an accelerated development platform and prototyping sandbox that will provide direct benefit to the Army’s Synthetic Training Environment (STE) as well as the larger DoD simulation communities.
RIDE combines a range of commonly used simulation features in a drag-and-drop development environment, including One World Terrain, NPC and vehicle placement, and AI behaviors.
RIDE is being developed at the USC Institute for Creative Technologies (ICT), a non-profit University Affiliated Research Center. RIDE has been made possible by funding from the Army Cross Functional Teams (CFT) and the Office of Naval Research (ONR).
Partnerships across the DoD will lead to unique capabilities and knowledge that become foundational within the STE collaborative environment.
The following capabilities integrated by the ICT’s STE Research Projects can be easily swapped out, augmented or used in conjunction with a different implementation based on user need.
Contributions from other projects in-progress!
The primary target audience of RIDE is developers working on DoD related training simulation systems.
Several RIDE releases typically occur throughout the year. Access to nightly releases available upon request.
Please choose an option below that best represents your organization.
RIDE is governed by its license agreement and all 3rd party licenses.
The Master Scenario Event List Injection (MSELI) and Narrative Summarization projects are two closely related AI research efforts. The MSELI project works to automate the functions of human Observer-Controllers for the STE. The goal is to build technologies that automatically recognize and interpret the behavior of human trainee teams in the context of a simulated battle.
The Narrative Summarization AI converts these interpretations into English-language narratives for use in After Action Review.