> For the complete documentation index, see [llms.txt](https://2025.istvs.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://2025.istvs.org/submissions/papers/6775.md).

# 6775 - MODELING AND SIMULATION OF AUTONOMOUS VEHICULAR SYSTEMS AT ERDC - I SOFTWARE INTEGRATION LABORATORY: DEVELOPMENT AND APPLICATIONS

{% hint style="info" %}
Paper presented at ISTVS 2025 | 55th Conference of the International Society for Terrain-Vehicle Systems <https://doi.org/10.56884/N1CGA6U2>
{% endhint %}

**Authors:** *Peilin Song, Burhman Gates*

**Keywords:** Modeling and Simulation; Autonomous Drive; terramechanics; Vehicle Dynamics; Software Integration Laboratory

**Abstract:**

Unmanned Ground Vehicles (UGVs) are becoming critical assets for the Army, offering enhanced capabilities for mission execution. However, the complexity of autonomous systems presents challenges that traditional analysis tools are ill-equipped to handle. To address this, ERDC has developed a Software Integration Laboratory (SIL) to support the modeling and simulation (M\&S) of UGVs in virtual environments. The SIL provides a digital testbed for performance prediction and risk mitigation across both typical and edge-case scenarios. As part of ongoing test and evaluation (T\&E) endeavors, ERDC’s SIL supports a wide range of activities that complement physical field trials. This includes the creation of high-fidelity virtual environments that integrate vehicle dynamics, terramechanics, terrain models, and sensor simulations. These environments enable realistic testing of autonomous navigation systems—such as the Robotic Technology Kit (RTK) and its variants—in off-road and contested conditions. This paper highlights the design and capabilities of ERDC’s SIL and its application to autonomous ground vehicle testing and development. It demonstrates how digital experimentation using the SIL supports the integration of autonomous systems into manned-unmanned teams and helps inform future mission planning. The paper also presents the application of the SIL in various projects, including both single autonomous vehicle operations and the coordinated motion of multiple vehicles in team-based scenarios.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://2025.istvs.org/submissions/papers/6775.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.