> 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/5493.md). # 5493 - EFFECTS OF ELECTRONIC CONTROL SYSTEMS ON AUTONOMOUS VEHICLE PERFORMANCE IN GRANULAR TERRAIN {% hint style="info" %} Paper presented at ISTVS 2025 | 55th Conference of the International Society for Terrain-Vehicle Systems {% endhint %} **Authors:** *Bohumir Jelinek, Aidan Dickerson, Angela Card, Greg Henley, George Mason, John Ethan Salmon, Ch. Michael Gibson, Tyler Hannis, Tom Skorupa, Michael Cole, Jody Priddy, Miriam Figueroa-santos, Sara Boyle, Jeremy Mange* **Keywords:** Off-Road Mobility; Soft Terrain; Electronic Stability Control; Antilock Braking System; Double Lane Change **Abstract:** Understanding effects of electronic control systems, such as Antilock Braking System (ABS) and Electronic Stability Control (ESC), and their interaction with the steering control algorithm is critical for improving mobility and maneuverability of autonomous wheeled vehicles in off-road environments. In this work, we evaluate effects of wheel-speed based ABS and yaw-rate-following ESC on the performance of autonomously driven Polaris RZR vehicle performing a double-lane-change (DLC) maneuver in granular terrain by identification of maximum DLC passing speeds. Two lateral speed controllers are compared: simple PID and Stanley autonomous steering controller, along with the longitudinal speed controller that accelerates the vehicle to identify maximum DLC passing speed. The simulations were conducted using Chrono simulation package with the Soil Contact Model (SCM) parameters. The SCM parameters were calibrated to represent dry sand by using data from published experimental measurements. The ABS effects were found to be negligible or detrimental, while ESC augmented the lateral steering control algorithm allowing the vehicle to achieve higher DLC passing speeds. --- # 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/5493.md?ask=&goal= ``` `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.