The next wave of innovation isn’t happening on roads or highways — it’s unfolding in fields, mines, and construction sites. Tractors, excavators, and haul trucks are becoming increasingly software-defined, expected to operate with higher levels of automation to support operators in complex, unstructured environments. But how do we test these advanced systems safely and effectively?

The answer lies in digital twins and scenario-based testing.

Unlike passenger cars, off-highway machines face unique challenges: seasonal testing windows, dust and weather variability, and extreme terrain. Traditional field trials are not only expensive, but they also expose operators and equipment to risk. Digital twins allow us to replicate these conditions virtually—reducing cost, accelerating development, and enhancing safety.

Scenario-Based Testing in Harsh Conditions
No two job sites look alike. Dust clouds can distort cameras, muddy terrain can confuse traction control, and sudden weather changes can stress control systems. Scenario-based testing ensures that operator-assistive features and semi-autonomous functions are validated across hundreds—or even thousands—of realistic conditions.

Instead of building one-off tests, engineers can systematically vary lighting, dust levels, vibration, terrain roughness, and weather in simulation, then observe how perception and control systems respond. This creates confidence that features like emergency braking, adaptive cruise, or load-assist will remain reliable even in unpredictable environments.

Case in Point: Operator-Assistive Emergency Braking
For tractors, engineers must determine sensor placement, accuracy, and how braking controllers interact with both machine dynamics and human operators. Limited field testing makes it impossible to cover every scenario. Digital twins enable systematic testing of braking algorithms under diverse weather, dust, and terrain conditions—before a single wheel touches the ground.

System-Level Perspective
Advanced control, operator-assist automation, and semi-autonomy don’t operate in isolation. They must account for:

• Vehicle physics
• Sensor reliability in noisy, dusty, or low-visibility conditions.
• Environmental variability such as mud, slopes, or glare.
• Operator-in-the-loop, where operator inputs interact with automated functions.

Virtual test benches combine all these elements, enabling repeatable, scenario-based validation of assistive features in the toughest off-road conditions.

As industries push toward smarter, more sustainable machines, those who lead the way will be the ones who use simulation and scenario-based testing as the foundation of development.

Digital twins are no longer futuristic—they’re the backbone of building reliable, operator-friendly, and safe machines for the harshest environments.

🔗 Want to see these ideas in action?
Join me at our upcoming webinar, Smarter Offroad Automation Starts with Simulation and Virtual Testing where Christoph Kammer and I’ll walk through some examples of how simulation accelerates development of advanced control, automation, and semi-autonomous systems in off-highway vehicles.