Operational challenges like this are never going to go away. With SemiCab, our optimization works in real-time, so it is always learning. The predictive piece doesn’t just tell us when the demand is going to come up, it also tells us where, providing insight into where all trucks are going to be at any particular point in time. The advantage of machine learning is that it can predict that something is going to go wrong with a particular trip/load assignment. From there, you can feed that scenario into the optimization algorithm and let it deal with avoiding the issue by reassigning and rerouting.
Another benefit of machine learning is that as issues arise over time, a pattern emerges and from there, we’re able to adjust and learn from it. The combination of prediction through machine learning and continuous optimization is at the core of what we do to ensure we adhere to pickup and delivery windows, carrier duty cycles, and HOS regulations.