More than distance over speed
An estimated time of arrival is not just route length divided by a speed limit. Real travel time depends on traffic, time of day, weather, turns, and stops. A good ETA service learns these patterns from historical trips rather than guessing.
A layered estimate
- Baseline from the route. Start with the planned route and its segment level speeds.
- Live adjustment. Fold in current traffic from real time location streams.
- Learned correction. A model trained on past trips corrects for systematic errors like intersections that always run slow.
Serving it reliably
- ETAs are requested constantly, so segment predictions are cached and composed per route.
- The service must degrade gracefully, falling back to historical averages when the live or model layer is unavailable.
- Quality is tracked by comparing predicted to actual arrival, and the gap feeds back into training.
Key idea
An ETA service composes a route baseline, live conditions, and learned corrections, while degrading to historical averages when layers fail.