DATA-DRIVEN ETA PREDICTION IN UZBEK FREIGHT TRANSPORT: A TOOL FOR IMPROVING DELIVERY RELIABILITY

Abstrak

Estimated Time of Arrival prediction has become an important analytical tool in modern freight transport because delivery reliability depends not only on distance, but also on real-time operational conditions. In Uzbekistan, this issue is especially relevant because road transport carries the dominant share of cargo and national transport policy increasingly emphasizes digitalization, faster delivery, and better logistics performance. This article examines how data-driven ETA prediction can improve freight reliability by using real-time vehicle location, route progress, historical trip patterns, and operational events such as stops and delays. The study argues that ETA prediction can strengthen communication between drivers, dispatchers, and cargo owners, while also reducing uncertainty in freight operations