The dataset provided by Sendy includes order details and rider metrics based on orders made on the Sendy platform. The challenge is to predict the estimated time of arrival for orders- from pick-up to drop-off.
Sendy provides an API as well as a web and mobile application platform to link customers who have delivery needs with vetted transporters. The customers select their vehicle of choice, get their price quote upfront and pay using various payment options. The system optimises the route, looks for the closest available riders and dispatches the orders in the most efficient way.
The training dataset provided here is a subset of over 20,000 orders and only includes direct orders (i.e. Sendy “express” orders) with bikes in Nairobi. All data in this subset have been fully anonymized while preserving the distribution. Furthermore, we have added data about the weather, that corresponds to the time of the order.
You may use only the data provided here in your solution.
Arrival at Pickup times
Arrival at Destination times (column missing in Test set)