Nowadays, Informed Driving is crucial to the
transportation industry. We present an online recommendation
model to help the driver to decide about the best stand to head in
each moment, minimizing the waiting time. Our approach uses
time series forecasting techniques to predict the spatiotemporal
distribution in real-time. Then, we combine this information with
the live current network status to produce our output. Our online
test-beds were carried out using data obtained from a fleet of 441
vehicles running in the city of Porto, Portugal. We demonstrate
that our approach can be a major contribution to this industry:
395.361/506.873 of the services dispatched were correctly
predicted. Our tests also highlighted that a fleet equipped with
such framework surpassed a fleet that is not: they experienced an
average waiting time to pick-up a passenger 5% lower than its
competitor.