ChangiNOW: A Mobile Application for Efficient Taxi Allocation at Airports

We present an application that uses a predictive queueing model to efficiently allocate taxis. The system uses observed taxi and flight data at each of the four terminals of Singapore's Changi Airport to estimate the expected waiting time and queue length for taxis arriving at these terminals, and then sends taxis to terminals where demand is highest. We propose a service model that enables our system to be deployed on a smartphone platform to participating taxi drivers. We present the theoretical details which underpin our prediction engine and corroborate our theory with several targeted numerical simulations. Finally, we evaluate the performance of this system in large-scale experiments and show that our system achieves a significant improvement in both passenger and taxi waiting time.