Estimating Taxi Demand-Supply Level Using Taxi Trajectory Data Stream

Taxis provide a flexible and indispensable service to satisfy the urban travel demand of public commuters. Understanding taxi supply and commuter demand, especially the imbalance between the supply and the demand, would directly help to improve the quality of taxi service and eventually increase a city's traffic system efficiency. In this paper, we consider the taxi demand from a region during a period of time to include two parts: satisfied demand, i.e., passengers successfully receive taxi service during this period of time, and unmet demand, i.e., passengers are still waiting for taxi service. To properly estimate the demand-supply level (short for "the level of the taxi demand vs. supply imbalance"), we propose a novel indicator that reflects how fast an available taxi is taken in any given region. Accordingly, we design and implement a taxi analytics system to provide such information in near real time. Finally, we use the passenger waiting time survey data and the taxi streaming data to validate the proposed indicator on the built taxi analytics system.