Taxi-Aware Map: Identifying and Predicting Vacant Taxis in the City

Knowing where vacant taxis are and will be at a given time and location helps the users in daily planning and scheduling, as well as the taxi service providers in dispatching. In this paper, we present a predictive model for the number of vacant taxis in a given area based on time of the day, day of the week, and weather condition. The history is used to build the prior probability distributions for our inference engine, which is based on the na

• Type: Journal
• Year: 2010
• Where: AMI
• Authors: Santi Phithakkitnukoon, Marco Veloso, Carlos Bento, Assaf Biderman, Carlo Ratti
• Keywords: AMI 2010, Artificial Intelligence, Na¨ive Bayesian Classifier, Prior Probability Distributions, Vacant Taxis