The success of modern ride-sharing platforms crucially depends on the profit of the ride-
sharing fleet operating companies, and how efficiently the resources are managed. Further …

Traditional transportation systems in metropolitan areas often suffer from inefficiencies due
to uncoordinated actions as system capacity and traffic demand change. With the pervasive …

In big cities, taxi service is imbalanced. In some areas, passengers wait too long for a taxi,
while in others, many taxis roam without passengers. Knowledge of where a taxi will …

Utilizing large-scale GPS data to improve taxi services becomes a popular research problem
in the areas of data mining, intelligent transportation, and the Internet of Things. In this …

Time series prediction has wide applications ranging from stock price prediction, product
demand estimation to economic forecasting. In this article, we treat the taxi and Uber …

Given a spatial field and the traffic flow between neighboring locations, the early detection of
gathering events (edge) problem aims to discover and localize a set of most likely gathering …

Investigating passenger demand is essential for the taxicab business. Existing solutions are
typically based on offline data collected by manual investigations, which are often dated and …

Emerging on-demand transport services, such as Uber and GoGoVan, usually face the
dilemma of demand supply imbalance, meaning that the spatial distributions of orders and …

Uber has attracted the attention of economists and policy makers for its innovations in the
taxicab market and its potential for significant consumer welfare gains. The size of this gain …