686 citations · 3.3k across the 81 of their papers we have counts for
4 papers · 2 filters
Using reinforcement learning to minimize taxi idle times
Kevin O'Keeffe, Sam Anklesaria, Paolo Santo +1
Taxis spend a significant amount of time idle, searching for passengers. The routes vacant taxis should follow in order to minimize their idle times are hard to calculate; they dep…
Modeling vehicular mobility patterns using recurrent neural networks
Kevin O'Keeffe, Paolo Santi, Carlo Ratti
Data on vehicular mobility patterns have proved useful in many contexts. Yet generative models which accurately reproduce these mobility patterns are scarce. Here, we explore if re…
A pedestrian level strategy to minimize outdoor sunlight exposure in hot summer
Xiaojiang Li, Yuji Yoshimura, Wei Tu +1
Too much sunlight exposure would cause heat stress for people during the hot summer, although a minimum amount of sunlight is required for humans.
Urban sensing as a random search process
Kevin O'Keeffe, Paolo Santi, Brandon Wang +1
We study a new random search process: the \textit{taxi-drive}. The motivation for this process comes from urban sensing, in which sensors are mounted on moving vehicles such as tax…