686 citations · 3.3k across the 81 of their papers we have counts for
9 papers · 1 filter
Quantifying Urban Canopy Cover with Deep Convolutional Neural Networks
Bill Cai, Xiaojiang Li, Carlo Ratti
Urban canopy cover is important to mitigate the impact of climate change. Yet, existing quantification of urban greenery is either manual and not scalable, or use traditional compu…
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.
Assessing the interplay between human mobility and mosquito borne diseases in urban environments
Emanuele Massaro, Daniel Kondor, Carlo Ratti
Urbanization drives the epidemiology of infectious diseases to many threats and new challenges. In this research, we study the interplay between human mobility and dengue outbreaks…
Estimating the potential for shared autonomous scooters
Dániel Kondor, Xiaohu Zhang, Malika Meghjani +3
Recent technological developments have shown significant potential for transforming urban mobility. Considering first- and last-mile travel and short trips, the rapid adoption of d…