Examining the world through signals and systems
Assistant Professor Cathy Wu aims to help autonomous vehicles fulfill their promise by better understanding how to integrate them into the transportation system.
How many taxis does a city need?
New dispatching approach could cut the number of cars on the road while meeting rider demand.
3 Questions: Chris Zegras on designing your city’s transit system
MIT-designed tool lets people test realistic changes to local transit networks.
A simple solution for terrible traffic
Study: Without HOV policies, urban traffic gets much, much worse.
MIT awarded Dept. of Energy grant to create and deploy energy-saving travel information and incentives system
$4 million grant will determine whether travel choices can be influenced by data and rewards to save energy.
Better traffic signals can cut greenhouse gas emissions
Analysis shows that smarter programming of stoplights could improve efficiency of urban traffic.
New way to predict how traffic will flow
Model provides a more accurate tool for city planning, emergency evacuations, tracking disease spread.
Reducing traffic congestion, remotely
Reducing traffic congestion with wireless systemSystem that would wirelessly route drivers around congested roadways wins best-paper award.
Ride-sharing could cut cabs’ road time by 30 percent
A new analytic framework enables analysis of GPS data on 150 million cab rides in New York City.
Traffic lights: There’s a better way
MIT researchers develop an improved system for timing of urban lights to minimize commuting times.
Forbes magazine highlights SMART research on robotaxis
Professor Emilio Frazzoli co-authors paper on automated mobility-on-demand systems in Singapore
HuMNet Lab students win big at MIT Big Data Challenge
Urban transportation expertise gave team the edge to earn first- and second-place prizes in different categories.
Eliminating unexplained traffic jams
If integrated into adaptive cruise-control systems, a new algorithm could mitigate the type of freeway backup that seems to occur for no reason.
Study shows that people organize daily travel efficiently
A population-level study discovers small-scale details about individuals’ choices.