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.
Cellphone data helps pinpoint source of traffic tie-ups
Study: Congestion can be alleviated throughout a metropolitan area by altering the trips of drivers in specific neighborhoods.
Increasing fuel efficiency with a smartphone
A network of dashboard-mounted phones can collect data on traffic lights and tell drivers how to avoid inefficient stopping and starting.