The curse of variety in transportation systems
Assistant Professor Cathy Wu is addressing traffic control problems by leveraging deep reinforcement learning.
Assistant Professor Cathy Wu is addressing traffic control problems by leveraging deep reinforcement learning.
Associate Professor Jinhua Zhao studies how and why people move, and designs multi-modal mobility systems.
Measuring traffic properties requires vast amounts of data. Meshkat Botshekan, a PhD student working with the MIT CSHub, is discovering a more efficient and affordable physics-inspired alternative.
Assistant professor of civil engineering describes her career in robotics as well as challenges and promises of human-robot interactions.
Strategy accelerates the best algorithmic solvers for large sets of cities.
A deep model was trained on historical crash data, road maps, satellite imagery, and GPS to enable high-resolution crash maps that could lead to safer roads.
PhD student Limiao Zhang sees surprising connections between the behavior of cars and bubbles.
Assistant Professor Cathy Wu aims to help autonomous vehicles fulfill their promise by better understanding how to integrate them into the transportation system.
New dispatching approach could cut the number of cars on the road while meeting rider demand.
MIT-designed tool lets people test realistic changes to local transit networks.
Study: Without HOV policies, urban traffic gets much, much worse.
$4 million grant will determine whether travel choices can be influenced by data and rewards to save energy.
Analysis shows that smarter programming of stoplights could improve efficiency of urban traffic.