New tool evaluates progress in reinforcement learning
“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
Puzzling out climate change
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
The curse of variety in transportation systems
Assistant Professor Cathy Wu is addressing traffic control problems by leveraging deep reinforcement learning.
Taking the congestion out of commuting
Associate Professor Jinhua Zhao studies how and why people move, and designs multi-modal mobility systems.
3 Questions: What a single car can say about traffic
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.
Q&A: Cathy Wu on developing algorithms to safely integrate robots into our world
Assistant professor of civil engineering describes her career in robotics as well as challenges and promises of human-robot interactions.
Machine learning speeds up vehicle routing
Strategy accelerates the best algorithmic solvers for large sets of cities.
Deep learning helps predict traffic crashes before they happen
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.
Crossing disciplines, adding fresh eyes to nuclear engineering
PhD student Limiao Zhang sees surprising connections between the behavior of cars and bubbles.
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.
