Anticipating others’ behavior on the road
A new machine-learning system may someday help driverless cars predict the next moves of nearby drivers, cyclists, and pedestrians in real-time.
A new machine-learning system may someday help driverless cars predict the next moves of nearby drivers, cyclists, and pedestrians in real-time.
In MIT Mobility Forum talk, experts discuss a future for vehicle automation that lets technology and drivers interact.
In collaboration with industry representatives, Momentum students tackle wildfire suppression and search-and-rescue missions while building soft skills.
MIT ocean and mechanical engineers are using advances in scientific computing to address the ocean’s many challenges, and seize its opportunities.
A levitating vehicle might someday explore the moon, asteroids, and other airless planetary surfaces.
Assistant professor of civil engineering describes her career in robotics as well as challenges and promises of human-robot interactions.
Deep-learning methods confidently recognize images that are nonsense, a potential problem for medical and autonomous-driving decisions.
Electrical engineer and Stanford University professor discusses how computer software can support advanced designs and new functionalities.
Mechanical engineers are using cutting-edge computing techniques to re-imagine how the products, systems, and infrastructures we use are designed.
A certain type of artificial intelligence agent can learn the cause-and-effect basis of a navigation task during training.
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.
The transaction-based communications system ensures robot teams achieve their goal even if some robots are hacked.
PhD student Heng Yang is developing algorithms to help driverless vehicles quickly and accurately assess their surroundings.
New algorithm could enable fast, nimble drones for time-critical operations such as search and rescue.