A new study finds autonomous mobility-on-demand research must become more transparent and reproducible to guide real-world transportation decisions As cities and companies move towards fleets of self-driving taxis, a group of researchers is urging the field […]
MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits. […]
MIT researchers developed a way to identify the smallest dataset that guarantees optimal solutions to complex problems. […]
The approach could enable autonomous vehicles, commercial aircraft, or transportation networks that are more reliable in the face of real-world unpredictability. […]
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent. […]
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems. […]
“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms. […]
Using diagrams to represent interactions in multipart systems can provide a faster way to design software improvements. […]
By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews. […]
Engineers developed a planning tool that can help independent entities decide when they should invest in joint projects. […]
A new MIT study identifies steps that can lower not only emissions, but also costs, across the combined electric power and natural gas industries that now supply heating fuels. […]
Research project embeds autonomous mobility and energy justice into public transit services Jinhua Zhao, Professor of Cities and Transportation, and Gioele Zardini, Rudge (1948) and Nancy Allen Career Development Assistant Professor of Civil and Environmental Engineering, […]
The technique could make AI systems better at complex tasks that involve variability. […]
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse. […]
A new study finds human supervisors have the potential to reduce barriers to deploying autonomous vehicles. […]
