McKinsey's latest report predicts that by 2040 autonomous vehicles will become commonplace, reshaping daily routines, urban design, AI technology, trust dynamics, and the talent landscape, offering a glimpse into a future where mobility is seamless, safe, and deeply integrated with our lifestyles.
This article examines traditional Feng Shui concepts through the lens of modern environmental science, translating the notion of "qi" into measurable physical variables, building fluid‑dynamic, solar‑geometry, and graph‑theoretic models, and applying them to classic Chinese sites for quantitative evaluation.
A multidisciplinary team from Tsinghua, MIT, and Northeastern University proposes a closed‑loop, LLM‑powered urban planning workflow that combines concept design, visual generation, and AI‑based evaluation to overcome traditional planning bottlenecks and enable human‑AI co‑creation of smarter cities.
This article introduces the open‑source Python library TRACC, explains how to install it, prepare destination and travel‑cost data, and walk through a step‑by‑step workflow—including code snippets—to compute potential, passive, and minimum travel‑cost accessibility metrics for urban areas.
This article explains how a deep reinforcement learning model, built on a graph‑based representation of urban elements and trained with PPO, can automate land‑use and road planning to achieve Service, Ecology, and Traffic objectives for 15‑minute city neighborhoods.
