17 citations · 34 across the 11 of their papers we have counts for
11 papers
iOSPointMapper: RealTime Pedestrian and Accessibility Mapping with Mobile AI
Himanshu Naidu, Yuxiang Zhang, Sachin Mehta +1
Accurate, up-to-date sidewalk data is essential for building accessible and inclusive pedestrian infrastructure, yet current approaches to data collection are often costly, fragmen…
Can Large Language Models Integrate Spatial Data? Empirical Insights into Reasoning Strengths and Computational Weaknesses
Bin Han, Robert Wolfe, Anat Caspi +1
We explore the application of large language models (LLMs) to empower domain experts in integrating large, heterogeneous, and noisy urban spatial datasets. Traditional rule-based i…
Reliable, Routable, and Reproducible: Collection of Pedestrian Pathways at Statewide Scale
Yuxiang Zhang, Bill Howe, Anat Caspi
While advances in mobility technology including autonomous vehicles and multi-modal navigation systems can improve mobility equity for people with disabilities, these technologies…
Towards Zero-Shot Annotation of the Built Environment with Vision-Language Models (Vision Paper)
Bin Han, Yiwei Yang, Anat Caspi +1
Equitable urban transportation applications require high-fidelity digital representations of the built environment: not just streets and sidewalks, but bike lanes, marked and unmar…
PathwayBench: Assessing Routability of Pedestrian Pathway Networks Inferred from Multi-City Imagery
Yuxiang Zhang, Bill Howe, Sachin Mehta +2
Applications to support pedestrian mobility in urban areas require a complete, and routable graph representation of the built environment. Globally available information, including…
APE: An Open and Shared Annotated Dataset for Learning Urban Pedestrian Path Networks
Yuxiang Zhang, Nicholas Bolten, Sachin Mehta +1
Inferring the full transportation network, including sidewalks and cycleways, is crucial for many automated systems, including autonomous driving, multi-modal navigation, trip plan…