The recent network disruptions in the Washington Metro system showed the new reality associated with aging transit infrastructure and highlighted the potential severity of such disruptions. However, relevant studies in the literature are limited and agencies need more empirical evidence to help them better planning and implementing maintenance work.
Creating a quality-aware crowdsourced road sensing system that integrates sensory data from multiple vehicles while placing more weight on the vehicles that provide high quality data to significantly improve integration accuracy.
The project suggests a bottom-up travel behavior driven approach which obtains trends in individual travel behavior first and use such information to enhance longitudinal origin-destination demand monitoring.
Integrating machine learning, big data, sensor networks, and agent-based transportation modeling to prototype an algorithm that combines the power of a model-driven approach with the power of big data.
CUBRC is a leading research, development, testing and systems integration company specializing in the areas of data science and information fusion; chemical, biological and medical sciences; and aeronautics.