Extending the work that was completed for year one funding related to “Developing Highway Safety Performance Metrics in an Advanced Connected Vehicle Environment Utilizing Near-Crash Events from the SHRP 2 Naturalistic Driving Study.”
Investigating how multiple traffic data sources can be integrated in a consistent manner, and how they may be best used for arterial performance measurement.
This project develops novel data mining methodologies that integrate heterogeneous urban data for the estimation of city-wide transportation information.
Conducting a detailed, multivariate statistical assessment of pavement treatments by public-private partnerships, and studying their performance in terms of extending pavement lives.
Developing the tools needed to process immense amounts of data, develop new performance metrics based on the data collected, and propose methods to enhance performance.
The project investigates how real-time conditions interact to affect driver safety performance changes. From that understanding, practitioners and drivers can make more informed decisions to reduce the likelihood of a crash.
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 proposes a deep learning model to predict the best recharging recommendation including best recharging time and location for eTaxi drivers.
GMU is a young university that has made impressive strides in size, stature and influence. Today, GMU is Virginia’s largest public research university.
The Mayagüez Campus of the University of Puerto Rico is a co-educational, bilingual, and non-sectarian school with 106 years of educational excellence.
UB is the premier public research university in the northeastern United States and the largest and most comprehensive campus in the 64-campus SUNY system.
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.
