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.

Examining in-vehicle and infrastructure-based technologies to assess how they might impact emergency responders, particularly EMS.

Developing a smartphone-based travel behavior data collection platform that recruits participants by rewarding users with real-time parking information.

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.”

Designing a transportation data-warehouse prototype for the Buffalo-Niagara region and demonstrating its usefulness through a specific application.

Creating a mobile computer application for documenting and sharing data regarding vehicular accidents.

Developing models that will predict the delay a passenger car or a truck is likely to encounter by the time the vehicle arrives at the border.

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.

Invistigating aggressive driving behavior under driver fatigue, and under normal and distracted driving conditions.

This project develops novel data mining methodologies that integrate heterogeneous urban data for the estimation of city-wide transportation information.