Research in Transportation Safety aims to address issues related to multiple modes as well as the needs of a variety of roadway users. Both descriptive- (understanding traveler behavior) and predictive- (making quantitative projections for project evaluations) studies are undertaken. The studies employ state-of-the-art econometric methods and spatial-analysis techniques. Efforts are also undertaken to develop and implement protocols to assist small agencies identify and address their local safety problems.


Title Principal Investigators Agency/Source Description
Big Data Management Pilot, Florida Department of Transportation Sanjay Ranka, Siva Srinivasan and Ilir Bejleri FDOT Demonstrated the application of big-data analysis / machine learning techniques to five transportation use cases covering transportation safety, operations, and performance measures.
Before and After Implementation of Advanced Signal Control Lily Elefteriadou, Yafeng Yin, Siva Srinivasan


FDOT Assessed the impacts of signal coordination on safety by examining crash data patterns before and after the implementation in several corridors in Florida.
Transportation Safety Center (Phase 3) Nithin Agarwal, Siva Srinivasan, Ilir Bejleri


FDOT Develop systemic safety analysis methods and apply these to assist with small and rural counties identify safety problems and implement low-cost countermeasures.  The center has assisted three counties already and will assist more in next phases of this project.
Warrants, Design, and Safety of Road Ranger Patrols Yafeng Yin, Siva Srinivasan, and Grady Carrick


FDOT Develop a statistically driven methodology to assist Florida prioritize the expansion of the road ranger service patrol program on its highways. Develop an optimization algorithm to allocate vehicles to beats for patrolling. Implement methods in a software tool.
Crash Prediction Method for Freeway Facilities with HOV and HOT Lanes Siva Srinivasan in collaboration with FIU (Albert Gan and Priyanka Alluri) and Kittelson and Associates (Jim Bonneson) FDOT Develop a statistically driven method to predict crash rates on new freeway facilities with HOV and HOT lanes. Emphasis was placed on the impact of separation type between the general purpose lanes and managed lanes.
GIS-Based Instructional Tool for Crash Prediction Methods Ilir Bejleri and Siva Srinivasan STRIDE Developed a web-based instructional tool for teaching highway safety manual methods incorporating data from Florida.

More projects can be found on the TRID database at


Siva Srinivasan, Ph.D.

Associate Professor Department of Civil and Coastal Engineering

Ilir Bejleri, PhD

Associate Professor Department of Urban and Regional Planning

Ruth Steiner, PhD

Professor Department of Urban and Regional Planning

Lori Pennington-Gray, Ph.D.

Associate Professor Department of Tourism, Recreation; Sport Management