Research
Research
My work addresses critical challenges in transportation safety, connected and autonomous vehicles, traffic operations, public transportation, multimodal mobility, and transportation system optimization. My long-term research vision is to help develop transportation systems that are smarter, safer, more efficient, more reliable, and more sustainable through the integration of transportation engineering, artificial intelligence, data analytics, and emerging mobility technologies.
Machine learning
AI
Prediction
Behavioral modeling
Data analytics
CAVs
Vehicle trajectories
Connected infrastructure
Electric mobility
Crash analysis
Vulnerable road users
Injury severity
Safety analytics
Transit
Rail
Shared mobility
Active transportation
Machine learning
AI
Prediction
Behavioral modeling
Data analytics
My current research increasingly focuses on the convergence of artificial intelligence, emerging mobility technologies, transportation safety, and multimodal transportation systems.
Developing machine learning, deep learning, explainable AI, and reinforcement learning methods for transportation prediction, analysis, optimization, and control.
Investigating connected and autonomous vehicles, intelligent infrastructure, vehicle-to-infrastructure communication, and emerging approaches to transportation system management.
Using advanced statistical and machine-learning methods to better understand crash occurrence, injury severity, vulnerable road user safety, and the safety implications of changing vehicle fleets and transportation environments.
Developing data-driven methods for improving transit operations, rail and bus system efficiency, multimodal mobility, and integration among emerging transportation services.
Developing optimization and control approaches for traffic signals, freeway operations, transit operations, transportation networks, and transportation system reliability.
My research portfolio includes projects supported by federal, state, university, and industry sponsors.
NC Transportation Center of Excellence on Connected and Autonomous Vehicle Technology (NC-CAV), NC CAV Brochure; Phase I Report; Phase II Report; NCDOT
Dynamic Coordinated Speed Control and Synergistic Performance Evaluation in Connected and Automated Vehicle Environments, Technical Report, USDOT
Transit Signal Priority Control with Connected Vehicle Technology: Deep Reinforcement Learning Approach, Technical Report, USDOT
Machine Learning-Based Trajectory Optimization of Connected and Autonomous Vehicles, Technical Report, USDOT
Impact of Connected and Automated Vehicles on Freeway Capacity, Technical Report, USDOT
Optimization of Long-Term Highway Work Zone Scheduling, Technical Report, USDOT
Impact of Connected and Autonomous Vehicles on Nontraditional Intersection Design: Superstreets, Technical Report, USDOT
Optimal Variable Speed Limit Control for Mixed Traffic in Connected and Autonomous Vehicle Environments, Technical Report, USDOT
Developing a Systematic Approach to Improving Bottleneck Analysis in North Carolina, Technical Report, NCDOT
Prevention of Backing Fatalities in Construction Work Zones, Technical Report, TxDOT
Travel Time Forecasting on Freeway Corridors: Dynamic Information Fusion Using Random Forests, Technical Report, USDOT
Predicting Travel Time on Freeway Corridors: Machine Learning Approach, Technical Report, USDOT
Use of Multisensor Data in Modeling Freeway Travel Time Reliability, Technical Report, USDOT
Estimation of Origin-Destination Matrices and Identification of User Activities Using Public Transit Smart Card Data, Technical Report, USDOT
Bicycle Volume: Counting Machine Validation & Correction, Estimating & Forecasting, and Analysis of Injury Risk, Technical Report, NCDOT
Optimizing Transit Equity and Accessibility by Integrating Relevant GTFS Data Performance Metrics, Technical Report, USDOT
Using General Transit Feed Specification (GTFS) Data as a Basis for Evaluating and Improving Public Transit Equity, Technical Report, USDOT
Optimal Transit Route Network Design: Algorithms, Implementations, and Numerical Results, Technical Report, UT Austin
Geo-FRIT: A Web-Based Geospatial Analytics Tool for Quantifying Freight Risk and Resilience in Transportation, Technical Report, NCDOT
Improving the Movements of People and Freight: A Case Study of the Piedmont Atlantic Megaregion, Technical Report, USDOT
Utilization Measurement and Management of Fleet Equipment, Technical Report, NCHRP
Equipment Replacement/Retention Decision Making, Technical Report, TxDOT
My research has been supported by agencies and organizations including the U.S. Department of Transportation (USDOT), Federal Highway Administration (FHWA), National Cooperative Highway Research Program (NCHRP), Texas Department of Transportation (TxDOT), and North Carolina Department of Transportation (NCDOT). My research has resulted in a broad portfolio of scholarly publications, sponsored research projects, student training, and collaborations with transportation agencies and universities.
Sponsored Research Funding
Peer-Reviewed Journal Articles
Students engaged through CAMMSE
Research projects through CAMMSE
Collaborators Across U.S. Universities
Global Scientist Recognition
My research leadership has been supported by major interdisciplinary research programs and centers that bring together faculty, students, transportation agencies, and industry partners.
Director, 2016-2024
The Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE) was a U.S. Department of Transportation University Transportation Center led by UNC Charlotte under the FAST Act.
As Director, I led a multi-university research and education program focused on improving the mobility of people and goods through advanced transportation technologies, methods, and models.
CAMMSE brought together researchers from five universities, transportation agencies, industry partners, and students to conduct interdisciplinary research addressing emerging transportation challenges.
87 research projects
219 journal publications across the consortium
More than 200 students engaged in research
Undergraduate and graduate transportation education and workforce development
Annual research symposium and seminar activities
National dissemination through TRB and other transportation conferences
Research partnerships with universities, government agencies, and industry
[Learn More About CAMMSE → ]
Thrust Leader
The NC Transportation Center of Excellence on Connected and Autonomous Vehicle Technology (NC-CAV) supports interdisciplinary research, education, and technology development related to connected and autonomous transportation systems.
My research leadership within NC-CAV focuses on the development, evaluation, and application of connected and autonomous vehicle technologies, including their impacts on transportation operations, mobility, safety, and infrastructure.
Research activities include:
Connected and autonomous vehicle operations
CAV traffic flow and capacity
Vehicle trajectory planning
Traffic control in connected environments
CAV simulation and impact assessment
Connected infrastructure and intelligent transportation systems
Emerging transportation technologies
[Learn More About NC-CAV → ]
Founding Director
The S³ Transportation Lab: Smart, Safe & Sustainable Mobility is an interdisciplinary research group at UNC Charlotte focused on developing next-generation transportation systems through the integration of artificial intelligence, data analytics, transportation modeling, and emerging mobility technologies.
The lab brings together graduate and undergraduate students, faculty collaborators, transportation agencies, and industry partners to address real-world transportation challenges.
Smart Transportation
AI, machine learning, data analytics, intelligent transportation systems, and transportation modeling.
Safe Transportation
Transportation safety analytics, vulnerable road users, crash modeling, and safety applications of emerging technologies.
Sustainable Transportation
Public transportation, multimodal mobility, shared mobility, electric vehicles, and sustainable transportation systems.
Connected & Autonomous Mobility
Connected vehicles, autonomous vehicles, intelligent infrastructure, simulation, optimization, and control.
[Visit the S³ Transportation Lab → ]
Transportation challenges increasingly require interdisciplinary and collaborative approaches. I have collaborated with researchers at 60+ U.S. universities, as well as national and international researchers, transportation agencies, and industry partners. My collaborations span: Transportation Engineering; Artificial Intelligence & Data Science; Civil & Environmental Engineering; Operations Research; Computer Science; Urban Planning; Public Transportation; Connected & Autonomous Vehicles; and Transportation Safety. I welcome collaborations that combine transportation expertise with emerging technologies, data science, AI, and interdisciplinary approaches to address important mobility challenges.
My research has produced 150+ peer-reviewed journal publications covering a broad range of transportation topics. Major publication areas include: Artificial intelligence and machine learning; Connected and autonomous vehicles; Transportation safety; Public transportation and rail; Traffic operations and control; Shared and multimodal mobility; Transportation networks and optimization; and Travel demand and behavioral modeling.
[View Journal Publications → ]
[View Google Scholar Profile → ]
Opportunities for undergraduate, master's, and Ph.D. students interested in AI, transportation, mobility, safety, and data analytics.
[Explore Student Opportunities → ]
We welcome interdisciplinary collaborations spanning transportation engineering, AI/ML, data science, computer science, operations research, and urban planning.
[Contact Me → ]
"Research is what I'm doing when I don't know what I'm doing." - Wernher von Braun