Research
The Smart Mobility Lab works in four thrusts. AI runs through all of them: in how vehicles perceive and decide, how charging demand is predicted, and how system models are calibrated. Each thrust ends in something agencies can use, such as a tested algorithm, a deployment guideline, a planning model, or a dataset.
Automated & Cooperative DrivingPerception, prediction, and control for automated vehicles, built on AI and tested on a full-size vehicle.Work Zone Automation (ATMA)Driverless follow trucks that take highway maintenance workers out of the crash zone.Transportation ElectrificationWhere EV charging is needed, who invests in it, and how fleets make the switch.Transportation System ModelingAnalytical and data-driven models of how traffic, travelers, and networks behave.
Inside each thrust
Automated & Cooperative Driving
21 selected publications, 8 sponsored projects
- Perception and localization
- Prediction, behavior, and scenario generation
- Planning and control
- Infrastructure and policy for automation
Work Zone Automation (ATMA)
8 selected publications, 13 sponsored projects
- Field testing and evaluation
- Operational design domain and guidelines
- Resilience and localization
- Operations planning
Transportation Electrification
7 selected publications, 10 sponsored projects
- Charging demand and driver behavior
- Charging infrastructure planning and investment
- Streetlight charging
- Medium- and heavy-duty fleet electrification
Transportation System Modeling
22 selected publications, 7 sponsored projects
- Queueing, bottlenecks, and capacity
- Network modeling and demand calibration
- Connected vehicle data and road conditions
- Privacy-preserving mobility data
- Travel behavior and demand management