Intelligent Transportation Systems
This project thread studies how connected and autonomous vehicles can interact with transportation infrastructure to improve safety, efficiency, and emergency response. The work spans signal-aware planning, eco-driving, and control strategies for connected emergency vehicles.
Core Questions
- How can autonomous vehicles exploit traffic-signal information to reduce delay and energy use?
- How can emergency vehicles be prioritized without causing unacceptable disruption to the rest of the network?
- How can intelligent control strategies remain effective in mixed traffic with both connected and non-connected road users?
Methods
- Traffic-signal-aware planning and control
- Dynamic path planning and signal preemption
- Microscopic traffic simulation and policy evaluation
- Learning-based and optimization-based control strategies
Representative Outputs
- Eco-Driving Framework for Autonomous Vehicles at Signalized Intersection in Mixed-Traffic Environment
- Multiple Intelligent Control Strategies for Travel-Time Reduction of Connected Emergency Vehicles
- Enhancing Internet of Things (IoT) strategies for autonomous electric vehicles (AEV) with existing transportation infrastructure and road users
Research Stack
- PTV Vissim
- SUMO
- MATLAB and Simulink
- Python-based experiment pipelines
- Data analytics for traffic performance evaluation