Data-driven and mechanics-based traffic safety, efficiency prediction, and intervention under hazardous conditions
Traffic system resilience assessment and intervention solution
Driving behavior characterization and ITS technology application on highway networks
- Advanced statistical approach to understand traffic safety performance with refined-scale models;
- Data-driven injury severity study and intervention techniques to promote safer driving experience;
- AI-based traffic forecasting using hybrid data and simulation approach.
- Mechanics-based probabilistic single-vehicle crash risk assessment models of vehicles under adverse weather, road surface conditions, and complex geometric terrains;
- Risk-informed decision-makings of traffic management under windy environment.
Traffic system resilience assessment and intervention solution
- Multi-scale traffic system resilience modeling from a holistic angle, starting from individual infrastructure like bridges, to road links, traffic network and whole city considering interdependency with other infrastructure systems (e.g., energy and water);
- Efficiency- & graph-based integrated traffic resilience modeling considering various physical and data disruptions under hazards with the hybrid data and simulation approach;
- Emergency Medical Response (EMS) investigation before, during, and following major hazards;
- Retrofitting planning and optimization of bridges and independent infrastructures following hazards;
- Deep-learning-based proactive traffic intervention through intelligent intersection traffic control to improve mobility, system resilience, and energy efficiency, which can adapt to the environment.
Driving behavior characterization and ITS technology application on highway networks
- Driving behavior characterization based on experiments and data mining;
- ITS solutions to improve adaptive speed limit, evacuation, law enforcement and traffic management;
- Connected vehicle and autonomous algorithms in adverse conditions.