Research
Where Simulation, Data & Algorithms Meet
I study how urban traffic behaves—rebuilding scenes with simulation, revealing patterns with data, and seeking better solutions with algorithms.
Direction 1
Traffic Simulation & Flow Theory
Studying intersection and network performance with simulation platforms, calibrating micro/macro flow models against real-world scenarios.
SUMOVISSIMPythonTraCI
Research Topics
- Intersection signal timing optimization
- Network capacity analysis
- Traffic flow model calibration
- Simulation scenario construction & validation
Direction 2
Intelligent Transportation & Big Data
Mining massive trajectory data to reveal the spatio-temporal patterns of urban traffic, supporting state recognition and short-term forecasting.
PythonSQLPyTorchGIS
Research Topics
- Trajectory data mining
- Traffic state identification
- Travel pattern analysis
- Spatio-temporal short-term forecasting
Integration
How They Work Together
Simulation
A controllable proving ground that reproduces edge cases.
Data
Calibrates demand and parameters, driving model refinement.
Algorithm
Bridges simulation and data, turning insight into control.
「Simulation provides the proving ground, data drives model refinement, and algorithms bridge the two.」
Future Interests