The Smart Transport Group at McGill University targets to bring innovative methodologies and applications to address efficiency, resilience, and sustainability issues in urban transportation systems.
We see the rising power of machine learning techniques and its potential in shaping tommorrow's transportation system and discovering the city dynamics. We organize our research categories into three main themes, including Machine Machine Learning for Mobility Modeling, Intelligent Transportation System, and Agent-based Modeling and Simulation. You may kindly see the gallery of our
research projects and
industrial collaboration.
The Smart Transport Group is led by
Prof. Lijun Sun, the Assistant Professor at McGill University, working with an innovative group of transportation researchers. Our interdisciplinary lab includes welcomes students with different backgrounds and research interests. Check
here to see our wonderful group members.
Sec I: Machine Learning for Mobility Modeling
Sec II: Intelligent Transportation System
Sec III: Agent-based Modeling and Simulation
Worldwide visitors
Pattern discovery
Destination inference
Probabilistic modeling
Anomaly diagnoising
Spatiotemporal tensor learning
Kriging
Bus bunching control
MAGRL for CAVs
Bus bunching corridor