To estimate network flow and travel behavior under recurrent traffic conditions, we leverage
computational graphs and multi-source system-level data and solve a single-level …

This paper studies how to reduce the overall travel time of commuters in a transportation
network by reversing the direction of some lanes in the network using a macroscopic …

The reliability of urban transportation systems is crucial for ensuring smooth traffic flow and
minimizing disruptions caused by external factors. This study focuses on improving the …

This paper leverages macroscopic models and multi-source spatiotemporal data collected
from automatic traffic counters and probe vehicles to accurately estimate traffic flow and …

System-level decision making in transportation needs to understand day-to-day variation of
network flows, which calls for accurate modeling and estimation of probabilistic dynamic …

With the development of smart city transportation systems, developing reasonable
dispatching strategies for idle ride-hailing vehicles has become an urgent research problem …

This dissertation develops new algorithms that integrate some of the tools developed in the
travel behavior and network modeling community to better infer large-scale transportation …

While the traditional approach to ease traffic congestion has focused on building
infrastructure, the recent emergence of Connected and Automated Vehicles (CAVs) and …