10 papers
PhaseShift: Topology-Aware Data Harmonization and Model Consolidation Across Signalized Intersections
Yash Ranjan, Artur Kumik, Rahul Sengupta +2
Learned traffic-behavior models are commonly trained separately for each intersection, creating model portfolios that cannot share evidence across sites. We present PhaseShift, a t…
A Generative Model for Closed-Loop Microsimulation of Signalized Intersections
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic microsimulators rely on hand-crafted behavior models that reproduce aggregate flow but miss the heterogeneous interactions between vehicles at signalized intersections. Lea…
Enactor: From Traffic Simulators to Surrogate World Models
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic microsimulators are widely used to evaluate road network performance under various ``what-if" conditions. However, the behavior models controlling the actions of the actors…
BigSUMO: A Scalable Framework for Big Data Traffic Analytics and Parallel Simulation
Rahul Sengupta, Nooshin Yousefzadeh, Manav Sanghvi +7
With growing urbanization worldwide, efficient management of traffic infrastructure is critical for transportation agencies and city planners. It is essential to have tools that he…
Evaluating Generative Vehicle Trajectory Models for Traffic Intersection Dynamics
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic Intersections are vital to urban road networks as they regulate the movement of people and goods. However, they are regions of conflicting trajectories and are prone to acc…
IntTrajSim: Trajectory Prediction for Simulating Multi-Vehicle driving at Signalized Intersections
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic simulators are widely used to study the operational efficiency of road infrastructure, but their rule-based approach limits their ability to mimic real-world driving behavi…
TGDT: A Temporal Graph-based Digital Twin for Urban Traffic Corridors
Nooshin Yousefzadeh, Rahul Sengupta, Jeremy Dilmore +1
Urban congestion at signalized intersections leads to significant delays, economic losses, and increased emissions. Existing deep learning models often lack spatial generalizabilit…
Dynamic Graph Attention Networks for Travel Time Distribution Prediction in Urban Arterial Roads
Nooshin Yousefzadeh, Rahul Sengupta, Sanjay Ranka
Effective congestion management along signalized corridors is essential for improving productivity and reducing costs, with arterial travel time serving as a key performance metric…
Graph Attention Network for Lane-Wise and Topology-Invariant Intersection Traffic Simulation
Nooshin Yousefzadeh, Rahul Sengupta, Yashaswi Karnati +2
Traffic congestion has significant economic, environmental, and social ramifications. Intersection traffic flow dynamics are influenced by numerous factors. While microscopic traff…
MTDT: A Multi-Task Deep Learning Digital Twin
Nooshin Yousefzadeh, Rahul Sengupta, Yashaswi Karnati +2
Traffic congestion has significant impacts on both the economy and the environment. Measures of Effectiveness (MOEs) have long been the standard for evaluating traffic intersection…