10 papers
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…
Residual Modeling for High-Fidelity Learned Compression of Scientific Data
Liangji Zhu, Sanjay Ranka, Anand Rangarajan
Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at moderate accuracy targets, bu…
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…