activity
20232026
collaborators

7 papers

cs.SE2026

Measuring Braking Behavior Using Vehicle Tracking and Camera-to-Satellite Homography Rectification

J. P. Fleischer, Tanchanok Sirikanchittavon, Chonlachart Jeenprasom +3

This paper presents an open-source software application for analyzing traffic camera footage, focusing on vehicle behavior and braking events at signalized urban highways. The core…

cs.DC2026

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…

cs.LG2025

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…

cs.LG2024

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…

cs.LG2024

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…

cs.LG2024

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…