5 papers
Adapting a Large Language Model Crash-Severity Pipeline to Tennessee: Performance Across Sampling Strategies
Abhilasha Saroj, Pranav Govindu, Bharat Sharma +1
State crash databases differ in structure, coding, and injury-severity distributions, limiting direct reuse of predictive workflows across jurisdictions. This study adapts the Safe…
A Graph Neural Network Surrogate Model for Incident-Based Travel Time Prediction Under Limited Sensor Data
Abhilasha Saroj, Natalie Myers, Haoran Niu
Localized roadway incidents can produce congestion well beyond their point of origin, but evaluating these effects with microscopic simulation requires a separate run for each scen…
Emergency Vehicle Preemption Strategies using Machine Learning to Optimize Traffic Operations
Somdut Roy, Michael Hunter, Abhilasha Saroj +1
Emergency response vehicles (ERVs), such as fire trucks, operate to save lives and mitigate property damage. Emergency vehicle preemption (EVP) is typically implemented to provide…
Modeling Disruptions to Urban Metabolism using Interconnected Networks
Bharat Sharma, Abhilasha J. Saroj, Evan Scherrer +1
Representation of cities as organisms with metabolic processes is a useful analogy for urban design, development and sustainability. Urban metabolism can be modeled by representing…
Memory-Guided Trust-Region Bayesian Optimization (MG-TuRBO) for High Dimensions
Abhilasha Saroj, Shaked Regev, Guanhao Xu +3
Traffic simulation and digital-twin calibration is a challenging optimization problem with a limited simulation budget. Each trial requires an expensive simulation run, and the rel…