5 papers
A Dimensionality-Reduced XAI Framework for Roundabout Crash Severity Insights
Rohit Chakraborty, Subasish Das
Roundabouts reduce severe crashes, yet risk patterns vary by conditions. This study analyzes 2017-2021 Ohio roundabout crashes using a two-step, explainable workflow. Cluster Corre…
From Tiny Machine Learning to Tiny Deep Learning: A Survey
Shriyank Somvanshi, Md Monzurul Islam, Gaurab Chhetri +8
The rapid growth of edge devices has driven the demand for deploying artificial intelligence (AI) at the edge, giving rise to Tiny Machine Learning (TinyML) and its evolving counte…
Comparative Analysis of Advanced AI-based Object Detection Models for Pavement Marking Quality Assessment during Daytime
Gian Antariksa, Rohit Chakraborty, Shriyank Somvanshi +4
Visual object detection utilizing deep learning plays a vital role in computer vision and has extensive applications in transportation engineering. This paper focuses on detecting…
Crash Severity Analysis of Child Bicyclists using Arm-Net and MambaNet
Shriyank Somvanshi, Rohit Chakraborty, Subasish Das +1
Child bicyclists (14 years and younger) are among the most vulnerable road users, often experiencing severe injuries or fatalities in crashes. This study analyzed 2,394 child bicyc…
Applying Tabular Deep Learning Models to Estimate Crash Injury Types of Young Motorcyclists
Shriyank Somvanshi, Anannya Ghosh Tusti, Rohit Chakraborty +1
Young motorcyclists, particularly those aged 15 to 24 years old, face a heightened risk of severe crashes due to factors such as speeding, traffic violations, and helmet usage. Thi…