From the 1 of 17 linked papers with an AI index.
1 citations · 1 across the 1 of their papers we have counts for
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A Prescriptive Framework for Determining Optimal Days for Short-Term Traffic Counts
Arthur Mukwaya, Nancy Kasamala, Nana Kankam Gyimah +5
The Federal Highway Administration (FHWA) mandates that state Departments of Transportation (DOTs) collect reliable Annual Average Daily Traffic (AADT) data. However, many U.S. DOT…
Real-Time Conflict Prediction for Large Truck Merging in Mixed Traffic at Work Zone Lane Closures
Abyad Enan, Abdullah Al Mamun, Gurcan Comert +4
Large trucks substantially contribute to work zone-related crashes, primarily due to their large size and blind spots. When approaching a work zone, large trucks often need to merg…
Crash Severity Risk Modeling Strategies under Data Imbalance
Abdullah Al Mamun, Abyad Enan, Debbie A. Indah +3
This study investigates crash severity risk modeling strategies for work zones involving large vehicles (i.e., trucks, buses, and vans) under crash data imbalance between low-sever…
Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign Classification
Reek Majumder, Mashrur Chowdhury, Sakib Mahmud Khan +6
Deep learning (DL)-based image classification models are essential for autonomous vehicle (AV) perception modules since incorrect categorization might have severe repercussions. Ad…
Unraveling Pedestrian Fatality Patterns: A Comparative Study with Explainable AI
Methusela Sulle, Judith Mwakalonge, Gurcan Comert +2
Road fatalities pose significant public safety and health challenges worldwide, with pedestrians being particularly vulnerable in vehicle-pedestrian crashes due to disparities in p…
Analyzing Factors Influencing Driver Willingness to Accept Advanced Driver Assistance Systems
Hannah Musau, Nana Kankam Gyimah, Judith Mwakalonge +2
Advanced Driver Assistance Systems (ADAS) enhance highway safety by improving environmental perception and reducing human errors. However, misconceptions, trust issues, and knowled…