57 citations · 93 across the 5 of their papers we have counts for
5 papers
From Canopy to Collision: A Hybrid Predictive Framework for Identifying Risk Factors in Tree-Involved Traffic Crashes
Abdul Azim, Ahmed Hossain, Soumyadip Maitra +1
Tree-involved crashes represent a critical subset of run-off-road (ROR) collisions, often resulting in fatal or severe injuries due to high-energy impacts. This study develops a co…
Assessing the Role of Intersection Proximity in Pedestrian Crashes: Insights from Data Mining Approach
Ahmed Hossain, Xiaoduan Sun
Although intersections are the most complex parts of the roadway network, pedestrian crashes at non-intersection locations are disproportionately frequent, highlighting a serious t…
A Survey on Deep Tabular Learning
Shriyank Somvanshi, Subasish Das, Syed Aaqib Javed +2
Tabular data, widely used in industries like healthcare, finance, and transportation, presents unique challenges for deep learning due to its heterogeneous nature and lack of spati…
Identifying roadway departure crash patterns on rural two-lane highways under different lighting conditions: association knowledge using data mining approach
Ahmed Hossain, Xiaoduan Sun, Shahrin Islam +2
More than half of all fatalities on U.S. highways occur due to roadway departure (RwD) each year. Previous research has explored various risk factors that contribute to RwD crashes…
Applying Association Rules Mining to Investigate Pedestrian Fatal and Injury Crash Patterns Under Different Lighting Conditions
Ahmed Hossain, Xiaoduan Sun, Raju Thapa +1
The pattern of pedestrian crashes varies greatly depending on lighting circumstances, emphasizing the need of examining pedestrian crashes in various lighting conditions. Using Lou…