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Review Open access Aug 2026

Improving the Denominator of Safety Rankings for Bicyclist and Pedestrian Safety

Active transportation increases physical activity and improves health, yet rising pedestrian and bicyclist deaths are a growing public health concern. In North America, regional agencies allocate transportation investments to support safe walking and bicycling. While comparing crash statistic across regions is standard...

Caitlyn Linehan, T. Nelson, Achituv Cohen · 0 citations
Conference Open access Oct 2026

Reproducing Weekly Crash Patterns Using a Minimalist Driver Error Model

Microscopic traffic simulation models are increasingly used for safety assessment, yet their ability to reproduce realistic crash patterns remains poorly understood. This study compares weekly patterns of real crashes at one of Berlin’s most accident-prone intersections (“Schlesisches Tor”) with simulated crashes gener...

A. Leich, R. Nippold, Peter Wagner · 0 citations
Open access 2021

Spatial Clustering of Road Traffic Crash Locations on IntercityCorridors Using National Road Safety Records

A crash hotspot map is only as good as the coordinates it is built from, and in most of theworld those coordinates record where a responder attended rather than where the crash occurred. We ask what that costs a corridor prioritization decision. Using two intercity corridors,the 54.0 km Ilorin to Ogbomoso trunk in Kwar...

Oladimeji Basit Alaka, Ridwan Tiamiyu, Olayemi Bolaji · 0 citations
#artificial intelligence Preprint Oct 2026

Trajectory Prediction for Autonomous Driving in Road Construction Zones Using Human-in-the-Loop Driving Data

Ego-trajectory prediction in urban roadway work zones remains an underexplored topic in autonomous-driving research, with limited dedicated data and systematic evaluation. Roadway work zones involve temporary changes in the lane layouts and connectivity of the roads, complicating interactions with surrounding vehicles...

Shuo Zhang, Aman Sunesh, S. Ergan et al. · 0 citations
Aug 2026

Addressing data limitations in autonomous vehicles crash severity analysis: A hybrid framework for small samples and sample imbalance.

OBJECTIVE This study aimed to address key data limitations in autonomous vehicle (AV) crash-severity analysis, including small samples and sample imbalance, and to identify interpretable risk factors associated with injury outcomes in AV crashes. METHODS A verified dataset of 2,946 AV crash events from 2015 to 2024 w...

Feng Tang, Ruien Wu, Ning Li et al. · 0 citations

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