Examining Injury Severity of Moped and Motorcycle Occupants with Real-Time Traffic and Weather Data

Abstract

Currently studies exploring the effect of real-time traffic and weather characteristics on crash severity are relatively limited, and studies focusing on powered two-wheelers (PTWs) are even fewer. The objective of this paper is to add to current knowledge through the investigation of PTW occupant injury severity on the urban motorway Attica Tollway in Athens, Greece. For that purpose, 163 crashes (23 severe/fatal and 14 slight) that occurred between 26 and 211 were analyzed by considering real-time traffic and weather parameters. The required crash data was extracted from the Greek crash database of the National Technical University of Athens and also Attica Tollway. Traffic data were extracted from the Traffic Management Center of Attica Tollway, and weather data were extracted from the Hydrological Observatory of Athens (HOA). To reduce data dimensionality and to overcome multicollinearity between variables, a two-step approach was followed. First, principal component analysis and random forests were used as preliminary analyses. To account for the low number of and proportion of killed and severely injured (KSI) occupants, a Firth logistic regression was then applied. Results showed that in general, traffic and speed variations caused more severe injuries whereas weather parameters seemed to have no effect. It was also found that mean speeds and variations in volumes of trucks increased the crash injury severity of PTW crashes, but it was interesting that an increased proportion of trucks led to slighter injuries. The findings of this paper are considered promising and will contribute to better understanding of occupant injury severity on urban motorways by focusing on PTWs.