In the paper, results from in-depth investigation of 2,750 run-off-the-road (ROR) crashes on the motorway A16 (Italy) are presented. The research is aimed at pointing out risk factors that can address highway agencies and designers toward the selection of safety countermeasures aimed at reducing ROR crashes severity. Crash data were collected through the analysis of police crash reports and relate to the period 2001-2011. Crash severity was assessed in three categories (property damage only, slight injury, and severe injury/fatal) basing on police and hospital reports. Effects on crash severity were estimated through a multinomial logit model. The investigated factors included crash dynamics, number of crash events, day type, weather conditions, lighting conditions, cross-section characteristics, alignment, pavement conditions, most harmful impacted object, point of first impact, safety barrier performance, involved vehicles, driver’s gender, driver’s age, driver’s behavior, presence of passengers, passenger gender, passenger age, and seat belt use. Factors significantly contributing to an increase of crash severity were crash dynamics, alignment, most harmful impacted object, point of first impact, safety barrier performance, driver’s gender, driver’s behavior, and seat belt use.

Factors Contributing to Run-off-the-Road Severe Crashes

pernetti mariano
Methodology
2015

Abstract

In the paper, results from in-depth investigation of 2,750 run-off-the-road (ROR) crashes on the motorway A16 (Italy) are presented. The research is aimed at pointing out risk factors that can address highway agencies and designers toward the selection of safety countermeasures aimed at reducing ROR crashes severity. Crash data were collected through the analysis of police crash reports and relate to the period 2001-2011. Crash severity was assessed in three categories (property damage only, slight injury, and severe injury/fatal) basing on police and hospital reports. Effects on crash severity were estimated through a multinomial logit model. The investigated factors included crash dynamics, number of crash events, day type, weather conditions, lighting conditions, cross-section characteristics, alignment, pavement conditions, most harmful impacted object, point of first impact, safety barrier performance, involved vehicles, driver’s gender, driver’s age, driver’s behavior, presence of passengers, passenger gender, passenger age, and seat belt use. Factors significantly contributing to an increase of crash severity were crash dynamics, alignment, most harmful impacted object, point of first impact, safety barrier performance, driver’s gender, driver’s behavior, and seat belt use.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/412297
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