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Geometric and Operational Features of Horizontal Curves with Specific Regard to Skidding Proneness
(1) Run-off-road (ROR) crashes are a crucial issue worldwide, resulting in a disproportionate number of traffic deaths. In safety research, macro-level analysis on large datasets is usually conducted by linking explanatory variables to ROR crash frequency/severity. Micro-analysis approaches, like th...
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Published in: | Infrastructures (Basel) 2020-01, Vol.5 (1), p.3 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | (1) Run-off-road (ROR) crashes are a crucial issue worldwide, resulting in a disproportionate number of traffic deaths. In safety research, macro-level analysis on large datasets is usually conducted by linking explanatory variables to ROR crash frequency/severity. Micro-analysis approaches, like the one used in this study, are instead less frequent. (2) A comprehensive Italian Fatal + Injury (FI) crash dataset was filtered to identify two-way two-lane rural road curves on the national road network on which more than one ROR FI crash (i.e., at least two crashes) in the observation period of four years had occurred. The typical features of the ROR FI crashes and the recurrent geometric (characteristics of tangents and curves) and operational features (inferred speeds, acceleration/decelerations) of the crash sites were reconstructed. (3) The main contributory factors in ROR FI crashes are: wet pavements, speeding, and distraction. Sites with a relevant history of ROR FI crashes present recurrent safety issues such as inadequate horizontal curve coordination, an insufficient tangent length for decelerating, and inferred operating speeds comparable/higher than the inferred design speeds. (4) Based on findings, some practical suggestions for road safety management and maintenance are proposed through specific indicators and countermeasures (speed, perception, and friction related). |
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ISSN: | 2412-3811 2412-3811 |
DOI: | 10.3390/infrastructures5010003 |