The objective of this study is the comparative assessment and review of infrastructure related risk factors with the explicit purpose of ranking them based on how detrimental they are towards road safety (i.e. crash risk, frequency and severity). This analysis was carried out within the SafetyCube project, which aims to identify and quantify the effects of risk factors and measures related to behaviour, infrastructure or vehicle factors, and integrate the results in an innovative road safety Decision Support System (DSS). This evaluation was conducted by examining studies from the existing literature. These were selected and analysed using a specifically designed common methodology. All risk factors to be analysed were structured in a taxonomy. The infrastructure risk factors covered 10 areas with several risk factors in each area (59 risk factors in total), examples include: alignment features (e.g. horizontal-vertical alignment deficiencies), cross-section characteristics (e.g. superelevation, lane, median and shoulder deficiencies), road surface deficiencies, workzones, junction deficiencies (interchange and at-grade) etc. Consultation with infrastructure stakeholders (international organisations, road authorities, etc.) took place in dedicated workshops to identify user needs for the DSS, as well as topics of particular importance. The following analysis methodology was applied to each infrastructure risk factor:i) A search for relevant international literature, ii)Selection of studies on the basis of rigorous criteria, iii) Analysis of studies in terms of design, methods and limitations, iv) Synthesis of findings – and meta-analysis, when feasible. More than 270 high quality studies were selected and analysed. In total, 6 original meta-analyses were carried out, as well as 31 other syntheses. This allowed the ranking of infrastructure related risk factors into three groups: risky (8 risk factors), probably risky (21 risk factors), and unclear (7 risk factors).
|Tags||intelligent systems, road infrastructure|