Review and ranking of crash risk factors related to the road infrastructure.

The objective of this paper is the review and comparative assessment of infrastructure related crash 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 aimed to identify and quantify the effects of risk factors and measures related to behaviour, infrastructure or vehicles, and integrate the results in an innovative road safety Decision Support System (DSS). The evaluation was conducted by examining studies from the existing literature. These were selected and analysed using a specifically designed common methodology. Infrastructure risk factors were structured in a hierarchical taxonomy of 10 areas with several risk factors in each area (59 specific risk factors in total), examples include: alignment features (e.g. horizontal-vertical alignment deficiencies), cross-section characteristics (e.g. superelevation, lanes, 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 "hot 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. In total 243 recent and high quality studies were selected and analysed. Synthesis of results was made through 39 'Synopses' (including 4 original meta-analyses) on individual risk factors or groups of risk factors. This allowed the ranking of infrastructure risk factors into three groups: risky (11 risk factors), probably risky (18 risk factors), and unclear (7 risk factors).

[1]  G. Yannis,et al.  Meta-analysis of the effect of road work zones on crash occurrence. , 2017, Accident; analysis and prevention.

[2]  George Yannis,et al.  Best Practice for Cost-Effective Road Safety Infrastructure Investments , 2008 .

[3]  R Elvik,et al.  Area-wide urban traffic calming schemes: a meta-analysis of safety effects. , 2001, Accident; analysis and prevention.

[4]  Niklas Strand,et al.  Identification of road user related risk factors, deliverable 4.1 of the H2020 project SafetyCube. , 2016 .

[5]  Yannis George,et al.  Inventory and Critical Review of existing APMs and CMFs and related Data Sources, Deliverable WP4, Predicting Road Accidents a Transferable methodology across Europe. , 2015 .

[6]  George Yannis,et al.  Traffic Safety Basic Facts 2012 : Motorways , 2013 .

[7]  Rune Elvik,et al.  Safety-in-numbers: A systematic review and meta-analysis of evidence , 2017 .

[8]  Theo Stijnen,et al.  Advanced methods in meta‐analysis: multivariate approach and meta‐regression , 2002, Statistics in medicine.

[9]  Martijn Vis,et al.  Development of Road Safety Performance Indicators for the European Countries , 2014 .

[10]  Athanasios Theofilatos,et al.  Meta-Analysis of Crash-Risk Factors in Freeway Entrance and Exit Areas , 2017 .

[11]  Rune Elvik,et al.  Inventory of assessed infrastructure risk factors and measures, Deliverable 5.4 of the H2020 project SafetyCube , 2017 .

[12]  Wolfgang Viechtbauer,et al.  Conducting Meta-Analyses in R with the metafor Package , 2010 .

[13]  Rune Elvik,et al.  The European road safety decision support system on risks and measures. , 2019, Accident; analysis and prevention.

[14]  Rune Elvik,et al.  The Handbook of Road Safety Measures , 2009 .

[15]  George Yannis,et al.  Traffic Safety Basic Facts 2012 : Junctions , 2013 .

[16]  A Baruya,et al.  THE EFFECTS OF DRIVERS' SPEED ON THE FREQUENCY OF ROAD ACCIDENTS , 2000 .

[17]  Rune Elvik,et al.  Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube , 2016 .

[18]  C S Berkey,et al.  A random-effects regression model for meta-analysis. , 1995, Statistics in medicine.

[19]  Simon Washington,et al.  Impact of real-time traffic characteristics on freeway crash occurrence: systematic review and meta-analysis. , 2015, Accident; analysis and prevention.

[20]  George Yannis,et al.  Traffic Safety Basic Facts 2012 : Roads outisde urban areas , 2013 .

[21]  Rune Elvik,et al.  The European road safety decision support system. A clearinghouse of road safety risks and measures, Deliverable 8.3 of the H2020 project SafetyCube , 2018 .

[22]  Rune Elvik,et al.  The range of replications technique for assessing the external validity of road safety evaluation studies. , 2012, Accident; analysis and prevention.