Road user related risks and measures – evidence based decision support for road safety policy

The EU-funded SafetyCube project aims at facilitating decision making in road safety by providing systematically analysed and assessed scientific evidence on risk factors and countermeasures. While this is done for the areas infrastructure, vehicle and road users, this paper focus solely on the latter. The project outcomes are available online and are targeted at actual decision makers as well as researchers. Various stakeholders were consulted to identify hot topics and the needs of practitioners. The accessible database currently contains about 450 individual study outcomes and synopses with condensed information for 49 road risks (e.g. speeding, drink-driving, fatigue) and measures (fitness to drive, education, enforcement, campaigns, etc.) associated with all kinds of road users (vehicle drivers, cyclists, pedestrians, elderly, young, commercial drivers). In a further step, cost-benefit will be assessed on the basis of the effectiveness of countermeasures. While vehicle and infrastructure related risks and measures are well suited for effect quantification, this is a challenging endeavour for road users for many reasons

Compilation of analyses of risks and measures, deliverable 8.2 of the H2020 project SafetyCube

This deliverable provides information on how the information on road safety risks and measures that has been collected within SafetyCube, is processed, stored and made available to users through the SafetyCube Decision Support System (DSS) [...continues]

Developing the European road safety decision support system

The Decision Support System (DSS) is one of the key objectives of the European co-funded research project SafetyCube in order to better support evidence-based policy making. Results will be assembled in the form of a DSS that will present for each suggested road safety measure: details of risk factor tackled, measure, best estimate of casualty reduction effectiveness, cost-benefit evaluation and analytic background. The development of the DSS presents a great potential to further support decision making at local, regional, national and international level, aiming to fill in the current gap of comparable measures effectiveness evaluation. In order to provide policy-makers and industry with comprehensive and well-structured information about measures, it is essential that a systems approach is used to ensure the links between risk factors and all relevant safety measures are made fully visible. The DSS is intended to become a major source of information for industry, policy-makers and the wider road safety community

A systematic cost-benefit analysis of 29 road safety measures

Economic evaluations of road safety measures are only rarely published in the scholarly literature. We collected and (re-)analyzed evidence in order to conduct cost-benefit analyses (CBAs) for 29 road safety measures. The information on crash costs was based on data from a survey in European countries. We applied a systematic procedure including corrections for inflation and Purchasing Power Parity in order to express all the monetary information in the same units (EUR, 2015). Cost-benefit analyses were done for measures with favorable estimated effects on road safety and for which relevant information on costs could be found. Results were assessed in terms of benefit-to-cost ratios and net present value. In order to account for some uncertainties, we carried out sensitivity analyses based on varying assumptions for costs of measures and measure effectiveness. Moreover we defined some combinations used as best case and worst case scenarios. In the best estimate scenario, 25 measures turn out to be cost-effective. 4 measures (road lighting, automatic barriers installation, area wide traffic calming and mandatory eyesight tests) are not cost-effective according to this scenario. In total, 14 measures remain cost-effective throughout all scenarios, whereas 10 other measures switch from cost-effective in the best case scenario to not cost-effective in the worst case scenario. For three measures insufficient information is available to calculate all scenarios. Two measures (automatic barriers installation and area wide traffic calming) even in the best case do not become cost-effective. Inherent uncertainties tend to be present in the underlying data on costs of measures, effects and target groups. Results of CBAs are not necessarily generally valid or directly transferable to other settings.acceptedVersio

Crash cost estimates for European countries, deliverable 3.2 of the H2020 project SafetyCube

Crash cost estimates for European countries, deliverable 3.2 of the H2020 project SafetyCub

Consultation of a panel of experts on the needs for data and technical tools in road safety policy-making. Deliverable 1.1/4.1 of the EC FP7 project DaCoTA

Consultation of a panel of experts on the needs for data and technical tools in road safety policy-making. Deliverable 1.1/4.1 of the EC FP7 project DaCoT

SafetyCube: Building a decision support system on risks and measures

The EU research project SafetyCube (Safety CaUsation, Benefits and Efficiency) is developing an innovative road safety Decision Support System (DSS) collecting the available evidence on a broad range of road risks and possible countermeasures. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs

Stakeholder's contribution. Deliverable 1.3 of the EC FP7 Project DaCoTA

The aim of DaCoTA’s Work Package 1 is to shed light on road safety policy-making and management processes in Europe and to explore how these can be better supported by data and knowledge. This was done by assessing demands and views of stakeholders as well as by building a good practice model for road safety management investigation. Future versions of the European Road Safety Observatory (ERSO, www.erso.eu) are envisaged to be built on the findings of this project. This report describes the methodology and presents the first aggregated results of an on-line stakeholder consultation carried out in Task 1.3. The survey was successfully carried out among more than 3000 road safety stakeholders in Europe and beyond

The European road safety decision support system on risks and measures

The European Road Safety Decision Support System (roadsafety-dss.eu) is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation instrument (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs

Description of data-sources used in SafetyCube. Deliverable 3.1 of the H2020 project SafetyCube

Safety CaUsation, Benefits and Efficiency (SafetyCube) is a European Commission supported Horizon 2020 project with the objective of developing an innovative road safety Decision Support System (DSS) that will enable policy-makers and stakeholders to select and implement the most appropriate strategies, measures and cost-effective approaches to reduce casualties of all road user types and all severities. This deliverable describes the available data in the form of an inventory of databases that can be used for analyses within the project. Two general types of data are available: one describing the involvement of different components for the road safety (vehicles, infrastructure, and the road user) and one describing the injury outcomes of a crash. These two database categories are available to the partners of SafetyCube and gathered in two excel tables. One table contains traffic databases (accident and naturalistic driving studies) and the second table contains injury databases. The tables contain information on 58 and 35 variables, respectively. The key information describing the databases that was needed for the inventory were items such as: Type of data collected (crashes, injuries, etc.) Documentation of the variables Sampling criteria for the data collected SafetyCube partners with access to the data Extent of data access (raw data vs. summary tables) The tables contain 36 traffic accident databases, five naturalistic driving studies or field-tests and 22 injury databases where of four were coded in both sheets