20 research outputs found
SaferWheels study on powered two-wheeler and bicycle accidents in the EU - Annex 6 case summaries
SaferWheels study on powered two-wheeler and bicycle accidents in the EU - Annex 6 case summarie
Recommendations for establishing Pan European transparent and independent road accident investigations
A set of recommendations for pan-European transparent and independent road accident investigations has been developed by
the SafetyNet project. The aim of these recommendations is to pave the way for future EU scale accident investigation
activities by setting out the necessary steps for establishing safety oriented road accident investigations in Member States.
This can be seen as the start of the process for establishing road accident investigations throughout Europe which operate
according to a common methodology.
The recommendations propose a European Safety Oriented Road Accident Investigation Programme which sets out the
procedures that need to be put in place to investigate a sample of every day road accidents. They address four sets of issues;
institutional addressing the characteristics of the programme; operational describing the conditions under which data is
collected; data storage and protection; and reports, countermeasures and the dissemination of data
SaferWheels study on powered two-wheeler and bicycle accidents in the EU - Final report
Road Safety remains a major societal issue within the European Union. In 2014, some 26,000 people died and more than 203,500 were seriously injured on the roads of Europe, i.e. the equivalent of a medium town. However, although there are variations between Member States, road fatalities have been falling throughout the EU. Over the last 20 years, most Member States have achieved an overall reduction, some more than 50%. During this period, research on road safety and accident prevention has predominantly focused on protecting car occupants, with significant results. However, at the same time the number of fatalities and injuries among other categories of road users has not fallen to the same extent, indeed, in some cases, they have risen. The âVulnerable Road Usersâ (VRUs) in particular are a priority and represent a real challenge for researchers working on road safety and accident prevention. Accidents involving VRUs comprised approximately 48% of all fatalities in the EU during 2014, with Powered Two-Wheelers (PTWs) comprising 18% and cyclists comprising 8% of the total numbers of fatalities. The Commission adopted in July 2010 its Policy Orientations on Road Safety for 2010-2020. One of the strategic objectifies identified by the Commission is to improve the safety of Vulnerable Road Users. With this category of road users, motorcycle and moped users require specific attention given the trend in the number of accidents involving them and their important share of fatalities and serious injuries. The SaferWheels study was therefore conducted to investigate accident causation for traffic accidents involving powered two-wheelers and bicycles in the European Union. The objective of the study was to gather PTW and bicycle accident data from in-depth crash investigations, obtain accident causation and medical data for those crashes, and to store the information according to an appropriate and efficient protocol enabling a causation-oriented analysis. The expected outcomes were: - Collection of accident data for at least 500 accidents of which approximately 80% would involve Powered TwoâWheelers and the remainder bicycles. Equal numbers of cases were to be gathered in six countries; France, Greece, Italy, the Netherlands, Poland and the UK. - In-depth investigation and reporting for each of the accidents on the basis of the data collected. - Description of the main accident typologies and accident factors. - Proposal of most cost-effective measures to prevent PTW and bicycle accidents
Proposing a framework for pan European transparent and independent road accident investigation
Unlike the rail, civil aviation and maritime transport modes, there is currently
no standard process for investigating road accidents within Europe. There is,
therefore, a wide range of road accident investigation procedures and
protocols in place across Europe. However, as countries work towards
meeting both their own road safety targets and those set by the European
Commission, it may be that existing investigation practices are no longer
suited to facilitating the decision making processes of road safety policymakers
or practitioners.
SafetyNet is a European Commission supported project, which is building a
European Road Safety Observatory to facilitate the formulation of road safety
policy in the European Union. Work package 4 of SafetyNet is developing
recommendations for a Transparent and Independent pan-European
approach to road accident investigation.
These recommendations propose the establishment of an independent body
for undertaking transparent and independent accident investigations where
necessary, or the implementation of these investigations in existing national
safety orientated accident investigation activities, in each of the EU Member
States. This body would gather and manage accident investigation data and
use this data to further progress road safety within the EU.
To define the framework in which this body might operate, âBest practiceâ from
existing investigative organisations across Europe was examined in order to
produce a set of draft recommendations which focused on four categories of
issues:
1. Institutional, referring to the structure and functioning of the body
responsible for road safety investigations;
2. Operational, detailing how the body carries out investigations;
3. Data, addressing issues surrounding the storage, retrieval and
analysis of data generated by investigations; and
4. Development of Countermeasures, dealing with how investigation
conclusions should be presented, used and disseminated.
A consultation exercise was then undertaken in order to gather the expert
opinion of European road safety stakeholders and to further develop the
recommended framework. This highlighted a number of key questions about
the Draft Recommendations including:
⢠Is the proposed level of transparency and independence appropriate
for road accident investigations?
⢠Is one type of investigative activity appropriate for all types of accidents
ranging from the most severe or âmajorâ accidents to the large number
of more minor accidents that occur everyday?
The major conclusion was that a âone size fits allâ approach is not appropriate
for the investigation of road accidents and therefore multiple sets of
recommendations are required. This paper discusses how the four categories
of recommendations combine to form a framework where the data gathered
during road accident investigations can be used to develop road accident
countermeasures which will assist in casualty reduction throughout Europe
Economic evaluation of road user related measures. Deliverable 4.3 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). The DSS 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 document is the third deliverable (4.3) of work package 4, which is dedicated to the economic
evaluation - mainly by means of a cost-benefit analysis - of road user related safety measures [...continues]
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
Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube
The present Deliverable (D5.1) describes the identification and evaluation of infrastructure related risk factors. It outlines the results of Task 5.1 of WP5 of SafetyCube, which aimed to identify and evaluate infrastructure related risk factors and related road safety problems by (i) presenting a taxonomy of infrastructure related risks, (ii) identifying âhot topicsâ of concern for relevant stakeholders and (iii) evaluating the relative importance for road safety outcomes (crash risk, crash frequency and severity etc.) within the scientific literature for each identified risk factor. To help achieve this, Task 5.1 has initially exploited current knowledge (e.g. existing studies) and, where possible, existing accident data (macroscopic and in-depth) in order to identify and rank risk factors related to the road infrastructure. This information will help further on in WP5 to identify countermeasures for addressing these risk factors and finally to undertake an assessment of the effects of these countermeasures.
In order to develop a comprehensive taxonomy of road infrastructure-related risks, an overview of infrastructure safety across Europe was undertaken to identify the main types of road infrastructure-related risks, using key resources and publications such as the European Road Safety Observatory (ERSO), The Handbook of Road Safety Measures (Elvik et al., 2009), the iRAP toolkit and the SWOV factsheets, to name a few. The taxonomy developed contained 59 specific risk factors within 16 general risk factors, all within 10 infrastructure elements.
In addition to this, stakeholder consultations in the form of a series of workshops were undertaken to prioritise risk factors (âhot topicsâ) based on the feedback from the stakeholders on which risk factors they considered to be the most important or most relevant in terms of road infrastructure safety. The stakeholders who attended the workshops had a wide range of backgrounds (e.g. government, industry, research, relevant consumer organisations etc.) and a wide range of interests and knowledge. The identified âhot topicsâ were ranked in terms of importance (i.e. which would have the greatest effect on road safety). SafetyCube analysis will put the greatest emphasis on these topics (e.g. pedestrian/cyclist safety, crossings, visibility, removing obstacles).
To evaluate the scientific literature, a methodology was developed in Work Package 3 of the SafetyCube project. WP5 has applied this methodology to road infrastructure risk factors. This uniformed approach facilitated systematic searching of the scientific literature and consistent evaluation of the evidence for each risk factor. The method included a literature search strategy, a âcoding templateâ to record key data and metadata from individual studies, and guidelines for summarising the findings (Martensen et al, 2016b). The main databases used in the WP5 literature search were Scopus and TRID, with some risk factors utilising additional database searches (e.g. Google Scholar, Science Direct). Studies using crash data were considered highest priority. Where a high number of studies were found, further selection criteria were applied to ensure the best quality studies were included in the analysis (e.g. key meta-analyses, recent studies, country origin, importance).
Once the most relevant studies were identified for a risk factor, each study was coded within a template developed in WP3. Information coded for each study included road system element, basic study information, road user group information, study design, measures of exposure, measures of outcomes and types of effects. The information in the coded templates will be included in the relational database developed to serve as the main source (âback endâ) of the Decision Support
System (DSS) being developed for SafetyCube. Each risk factor was assigned a secondary coding partner who would carry out the control procedure and would discuss with the primary coding partner any coding issues they had found.
Once all studies were coded for a risk factor, a synopsis was created, synthesising the coded studies and outlining the main findings in the form of meta-analyses (where possible) or another type of comprehensive synthesis (e.g. vote-count analysis). Each synopsis consists of three sections: a 2 page summary (including abstract, overview of effects and analysis methods); a scientific overview (short literature synthesis, overview of studies, analysis methods and analysis of the effects) and finally supporting documents (e.g. details of literature search and comparison of available studies in detail, if relevant).
To enrich the background information in the synopses, in-depth accident investigation data from a number of sources across Europe (i.e. GIDAS, CARE/CADaS) was sourced. Not all risk factors could be enhanced with this data, but where it was possible, the aim was to provide further information on the type of crash scenarios typically found in collisions where specific infrastructure-related risk factors are present. If present, this data was included in the synopsis for the specific risk factor.
After undertaking the literature search and coding of the studies, it was found that for some risk factors, not enough detailed studies could be found to allow a synopsis to be written. Therefore, the revised number of specific risk factors that did have a synopsis written was 37, within 7 infrastructure elements. Nevertheless, the coded studies on the remaining risk factors will be included in the database to be accessible by the interested DSS users. At the start of each synopsis, the risk factor is assigned a colour code, which indicates how important this risk factor is in terms of the amount of evidence demonstrating its impact on road safety in terms of increasing crash risk or severity. The code can either be Red (very clear increased risk), Yellow (probably risky), Grey (unclear results) or Green (probably not risky). In total, eight risk factors were given a Red code (e.g. traffic volume, traffic composition, road surface deficiencies, shoulder deficiencies, workzone length, low curve radius), twenty were given a Yellow code (e.g. secondary crashes, risks associated with road type, narrow lane or median, roadside deficiencies, type of junction, design and visibility at junctions) seven were given a Grey code (e.g. congestion, frost and snow, densely spaced junctions etc.). The specific risk factors given the red code were found to be distributed across a range of infrastructure elements, demonstrating that the greatest risk is spread across several aspects of infrastructure design and traffic control. However, four âhot topicsâ were rated as being risky, which were âsmall work-zone lengthâ, âlow curve radiusâ, âabsence of shoulderâ and ânarrow shoulderâ.
Some limitations were identified. Firstly, because of the method used to attribute colour code, it is in theory possible for a risk factor with a Yellow colour code to have a greater overall magnitude of impact on road safety than a risk factor coded Red. This would occur if studies reported a large impact of a risk factor but without sufficient consistency to allocate a red colour code. Road safety benefits should be expected from implementing measures to mitigate Yellow as well as Red coded infrastructure risks. Secondly, findings may have been limited by both the implemented literature search strategy and the quality of the studies identified, but this was to ensure the studies included were of sufficiently high quality to inform understanding of the risk factor. Finally, due to difficulties of finding relevant studies, it was not possible to evaluate the effects on road safety of all topics listed in the taxonomy.
The next task of WP5 is to begin identifying measures that will counter the identified risk factors. Priority will be placed on investigating measures aimed to mitigate the risk factors identified as Red. The priority of risk factors in the Yellow category will depend on why they were assigned to this category and whether or not they are a hot topic
Identification of safety effects of infrastructure related measures, Deliverable 5.2 of the H2020 project SafetyCube
Identification of safety effects of infrastructure related measures, Deliverable 5.2 of the H2020 project SafetyCub
Inventory of assessed infrastructure risk factors and measures, Deliverable 5.4 of the H2020 project SafetyCube
Inventory of assessed infrastructure risk factors and measures, Deliverable 5.4 of the H2020 project SafetyCub
Innovative guidelines and tools for vulnerable road users safety in India and Brazil [SaferBraIn]. D4.1 Guidelines for integrated land use and transport planning for VRU safety
Innovative guidelines and tools for vulnerable road users safety in India and Brazil [SaferBraIn]. D4.1 Guidelines for integrated land use and transport planning for VRU safet