Combining road safety information in a performance index

Hermans, Elke; Bossche, Filip Van den; Wets, Geert

doi:10.1016/j.aap.2008.02.004

Cited by 163 publications

(114 citation statements)

References 14 publications

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“…For this case, 11 road safety experts from several European countries were asked to distribute a given budget over a set of risk domains in such a way that spending more on a domain implies that (s)he wants to stress its importance. The experts, participating in the European SafetyNet project and familiar with road safety risk domains and performance indicators, indicated the share of the budget they would spend on alcohol and drugs, speed, protective systems, vehicle, infrastructure and trauma management (Hermans et al, 2008a). For each domain, the minimum (Li) and maximum share (Ui) over the 11 experts, shown in Table 1, is taken into account by the model.…”

Section: Modelmentioning

confidence: 99%

“…The composite indicators field uses several weighting methods of which budget allocation, analytic hierarchy process, data envelopment analysis (DEA), factor analysis and equal weighting are the most common ones (Nardo et al, 2005;Saisana & Tarantola, 2002). A comparison of these five methods on road safety data revealed that the DEA method resulted in the best fit with the ranking based on the number of traffic fatalities per million inhabitants (Hermans et al, 2008a). These good results of the data envelopment analysis in addition to its interesting characteristics (determination of the most optimal score for each country, consideration of both inputs and outputs, easy incorporation of value judgements to obtain realistic weights, etc) caused the elaboration of a DEA model adapted to and suitable for the specific road safety context.…”

Section: Introductionmentioning

confidence: 99%

“…However, this domain is not considered in this study as, in literature, the importance of this rather small aspect of road safety is less obvious. Additionally, road safety experts consider this as the least important risk domain of all (Hermans et al, 2008a). Some Northern countries constituted a daytime running lights' law a long time ago.…”

mentioning

confidence: 99%

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Benchmarking road safety: Lessons to learn from a data envelopment analysis

Hermans

Brijs

Wets

et al. 2009

Accident Analysis & Prevention

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127

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Road safety performance indicators (SPI) have recently been proposed as a useful instrument in comparing countries on the performance of different risk aspects of their road safety system. In this respect, SPIs should be actionable, i.e. they should provide clear directions for policymakers about what action is needed and which priorities should be set in order to improve a country's road safety level in the most efficient way.This paper aims at contributing to this issue by proposing a computational model based on data envelopment analysis (DEA). Based on the model output, the good and bad aspects of road safety are identified for each country. Moreover, targets and priorities for policy actions can be set. As our data set contains 21 European countries for which a separate, best possible model is constructed, a number of country-specific policy actions can be recommended. Conclusions are drawn regarding the following performance indicators: alcohol, speed, protective systems, vehicle, infrastructure and trauma management. For each country that performs relatively poorly, a particular country will be assigned as a useful benchmark. Road safety performance information from other countries can help in this respect.Better insight into the road safety situation can be gained by studying the available data.In this context, a comparison between countries is often made based on crash data. The number of injury crashes and the number of casualties (divided into fatalities, serious injuries and slight injuries) per capita can be used to set up a ranking. In respect to the number of fatalities, Sweden, the United Kingdom and the Netherlands -being referred to as the SUN countries -are seen as an example for other European countries. Furthermore, in addition to the development of a set of useful crash related variables on the one hand and road safety performance indicators on the other hand, it would be interesting to create one road safety index (a combination of relevant road safety aspects into one index) enabling an overall comparison across entities (e.g. countries). The multidimensionality is summarised and the total road safety picture can be presented. The SafetyNet project stresses the importance of daytime running lights as an extra risk domain (in addition to the other six). However, this domain is not considered in this study as, in literature, the importance of this rather small aspect of road safety is less obvious. Additionally, road safety experts consider this as the least important risk domain of all (Hermans et al., 2008a). Some Northern countries constituted a daytime running lights' law a long time ago. Recently, there is no agreement regarding the obligation of daytime running lights on a larger (European) scale as the possible effects are unclear. Moreover, the availability and quality of the data is very poor compared to the other indicators. 2 Road safety outcomes can be decomposed in two main components, i.e. exposure and risk. To fairly compare countries road safety outcomes (e.g. the nu...

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Section: Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Benchmarking road safety: Lessons to learn from a data envelopment analysis

Hermans

Brijs

Wets

et al. 2009

Accident Analysis & Prevention

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127

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“…For instance, applications for Expert Choice® can be found in transport-related assessment (e.g., [4,119]), marine and coastal resources (e.g., [120,121]), and project management (e.g., [122]). …”

Section: About Ahpmentioning

confidence: 99%

Integrated approach to the assessment of CO2e-mitigation measures for the road passenger transport sector in Bahrain

Alsabbagh

Siu

Guehnemann

et al. 2017

Renewable and Sustainable Energy Reviews

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Integrated approach to the assessment of CO 2 e-mitigation measures for the road passenger transport sector in Bahrain AbstractThe transport sector is one of the fastest-growing energy-consuming sectors in the world and it contributes greatly to emissions of carbon dioxide equivalent (CO 2 e). In Bahrain, CO 2 e emissions from the transport sector grew by an average of 8% annually between 1994 and 2006. The aim of this research was to develop an integrated approach to assess the measures adopted to reduce CO 2 e emissions by the transport sector within the context of climate change mitigation. This approach used the multi-criteria analysis methodology of the Analytic Hierarchy Process (AHP) to embed conventional assessment methods and a participatory approach. Three extensions to the original AHP methodology were developed: multi-AHP models, scenario packaging, and the examination of the plausibility of the results. The AHP results showed that certain fuel economy standards achieved the highest scores against five qualitative and quantitative criteria. Using socially and politically acceptable options, an integrated approach to CO 2 e mitigation could achieve a reduction in emissions of around 22% by 2030 (compared with 2010), at a cost of USD 112 per metric tonne of avoided CO 2 e emissions. Results from surveys of policymakers, experts, and the general public indicated that the outcomes of scenario packaging were plausible. The contributions of this research are two-fold. First, for the first time in Bahrain, the preferences of the general public have been considered and integrated with both the preferences of policymakers and experts and the results obtained from conventional assessment methods. Second, a structured approach for the integration of different assessment methods, transferable to other contexts, was developed and examined. Furthermore, multi-AHP models were introduced that can reflect the preferences of different concerned groups. Applications of this approach include 3 assessment of the implementation of mitigation measures that could affect a number of concerned groups, decision making in energy-consuming sectors, and development of mitigation policy packages.

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“…In the future the weighting method should be considered in a broader sense. Other relevant weighting techniques for the road safety context such as data envelopment analysis [21] should be incorporated in the model as the choice between several weighting methods may influence the end result to a large extent.…”

Section: Conclusion and Further Researchmentioning

confidence: 99%

Uncertainty assessment of the road safety index

Hermans

Bossche²,

Wets

2009

Reliability Engineering & System Safety

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a b s t r a c tComposite indicators aggregate domain-specific information in one index, on the basis of which countries can be assigned a relative ranking. Recently, the road safety community got convinced of the policy supporting role of indicators in terms of benchmarking, target setting and selection of measures. However, combining the information of a set of relevant risk indicators in one index presenting the whole picture turns out to be very challenging. In particular, the rank of a country can be largely influenced by the methodological choices made during the composite indicator building process. Decisions concerning the selection of indicators, the normalisation of the indicator values, the weighting of indicators and the way of aggregating can influence the final ranking. In this research, it is shown that the road safety ranking of countries differs significantly according to the selected weighting method, the expert choice and the set of indicators. From these three input factors, the selection of the set of indicators is most influential. A well considered selection of indicators will therefore establish the largest reduction in ranking uncertainty. With a set of appropriate indicators, the proposed framework reveals the major sources of uncertainty in the creation of a composite road safety indicator.

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Combining road safety information in a performance index

Cited by 163 publications

References 14 publications

Benchmarking road safety: Lessons to learn from a data envelopment analysis

Benchmarking road safety: Lessons to learn from a data envelopment analysis

Integrated approach to the assessment of CO2e-mitigation measures for the road passenger transport sector in Bahrain

Uncertainty assessment of the road safety index

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