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Economic evaluation of road user related measures

Deliverable 4.3 of the H2020 project SafetyCube

Auteur(s)

Daniels, S.; Aigner-Breuss, E.; Kaiser, S.; Goldenbeld, C.; Katrakazas, C.; Schoeters, A.; Ziakopoulos; Usami, D.S.; Bauer, R.; Papadimitriou, E.; Weijermars, W.; Rodriguez Palmeiro, A.; Talbot, R.

Jaar

2017

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.

The following steps have been taken to achieve the results presented in this document:

  • Selecting effective measures, suitable for a cost-benefit analysis
  • Collecting data on measure costs, target group, effectiveness and penetration rates
  • Applying the common methodology to conduct cost-benefit analyses, using the E3 calculator developed in WP3
  • Searching for existing cost-benefit analyses on effective measures if required data is missing
  • Updating existing cost-benefit analyses in the SafetyCube E3 calculator with updated crash and measure costs
  • Documenting all steps and assumptions for each cost-benefit analysis

In a previous task of work package 4 (Theofilatos et al., 2017) the effectiveness of road safety measures in preventing road crashes or casualties was assessed by giving color codes to each measure. Measures which were marked with the colour codes ‘green’ (effective) or ‘light green’ (probably effective) were screened for their suitability in terms of economic evaluation. It is important to note that studies dealing with road user related countermeasure often assess the impact on safety performance indicators rather than accident outcomes (see Theofilatos et al., 2017 for further information). That leads to a limited number of measure topics that qualify for economic evaluation in the SafetyCube E3 calculator in the first place.

An economic evaluation can be done by cost-effectiveness analysis, cost-utility analysis or costbenefit analysis. Within SafetyCube the economic evaluation principally is done by executing costbenefit analyses (CBA). In a CBA, the crash costs enter as benefits (because they are prevented) and the costs for measures are compared to them. The core output of this task are exemplary economic evaluations for 12 road-user related road safety measures, of which 11 cost-benefit analyses and 1 measure for which the break-even costs are calculated.
The documentation of these CBAs is added in the Appendix and provide detailed information on the used data and calculations. The principal tool for all the analyses was the Economic Efficiency Evaluation (E3) calculator that has been developed in the SafetyCube project. A major advantage of this tool is that it enables to standardise the input and output information.

Most of the assessed human related measures have a benefit-to-cost ratio (CBR) that is higher than 1. This means that the benefits outweigh the costs and are economically efficient. The conducted calculationsshow a wide range of benefit-to-cost ratios (BCR) between 1 and 125.1. For only one measure the CBA resulted in a BCR smaller than 1, which means that it is not economically efficient.

Sensitivity analyses are performed using different rates of effectiveness of the measure in preventing crashes, and different values for measure costs. A best and worst-case scenario are estimated, and it was shown that in a worst-case scenario (with a lower effectiveness estimate and higher costs) the BCR still remains above 1 for the majority of the measures benefit-to-cost ratio.

The most important limitation of using cost-benefit analyses is its dependence on the underlying assumptions about the measure effectiveness, the target group and the measure costs. Therefore, the CBAs were accompanied by a sensitivity analysis. These analyses clearly demonstrated that changing the basic assumptions on the effectiveness or costs of measures has a large influence on the value of the BCR. Furthermore, it has to be noted that in the 12 economic evaluations conducted, side effects of countermeasures were only available for mandatory exe-sight testing, but are generally hardly reported.

The results of these CBAs can be used by policymakers, but – given the limitations – the values should be used carefully and with a critical eye. The assumptions that are made should be checked thouroughly. Furthermore, it is recommended to complement the available information with specific information on the measure’s target group, likely effects, the measure costs and the circumstances in which they are applied.

All together the number of CBAs on road safety measures in the scientific literature is very limited and much further work is needed to systematically assess costs and benefits of road safety measures.

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European Commission, Brussels