The estimates of the possible effects of road safety strategies presented in figures 14 and 15 are based on the following main assumptions:
• They refer to the effects of fully implementing all measures in a road safety strategy consistently for a period of ten years.
19539
15254
11093
9183
21721
0 5000 10000 15000 20000 25000
Basis for estimates
Business as usual
Cost-benefit strategy
Vision Zero strategy
Maximum safety potential
Number of killed or injured road users
• They take the current number of killed or injured road users, that is the mean annual numbers for the years 1994-1998 as the basis for estimating the effects of the road safety strategies.
• They do account for the effects of traffic growth or other factors that may affect road safety.
In order to give somewhat more realistic predictions of the number of killed or injured road users that can be expected to occur in a specific year, the effects of traffic growth and other factors that influence road safety have to be estimated.
According to the National Road Plan 1998-2007 (Vägverket 1998), road traffic is expected to grow by about 1% per year from 1993 until 2010. In recent years, traffic has grown by more than 1% per year. The growth from 1998 to 1999 was 3%. A forecast based on an assumption of 1% annual growth in traffic volume has nevertheless been applied in this report.
The effects of a 1% annual growth in traffic volume on the number of accidents and road accident victims depends on a number of factors. Some of these factors, like the road safety measures introduced, can be controlled by government. Other factors are, for all practical purposes outside government control. Some of the factors that are outside government control can have a major effect on road safety.
An illustration of the importance for road safety of two factors that are mostly outside government control is given in a report by Brüde (1999A). In the report, the effects on the number of traffic accident fatalities of the reduction in the proportion of car kilometres driven by young drivers (age 18-24 years) after about 1990 and the reduction in the proportion of drinking drivers in Sweden has been estimated. It is concluded that these two factors are likely to have reduced the number of traffic accident fatalities in Sweden by 55 to 93 during the years 1994- 1996. This amounts to an effect of 10-17%, which is very substantial.
The same report contains predictions for the number of traffic accident fatalities for the year 2007. The predictions are based on a model with the following structure:
Predicted number of traffic accident fatalities = a ⋅ bYear⋅ Fuelc
This simple model fits the past changes in the number of traffic accident fatalities in Sweden very well. The fuel term captures the effects of changes in traffic volume on the number of traffic accident fatalities. The year term captures the total effects of all other factors on the number of fatalities. This includes the effects of road safety measures that are introduced, as well as effects of demographic changes, changes in road user behaviour and so on.
During the years from 1977 through 1997, the fatality rate per kilometre of travel declined by about 5% per year. Hence, it was only in periods of very strong traffic growth, combined with other unfavourable changes that the number of traffic accident fatalities increased. Based on the model fitted to data for the years 1977- 1997, Brüde predicts 388 traffic accident fatalities in Sweden in the year 2007.
Other predictions, based on the same model fitted to different years, range from 383 to 417 fatalities in the year 2007.
In a subsequent report (Brüde 1999B), predictions have been broken down by region and group of road user. However, this report gives predictions just for the year 2000, not for 2007.
Unfortunately, the prediction models developed by Brüde cannot be applied to the estimations presented in this report. The chief reason why these prediction models cannot be applied, is that they contain the effects of road safety measures. The decline in accident rate that has been observed in Sweden after 1977 is partly due to the road safety measures that have been introduced. The models developed by Brüde contains the effects of these measures, but lumps it together with whatever other factors have affected the accident rate as well, such as the recent decline in the proportion of young drivers and drinking drivers.
A main objective of this report is to estimate the potential effects of alternative road safety measures. Predictions of the future number of fatalities and injuries cannot then be based on a model which assumes that certain road safety measures have been implemented. An ideal prediction model for the purposes of this report would be a model that included all factors that influence road safety, except road safety measures. Such a model could then be applied to predict the number of fatalities and injuries expected to occur if no new road safety measures are
introduced. It is, of course, assumed that no road safety measures already in place are removed. Briefly speaking this means that all elements of the road system are maintained at their current standard, and that turning over of the vehicle fleet is allowed to occur without government intervention or new vehicle safety
standards.
The closest to such a model that has been found, is the model developed by Fridstrøm, Ifver, Ingebrigtsen, Kulmala and Krogsgård Thomsen (1993).
Although this model does not perfectly fit the description above, it comes close to it. Moreover, the model has been shown to fit historical accident records quite well. The model accounts for the effects of:
• Traffic exposure (measured by means of fuel sales)
• Changes in the rules and routines for accident reporting
• Weather conditions (precipitation, temperature)
• Length of daylight
• Annual trend
• Pure random variation
As in the model developed by Brüde, the annual trend term is likely to contain effects of road safety measures. However, the model was fitted by means of state- of-the-art multivariate techniques, which means that the parameters estimated for each variable can be interpreted as the partial effect of that variable, controlling for all other variables in the model. This means that the model can be readily applied to estimate the effect on traffic injuries of traffic growth, controlling for all other factors that affect road safety.
For Sweden, elasticities have been estimated for the number of road users killed and the number of road users injured with respect to traffic volume. These
elasticities were 0.64 for fatalities and 0.99 for injuries. This means that as traffic volume grows by 1%, one can expect a 0.64% growth in the number of fatalities
and an 0.99% growth in the total number of police reported injuries. These results have been applied to predict the number of traffic accident fatalities and the number of people injured in traffic accidents in Sweden in the years from 1999 to 2012.
A traffic growth of 3% from 1998 to 1999 was assumed. For the subsequent years, an annual growth rate of 1% was assumed. The predicted number of traffic
accident fatalities in 2012 came to 613. The predicted number of killed or injured road users in 2012 came to 25,422.
It should be noted that these predictions are likely to be quite pessimistic. These predictions assume that the only factor than contributes to improving road safety in the long run is the introduction of new road safety measures. This is unlikely to be true. As recent experience has shown, other factors may contribute to road safety as well. Predicting these factors is, however, very difficult.
8.3 Effects of road safety strategies in relation to road safety