The endurance of the effects of the penalty point system in Spain three years after. Main influencing factors

In this work we have used ARIMA time series models to analyse the contribution of the penalty point system, the most important legislative measure for driving licences, in reducing the number of fatalities over 24 h on the roads in Spain during the study period (January 1995 to June 2009). In addition, because of this long period of analysis, other control variables were introduced to model the enactment of the Reform of the Penal Code in December 2007, together with other more specific effects needed to fit the model correctly. The ARIMA intervention models methodology combines the basic features of specific times series models: it controls the trend and seasonal variation in data that is present when modelling the structure through autoregressive and moving average parameters and allows for inserting step or impulse input variables for checking and evaluating the effects of deterministic measures, such as legislative changes which are the object of study in this work. This paper analyses the surveillance and control measures introduced in the periods before and after the implementation of the penalty point system and helps to partly explain its apparent endurance over time. The results show that the introduction of the penalty point system in Spain had a very positive effect in reducing the number of fatalities (over 24 h) on the road, and that this effect has endured up to the present time. This success may be due to the continuing increase in surveillance measures and fines as well the significantly growing interest shown by the news media in road safety since the measures were introduced. All this has led to positive changes in driver behaviour. It is, therefore, a combination of three factors: the penalty point system, the gradual stepping up of surveillance measures and sanctions, and the publicity given to road safety issues in the mass media would appear to be the key to success. The absence of any of these three factors would have predictably led to a far less positive evolution of the accident rate on Spanish roads.     

Sustainability of the effects of the demerit points system on seat belt use: a region-wide before-and-after observational study in Italy

To assess the short and long term effects of the demerit points system on seat belt use, we set a region-wide cross-sectional observational study 3 months before, and 3 and 15 months after the introduction of the scheme (July 2003) in the Veneto Region, Italy. We analysed differences in seat belt use by year of observation, gender and position in the vehicle, and obtained adjusted prevalence ratio (APR) through Poisson regression. A total of 29,303 drivers, 28,778 front and 12,186 rear passengers were observed. Prevalence levels of 54% for drivers and 53% for front passengers in 2003 switched to 83 and 76%, respectively, 3 months after the new legislation, with further slight increases 15 months thereafter. Seventy-four percent rear passengers were still not compliant with the legislation in 2005. The probability of being belted was 25% lower in males than females (APR=0.75, 95% CI 0.73-0.77) at the beginning of the study period. However, the effect of the new legislation was 19% greater among males (APR=1.19, 95% CI 1.16-1.23). A substantial increase in seat belt use was reached and sustained with the demerit points system. Specific efforts should target rear passengers whose seat belt use still remains worryingly low.     

On statistical inference in time series analysis of the evolution of road safety

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research.     

The effects of speed enforcement with mobile radar on speed and accidents. An evaluation study on rural roads in the Dutch province Friesland

In an evaluation study, the effects of targeted speed enforcement on speed and road accidents were assessed. Enforcement was predominantly carried out by means of mobile radar and focused on rural non-motorway roads. Information and publicity supported the enforcement activities. The evaluation covered a period of 5 years of enforcement. The speed data of these 5 years and the year preceding the enforcement project showed a significant decrease in mean speed and the percentage speed limit violators over time. The largest decrease was found in the first year of the enforcement project and in the fourth year of the project, when the enforcement effort was further intensified. There were similar decreases in speeding at both the enforced roads and at the nearby comparison roads that were not subjected to the targeted speed enforcement project, which may be explained by spillover effects. The best estimate for the safety effect of the enforcement project is a reduction of 21% in both the number of injury accidents and the number of serious casualties. This was based on comparison between the number of accidents/casualties during the enforcement project (5 years) and and the 8 preceding years on the enforced roads and at all other roads outside urban areas in the same region.     

An analysis of the electrical conductivity in BaSO4-added Ag2SO4 solid electrolyte system

The compositions (1 −x)Ag₂SO₄−(x)BaSO₄, wherex=0·01 to 0·6, were prepared by slow cooling of the melt. The extent of the solid solubility of Ba²⁺ in Ag₂SO₄ was determined by X-ray powder diffraction and scanning electron microscopy. The bulk conductivity of each sample was obtained using a detailed impedance analysis. The partial substitution of Ba²⁺ results in the enhancement of conductivity in compliance with the classical aliovalent doping theory. A simplistic model based on lattice distortion (expansion) due to partial substitution of Ag⁺ by the bigger Ba²⁺ has been considered to explain enhanced conductivity. Beyond solid-solubility limit (5·27 mole%) the BaSO₄-dispersed Ag₂SO₄ conductivity follows the usual trend seen in binary systems. An increase in conductivity in this case is discussed in the light of interfacial reactions and surface defect chemistry. The maximum conductivity in 20 mole% BaSO₄ dispersed Ag₂SO₄ is due to percolation threshold.