Are speed enforcement cameras more effective than other speed management measures?: An evaluation of the relationship between speed and accident reductions

doi:10.1016/j.aap.2005.03.014

Accident Analysis & Prevention

Volume 37, Issue 4, July 2005, Pages 731-741

https://doi.org/10.1016/j.aap.2005.03.014 Get rights and content

Abstract

In this paper, models are developed which enable a prediction of how the impact of speed management schemes on accidents varies both with speed changes and with site and scheme characteristics. It was found that, the impact of schemes with vertical deflections is independent of the change in mean speed: an accident reduction of 44% is predicted by the model irrespective of the impact on speed. For cameras and other types of engineering schemes, a simple relationship between the change in mean speed and the consequent change in accidents is available. For the range of mean speeds typically found on 30 mph roads, the percentage accident reduction per 1mph speed reduction is around 4% for cameras and 7–8% for schemes with horizontal features. While larger percentage accident reductions are achieved per 1 mph speed reduction on lower speed roads, larger speed reductions and larger overall percentage accident reductions are obtained on roads with higher before mean speeds. It is possible to predict both changes in speeds and accidents before treatment using the models derived from this study and these models confirm that schemes with vertical deflections are most effective in reducing both speeds and accidents.

Introduction

Although there is evidence that inappropriate speed is a major factor affecting road accident frequency and severity, the effectiveness of speed management schemes in reducing speeds and accidents, and the nature of the relationship between these reductions, is not well understood. It has been suggested that a progressive relationship exists between reductions in accidents and reductions in mean speed (see for example, Finch et al., 1994, Webster and Mackie, 1996, Taylor et al., 2000). A 5% reduction in accidents for each 1mph reduction in mean speed is widely quoted although Taylor et al. (2000) suggest that the actual percentage accident reduction depends on the nature of the road and the before mean speed: with larger reductions on urban roads with low average speeds and smaller reductions on higher speed roads. However, these findings must be treated with some caution. Cross-sectional studies of roads with different speed and accident distributions (for example, Finch et al., 1994 and Taylor et al., 2000) examine how differences in the distributions of speeds on different roads may affect accidents but, since these roads have no speed management schemes in place, such studies cannot examine how a specific treatment intervention may impact on speeds, or how this change in speed might relate to changes in accidents. Numerous before-and-after studies of specific speed management schemes have been published but few have had available both accident and speed data and, until recently, none have fully separated the accident changes attributable to the effects of speed changes from those due to the various confounding factors that hamper the analysis of before-and-after accident data (for example, Webster and Mackie, 1996). Thus, the true relationship between the speed changes associated with various types of speed management measures and their consequent accident changes have yet to be established.

The aim of the research on which this paper is based, was thus to investigate this issue, comparing the impact of a range of speed management schemes on both accidents and speed distributions, taking proper account of non-scheme effects on accidents. A separate paper presented details of the average effects of such schemes (Mountain et al., 2005). It was found that, on average, all types of speed management schemes reduced accidents although not all schemes were successful. Engineering schemes with vertical deflections (such as speed humps, tables or cushions (see, for example, County Surveyors Society, 1994)) offered the largest and most consistent percentage accident reductions: an overall fall in personal injury accidents (PIAs) attributable to scheme effects of 44%, of which a 38% fall was attributable to speed changes and the remaining 6% due to traffic diversion away from the speed managed section. The impact of vertical deflections on accidents was twice that at sites where safety cameras were used to control speeds: an overall fall in PIAs of 22%, of which a fall of 17% was attributable to speed reductions. Schemes with vertical deflections were also the only type of scheme to have a significant impact on fatal and serious accidents. Other types of engineering schemes (with a fall in PIAs of 29%) were, on average, less effective in reducing accidents than schemes with vertical features but more effective than cameras. It was also shown that, on average, all types of speed management scheme were successful in reducing vehicle speeds. Schemes with vertical deflections had the greatest impact on speed: an average reduction in the mean speed of 8.4 mph and a reduction in the percentage of drivers exceeding the speed limit from 56% to only 16%.

This analysis was concerned with the average effect of the various types of speed management scheme on accident frequencies and speeds. The variation in the reduction in annual accidents within each scheme type was, however, considerable, as was the impact on speed. It was thus of interest to attempt to understand the underlying causes of this variation with a view to establishing which type of speed management scheme was most effective for any given set of site conditions. This paper thus describes the next stage of the analysis: to develop models that would enable a prediction of how the impact of treatment on accidents varies both with speed changes and with site and scheme characteristics.

Section snippets

Data

The data for this study relate to 149 speed management schemes on 30 mph roads throughout Great Britain (Mountain et al., 2005). These schemes include 79 speed enforcement cameras (17 mobile and 62 fixed cameras) and 70 engineering schemes of various types. The engineering schemes were split into two categories: “vertical deflections” and “horizontal features”. The first category comprised the 39 schemes that included any form of vertical deflection. The remaining 31 schemes were classified as

Estimation of confounding factors

A detailed description of the approach to the accident analysis is given elsewhere (Hirst et al., 2004a, Hirst et al., 2004b, Mountain et al., 2005). A review of existing methodologies for estimating confounding factors in observational before and after accident studies was carried out (Hirst et al., 2004a). While the empirical Bayes (EB) method appeared to have the greatest potential to allow for RTM effects, in its simplest form potential sources of error were identified. In particular, it

Treatment effect models

In order to model the safety effect of speed management schemes it is necessary to model accidents in the period after the scheme has been implemented. This is not straightforward. The usual negative binomial (NB) model for analysing annual accident counts, Y_i, for n sites is of the form: $Y_{i} \sim NB (μ_{i}, K) where \log (μ_{i}) = \log (t_{i}) + f (Z_{i} β) for i = 1, \dots, n .$ K is the shape parameter, Z_i is the vector of explanatory variables and β is the vector of coefficients. In this model, the offset is the logarithm of

Predictive models

With the exception of the model for schemes with vertical deflections, the models described above require measurements of mean speeds after scheme implementation. Since after speeds can be measured soon after scheme implementation, while useful accident data takes several years to accumulate, they can be used predictively in the early life of a scheme. It may, however, also be useful to predict the likely treatment effect prior to scheme implementation. The next stage in the modelling was thus

Discussion

As noted in the introduction, it has been suggested that a progressive relationship exists between reductions in accidents and mean speed: a 5% reduction in accidents for each 1mph reduction in mean speed is widely quoted. The results presented here suggest that in fact the relationship between accident changes and speed changes is complex and is dependent on the nature of the speed management scheme.

Further work is needed to establish the reasons for this variation. It may, for example, be

Conclusions

The main conclusions that can be drawn from this analysis of the relationship between speed and accident reductions following the implementation of speed management schemes on roads subject to a 30 mph speed limit can be summarized as follows.

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For cameras and engineering schemes with horizontal features, a simple relationship between the change in mean speed and the change in accidents due to speed is available. The impact of schemes with vertical deflections on accidents is similar regardless of

Acknowledgements

The authors gratefully acknowledge the financial support of the Engineering and Physical Sciences Research Council and the assistance of the staff of the local authorities, their consultants, and the police forces that supplied data for this project. The areas for which data have been provided include: Blackpool, Bournemouth, Bradford, Bridgend, Buckinghamshire, Cambridgeshire, Cleveland, Devon, Doncaster, Durham, Essex, Gloucestershire, Herefordshire, Lancashire, Leicestershire, Lincolnshire,

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Are speed enforcement cameras more effective than other speed management measures?: An evaluation of the relationship between speed and accident reductions

Abstract

Introduction

Section snippets

Data

Estimation of confounding factors

Treatment effect models

Predictive models

Discussion

Conclusions

Acknowledgements

Accid. Anal. Prev.

Accid. Anal. Prev.

Accid. Anal. Prev.

Traffic Calming in Practice