Explaining the road accident risk: Weather effects

Abstract

This research aims to highlight the link between weather conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road safety monitoring at a national level. It is based on some case studies carried out in Work Package 7 on "Data analysis and synthesis" of the EU-FP6 project "SafetyNet-Building the European Road Safety Observatory", which illustrate the use of weather variables for analysing changes in the number of road injury accidents. Time series analysis models with explanatory variables that measure the weather quantitatively were used and applied to aggregate datasets of injury accidents for France, the Netherlands and the Athens region, over periods of more than 20 years. The main results reveal significant correlations on a monthly basis between weather variables and the aggregate number of injury accidents, but the magnitude and even the sign of these correlations vary according to the type of road (motorways, rural roads or urban roads). Moreover, in the case of the interurban network in France, it appears that the rainfall effect is mainly direct on motorways--exposure being unchanged, and partly indirect on main roads--as a result of changes in exposure. Additional results obtained on a daily basis for the Athens region indicate that capturing the within-the-month variability of the weather variables and including it in a monthly model highlights the effects of extreme weather. Such findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated. The outlook for the approach and its added value are discussed in the conclusion.

Road Safety Trends at National Level in Europe: A Review of Time-series Analysis Performed during the Period 2000–12

“…From 2000 onwards in particular, light approaches for adjusting the changes in aggregate road safety indicators, which account for a few number of risk factors and the main road safety measures, were progressively adopted. Researchers have mainly focused on structural modelling introduced by Harvey (1989), whether on an annual, quarterly or monthly basis (Lassarre, 2001;Commandeur, Bijleveld, & Bergel, 2007;Bergel-Hayat, Debbarh, Antoniou, & Yannis, 2013). Although structural modelling was presented as more appropriate than the autoregressive integrated and moving average (ARIMA) modelling commonly used on a quarterly or monthly basis (Harvey, & Durbin, 1986), it is worth noting that these two approaches are coherent as some forms of structural models may be written with an equivalent ARIMA model form (Commandeur et al, 2013).…”

“…Comparing the inclusion of the weather as a factor for a number of European regions. An analysis of the effects of weather on injury accident data has been conducted for a number of European regions, on a monthly basis and over periods of more than 20 years (Bergel-Hayat, Debbarh, Antoniou, & Yannis, 2013). Rainfall, temperature and the occurrence of frost were retained to measure the weather risk factor, and computed as the daily value of the variable registered at a weather station or, eventually averaged over a set of weather stations, and averaged over a month.…”

Weather Conditions, Weather Information and Car Crashes

“…Gitelman et al [17] Shows, for the world's best performing countries in terms of road safety, that only a few perform really well across the board, whereas most of these overall good performing countries appear to have some weak spots in their policy portfolio. Bergel-Hayat et al [18] adopts a kind of meso-level approach comparing accident proneness by means of monthly data with respect to weather conditions in France, Greece and the Netherlands, while differentiating between road systems.…”

Effects of rainfall intensity on traffic crashes in Hong Kong

“…Over the past three decades, many studies have examined the impacts of adverse weather conditions on road safety (Andrey et al, 2013;Bergel-Hayat et al, 2013;Mujalli and Oña, 2013) and traffic conditions (Chen et al, 2012(Chen et al, , 2013(Chen et al, , 2014Lam et al, 2008;Mohaymany et al, 2013;Tsapakis et al, 2013). It has been found that adverse weather in the form of rain or snow has significant detrimental effects on traffic safety.…”