Filip Van den Bossche

Describing the Evolution in the Number of Highway Deaths by Decomposition in Exposure, Accident Risk, and Fatality Risk

The general purpose of this research is to improve insight into road safety on Belgian highways by means of a layered model. The monthly number of persons killed on highways in Belgium is decomposed into three parts: exposure, accident risk, and fatality risk. The evolution in each of these dimensions is investigated separately. More specifically, for each dimension a descriptive and explanatory analysis reveals the optimal unobserved components model. The separate analysis of each dimension may reveal different underlying developments. The impact of meteorological, socioeconomic, legislative, and calendar factors on exposure, accident risk, and fatality risk is investigated. The analysis indicates that, although for each dimension the same basic components are available, the optimal model of each dimension has its unique structure of descriptive components and significant variables. Precipitation and snow enhance accident risk, while temperature plays a significant role for exposure. Fatality risk decreases in case of an extra day with precipitation and was significantly affected by the child restraint law. The economic indicators mainly affect accident risk. When the three models are brought back together, the number of highway deaths between 1993 and 2001 is well reconstructed.

Analysis of Road Risk by Age and Gender Category: Time Series Approach

A road safety analysis for different age and gender categories of road users is introduced. In contrast to many previous studies, the time series of road crashes by age and gender category is considered. The objective is to analyze Belgian data on the yearly number of fatalities for age and gender groups by using a decomposition of the number of fatalities in terms of exposure and risk in a time series perspective. For each category, a state space time series model is developed for the risk, which is defined in this study as the number of fatalities per capita. It was found that road risk is changing over age groups according to a U-shaped curve and that men generally have a higher risk than women. Further, the risk is decreasing over time but not at the same rate for all age and gender groups. The highest yearly reduction in risk is found for the oldest and youngest road users. The models also are useful to assess the attainability of formulated road safety targets, which makes them useful policy instruments. Especially for young men, the reduction in road risk is not in line with Belgian and Flemish policy expectations.

Role of Exposure in Analysis of Road Accidents: A Belgian Case Study

Exposure is a key variable in traffic safety research. In the literature, it is noted as the first and primary determinant of traffic safety. In many cases, however, no valid exposure measure is available. In Belgium, monthly traffic counts for 12 years are available. This offers the opportunity to investigate the added value of exposure in models, next to legal, economic, and climatologic variables. Multiple regression with autoregressive moving average (ARMA) errors is used to quantify the impact of these factors on aggregated traffic safety. For each dependent variable, a model with and without exposure is constructed. The models show that exposure is significantly related to the number of accidents with persons killed and seriously injured and to the corresponding victims, but not to the lightly injured outcomes. Moreover, the addition or deletion of exposure does not influence the effects of the remaining variables in the model. The effects of exposure clearly depend on the type of measure used and on the time horizon considered. The framework of a regression model with ARMA errors allows for missing variables being accounted for by the error term. Even without a variable such as exposure, valid models can be constructed.