Analysing the development of road safety using demographic data

H. Stipdonk, F.D. Bijleveld, Y. van Norden, J.J.F. Commandeur

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The purpose of this paper is to show that time series analyses of road safety and risk can be improved by using demographic data. We demonstrate that the distance travelled by drivers or riders of a certain age reflects the fluctuations over the years of the number of people of that age within the population. We further demonstrate that the change over time of per capita distance travelled, i.e. distance travelled per person, is often less subject to stochastic fluctuations, and therefore more smooth than the total distance travelled for drivers of that age. This smoothness is used to obtain forecasts of distance travelled, or to average out year-to-year fluctuations of data of distance travelled. Analysis of such data stratified by age group, gender or both reveals that, for most travel modes, per capita distance travelled is to a large extent constant or slowly changing over time. The consequences for the evaluation of risk, i.e. casualties per distance travelled, with and without the use of population data, are explored. Dutch data are used to illustrate the model concept. It is shown that the analyses and forecasts of distance travelled could gain substantially by incorporating demographic data, as compared to an analysis with data of distance travelled alone. The paper further shows that, for an analysis of risk and therefore for traffic safety forecasts in the absence of any data of distance travelled, stratified analysis of mortality, i.e. casualties per inhabitant, may be a reasonable alternative. © 2012 Elsevier Ltd.
LanguageEnglish
Pages435-444
JournalAccident Analysis and Prevention
Volume60
DOIs
Publication statusPublished - 2013

Fingerprint

Demography
road
Safety
fluctuation
Population
Time series
Age Groups
Mortality
driver
traffic safety
inhabitant
time series
age group
mortality
travel
human being
gender
evaluation

Cite this

@article{9896dff3ea034869ad686ac23582e252,
title = "Analysing the development of road safety using demographic data",
abstract = "The purpose of this paper is to show that time series analyses of road safety and risk can be improved by using demographic data. We demonstrate that the distance travelled by drivers or riders of a certain age reflects the fluctuations over the years of the number of people of that age within the population. We further demonstrate that the change over time of per capita distance travelled, i.e. distance travelled per person, is often less subject to stochastic fluctuations, and therefore more smooth than the total distance travelled for drivers of that age. This smoothness is used to obtain forecasts of distance travelled, or to average out year-to-year fluctuations of data of distance travelled. Analysis of such data stratified by age group, gender or both reveals that, for most travel modes, per capita distance travelled is to a large extent constant or slowly changing over time. The consequences for the evaluation of risk, i.e. casualties per distance travelled, with and without the use of population data, are explored. Dutch data are used to illustrate the model concept. It is shown that the analyses and forecasts of distance travelled could gain substantially by incorporating demographic data, as compared to an analysis with data of distance travelled alone. The paper further shows that, for an analysis of risk and therefore for traffic safety forecasts in the absence of any data of distance travelled, stratified analysis of mortality, i.e. casualties per inhabitant, may be a reasonable alternative. {\circledC} 2012 Elsevier Ltd.",
author = "H. Stipdonk and F.D. Bijleveld and {van Norden}, Y. and J.J.F. Commandeur",
year = "2013",
doi = "10.1016/j.aap.2012.08.005",
language = "English",
volume = "60",
pages = "435--444",
journal = "Accident Analysis and Prevention",
issn = "0001-4575",
publisher = "Elsevier Limited",

}

Analysing the development of road safety using demographic data. / Stipdonk, H.; Bijleveld, F.D.; van Norden, Y.; Commandeur, J.J.F.

In: Accident Analysis and Prevention, Vol. 60, 2013, p. 435-444.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Analysing the development of road safety using demographic data

AU - Stipdonk, H.

AU - Bijleveld, F.D.

AU - van Norden, Y.

AU - Commandeur, J.J.F.

PY - 2013

Y1 - 2013

N2 - The purpose of this paper is to show that time series analyses of road safety and risk can be improved by using demographic data. We demonstrate that the distance travelled by drivers or riders of a certain age reflects the fluctuations over the years of the number of people of that age within the population. We further demonstrate that the change over time of per capita distance travelled, i.e. distance travelled per person, is often less subject to stochastic fluctuations, and therefore more smooth than the total distance travelled for drivers of that age. This smoothness is used to obtain forecasts of distance travelled, or to average out year-to-year fluctuations of data of distance travelled. Analysis of such data stratified by age group, gender or both reveals that, for most travel modes, per capita distance travelled is to a large extent constant or slowly changing over time. The consequences for the evaluation of risk, i.e. casualties per distance travelled, with and without the use of population data, are explored. Dutch data are used to illustrate the model concept. It is shown that the analyses and forecasts of distance travelled could gain substantially by incorporating demographic data, as compared to an analysis with data of distance travelled alone. The paper further shows that, for an analysis of risk and therefore for traffic safety forecasts in the absence of any data of distance travelled, stratified analysis of mortality, i.e. casualties per inhabitant, may be a reasonable alternative. © 2012 Elsevier Ltd.

AB - The purpose of this paper is to show that time series analyses of road safety and risk can be improved by using demographic data. We demonstrate that the distance travelled by drivers or riders of a certain age reflects the fluctuations over the years of the number of people of that age within the population. We further demonstrate that the change over time of per capita distance travelled, i.e. distance travelled per person, is often less subject to stochastic fluctuations, and therefore more smooth than the total distance travelled for drivers of that age. This smoothness is used to obtain forecasts of distance travelled, or to average out year-to-year fluctuations of data of distance travelled. Analysis of such data stratified by age group, gender or both reveals that, for most travel modes, per capita distance travelled is to a large extent constant or slowly changing over time. The consequences for the evaluation of risk, i.e. casualties per distance travelled, with and without the use of population data, are explored. Dutch data are used to illustrate the model concept. It is shown that the analyses and forecasts of distance travelled could gain substantially by incorporating demographic data, as compared to an analysis with data of distance travelled alone. The paper further shows that, for an analysis of risk and therefore for traffic safety forecasts in the absence of any data of distance travelled, stratified analysis of mortality, i.e. casualties per inhabitant, may be a reasonable alternative. © 2012 Elsevier Ltd.

U2 - 10.1016/j.aap.2012.08.005

DO - 10.1016/j.aap.2012.08.005

M3 - Article

VL - 60

SP - 435

EP - 444

JO - Accident Analysis and Prevention

T2 - Accident Analysis and Prevention

JF - Accident Analysis and Prevention

SN - 0001-4575

ER -