SWOV

Leidschendam, Netherlands
Leidschendam, Netherlands
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Stipdonk H.,SWOV | Bijleveld F.,SWOV | Van Norden Y.,SWOV | Commandeur J.,SWOV
Accident Analysis and Prevention | Year: 2013

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.


Stipdonk H.,SWOV | Wesemann P.,SWOV | Ale B.,Technical University of Delft
Safety Science | Year: 2010

Road safety policy plans often require robust calculation of the expected number of road casualties in a certain target year. The relevance of such estimations should be measured by their power to influence and support safety policy makers. Thus, techniques to evaluate the safety developments and the estimating methods must be sound, robust, and preferably accepted by both policy makers and the scientific community. In this paper, we concentrate on choosing an appropriate model used for the calculation, rather than on statistical techniques. We calculate a casualty rate from casualty data and mobility (distance travelled) data, which is extrapolated and subsequently multiplied by an expected future distance travelled. After correction for separately assessed effects of additional safety measures, the number of casualties is estimated. We investigate a method where this is done after both mobility data and casualty data are stratified into properly chosen subsets. Projecting these different trends generally leads to a result that differs from the projection of the aggregated data. Also, stratification enables incorporation in the estimation of explaining factors or additional measures related to a specific subset of the casualties. The principles of stratified projections are illustrated by three Dutch projections which were carried out between 2006 and 2008. Also, some preliminary results of further research on stratification are given. The results imply that the rates of change in casualty rate for different traffic modes or driver age, are not necessarily equal. We propose that these specific decreasing trends are a consequence of external influencing factors. © 2010 Elsevier Ltd.


Wesemann P.,SWOV | Norden Y.V.,SWOV | Stipdonk H.,SWOV
Safety Science | Year: 2010

This paper discusses the method used for an outlook on road safety in the Netherlands until 2020. The objectives of the outlook are to judge the feasibility of the Dutch road safety policy targets and to estimate the effects in 2020 of new measures. The outlook consists of baseline forecasts assuming the unchanged continuation of the effect of current road safety policy as a starting point, and the effect of new measures on top of that. We used four different mobility scenarios, derived from a comprehensive study about the macro-economic development of Dutch society until 2040. In the mobility scenario with the largest growth it appeared doubtful whether the policy targets of that time for the maximum number of fatalities in 2020 (580) can be achieved. An extensive inventory of new measures after 2010 produced five already intended new measures, the effects of which were estimated. The results show that the target of maximum 580 fatalities in 2020 can probably be met. The recently adjusted policy target of 500 fatalities in 2020 is also feasible if additional new measures are taken. © 2010 Elsevier Ltd.


Stipdonk H.,SWOV | Reurings M.,SWOV
Traffic Injury Prevention | Year: 2012

Objective: To describe and apply a method to assess the effect on road safety of a modal shift from cars to bicycles.Method: Ten percent of all car trips shorter than 7.5 km were assumed to be replaced by bicycle trips. Single-vehicle and multivehicle crashes involving cars and/or bicycles were considered. The safety of car occupants and cyclists was taken into account as well as the safety of other road users involved in such crashes. The computations were carried out by age and gender. Assuming constant risk (casualties per distance traveled), the expected number of accidents is proportional to the mobility shift. Several types of risk were considered: the risk of being injured as a car driver or cyclist and the risk of being involved as a car driver or cyclist in a crash in which another road user is injured.Results: The results indicated that the total gain of the modal shift was negative for fatalities, which means that there was a net increase in the number of fatalities. The modal shift was advantageous for young drivers and disadvantageous for elderly drivers. In addition, it was more positive for males than for females. The turning point was around the age of 35. For hospitalized casualties, due to the strong influence of the many hospitalized cyclists in nonmotorized vehicle crashes, there was a strong negative overall effect, and the modal shift resulted in a positive effect for 18- and 19-year-old males only.Overall, a small increase (up to 1%) in the number of cyclist fatalities and a greater increase of 3.5 percent in the number of inpatients was expected. The increase in casualties was mainly due to the proportion of single-vehicle bicycle crashes with serious injuries in relation to the total number of injured cyclists. The effect of the modal shift was shown to depend on age and gender, resulting in fewer casualties for younger drivers and for women.Conclusions: It is possible to provide a first approximation of the effect on road safety of a mobility shift from cars to bicycles. This approximation indicates that, in general, road safety does not benefit from this modal shift. The effect differs for gender and age groups. Elderly drivers are safer inside a car than on a bicycle. For the number of hospitalized casualties, the modal shift increases the number of casualties for practically all ages and both genders. © 2012 Copyright Taylor and Francis Group, LLC.


Goldenbeld C.,SWOV | Houtenbos M.,SWOV | Ehlers E.,University of California at Berkeley | De Waard D.,University of Groningen
Journal of Safety Research | Year: 2012

Introduction: In the Netherlands, a survey was set up to monitor the extent of the use of portable, electronic devices while cycling amongst different age groups of cyclists and to estimate the possible consequences for safety. Method: The main research questions concerned age differences in the self-reported use of electronic devices while cycling, self-reported crash involvement and risk, and self-reported compensatory behaviour. Teen cyclists (12-17 years) and young adult cyclists (18-34 years) were more frequent users, and also more indiscriminate users of portable devices while cycling than middle-aged and older adult cyclists (35-49 years; 50 + years). Results: After statistical correction for influences on crash risk of urbanization level, weekly time spent cycling, and cycling in more demanding traffic situations, the odds of being involved in a bicycle crash were estimated to be higher for teen cyclists and young adult cyclists who used electronic devices on every trip compared to same age groups cyclists who never used these devices. For middle-aged and older adult cyclists, the use of portable electronic devices was not a significant predictor of bicycle crashes, but frequency of cycling in demanding traffic situations was. Possible implications for education or legal measures are discussed. Impact on Industry: Results may inform researchers, policy makers, and cyclists themselves. Educational campaigns may use risk information to warn young cyclists about risk of device use while cycling. © 2012 National Safety Council and Elsevier Ltd. All rights reserved.


De Waard D.,University of Groningen | Houwing S.,SWOV | Lewis-Evans B.,University of Groningen | Twisk D.,SWOV | Brookhuis K.,University of Groningen
Transportation Research Part F: Traffic Psychology and Behaviour | Year: 2015

Objective: According to international data estimates the proportion bicyclists with a positive Blood Alcohol Concentration (BAC) who are involved in accidents ranges from 15% to 57%. This large variance, and the fact that the reliance on accident statistics means that only the BAC of injured bicyclists is being collected, shows that we do not really know what the average and variation in BAC of bicyclists is, particularly on nights out. Method: On a total of four nights between 5. PM and 8. AM BAC levels of bicyclists were collected with a Breathalyser (N = 687). Samples were collected in two Dutch cities, one with a high (Groningen), and one with a modest, student population (The Hague). Results: The results showed that the percentage of bicyclists who had alcohol in their blood rose over the night from 7.7% at 6. PM to over 89% after 1. AM. Furthermore, the percentage of bicyclists with an illegal BAC above 0.5. g/l rose from zero percent at 6. PM to 68% at 1. AM. The average BAC of bicyclists with a BAC above zero was 0.79. g/l. Differences between the two cities were limited. Conclusion: Cycling with illegal levels of blood alcohol turns out to be very common on nights out in the Netherlands. © 2015 Elsevier Ltd.


Weijermars W.,SWOV | Wesemann P.,SWOV
Transportation Research Part A: Policy and Practice | Year: 2013

Road safety forecasting and ex-ante evaluation of road safety policy are useful tools in policy making. This paper illustrates the use of these instruments in policy making in the Netherlands. As part of an interim evaluation of achieving Dutch road safety targets, the numbers of fatalities and serious road injuries were estimated for 2020. From these forecasts, it was concluded that the target for serious road injuries most probably would not be met without additional policy measures. Therefore, the Minister of Infrastructure and the Environment in the Netherlands decided to take additional measures. From an ex-ante evaluation of these measures, it was concluded that also with these additional measures the target for the number of serious road injuries in 2020 will most probably not be met. © 2013 Elsevier Ltd.


PubMed | SWOV
Type: Journal Article | Journal: Journal of safety research | Year: 2012

In the Netherlands, a survey was set up to monitor the extent of the use of portable, electronic devices while cycling amongst different age groups of cyclists and to estimate the possible consequences for safety.The main research questions concerned age differences in the self-reported use of electronic devices while cycling, self-reported crash involvement and risk, and self-reported compensatory behaviour. Teen cyclists (12-17 years) and young adult cyclists (18-34 years) were more frequent users, and also more indiscriminate users of portable devices while cycling than middle-aged and older adult cyclists (35-49 years; 50+ years).After statistical correction for influences on crash risk of urbanization level, weekly time spent cycling, and cycling in more demanding traffic situations, the odds of being involved in a bicycle crash were estimated to be higher for teen cyclists and young adult cyclists who used electronic devices on every trip compared to same age groups cyclists who never used these devices. For middle-aged and older adult cyclists, the use of portable electronic devices was not a significant predictor of bicycle crashes, but frequency of cycling in demanding traffic situations was. Possible implications for education or legal measures are discussed.Results may inform researchers, policy makers, and cyclists themselves. Educational campaigns may use risk information to warn young cyclists about risk of device use while cycling.


PubMed | SWOV
Type: Journal Article | Journal: Traffic injury prevention | Year: 2012

To describe and apply a method to assess the effect on road safety of a modal shift from cars to bicycles.Ten percent of all car trips shorter than 7.5 km were assumed to be replaced by bicycle trips. Single-vehicle and multivehicle crashes involving cars and/or bicycles were considered. The safety of car occupants and cyclists was taken into account as well as the safety of other road users involved in such crashes. The computations were carried out by age and gender. Assuming constant risk (casualties per distance traveled), the expected number of accidents is proportional to the mobility shift. Several types of risk were considered: the risk of being injured as a car driver or cyclist and the risk of being involved as a car driver or cyclist in a crash in which another road user is injured.The results indicated that the total gain of the modal shift was negative for fatalities, which means that there was a net increase in the number of fatalities. The modal shift was advantageous for young drivers and disadvantageous for elderly drivers. In addition, it was more positive for males than for females. The turning point was around the age of 35. For hospitalized casualties, due to the strong influence of the many hospitalized cyclists in nonmotorized vehicle crashes, there was a strong negative overall effect, and the modal shift resulted in a positive effect for 18- and 19-year-old males only. Overall, a small increase (up to 1%) in the number of cyclist fatalities and a greater increase of 3.5 percent in the number of inpatients was expected. The increase in casualties was mainly due to the proportion of single-vehicle bicycle crashes with serious injuries in relation to the total number of injured cyclists. The effect of the modal shift was shown to depend on age and gender, resulting in fewer casualties for younger drivers and for women.It is possible to provide a first approximation of the effect on road safety of a mobility shift from cars to bicycles. This approximation indicates that, in general, road safety does not benefit from this modal shift. The effect differs for gender and age groups. Elderly drivers are safer inside a car than on a bicycle. For the number of hospitalized casualties, the modal shift increases the number of casualties for practically all ages and both genders.


PubMed | SWOV
Type: | Journal: Accident; analysis and prevention | Year: 2013

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.

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