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Road Safety Statistics in European Cities The International Transport Forum (ITF) developed indicators to evaluate, monitor and benchmark road safety outcomes in 72 urban areas, most of them in Europe. Road mortality varies by a factor of 10 between cities Map 1 – Road mortality Road fatalities per year per 100 000 daytime population
The indicator most frequently used to measure road safety is number of road fatalities per unit of population, also called road mortality. In cities however, where many jobs and services are concentrated, resident population isn’t a fair representation of activity-levels. For the elaboration of comparable mortality rates, daytime population is used instead, which is defined as resident population corrected with the net flow of commuters.
Results in Map 1 reflect a wide range of situations, with annual fatalities ranging from 0.8 to 7.4 per year and per 100 000 daytime population. There is certainly room for performance to improve in most cities, at least by catching up with safer cities.
Mortality rates tend to rise with the size of the urban perimeter. Mortality in Inner London is lower than in Greater London, which is also lower than in the whole London functional urban area (FUA). A similar pattern was observed in Paris, Lisbon, Milan, Zürich and Stockholm.
The influence of city size and population density was investigated in “Road Safety in European Cities: Performance indicators and governance solutions”. It reveals that cities with a higher population density tend to have a lower mortality rate.
Cycling exposure data is collected to best understand risk
For a given mode, the concept of fatality risk is defined as the likelihood of being killed per unit of travel. It’s an indicator which directly relates to quality of life. It is however rarely computed because of difficulties in collecting mobility data, also called exposure data in this context. The ITF primarily computes risk as the number of fatalities among a given road user group, divided by the total distance travelled by this group over the same period of time.
This page presents cycling exposure and risk figures. For other modes, the reader is invited to read “Road Safety in European Cities: Performance indicators and governance solutions” (URL to be added here)
Map 2 – Cycling traffic ##### fake map ##### (Distance cycled per year and per unit population)
An average resident in Berlin, Copenhagen or The Hague cycles over 500 kilometres per year. High pedal cycle traffic is observed outside of Europe in Bogota, Vancouver and Montreal, where an average resident cycles over 200 km per year. Low pedal cycle traffic is observed in Portuguese and Italian cities.
Map 3 – Cycling risk (Cycling fatalities per billion kilometres cycled)
Large variations in risk can be observed across cities (Map 3). The risk of being killed on a bicycle varies tenfold. Again, this could be interpreted as room for progress, and could help cities learn from their peers. Differences observed across cities reflect, to some extent, differences already observed across countries where the ITF reported cycling risk values between 8 and 51 fatalities per billion kilometres cycled (https://www.itf-oecd.org/cycling-safety).
The interactive map provides the 80% confidence intervals around the cycling risk estimates. This interval reflects the natural random fluctuation of small count data. Working on fatalities alone, at the city level, means working with small numbers – not small in human terms, of course, but statistically small. The use of serious injury data, where numbers would be higher, would dramatically improve the estimation of cycling risk.
Injury data are not yet comparable between cities and are not used in this piece of research. Prone to under-reporting, official injury numbers may fluctuate in line with police resources, with reporting channels and procedures, with modal split and with public attitudes to reporting. The support of the European Commission for the MAIS3+ injury severity standard, however, raises the hope that more cities will be able to make robust and comparable estimates of serious injury numbers.
Cycling numbers and safety
A positive correlation pattern can be observed between the level of cycling activity in the population and the safety of cycling. This correlation can be observed on maps 2 and 3, but is also reported by many other authors. The matter was discussed in a the recent ITF roundtable “Cycling Safety” (https://www.itf-oecd.org/cycling-safety). Whilst the correlation is evident, its interpretation is less so. Several hypotheses can be made: The pattern could indicate a reduction in risk caused by higher cycling activity. This hypothesis called “Safety-in-Numbers” could be explained by the higher awareness among motorists of pedal cycle movements where interactions are more frequent and/or where motorists are also cyclists. Some counter-examples were mentioned in the roundtable discussion in rare places where cycling numbers have grown but no cycling safety policy has been implemented, crash numbers have also grown.
The pattern could indicate growth in cycling activity resulting from a safer cycling environment. One could indeed imagine that lower speed limits, traffic calming features and speed enforcement together might encourage people to cycle more.
The pattern could be the result of confounding factors, such as policies which aim to increase both cycling numbers and cycling safety, for example the development of protected cycling networks.
Some consider that the apparent correlation could be an artefact, as randomly generated data can produce the same pattern (Elvik, 2013). Whilst measurement errors in exposure data inevitably exist and probably contribute to the pattern observed, their contribution shouldn’t be overstated. Differences in cycling level between countries and cities are real and well documented. These differences can be captured by surveys, at least through the analysis of the method of travel to work, a figure collected in many countries. Where cycling level varies by a factor of 100 between cities, the influence of measurement errors is limited. It is possible that all hypotheses listed above contribute to the pattern observed, in various proportions. To clarify this, causality pathways could be investigated in future research. However, more important than the apparent linkage between two variables, the key research questions remain to measure the effect of specific policies, regulations and actions on both cycling safety and the number of people cycling.
The bottom line is that insufficient evidence supports causality for the “safety in numbers” phenomenon. Policies increasing the number of cyclists should be accompanied by risk-reduction actions.
Method: All data refers to 2011-2015 averages, unless otherwise specified. Data was collected directly from local governments in 31 administrative perimeters (19 in Europe, 10 in the Americas and 2 in Oceania) but also from national- and European-level sources and databases in a further 41 European functional urban areas. The reader can find all sources, assumptions and methods in “Road Safety in European Cities: Performance indicators and governance solutions” (URL to be added here).
Definitions: A functional urban area (FUA) consists of a city plus its commuting zone, according to the definition jointly adopted by the OECD and the European Commission in 2012. The term was formerly LUZ (larger urban zone). FUA perimeters change over time. The perimeters used in this research were defined by Eurostat (2015) as part of the Urban Audit 2011-2014. Casualty figures at FUA level were taken from CARE, a database managed by the European Commission’s Directorate General for Mobility and Transport (DG MOVE). In countries recording accurate spatial information for all crashes, DG MOVE has matched crashes to the municipalities making up each FUA. This was not possible in all countries, but it enabled analysis of casualty figures in 41 FUAs.
Acknowledgments: The research was funded by the European Commission, as part of the Access and Safety in European Cities (https://www.itf-oecd.org/accessibility-and-safety-european-cities). It builds on the ITF Safer City Streets (https://www.itf-oecd.org/node/20216) network which is funded by the FIA Road Safety Grant Programme.