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Cyclists, while relatively small in proportion with respect to motorized vehicles, have a high level of vulnerability, creating a significant need to better understand the characteristics specific to this user group. A good insight into the problem provides an opportunity to improve the road safety of this cheap, convenient and environmentally friendly mode of transport. In 2013, more than 2.000 cyclists were killed in road traffic accidents in 27 EU countries, constituting almost 8% of all road accident fatalities for that year. Although a considerable decrease by 32% in the total number of bicycle fatalities in noted within the decade 2004–2013, it is still smaller than the respective reduction of the overall road fatalities by 45%. The objective of this research is the analysis of basic road safety parameters related to cyclists in European countries, by the use of the EU CARE database with disaggregate data on road accidents, as well as of other international data sources (OECD/IRTAD, Eurostat, etc.). Time-series data on road accidents involving cyclists from 27 EU countries over a period of 10 years (2004–2013) are correlated with basic safety parameters, such as road type, season of the year, age and gender. Data from the EU Injury Database are used to identify injury patterns and improve the assessment of injury severity, and additional insight into accident causation for cyclists is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System. The results of the analysis allow for an overall assessment of the cyclists safety level in Europe in comparison to other modes of transport, thus providing useful support to decision makers working for the improvement of safety in the European road network.
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Transportation Research Procedia 14 ( 2016 ) 2372 2381
2352-1465 © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of Road and Bridge Research Institute (IBDiM)
doi: 10.1016/j.trpro.2016.05.269
Available online at www.sciencedirect.com
ScienceDirect
6th Transport Research Arena April 18-21, 2016
How safe are cyclists on European roads?
Petros Evgenikos a,
*
, George Yannis a, Katerina Folla a, Robert Bauer b,
Klaus Machata b, Christian Brandstaetter b
aNational Technical University of Athens, Iroon Polytecheiou 5, Athens, 15773, Greece
bSenior researcher, Austrian Road Safety Board, Schleiergasse 18, Vienna, 1100, Austria
Abstract
Cyclists, while relatively small in proportion with respect to motorized vehicles, have a high level of vulnerability, creating
a significant need to better understand the characteristics specific to this user group. A good insight into the problem provides an
opportunity to improve the road safety of this cheap, convenient and environmentally friendly mode of transport. In 2013, more
than 2.000 cyclists were killed in road traffic accidents in 27 EU countries, constituting almost 8% of all road accident fatalities for
that year. Although a considerable decrease by 32% in the total number of bicycle fatalities in noted within the decade 20042013,
it is still smaller than the respective reduction of the overall road fatalities by 45%.The objective of this research is the analysis of
basic road safety parameters related to cyclists in European countries, by the use of the EU CARE database with disaggregate data
on road accidents, as well as of other international data sources (OECD/IRTAD, Eurostat, etc.). Time-series data on road accidents
involving cyclists from 27 EU countries over a period of 10 years (20042013) are correlated with basic safety parameters, such
as road type, season of the year, age and gender. Data from the EU Injury Database are used to identify injury patterns and improve
the assessment of injury severity, and additional insight into accident causation for cyclists is offered through the use of in-depth
accident data from the EC SafetyNet project Accident Causation System. The results of the analysis allow for an overall assessment
of the cyclists safety level in Europe in comparison to other modes of transport, thus providing useful support to decision makers
working for the improvement of safety in the European road network.
© 2016The Authors. Published by Elsevier B.V..
Peer-review under responsibility of Road and Bridge Research Institute (IBDiM).
* Corresponding author. Tel.: +30-6945877578; fax: +30-2107721454.
E-mail address: pevgenik@central.ntua.gr
© 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of Road and Bridge Research Institute (IBDiM)
2373
Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
Keywords: cyclists; EU CARE database; road accident causation; road safety; European countries
1. Introduction
An alternative way of everyday travels, gaining more followers worldwide each day, bicycle is becoming part of
our lives. Environmental friendly, needing no fuel and the minimum of space, no noise pollutant, cycling is an
important part of sustainable urban mobility and is becoming more and more critical for a balanced combination of
economic development and living standards. In an era when the environment is in the limelight and efforts on health,
safety, standards of living and economic prosperity are being made, it is commonly acknowledged that cycling is
a very effective and contemporary way of commuting (Yannis et al., 2015).
In most European countries, a high proportion of people own a bicycle (in Norway, for instance, 70% of adults
own a bicycle, in Switzerland, 69% of households own a bicycle). The number of bicycles per thousand inhabitants
ranges from 52 in the Czech Republic to 1.000 in the Netherlands. What differs though considerably from one country
to another is the way in which the bicycle is used. Some cyclists use it every day, as a means of transport, while others
do so only occasionally (ECMT, 2000) and additionally, significant differences are noted in the driving behavior and
culture of the other road users (cyclists are still often overlooked), as well as in the cycling infrastructure among the
countries.
However, cycling cannot be considered as a safe mean of transport due to the greater vulnerability of the riders
who are relatively unprotected road users interacting with traffic of high speed and mass, suffering the most severe
consequences in collisions with other road users (DaCoTA, 2012). Thus, although cycling effects on health and
environment seem to outweigh the costs related to crashes involving bicyclists (Kempen, van et al., 2010), it is still
very important to improve cycling safety as much as possible.
The objective of this research is the analysis of basic road safety parameters related to cyclists in European
countries, by the use of the EU CARE database with disaggregate data on road accidents, the EU Injury Database (EU
IDB) and the SafetyNet Accident Causation System (SNACS). More specifically, time-series road accident data
involving cyclists from CARE for 27 EU countries over a period of 10 years (20042013) are correlated with basic
safety parameters, such as area and junction type, season of the year, casualty age and gender, as well as the day of
the week and the time of the day. Moreover, EU IDB data for the period 20052008 are used to identify injury patterns
and improve the assessment of injury severity. Additional insight into accident causation recorded for bicycle riders
is offered through analysis of a set of in-depth data, collected for the period 20052008, using a common methodology
for samples of accidents that occurred in Germany, Italy, The Netherlands, Finland, Sweden and the UK. The data, on
which this analysis is based, along with much of the analysis and the way that the different types of databases were
combined, is obtained through the Traffic Safety Basic Facts 2015 Cyclists (European Commision, 2015), as well
as through SAFETYNET and DaCoTA EC co-funded research projects and the European Road Safety Observatory
(ERSO http://ec.europa.eu/transport/wcm/road_safety/erso/index-2.html).
The results of the analysis allow for an overall assessment of the cyclists safety level in Europe in comparison to
other modes of transport, thus providing useful support to decision makers working for the improvement of safety in
the European road network.
2. Overall road safety trends for cyclists in the EU
In 2013, 2.017 cyclists were killed in road traffic accidents in the 27 EU countries for which CARE accident data
are available, whereas in the US only 743 cyclists were killed, accounting for 2% of all traffic fatalities (NCSA, 2015).
In order to monitor the evolution of the cyclists’ safety level in Europe, accident trends for the decade 20042013
were considered. According to the following Figure 1, although the number of cyclist fatalities has decreased by 32%
over this period in these countries, the overall number of road accident fatalities has fallen faster (reduction by 45%)
and the share of bicycle fatalities of all road fatalities in the EU increased from about 6% to almost 8%, especially
from 2010 to 2012. In reality, the figures of cycling fatalities are actually higher since cyclist accidents are heavily
and disproportionally underreported in the police accident statistics compared to what hospital records and other
studies show (OECD, 1998), especially single-vehicle accidents in which the ‘vehicle’ is a bicycle (Petridou et al.,
2009).
2374 Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
Fig. 1. Number and proportion of cyclist fatalities in the EU, 20042013. Source: CARE database, data available in May 2015.
In road safety analysis exposure data is often used to calculate risk estimates, those being defined as the rate of the
number of accidents (or casualties) divided by the amount of exposure of a population over a time period (Hakkert
and Braimaster, 2002, Hauer, 1995), on that purpose data from other international databases such as OECD/IRTAD,
Eurostat etc. were also used. Since there is no reliable data available about vehicle kilometres or person kilometres
travelled by cyclists in each of the above countries, the population is used as exposure data. The calculated risk figures
may be used for different purposes, but their main objective is to enable the comparison of safety performance among
different units, populations or countries.
Although in absolute figures in 2013 most cyclist fatalities occurred in Germany and Poland (354 and 306 people
riding bicycles were killed in road accidents respectively), Romania, Poland and Slovenia have the highest cyclist
fatality rate. As indicated in Figure 2, there has been a general notable decrease in bicycle fatality rates for almost all
EU countries over a ten year period however, thirteen EU countries still have higher cyclist fatality rates than the EU
average.
Fig. 2. Cyclist fatality rates by country, 2004 and 2013. Source: CARE database (EUROSTAT for population data), data available in May 2015.
The revealed strong regional differences, with the share of cyclist fatalities differing widely between countries, can
mostly be attributed to the combination of two factors: the use of bicycles (exposure and cycling culture) and the
infrastructure devices of a country. For instance in 2013, in the Netherlands and Denmark with high bicycle modal
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Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
split, 25% and 17% respectively of all road accident fatalities are cyclists, whereas in countries such as Greece and
Spain with low cycle use, cyclists constitute only a small part of the road accident fatalities (2% and 4% respectively).
According to the results of a more detailed analysis by age groups and gender the majority of cyclist fatalities are
males (79%), however, with a considerable variation between countries (i.e. under 50% in Denmark and over 90% in
Romania and Portugal). Additionally, in 2013 more than 40% of the cyclists who died in a traffic accident in the EU
were at least 65 years old. Especially in the Netherlands, the related proportion of cyclist fatalities is increased (55%),
since there is a growing number of bicycle injuries among elderly bicyclists, as also in several other countries, such
as Austria, Germany and Belgium, the elderly (over 65 years old) tops the statistics both with respect to total number
of fatalities among cyclists and of the number of cyclist fatalities per inhabitant and even though these last years older
people cycle much less in many other European countries, making their risk exposure very low and accident figures
small, at present this trend has stated to change across Europe.
Fig. 3. Ten-year comparison of cyclist fatalities by age in the EU, 2004 and 2013. Source: CARE database, data available in May 2015.
Figure 3 indicates that over the period 20042013, there has been a marked reduction in cycling fatality numbers
across almost all ages in the EU countries. The least reduction was noted for cyclists aged around 75 years old where
the climax remained, confirming the results of studies showing that elderly cyclists (between 7080 years old) are
almost three times more at risk for a road accident injury than the average cyclist (Niska and Eriksson, 2013). On the
other hand, the peak in fatalities of cyclists aged between 12 and 17 years old disappeared within the same period,
with this age group having the most visible reduction, even though at that age children are likely to increasingly be
undertaking independent.
3. Road safety parameters of the cyclists in the EU
In order to answer the question when most cyclists’ accidents occur, the analysis of the fatalities seasonal
distribution showed that there is no clear trend in the incidence of cyclist fatalities by month among individual
countries. In 2013, the peak for the EU countries occurred in August (13% of cyclist fatalities) and the fewest fatalities
occurred in January and February (4% of cyclist fatalities). Figure 4 compares the distribution by month of cyclist and
overall fatalities and shows that about one third of cyclist fatalities in 2013 in the EU countries occurred in July,
August and September. The proportion of cyclist fatalities in January, February and March is slightly above 10%.
This is less than the proportion of all fatalities during these months. As the slippery wet conditions of many European
winters are conducive to high severity accident injuries, these analysis outcomes are likely to be associated with the
actual number of cyclists on the road during these seasons rather than an indication of risk of injury per cyclist.
2376 Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
Fig. 4. Proportion of cyclist fatalities and total road fatalities per month in the EU, 2013. Source: CARE database, data available in May 2015.
Day of week and time of the day were also considered. The distribution of the cyclist fatalities within the week is
almost the same (around 14%) in EU, with slightly less bicycle riders being killed on Sundays comparing to other
days (12%). In Sweden though, almost one third of the cyclist fatalities occur on Mondays and in Croatia on Saturdays.
Regarding the time of the day, compared to other transport modes, relatively many cyclists are killed between 08:00
and 18:00 and relatively few between 21:00 and 07:00, with two peaks being noted in the following Figure 5, one in
the 08:0012:00 period and another in the 14:0018:00 period. Data analysis did not reveal a clear trend in the time
of collision for individual countries. Some differences might be due to different daily cycling patterns due to climatic
conditions (i.e. in Sweden and Croatia there is no peak between 08:00 and 12:00). Additionally, some of the fatality
figures in individual countries were relatively low, thus differences are unlikely to be statistically significant.
Fig. 5. Distribution of cyclist fatalities and of all road fatalities by time of day in the EU, 2013. Source: CARE database, data available in May
2015.
The role of light conditions on the incidence of cyclist fatalities is also important since some fatalities occurring
between 16:00 and 20:00 may be related to lighting conditions. About a quarter of cyclist fatalities in the EU countries
were killed when lighting was poor (twilight or darkness) with the proportion exceeding 40% in Croatia and Portugal.
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According to the analysis carried out 55% of the bicycle fatalities in the EU countries occurred inside urban areas
but there are significant differences among the countries, as follows from Figure 6. In Romania, almost 80% of bicycle
riders were killed inside urban areas, whilst in Belgium less than 40% (Latvia has small figures). In the US 68% of all
cyclists who died in road accidents in 2013 were killed in urban area crashes (NCSA, 2015).
Fig. 6. Distribution of cyclist fatalities by area type and by country, 2013. Source: CARE database, data available in May 2015. Totals for EU
include latest available data (Lithuanian data not included in totals).
Bicycles compared to other modes of transport have a highest share of fatalities at junctions in 2013 in the EU
(approximately 30%) followed by the mopeds, as presented in Figure 7. Additionally, more than 55% of the cyclist
fatalities occurred at crossroads, comparing to 24% occurring at T or staggered junctions. In the Netherlands (63%)
and Denmark (58%) the highest proportion of cyclist fatalities at junctions were recorded in 2013.
Fig. 7. Fatality proportions involving cyclists at junctions compared to other modes of transport in the EU, 2013. Source: CARE database, data
available in May 2015.
4. Accident causation analysis
Additional insight into accident causation can be offered by in-depth data, such as those collected during the EU
co-funded SafetyNet project. During that project, in-depth data were collected using a common methodology for
samples of accidents that occurred in Germany, Italy, The Netherlands, Finland, Sweden and the UK (Bjorkman et
2378 Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
al., 2008; Reed and Morris, 2008). The SafetyNet Accident Causation Database was formed between 2005 and 2008,
and contains details of 1.006 accidents covering all injury severities. A detailed process for recording causation
(SafetyNet Accident Causation System SNACS) attributes one specific critical event to each driver, rider or
pedestrian. Links then form chains between the critical event and the causes that led to it. For example, the critical
event of late action could be linked to the cause observation missed, which was a consequence of fatigue, itself
a consequence of an extensive driving spell. Links are established by trained personnel directly involved in the
investigation according to the SNACS coding system, with full case evidence available to them. These data have been
analysed to compare the causation recorded for bicycle riders and other drivers/riders in bicycle accidents. Of the
accidents in the database, 9% (92 cases) involve the rider of a bicycle. Males account for 50% of this group and the
mean age is 47 years old. Figure 8 compares the distribution of specific critical events for bicycle riders against the
distribution for other drivers/riders in bicycle accidents.
Although ‘premature action’ is recorded most frequently for both bicycle riders and those others involved in bicycle
accidents, it is the difference for ‘incorrect direction’ that is most striking. ‘Incorrect direction’ refers to a manoeuvre
being carried out in the wrong direction (for example, turning left instead of right) or leaving the road (not following
the intended direction of the road). ‘Premature action’ describes a critical event with an action started too early, before
a signal was given or required conditions established. In combination with prolonged distance and prolonged
action/movement movements taken too far and manoeuvres that last for too long (for example, not returning to
correct lane) scenarios start to emerge of conflict between bicycle riders and other road users when sharing road
space. ‘No action’ is also prelevant in the cyclist group, describing those drivers/riders who have not reacted at all (or
at least in an effective time frame) to avoid a collision, for example, to avoid an oncoming vehicle. In general, in-depth
analysis of SNACS data showed specific critical events related to ‘timing’ for more than 60% of cyclists involved in
road accidents.
Fig. 8. Distribution of specific critical events bicycle riders and other drivers/riders in bicycle accidents. Source: SafetyNet Accident Causation
Database 2005 to 2008 / EC;N=181. Date of query: 2010.
The following Table 1 gives the most frequent links between causes for injury accidents involving bicycle
drivers/riders. For this group there are 74 such links in total. How often causes appear in the chains indicates their
importance for the road users selected. Here, only the most common links are presented but further interpretation can
take place by following the chains from critical event back to the first cause in the chain, as demonstrated by Talbot
et al. (2009) for inattention and distraction.
18% of the links between accident causes for cyclists are observed to be between ‘faulty diagnosis’ and
‘information failure’, closely followed by ‘inadequate plan’ (a lack of all the required details or that the driver’s ideas
do not correspond to reality). ‘Faulty diagnosis’ is an incorrect or incomplete understanding of road conditions or
another road user’s actions. It is linked to both ‘information failure’ (for example, a rider thinking another vehicle was
stopped when it was in fact moving and colliding with it) and ‘communication failure’ (for example, pulling out in
0% 5% 10% 15% 20% 25% 30%
Premature action
(initiated too early)
Incorrect direction
(includes leaving r oad)
Prolonged distance
(action/m ovement tak en too far)
Prolonged action/mov ement
(continued on too long)
Skipped act ion
Late action
Surplus speed
Surplus force
(excess acc eleration or braking)
Shortened distance
(road user(s)/environm ent too close)
Other
Proportion of drivers/r iders
Specif ic Critical E vent
bicycle ride rs n=92
other drivers/riders in bicycle accidents n=89
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Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
the continuing path of a driver who has indicated for a turn too early). The causes leading to ‘observation missed’ can
be seen to fall into two groups: physical obstruction to view’ type causes (for example, parked cars at a junction) and
‘human factor’ type causes (for example, not observing a red light due to distraction or inattention).
Table 1. Ten most frequent links between causes bicycle riders. Source: SafetyNet Accident Causation
Database 2005 to 2008/EC. Date of query: 2010.
Links between causes
Frequency
Faultydiagnosis Information failure (driver/environment or driver/vehicle)
13
Observation missed Faulty diagnosis
6
Observation missed Inadequate plan
6
Observation missed Temporary obstruction to view
5
Observation missed Distraction
4
Observation missed Permanent obstruction to view
4
Faulty diagnosis Communication failure
4
Inadequate plan Insufficient knowledge
4
Observation missed Inattention
3
Information failure (driver/environment or driver/vehicle) Inadequate information
design
3
Others
22
Total
74
5. Road accident health indicators
Injury data variables obtained through the EU Injury Database (EU IDB) can complement information from police
records and thus, provide a better insight for injury patterns and the improved assessment of injury severity in road
accidents. EU IDB is a system developed following a recommendation issued by the EU Council that urges member
states to use synergies between existing data sources and to develop national injury surveillance systems rooted in the
health sector. At present, thirteen member states are routinely collecting injury data in a sample of hospitals and
delivering these data to the EC (http://ec.europa.eu/health/data_collection/databases/idb/index_en.htm). IDB data
used in this research comes from nine EU Member States (DE, DK, LV, MT, AT, NL, SE, SI, CY) and concerns
accidents that occurred between 2005 and 2008. Figure 9 shows that 32% of road accident casualties recorded in the
IDB were admitted to the hospital overall, with the respective percentage being 23% for cyclists. Additionally, analysis
of the IDB data showed that the average length of stay in the hospital for cyclists and also overall was almost eight
days.
Fig. 9. Share of casualties who attended a hospital who were admitted to hospital, by mode of transport. Source: EU Injury Database (EU IDB
AI) hospital treated patients. (code 6.n [public road]); n-all = 73 600: n-admitted = 23.568.
0%
10%
20%
30%
40%
50%
Pedestrian Cars Motorcycles
and Mopeds Overall Other modes
of Transport Cyclists
2380 Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
Fractures, contusions and bruises account for almost two thirds of all injuries inflicted on cyclist casualties
attending hospital and as illustrated in the following Figure 10, presenting the distribution of body parts injured in
casualties by mode of transport, cyclists show a high proportion of injuries of the upper extremities.
Fig. 10. Body part injured, by mode of transport. Source: EU Injury Database (EU IDB AI) hospital treated patients. (code 6.n [public road]);
n-all = 73 600: n-admitted = 23.568.
6. Conclusions discussion
The various road safety parameters examined revealed that the cyclists are a special group of road users, with
increasing numbers and different needs and characteristics than other road users, mainly due to their vulnerability, but
also to their different mobility behaviour. The safety problem for cyclists vary systematically by region, reflecting
different climates, cultures and behavioural characteristics, intensity of traffic, modal shares, levels of cycling
infrastructure development and technology readiness levels.
Analysis of the cyclists’ road accident data derived from the EC CARE database for the decade 20042013, showed
that although the number of cyclist fatalities has decreased by 32% over this period in the EU countries, the overall
number of road accident fatalities has fallen faster (reduction by 45%) and the share of bicycle fatalities of all road
fatalities in the EU increased from about 6% to almost 8%, especially from 2010 to 2012, when the respective share
is the US was only 2%. CARE accident data were also combined with exposure data (population), allowing the more
accurate comparison of the calculated rates between EU countries. According to the results of the analysis, more than
40% of the cyclists in the EU were at least 65 years old when they died in an accident and about one third of cyclist
fatalities occurred during July, August and September. Additionally, more than half of cyclist fatalities occurred on
urban road network and a quarter of them in poor lighting conditions.
The analysis of other types of data such as in-depth accident data and injury data, allowed for additional insight
into accident causation recorded for bicycle drivers and riders, as well as for the identification of injury patterns
improvement of the assessment of injury severity for casualties of this road user group.
The results of the analysis allow for an overall assessment of the bicycle safety level in the European road network
relative to other modes of transport, providing thus useful support to decision makers working for the improvement
of safety in the European road network. Certainly, the effort of data-collection is an on-going challenge and there are
additional data that could help shed light to the problem of the cyclists’ road safety. Of particular interest are exposure
data related to the mobility of road users (bicycle fleet, veh-kms, passenger-kms travelled). Furthermore, the
macroscopic analysis presented in this paper could in the future be combined with more detailed analysis using
statistical models, which is necessary for the identification of the combined correlation of the parameters with an
impact on cyclists’ road safety and the underlining reasons behind their casualties.
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Petros Evgenikos et al. / Transportation Research Procedia 14 ( 2016 ) 2372 – 2381
Acknowledgements
This paper is based on work carried out by the National Technical University of Athens (NTUA), the Austrian
Road Safety Board (KFV) and the European Union Road Federation (ERF) for the European Commission DG
Mobility and Transport, updating work carried out within the SafetyNet (The European Road Safety Observatory) and
DaCoTA (Data Collection Transfer and Analysis) projects of the 6th and 7th (respectively) Framework Programs for
Research, Technological Development and Demonstration of the European Commission.
Appendix A Country abbreviations
Belgium
BE
Italy
IT
Romania
RO
Bulgaria
BG
Cyprus
CY
Slovenia
SI
Czech Republic
CZ
Latvia
LV
Slovakia
SK
Denmark
DK
Lithuania
LT
Finland
FI
Germany
DE
Luxembourg
LU
Sweden
SE
Estonia
EE
Hungary
HU
United Kingdom
UK
Ireland
IE
Malta
MT
Greece
EL
Netherlands
NL
Spain
ES
Austria
AT
France
FR
Poland
PL
Croatia
HR
Portugal
PT
References
Bjorkman K. et al., 2008. In-depth accident causation database and analysis report. Deliverable 5.8 of the SafetyNet research Project, European
Commission, Brussels.
DaCoTA, 2012. Pedestrians and Cyclists, Deliverable 4.8 of the EC FP7 project DaCoTA.
ECMT, 2000. Safety in road traffic for vulnerable users Organisation for Economic Co-operation and Development OECD, Paris.
European Commission, Traffic Safety Basic Facts onCyclists, European Commission, Directorate General for Transport, June 2015.
European Road Safety Observatory (ERSO), http://ec.europa.eu/transport/wcm/road_safety/erso/index-2.html.
Hakkert, A. S., Braimaister, L., 2002. The uses of exposure and risk in road safety studies. SWOV report R-2002-12. SWOV, Leidschendam, the
Netherlands.
Hauer, E., 1995. On exposure and accident rate. Traffic Engineering and Control, 36 (3), pp. 134138.
Injury Database (IDB) http://ec.europa.eu/health/data_collection/databases/idb/index_en.htm.
Kempen, E. van, Swart, W., Wendel-Vos, G., Steinberger, P., Knol, H. & Reurings, M., 2010. Exchanging car trips by cycling in the
Netherlands; A first estimation of health benefits. RIVM Report 630053001. Bilthoven, the Netherlands: RIVM, National Institute for Public
Health and the Environment.
National Center for Statistics and Analysis (NCSA), 2015. Bicyclists and other cyclists: 2013 data. Traffic Safety Facts, Report No. DOT HS 812
151, Washington, DC: National Highway Traffic Safety Administration.
Niska, A., Eriksson, J., 2013. Cycling accident statistics. Background information to the common policy strategy for safe cycling. VTI report 801,
Linköping.
OECD, 1998. Safety of vulnerable road users. Organisation for Economic Co-operation and Development OECD, Paris.
Petridou, E., Yannis, G., Terzidis, A., Dessypris, N., Germeni, E., Evgenikos, P., Tselenti, N., Chaziris, A., Skalkidis, I., 2009. Linking
Emergency Medical Department and Road Traffic Police Casualty Data: A Tool in Assessing the Burden of Injuries in Less Resourced
Countries, Traffic Injury Prevention,10:1,pp. 3743.
Reed S., Morris A., 2008. Glossary of data variables for fatal and accident causation databases. Deliverable 5.5 of the SafetyNet research Project,
European Commission, Brussels. Available on- line at:
http://erso.swov.nl/safetynet/fixed/WP5/D5.5%20Glossary%20of%20Data%20variables%20for%20Fatal%20and%20accident%20causation
%20databases.pdf (Accessed July 20, 2011)
Talbot, R., Fagerlind, H., 2009. Exploring Inattention and Distraction in the SafetyNet Accident Causation Database. Proceedings of the First
International Conference on Driver Distraction and Inattention, September 2829, 2009, Gothenburg, Sweden.
Yannis G.,Papantoniou P., Papadimitriou E., Tsolaki A., 2015. Analysis of preferences for the use of a bicycling sharing system in Athens.
International Cycling Safety Conference, September 1516, 2015, Hanover, Germany.
... In the literature, bicycling is widely considered an environmentally, socially and economically sustainable transport mode (Chapman 2007, Woodcock et al. 2007, Reynolds et al. 2009, de Hartog Jeroen et al. 2010, Oja et al. 2011, Vandenbulcke-Plasschaert 2011, Evgenikos et al. 2016, Pucher and Buehler 2017. It is not only associated with direct health benefits to the cyclist, but with numerous other indirect benefits for the entire society (Chapman 2007, de Hartog Jeroen et al. 2010. ...
... Though one major barrier for people not to cycle is a concern about traffic safety, which has been confirmed by different studies (Reynolds et al. 2009, Heinen et al. 2010, Winters et al. 2010, Fishman et al. 2012. Indeed, cycling is one of the most vulnerable of all transport modes (Evgenikos et al. 2016). Among the vulnerable transport modes, cyclists have some unique risk factors. ...
... Evaluations of bicycle-related crashes have found that more than one third of all injured persons were intoxicated with BACs above 1.60 g/l [3]. Bicycle or pedelec riders involved in road traffic accidents tend to sustain more severe injuries than those of motorised road users due to their lower mass and their lack of ability to dissipate collision energy [4]. This information underlines the need to ride a bicycle in a safe, unimpaired manner, which does not necessarily include only the state of soberness. ...
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Introduction Real or simulated cycling tests under the influence of alcohol might be biased by laboratory settings. Accident analyses consider incidents with injuries only. Herein, criminal offenses consisting of drunk cycling are evaluated in detail to fill this gap. Material and methods All police-recorded cases of cycling under the influence of alcohol that took place in Düsseldorf, Germany, from 2009 to 2018 were identified. A total of 388 respective prosecutor’s files were available for analyses. Results Mean blood alcohol concentrations were approximately 2 g/kg in both men and women. Men were overrepresented (6:1). Almost 60% of the cases were recorded between Friday and Sunday (the “weekend”). The average blood alcohol concentration (BAC) at night (01:00–05:59) was 0.39 g/kg lower than that during the day (06:00–17:59). Drinking after cycling allegations appear almost irrelevant among (German) cyclists. On average, the legal outcomes show 33 daily rates (median: 30). Additionally, the presented data raise doubts about whether the utilized medical tests or the ways in which they are carried out reliably discriminate between different grades of intoxication. Negative tests did not exclude high BACs, nor did positive tests correlate well with BACs. Discussion/Conclusion In practice, CUI is seen with BACs above 1.60 g/kg in most cases. BACs below 1.60 g/kg either seem to be a minor problem or they have been incompletely addressed thus far. In summary, to be prosecuted, drunk cyclists have to ride their bikes in either a highly insecure or rude manner or they must cause an accident.
... Cycling is much less widespread in CEE cities than in Western Europe. This fact seems to be, inter alia, linked to concerns about road safety (Evgenikos et al., 2016). It is generally agreed that walking and cycling have not been treated as distinct policy priorities in post-socialist countries. ...
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Automobile traffic has been recently on the rise in many post-socialist cities despite EU policies fostering public transportation and active modes of travel. Against this background, the contribution of this paper is to look deeper into the travel behaviours of residents using a survey of 887 questionnaires as well as GPS travel recordings (almost 3 billion logs) conducted in the city of Poznań (539,000 inhabitants). Based on our analysis we found that proximity to public transport and cycling infrastructure seem to be among the most important factors influencing travel behaviours of inhabitants. What is more, their accessibility affected also residential locational preferences. However, we also observed that even in neighbourhoods with good accessibility, commuting by car plays a major role.
... In Spain, 2173 cyclists were involved in road accidents in 2015, of whom, 48 lost their lives (Dirección General de Tráfico, 2015). Moreover, there has been an increasing trend in the share of bicyclist fatalities regarding overall road fatalities in EU countries in the last few years (Evgenikos et al., 2016). To get a better understanding of the causes of road accidents, previous research has developed and employed surrogate measures (e.g., Davis et al., 2011;Wu and Jovanis, 2012;Laureshyn et al., 2017), among which near misses can be found. ...
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Road anger constitutes one of the determinant factors related to safety outcomes (e.g. accidents, near misses). Although cyclists are considered vulnerable road users due to their relatively high rate of fatalities in traffic, previous research has solely focused on car drivers, and no study has yet investigated the effect of anger on cyclists’ safety outcomes. The present research aims to investigate, for the first time, the effects of cycling anger toward different types of road users on near misses involving such road users and near misses in general. Using a daily diary web-based questionnaire, we collected data about daily trips, bicycle use, near misses experienced, cyclist’s anger and demographic information from 254 Spanish cyclists. Poisson regression was used to assess the association of cycling anger with near misses, which is a count variable. No relationship was found between general cycling anger and near misses occurrence. Anger towards specific road users had different effects on th
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Distraction and inattention are considered to be very important and prevalent factors in the causation of road accidents. There have been many recent research studies which have attempted to understand the circumstances under which a driver becomes distracted or inattentive and how distraction/inattention can be prevented. Both factors are thought to have become more important in recent times partly due to the evolution of in-vehicle information and communication technology. This study describes a methodology that was developed to understand when factors such as distraction and inattention may have been contributors to crashes and also describes some of the consequences of distraction and inattention in terms of subsequent driver actions. The study uses data relating to distraction and inattention from the SafetyNet Accident Causation Database. This database was formulated as part of the SafetyNet project to address the lack of representative in-depth accident causation data within the European Union. Data were collected in 6 European countries using 'on-scene' and 'nearly on-scene' crash investigation methodologies. 32% of crashes recorded in the database, involved at least one driver, rider or pedestrian, who was determined to be 'Inattentive' or 'Distracted'. 212 of the drivers were assigned 'Distraction' and 140 drivers were given the code 'Inattention'. It was found that both distraction and inattention often lead to missed observations within the driving task and consequently 'Timing' or 'Direction' become critical events in the aetiology of crashes. In addition, the crash types and outcomes may differ according to the type and nature of the distraction and inattention as determined by the in-depth investigations. The development of accident coding methodology is described in this study as is its evolution into the Driver Reliability and Error Analysis Model (DREAM) version 3.0.
Article
The study aimed to (1) assess the magnitude of road traffic injuries in a country missing a formal linkage system of police with hospital data, (2) quantify the underreporting, and (3) produce a convenient algorithm exploring its constituent components. Linkage of disaggregate (individual) data collected by the road traffic police (RTP) with those by the Emergency Department Injury Surveillance System (EDISS) on the Greek island of Corfu and coded with different classification systems was carried out. The applied four-step methodology, also comprising the calculation of underreporting coefficients of the variation by basic demographic variables, mode of transport, and injury outcome, led to the identification of the overall underreporting from either registry. RTP data captured 96.6% (coefficient: 1.035), whereas EDISS captured only 54.4% of total fatalities (overall concordance: 51.1%). On the contrary, EDISS captured 94.6% of nonfatal injuries, whereas RTP only captured 16% (coefficient: 6.238), resulting in a low overall concordance (10.6%). Considering severity of injury assessed by EDISS, by using the ISS as the gold standard, RTP data misclassified 20.3% of severe injuries as less severe, and a statistically significant difference in the underreporting by gender was also noted. Relatively simple methodologies can provide essential coefficients to assess the actual numbers, severity, and components of road casualties by complementing routinely collected RTP with sentinel emergency department reporting systems.
Exchanging car trips by cycling in the Netherlands; A first estimation of health benefits
  • E Kempen
  • Van
  • W Swart
  • G Wendel-Vos
  • P Steinberger
  • H Knol
  • M Reurings
Kempen, E. van, Swart, W., Wendel-Vos, G., Steinberger, P., Knol, H. & Reurings, M., 2010. Exchanging car trips by cycling in the Netherlands; A first estimation of health benefits. RIVM Report 630053001. Bilthoven, the Netherlands: RIVM, National Institute for Public Health and the Environment. National Center for Statistics and Analysis (NCSA), 2015. Bicyclists and other cyclists: 2013 data. Traffic Safety Facts, Report No. DOT HS 812 151, Washington, DC: National Highway Traffic Safety Administration.
Glossary of data variables for fatal and accident causation databases Deliverable 5.5 of the SafetyNet research Project Available on-line at: http://erso.swov.nl/safetynet
  • S Reed
  • A Morris
Reed S., Morris A., 2008. Glossary of data variables for fatal and accident causation databases. Deliverable 5.5 of the SafetyNet research Project, European Commission, Brussels. Available on-line at: http://erso.swov.nl/safetynet/fixed/WP5/D5.5%20Glossary%20of%20Data%20variables%20for%20Fatal%20and%20accident%20causation %20databases.pdf (Accessed July 20, 2011)
Analysis of preferences for the use of a bicycling sharing system in Athens. International Cycling Safety Conference
  • G Yannis
  • P Papantoniou
  • E Papadimitriou
  • A Tsolaki
Yannis G.,Papantoniou P., Papadimitriou E., Tsolaki A., 2015. Analysis of preferences for the use of a bicycling sharing system in Athens. International Cycling Safety Conference, September 15–16, 2015, Hanover, Germany.
European Commission, Traffic Safety Basic Facts onCyclists, European Commission, Directorate General for Transport
ECMT, 2000. Safety in road traffic for vulnerable users Organisation for Economic Co-operation and Development OECD, Paris. European Commission, Traffic Safety Basic Facts onCyclists, European Commission, Directorate General for Transport, June 2015. European Road Safety Observatory (ERSO), http://ec.europa.eu/transport/wcm/road_safety/erso/index-2.html.
In-depth accident causation database and analysis report. Deliverable 5.8 of the SafetyNet research Project
  • K Bjorkman
Bjorkman K. et al., 2008. In-depth accident causation database and analysis report. Deliverable 5.8 of the SafetyNet research Project, European Commission, Brussels.