Aalborg Universitet. The safety impact of a yellow bicycle jacket Lahrmann, Harry Spaabæk; Madsen, Tanja Kidholm Osmann

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1 Aalborg Universitet The safety impact of a yellow bicycle jacket Lahrmann, Harry Spaabæk; Madsen, Tanja Kidholm Osmann Published in: Accident Analysis & Prevention Publication date: 2015 Document Version Preprint (usually an early version) Link to publication from Aalborg University Citation for published version (APA): Lahrmann, H., & Madsen, T. K. O. (2015). The safety impact of a yellow bicycle jacket. Accident Analysis & Prevention. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.? You may not further distribute the material or use it for any profit-making activity or commercial gain? You may freely distribute the URL identifying the publication in the public portal? Take down policy If you believe that this document breaches copyright please contact us at providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from vbn.aau.dk on: August 25, 2015

2 17. December 2014 Preprint of manuscript submitted to Accident Analysis & Prevention The safety impact of a yellow bicycle jacket Harry Lahrmann a Tanja Kidholm Osmann Madsen a Anne Vingaard Olesen a, Jens Chr. Overgaard Madsen b, a The Traffic Research Group, Department of Civil Engineering, Aalborg University, Denmark b Rambøll, Denmark Abstract The hypothesis of this project is that the safety of cyclists can be improved by increasing their visibility in traffic. This is explored by testing whether or not a high-visibility bicycle jacket (colour and reflectors) will increase the safety of cyclists. The project has been carried out as a randomized controlled trial with 6,800 volunteer cyclists. After random selection, half of the group the test group got the bicycle jacket at once and promised to wear it each time they biked during a year. The other half of the group composed a control group that got the bicycle jacket after the closing of the project, i.e. after a year. The safety effect of the bicycle jacket was analysed by comparing the number of self-reported accident for the test and control group. The self-reported accidents showed that the test group had 38 % fewer personal injury accidents with other road users so-called multi-party accidents than the group who did not wear the bicycle jacket. If one only looks at accidents between participants and vehicles, the difference is 48 %. The differences are statistically significant at 5 % level. In the test group, 37 % of the involved parties in an accident reported that they were not wearing the bicycle jacket or any other bright-coloured garment when the accident occurred. Keywords: bicycle, traffic safety, visibility, clothes 1 Introduction Cyclists are an exposed road user group. In 2010, nearly 2,000 cyclists were killed in traffic, corresponding to 7 % of all traffic fatalities in the EU (Candappa et al., 2012). The accident risk for cyclists is significantly higher than for other road user groups (A. S. Hansen & Jensen, 2012), and the risk is actually far greater than reflected by the official accident statistics. Thus, in 2012, 826 personal injuries involving cyclists were reported to the official Danish accident statistics, but if one counts the numbers from the emergency rooms and hospitals no fewer than 17,496 cyclists were injured in Of these numbers, 4,684 of the injured parties were attributed to accidents involving another road user (Statistics Denmark, 2014). The Danish Road Traffic Accident Investigation Board (AIB) has a working hypothesis stating that lack of visibility can be among the reasons for the higher accident risk for cyclists (AIB, 2008). This hypothesis is supported by a project on the use of permanent running lights for cyclists completed in collaboration with the Traffic Research Group at Aalborg University and Odense Municipality. The project documents that the use of permanent running lights significantly reduces the accident risk for cyclists. Specifically, the probability of cyclists being involved in multi-party accidents is reduced with 47 %. These accidents are typically the most severe ones for cyclists, and the reduction most likely caused by the cyclists increased visibility. (Madsen et al., 2013) A 2004 meta-analysis did not find any studies directly measuring the safety effect of bicycle lights, reflector vests, garments in bright colours etc., but 42 projects that studied the effect of visibility aids. The analysis concludes that the visibility aids have the potential to make the motorists aware of the cyclists sooner 1

3 (Kwan & Mapstone, 2004). This is supported by a Finnish in-depth study of vehicle-bicycle accidents concluding that motorists notice the cyclist too late in accidents (Räsänen & Summala, 1998). In a New Zealand study, 2,500 cyclists were asked about their bicycle accidents for the past 12 months, and the study showed that the number of self-reported accidents was lower among cyclists who stated that they always wore garments in fluorescent colours (Thornley et al., 2008). In an Australian study, 185 accident involved cyclists were interviewed, and only two of them stated their own lack of visibility as a factor in the accident while 61 % stated the driver s inattention as a factor (Lacherez et al., 2013). The study concludes that cyclists involved in accidents underestimate the value of their own visibility. Another Australian study shows that cyclists overestimate their own visibility at night (Wood et al., 2013). A number of the vehicle-bicycle accidents are characterized as looked but failed to see accidents where the motorist did not acknowledge the cyclist s presence in time, even though the motorist explains that he actually did look to the side from where the cyclist came. The assumption is that the number of these situations can be reduced by increasing the cyclists visibility; a visibility that can be important to whether or not the situation ends in an accident (Herslund & Jørgensen, 2003). The objective of this research project is to examine by a randomized controlled trial how cyclists use of high visibility garments on the upper body affects the accident risk of the cyclists. The hypothesis is that the use of such garment will notably increase the cyclists visibility and as such lead to a reduction of the accident risk for the cyclists. 2 Materials and methods 2.1 Project design The project has been carried out in collaboration with Tryg- Fonden who was in charge of the design and production of the bicycle jacket. The project is a randomized experiment where 4,000 participants are selected randomly from a group of participants for a test group. Similarly, 4,000 participants are selected randomly for a control group. The test group participants must wear the bicycle jacket every time they ride their bikes for one year. During the same year, the control group must use their regular bicycle garments. After the completion of the project, the control group is also given a bicycle jacket. By randomly selecting participants for the test group and control group among the people who signed up for the experiment, the two groups are ensured to be statistically similar and any differences in their accident risk as cyclists can be attributed to the use of the bicycle jacket in the test group. The ideal randomized experiment is double-blind, meaning the participants do not know e.g. whether they have been given the correct pill or just a calcium pill just like the researchers do not know which participants have been given the correct pill. This study is neither blind nor double-blind; both participants and researchers know who has been given the jacket. This can provide irregularities in the results, which will be discussed later on in this paper. The bicycle jacket, cf. Figure 1, was designed specifically for the experiment and was a bright-coloured shell jacket with limited reflecting material on it. The goal was to create a visible jacket that the cyclists will consider smart and wanted to wear, not to create a jacket that would be considered a piece of safety equipment. The reason for this was that a safety efficient bicycle jacket will only improve traffic safety in practice if it finds a broad usage among the cyclists. 2.2 Effect goal self-reported accidents Figure 1: The bicycle jacket 2

4 Each year, only one per thousand of the Danish population is involved in a bicycle accident which is registered by either the police or the emergency room. Thus, bicycle accidents are a rare occurrence for the individual person (Statistics Denmark, 2014). Therefore, it will take an unrealistically large (5 digits) attendance number if the safety effects of the bicycle jackets were based on the police and emergency room registered accidents. Should the safety effects be based on the number of police registered bicycle accidents only, the demand for the attendance number would be even higher (6 digits). In the previous project on the effects of permanent running lights on bikes, the effect was calculated from the self-reported accidents via the internet. The experiences with this method were good, which is why the method has also been used in this project (Madsen et al., 2013). 2.3 Experimental setup On the first day of each month, both the test and control group participants received an with a link to an internet based questionnaire. In this, they were asked whether or not they had been involved in an accident on their bike in the previous month. If they answered yes, they were guided through a questionnaire with contents corresponding to the information that the Danish police registers with accidents: time, place, accident type, counterpart, state of the road, lighting conditions, weather, any personal injury, if the accident was reported to the police and/or the insurance company and if the accident has required a trip to the emergency room or to their own doctor. Finally, they were asked to locate the accident and give a prose description of the accident. On a random day each month, the test group was given another web based questionnaire in which they were asked whether they had worn the bicycle jacket the last time they rode their bike. The goal of this questionnaire was to determine the usage rate of the jacket. The web based questionnaires are available in Lahrmann & Madsen (2014). 2.4 Recruiting project participants Based on previous studies (Lohmann-Hansen et al., 2001; Madsen et al., 2013), it was assessed that 8,000 participants were needed 4,000 participants in each group in order to be able to document whether or not the bicycle jacket had any safety effect. It was decided to recruit participants from the entire Denmark, partly because it would be easier to reach the desired number of participants and partly because a large geographical concentration of participants would undeniably lead to a safety in numbers effect of the jacket. The term safety in numbers means that the number of accidents per road user in a road user group typically declines when the number of road users in the group increases (Elvik, 2009). In this connection, the hypothesis would be that if e.g. ¼ of all cyclists in an area wore the bicycle jacket, the awareness of the cyclists would generally be increased and thereby the group without jackets would also gain a safety bonus. Moreover, a decision was made to only recruit cyclists who used their bike at least three times a week in the summer half and who had turned 18 years old when they signed up. The assessment was that the quality of the report would be less for children than for adults, contemporary with the fact that this age limitation would not be important to the general validity of the results. In order to end up with 8,000 participants, it was deemed necessary to recruit 50 % more than needed in the first round, meaning 12,000 people signing up. This was partly due to the fact that a certain defection should be expected when the participants were to decisively confirm their participation, and partly due to the fact that the project had the specific challenge of the different sizes of the jackets being produced before the recruitment. This was done in order to minimize the period between signing up for the project and the start of the project. With an excess of participants, a misjudgement in the advance assessment of the jacket size distribution could be intercepted. The participants were recruited via the project website, which besides receiving registrations also described the project and was used to give information to the participants during the project period. In addition to the website, a Facebook group was established for the project. In order to raise awareness of the project and to get cyclists to sign up, an intensive press campaign was conducted when the project was made public. The registration opened on 5 September The news was also distributed via s to professional contacts with encouragement to forwarding the . As seen in the bottom 3

5 curve in Figure 2, a large number of people signed up during the first couple of days, but the number decreased rapidly, and so a new recruitment round was initiated. In the period September, information about the project was sent out to municipalities and interest groups within the traffic area. Finally, everyone that had signed up for the project were encouraged to tip off five friends about the project who then received an encouraging to sign up with the project. A prize was offered among the participants who tipped friends. The top curve in Figure 2 shows the numbers of sent tip s. On 3 October 2012, the project reached 11,202 registrations a little below the goal of 12,000 but based on the timeline of the project the recruitment period could not be extended Tip Offs Registrations Figure 2 Sum of registrations and tip offs in the recruitment period (tip offs = s that the registered people sent to friends inviting them to participate. 2.5 Selection of project participants and the project process The data set was cleared for double registrations, false ( Donald Duck ) registrations and registered people who did not ride their bike the required 3 times a week in the summer half. Then the registered people were randomly distributed in the test group and control group respectively and were asked to confirm to participate. Not everyone accepted and, in total, the experiment ended up consisting of 3,402 people in the test group and 3,391 people in the control group. As previously mentioned, all participants were sent an each month with a link to a web based questionnaire on bicycle accidents during the past month. In case of lacking reply, the participants received a reminder after a week and if the participant still did not reply, the participant was excluded from the result for the specific month. The following month the participant was included in the experiment again. Only participants who actively unregistered from the experiment were excluded from all the following distributions. Table 1 shows how many people answered the accident questionnaire. Table 1 Replies of accident questionnaire Test group Control group Number of people in the start group 3,402 3,391 Number of people resigning during the year Number of people never answering an accident questionnaire Number of people answering between 1 to 11 accident questionnaires Number of people answering all 12 accident questionnaires Number of answered accident questionnaires 37,526 38,489 4

6 Since the participants are volunteers, they cannot be expected to be representatives of Danish cyclists that ride their bikes more than three times a week and are over 18 years old, neither in attitude or behaviour. Table 2 shows a number of participant characteristics for the participants who have, at minimum, filled out one accident questionnaire. The participants are on average 46 years old and as such probably significantly older than the average cyclist and most likely also more safety conscious. They use their bikes almost every day both summer and winter when their typical destination is work/education, but even though they ride their bike a lot, 80 % of the households have at least one car. Table 2 Participant characteristics divided in test group and control group. Includes all that have filled out the accident questionnaire at least once (test group n=3,324, control group n=3,337) Characteristics Test group Control group Gender Woman Man 42.7 % 57.3 % 43.7 % 56.3 % Age Middle 46.4 years 45.5 years Car ownership No car in the household 1 car in the household 2 cars in the household > 2 cars in the household Use of bike winter Daily 3-4 times a week 1-2 times a week Approx. every two weeks Monthly Rarely Use of bike summer Daily 3-4 times a week 17.4 % 63.7 % 17.9 % 0.9 % 51.2 % 38.1 % 9.8 % 0.5 % 0.1 % 0.3 % 73.1 % 26.9 % 19.8 % 62.1 % 17.0 % 1.1 % 52.2 % 38.1 % 9.0 % 0.5 % 0.1 % 0.0 % 74.1 % 25.9 % Most frequent destination To/from work/education To/from shopping To/from leisure activities To/from visiting family/friends Bike rides for the experience/exercise Business trips (e.g. delivering goods) Other 72.6 % 3.6 % 4.2 % 0.6 % 18.0 % 0.2 % 0.8 % 73.4 % 3.5 % 3.9 % 0.5 % 17.3 % 0.3 % 1.1 % 2.6 Practical execution of the project To communicate with the project participants, the project website the Facebook group Cykeljakken and a hotline were used. The hotline received over 3,000 enquiries during the project period, primarily via . As previously mentioned, the participants who had been involved in an accident on their bike had to describe the accident by filling out a web based questionnaire. We had good experiences with this form of self-reporting from the project about permanent running lights on bikes (Madsen et al., 2013), but for this project we also asked the participants to locate the accident. This was done by asking the participants to go on zoom in on the location of the accident on the map, mark the accident location and copy the coordinates from the accident location into the questionnaire. If the respondent could not use this location method, they could describe in words where the acci- 5

7 dent had taken place. After this, a project employee called the respondent and together could find the coordinates to the accident. This method for location of accident is as far as we know unique, and thus we were excited to see whether the participants could use this method. The result was surprisingly good; all reported accidents were located and less than 50 of the people in accidents needed help to locate the accident. Figure 3 shows an example of location of accident. Figure 3 Example of how a participant has marked where the accident occurred at Afterwards the coordinates have been copied into the questionnaire. A detailed description of the recruitment for the project and the practical execution are available in Hansen et al. (2014). 3. Data analysis 3.1 Usage data Another uncertainty factor in this project is to which degree the test group wears the jacket. In order to determine the usage rate, the participants received an on a random day in each month in which they were asked if they had used the bike in the current month. If yes, they were asked if they wore the bicycle jacket or another bright-coloured garment on this ride. The average usage rate over the year was 77 %, but with great variations during the 12 months of the project. The highest usage rate was in the first month of the project November and the lowest was in July. The usage rate was used for the assessment of the effect of the bicycle jacket. 3.2 Accident data 6

8 All participants received a web based questionnaire on the first day of each month in which they were asked about their bicycle accidents in the previous month. 81 % of the participants answered all 12 questionnaires, 88 % answered at least 11 out of the 12, and only 2 % did not answer any of the questionnaires. From 1 November 2012 to 31 October 2013, in these monthly accident reports the participants reported 694 accidents in total. 274 accidents were reported by the test group, and 420 were reported by the control group. An accident was defined as an event in which the participant was riding their bike and where at least one of the following requirements was met: The cyclist has been in physical contact with a counterpart. The cyclist has, as a consequence of the counterpart s behaviour, been toppled and/or has been injured. This also includes damages to their belongings even though there was not any physical contact between the road users. The cyclist has been toppled and/or injured during the bike ride without other road users being involved. Only accidents that occurred in Denmark and on public roads were included in the analysis. Figure 4 shows the residences of the participant - left - as well as the geographical location of the accidents right-. It is noted that the participants residence and the accidents are spread out over the entire Denmark. Figure 4 The 6,793 participants residence (left) and the 694 reported accidents (right) On the basis of the participants accident descriptions, it has been assessed whether the accidents were solo accidents or multi-party accidents. Furthermore, the severity of the accident has been assessed from the questionnaires. Tables 3 and 4 show the characteristics for the participants reported accidents for all accidents and multi-party accidents respectively. The column All accidents in Tables 3 and 4 includes both accidents without injury, accidents with only material damage and accidents with more severe personal injuries. The column Personal injury only includes the more severe personal injuries where the injury does not only consist of bruises. 7

9 Table 3 Accident characteristics. Personal injury accidents cover accidents where the participants sustained injuries more severe than bruises. Accident characteristics Test group Control group All accidents Pers onal injury accidents All accidents Pers onal injury accidents Accidents in total Type Solo accident Mul ti -party accident Season Winter Summer Lighting conditions Daylight Twilight Dark Risk willingness Low risk willingness High risk willingness Usage rate of bicycle jacket Low use of bicycle jacket High use of bicycle jacket No bicycle jacket Contact with police, emergency room and insurance Accidents reported by police Accidents reported to insurance companies Treatment at emergency room / hospital Treatment only by own doctor/ doctor from the emergency service Usage of bicycle jacket at accident Wore the bicycle jacket or another bright-coloured garment Did not wear the bicycle jacket Table 4 Accident characteristics for multi-party accidents. Personal injury accidents cover accidents where the participant sustained injuries more severe than bruises. Accident characteristics Test group Control group All accidents Personal injury accidents All accidents Personal injury accidents Multi-party accidents in total Season Winter Summer Lighting conditions Daylight Twilight Dark Counterpart Light counterpart Motorised counterpart Risk willingness Low risk willingness High risk willingness Usage rate of the bicycle jacket Low use of the bicycle jacket High use of the bicycle jacket No bicycle jacket

10 3.3 Analysis of accident data The effect of the bicycle jacket is evaluated by comparing the incidence rates between the test and control groups and between the different sub-groupings of the accident data. The incidence rate for a given accident type/grouping is stated by: IR g = X / I t g g,i i = 1 Where: X g is the number of reported accidents for participants belonging to group g. t g,i is the number of months where the individual participants has been active in group g. The incidence rate describes the number of accidents in group g per month. Example: the test group wore the jacket for 37,526 months in total and reported 274 accidents which gives a incidence rate of (274/37,526)=0.0073, and the control group drove without the jacket for 38,489 months and reported 420 accidents in total which gives an incidence rate of (420/38,489)= The effect of the bicycle jacket is given with the incidence rate ratio, which is defined as the relation between the incidence rate for the test group and the incidence rate for the control group: IRR j = IR j,t /IR j,c An incidence rate less than 1.0 indicates a positive safety effect, values over 1.0 indicate a negative safety effect and values around 1.0 indicate that the bicycle jacket does not have any safety effect. In the previous example, the incidence rate is (0.0073/0.0109)=0.67. Regarding the assessment of whether or not the bicycle jacket has any significant safety effect, the 95 % confidence interval for the incidence rate ratio is estimated: [ ln IRR 1.96*SE (ln IRR )] 95% CI (IRR j ) = exp j ± j Where: SE (ln IRR j) = 1/X j,t + 1/X j,c To the extent that the 95 % confidence interval does not hold the value 1.0, it means that the usage of the bicycle jacket has a significant safety effect. If we look at the previous example again, the standard deviation is , by which the confidence interval is estimated to exp(ln 0.67 ± 1.96*0.0777) = 0.58 to Since this is less than 1, it can be concluded that the bicycle jacket has a significant effect on all reported accidents. Meanwhile, from the figures in Table 3 it is noted that the control group has 199 solo accidents and the test group has 150 solo accidents. This difference is statistically significant. This is surprising since the higher visibility provided by the jacket could hardly have had any influence on the number of solo accidents. An explanation to the fewer solo accidents in the test group could be that the participants in the experiment are volunteers who believe in the effect of the jacket and thus have been affected by their belief to report accidents in such a manner that the test group reported fewer accidents than they should have objectively and the control group most likely a bit more. This hypothesis is supported by the participants answers in the final questionnaire of the project. To the question: To which degree do you believe that a brightcoloured bicycle jacket/vest can increase the safety in traffic in general? almost all participants answered that they believed in the safety effect of a bright-coloured bicycle jacket (Thedchanamoorthy et al., 2014). Thus, an adjusted analysis is conducted. In the adjusted analysis, the number of multi-party accidents in the control group is reduced using a correction factor equal to the apparent effect of the bicycle jacket on solo accidents. The correction factor is equal to the reciprocal of the incidence rate ratio for solo accidents: 9

11 C = corr IR solo,j,t 1 / IR solo,j,c The introduction of a correction factor involves a correction to the estimate of 95 % confidence interval as the number of solo accidents in the test group and control group must be calculated into the estimate of SE (ln IRR j ). The adjusted analysis is carried out solely for multi-party accidents. In practice, the adjusted analysis is based on an estimate of an adjusted incidence rate ratio given by the relation between the non-adjusted incidence rate ratio for multi-party accidents and the incidence rate ratio for solo accidents: Where: Corr IRR = IRR multi-party, j IRR multi -party, j = IR multi-party, j, T multi-party, j /IR * C corr multi-party, j, C To what extent the effect on multi-party accidents is significant is evaluated according to the below: [ ln (Corr IRR ) 1.96*SE (ln (Corr IRR )] 95% CI (Corr IRR multi -party, j) = exp multi-party, j ± multi-party, j Where: SE (ln (Corr IRR )) = SE (Ln IRR j multi-party, j) SE (Ln IRRsolo, j) multi-party, j) = 1/Xmulti-party, j,t 1/Xmulti-party, j,c SE (ln IRR + SE (ln IRR + solo, j) = 1/X solo,j,t 1/X solo,j,c It must be emphasized that accidents that occurred at times when the test group participants were not wearing the bicycle jacket have still been counted for in the test group. This means that the safety effect of the bicycle jacket is determined with a starting point in the usage rate among the test group participants. 4. Results 4.1 Safety effect of bicycle jacket Table 5 shows the safety effect of the bicycle jacket on the basis of the registered multi-party accidents and with adjustment for the presumed underreporting in the test group. Effects for a number of sub-groups for the reported multi-party accidents have been stated. The registered personal injury accidents were chosen for the basis of the analysis as this ensures the most uniform accident definition for both the test group and the control group. 10

12 Table 1: Corrected incidence rates, incidence rate ratios and 95 % confidence intervals for incidence rate ratios multi-party accidents with personal injury more severe than bruises. Correction made in order to control for the apparent underreporting of bicycle accidents in the treatment group. * Significant at 10 % level (90 % confidence interval for IRR). Multi-party accidents with personal injury Incidence rates * 10 3 Multi-party accidents Test group Control group (adjusted) IRR 95% CI (IRR) All [0.39 ; 1.00] Winter [0.27 ; 0.98] Summer [0.41 ; 1.26] Daylight [0.34 ; 0.96] Twilight [0.29 ; 3.40] Night time [0.20 ; 1.83] Counterpart: truck/bus, van, car, [0.29 ; 0.95] MC, moped Counterpart: cyclist, pedestrian [0.41 ; 1.36] Low risk willingness [0.37 ; 1.08]* High risk willingness [0.33 ; 1.38] Low jacket use [0.46 ; 1.34] High jacket use [0.26 ; 0.86] * Significant at the 10 % level It should be noted that all incidence rate ratios, except for the accidents that occurred in twilight, are less than 1.0. This means that there is a positive effect for all sub-groups, but it is also noted that some confidence intervals are higher than 1.0, which means that these effects are not statistically significant. A main result from Table 5 is that there were 48 % fewer personal injury accidents between cyclists and cars in the test group compared to the control group, and that the difference is statistically significant (p<0.05). If accidents between cyclists and pedestrians are included, the test group has 38 % fewer accidents than the control group this difference is also statistically significant. The difference between the groups is greater during winter than during summer and greater in daylight than in dark hours, which indicates that the greatest safety rewards are connected to using the bicycle jacket in the daytime and in the winter period; a difference that could be connected with the fact that the daytime hours during winter are in a period when the daylight is weak and at the same time the bikes do not have lights on and the jacket usage rate during winter was the highest. It has also been studies whether the safety effect of the bicycle jacket is greatest among cyclists who have a high risk willingness and lowest among cyclists who are less risk willing. The participants are divided into two groups by their risk willingness high risk willingness vs. low risk willingness. The division is based on the answers from a questionnaire (Thedchanamoorthy et al., 2014), in which the participants were asked, among other things, to rate a number of statements on behaviour in traffic on a scale from very safe to very dangerous, cf. Table 6. Each answer option was assigned a colour so that there were approximately an equal amount of dark grey and light grey answers for each statement. After this, the participants were divided into the above-mentioned groups so that the participants with three, four or five light grey answers had low risk willingness, and the participants with three, four or five dark grey answers had high risk willingness. As seen in Table 5, there is basically no difference in the safety effect of the jacket between the two groups. It is unclear whether this is due to the fact that there is no difference in the effect of the jacket in the two group or that the answers to the five questions do not disclose the participants risk willingness sufficiently in detail. 11

13 Table 5 Division of participants in two groups with high and low risk willingness respectively, based on their answers to five questions on risk willingness. Participants with three, four or five light grey answers have low risk willingness and participants with three, four or five dark grey answers have high risk willingness. Running the red light at night when you cannot see any other traffic Turning right on red on your bicycle Not signalling when you are stopping/turning Listening to music when you ride your bike Riding your bike without helmet Very safe Safe Almost safe Somewhat dangerous Dangerous Very dangerous Finally, it was examined whether the safety effect of the bicycle jacket is highest for the half of the test group that frequently used the jacket, compared to the half of the test group that used the jacket less frequently. In Table 5, it is noted that the group with high jacket usage had 53 % fewer accidents than the control group compared to only 21 % fewer accidents in the group with low jacket usage, where only the prior is statistically significant. So, the study shows that the safety effect of the bicycle jacket not surprisingly varies with the usage. Consequently, it should be emphasised that the study has described the safety effect of the bicycle jacket with the usage rate in the experiment test group. If the usage rate is increased, the safety effect also increases, and if the usage rate is reduced so is the safety rate. This underlines the point that it is important to develop visible action appealing to usage of the jacket. 5 Discussion 5.1 Recruiting the participants The project goal was 8,000 participants. We reached 11,202 registrations, which resulted in 6,793 participants. We chose to only announce the project through press coverage, professional networks, municipalities and interest groups. Finally, the registered persons were encouraged to tip off the project to their friends. The press coverage provided a large number of registrations in a short amount of time, and the announcement via the networks kept the registration rate up and going. The tip off a friend curve in Figure 2 shows that the channel especially was an effective way of marketing the project and that the registrations would have continued if we did not have to stop the recruitment due to the timeline of the project. The method of participant recruitment by open registration for the project has the great advantage that the participants were interested in the project and that interest raises and keeps the participation in the project. The average answer ratio of the 12 accidents questionnaires was as such 97.5 %. The activities on Facebook and the many positive enquiries on the project hotline are also testaments of this. The risk from of a large involvement in a randomized experiment that is not conducted blindly is that the two groups do not report in a similar manner the participants believe in the effect of the initiative which influences their reports. This has resulted in a likely underreporting of accidents from the test group participants. In this project and the previous project on permanent running lights on bikes (Madsen et al., 2013), we have made the imbalance probable through comparison of the number of solo accidents between the two groups and have adjusted for the imbalance by using the solo accidents as a correction factor. 5.2 Self-reported accidents as effect goals The experiences with self-reporting of accidents by via an attached web based questionnaire were good; we received both high answer ratios and high quality of answers. The method was also used successfully in a previous project (Madsen et al., 2013), but in this project we have gone one step further and asked the participants to locate the accident on a map. This was also a success succeeding all expectations. 12

14 From these experiences, you cannot conclude that the self-reporting of accidents can give good results in general. There is no doubt that the participants in both projects have been very dedicated to the projects with a large desire to contribute to a good project. But these two projects show that there looks to be a potential for using self-reporting in the accident preventing work. However, it must be added that the two projects do not clarify how large a bias will occur when only one part describes the accidents and as such may have a tendency to embellish their own behaviour prior to the accident. 5.3 Usage rate of the bicycle jacket It has been essential to the effect of the bicycle jacket that the participants used the jacket when they were biking. In order to clarify the usage rate, we asked the test group via on a random day each month whether or not they had worn the jacket the last time they rode their bike. The monthly evaluation of the usage rate showed an average usage of 77 % but with great variations. The usage rate was high over 80 % during the first winter months of the project, but fell over the summer to about 30 % just to rise again after the summer period. 5.4 Safety effect of the bicycle jacket The main result of the project of 48 % fewer personal injury accidents between cyclists and cars is in the same order as the result from the driving lights project (Madsen et al., 2013). As only 77 % wore the jacket on average in this project, the risk reduction seen from the individual cyclist who wears the jacket at all times is even greater. This is also underlined by the fact that the effect was largest during the winter when the usage rate was on its highest and largest among those who stated a large jacket usage in the questionnaire. The effect of the bicycle jacket is smaller when the counterpart is another light road user, i.e. other cyclists and pedestrians. The explanation for this could be that the visibility of the cyclist improves the most for motorists who have a poorer view from inside the car than pedestrians and cyclists whose view is not limited by the car body. Contrary to the driving light on a bike, which had the highest effect in daylight and twilight, in this project there is not a great difference on the safety effect of the bicycle jacket on various lighting conditions. 6. Conclusion This project documents the fact that a bright-coloured bicycle jacket significantly reduces cyclists accident risk. In the project, the number of multi-party accidents with personal injuries throughout a year was compared between approx. 3,400 cyclists who wore a bright-coloured yellow bicycle jacket four out of five times on their bike rides and approx. 3,400 cyclists who wore their usual cycling garments. The group with the bicycle jacket had 48 % fewer personal injury accidents with motorised vehicles as counterparts than the group with regular cycling wear, and the difference is statistically significant (p<0.05). In this way, the project documents the fact that apparel that significantly improves the cyclists visibility can cause a great reduction in the accident risk for cyclists. 7. Suggestions for further work Both this project and the project that evaluated the safety effects of permanent running lights on bicycles clearly document the fact that higher visibility of cyclists would significantly reduce the number of personal injury accidents with cyclists. The study has as such shown that there are large and cost-efficient safety improvements connected to initiatives that can increase the cyclists visibility in traffic, and therefore such initiatives could be prioritized with advantage in the traffic safety work. 8. Acknowledgement The project was funded by TrygFonden who was also responsible for the design, production and distribution of jackets to the participants. The authors would like to take the opportunity to thank TrygFonden for the funding of and collaboration in this project. 13

15 9. References AIB (2008). Krydsulykker mellem cykler og biler [Intersection accidents between cyclists and vehicles]. Copenhagen: Danish Road Traffic Accident Investigation Board (AIB). Candappa, N. et al. (2012). Basic fact sheet "cyclists", deliverable D3.9 of the EC FP7 project DaCoTa Elvik, R. (2009). The non-linearity of risk and the promotion of environmentally sustainable transport. Accident Analysis and Prevention, 41(4), Hansen, A. S., & Jensen, C. (2012). Risiko i trafikken [Risk in traffic ]. Kgs. Lyngby: DTU Transport. Hansen, S., Thedchanamoorthy, S., & Bloch, A. (2014). Projekt cykeljakken, NOTAT, rekruttering og gennemførelse [Project Bicycle Jacket, NOTES, Recruitment and Completion].Unpublished manuscript. Herslund, M., & Jørgensen, N. O. (2003). Looked-but-failed-to-see-errors in traffic. Accident Analysis and Prevention, 35(6), Kwan, I., & Mapstone, J. (2004). Visibility aids for pedestrians and cyclists: A systematic review of randomised controlled trials. Accident Analysis and Prevention, 36(3), Lacherez, P., Wood, J. M., Marszalek, R. P., & King, M. J. (2013). Visibility-related characteristics of crashes involving bicyclists and motor vehicles - responses from an online questionnaire study. Transportation Research Part F: Traffic Psychology and Behaviour, 20, Lahrmann, H., & Madsen, J. C. O. (2014). Projekt cykeljakken, NOTAT, to webbaserede spørgeskemaer [Project Bicycle Jacket, NOTES, Two web-based questionnaires]. Aalborg: Trafikforskningsgruppen, Aalborg Universitet. Lohmann-Hansen, A., Lahrmann, H. S., & Madsen, J. C. O. (2001). Cykelbus'ter projektet i århus: Fra bil til cykel eller bus med positive virkemidler - projektevaluering [The BikeBus'ter project in Aarhus: From car to bicycle or bus using positive means - Project evaluation]. Copenhagen: Danish Transport Council. Madsen, J. C. O., Andersen, T., & Lahrmann, H. S. (2013). Safety effects of permanent running lights for bicycles: A controlled experiment. Accident Analysis and Prevention, 50, Räsänen, M., & Summala, H. (1998). Attention and expectation problems in bicycle-car collisions: An indepth study. Accident Analysis and Prevention, 30(5), Statistics Denmark (2014). Injured in road traffic accidents reported by the police, casualty wards and hospitals by reporter, accident situation, transport unit, sex, age and type of injury. Retrieved from Thedchanamoorthy, S., Madsen, T. K. O., Araghi, B. N., & Lahrmann, H. (2014). Projekt cykeljakken, NOTAT, en spørgeskemaundersøgelse [Project Bicycle Jacket, NOTES, A questionnaire survey].unpublished manuscript. 14

16 Thornley, S. J., Woodward, A., Langley, J. D., Ameratunga, S. N., & Rodgers, A. (2008). Conspicuity and bicycle crashes: Preliminay findings of the taupo bicycle study. Injury Prevention, 14(1), Wood, J. M., Tyrrel, R. A., Marszalek, R., Lacherez, P., & Carberry, T. (2013). Bicyclists overestimate their own night-time conspicuity and underestimate the benefits of retroreflective markers on moveable joints. Accident Analysis and Prevention, 55,

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