- Email: [email protected]
Bicycle safety
Transportation Research Part F 41 (2016) 179–181
Contents lists available at ScienceDirect
Transportation Research Part F journal homepage: www.elsevier.com/locate/trf
Editorial
Bicycle safety 1. Background Bicycling is a healthy and environmentally friendly alternative to automobile use or public transport as well as a popular recreational activity. While cycling has clear benefits for an individual and the public health, cycling also reduces the negative effects of road transportation on environment and well-being (Lindsay, Macmillan, & Woodward, 2011; Shaw, Hales, Howden-Chapman, & Edwards, 2014). Because of the clear societal benefits of bicycle use, many countries promote cycling by various means (Andersen, Schnohr, Schroll, & Hein, 2000; de Hartog, Boogaard, Nijland, & Hoek, 2010) and, consequently, bicycling rates have increased in Europe (European Commission; Directorate-General for Mobility Transport, 2015) and well as in USA and Canada (Pucher, Buehler, & Seinen, 2011). Unfortunately, cycling can be considered also as a risky activity: 8% of all road fatalities are cyclists in EU the highest fatality proportion (24%) being in the Netherlands. In addition, the number of cyclist fatalities in EU has decreased by only 3% from 2010 to 2013 which is lower than the total fatality decrease of 18% (European Commission; Directorate-General for Mobility Transport, 2015). This modest improvement in cycling safety is partly due to increase in popularity of cycling. If the popularity of cycling continues to increase as expected, we can also expect an increase in injury rate among cyclists. Therefore, safety improvements should go hand in hand with promotion of cycling to minimize the number of bicycle injuries while increasing the popularity of cycling (Götschi, Garrard, & Giles-Corti, 2016). 2. Contributions This special issue is composed of ten articles which represent different methodological approaches and themes within bicycling safety. The methodological richness of bicycle studies is clearly presented in the selected articles: three articles report laboratory studies (Lehtonen, Havia, Kovanen, Leminen, & Saure, 2016; Stelling-Kon´czak, Hagenzieker, & Wee, 2016; Zeuwts, Vansteenkiste, Cardon, & Lenoir, 2016); three articles use surveys (Billot-Grasset, Amoros, & Hours, 2016; Lajunen, 2016; Paschalidis, Basbas, Politis, & Prodromou, 2016); two studies were conducted in naturalistic settings using an instrumented bicycle (Ahlstrom, Kircher, Thorslund, & Adell, 2016; Dozza, Bianchi Piccinini, & Werneke, 2016); one study was based on road side breath testing for alcohol (de Waard, Houwing, Lewis-Evans, Twisk, & Brookhuis, 2016); and finally one study was based on analysis of accident records (Lovelace, Roberts, & Kellar, 2016). The same richness as in methods can be seen also in topics. Three of the articles investigate different aspects of risk perception while riding. Zeuwts et al. (2016) report a study in which a hazard perception test for bicyclists was developed and differences between adults and children were studied. Lehtonen et al. (2016) had a slightly different approach: infrequent and frequent bicyclists were asked to evaluate how much caution different cycling situations needed by using video clips and continuous evaluation. These two studies show how different methods and instructions can be used in hazard perception tests. While the above mentioned studies were conducted in laboratory, Ahlstrom et al. (2016) studied bicyclists’ visual strategies when using a smartphone for listening to music, calls, text messages and internet searches while riding. Ahlstrom’s study shows how riders divide their attention according to the task. E-bicycles and e-cars pose new challenges and opportunities for the traffic system. While e-bikes and e-cars no doubt can reduce the environmental burden of road traffic, they bring new challenges for road users. E-bikes may increase the popularity of cycling but at the same time reduce the related health benefits. Dozza et al. (2016) compared the e-bike use to the use of ordinary non-powered bikes. Their results show how e-bike changes the cycling behaviour, which may result as new types of risks and crash characteristics. E-cars as rather quiet vehicles pose a new potential risk for pedestrians and cyclists. Stelling-Kon´czak et al. (2016) investigated the effects of ordinary car with combustion engine and e-car on perception of location and motion of the vehicle. Since the sense of hearing can decline with age, the sample included young, middle aged http://dx.doi.org/10.1016/j.trf.2016.07.013 1369-8478/Ó 2016 Published by Elsevier Ltd.
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Editorial / Transportation Research Part F 41 (2016) 179–181
and elderly participants. These two studies provide essential information about the possible effects of e-cars and e-bikes on safety. Conflicts between cyclists and vehicles on one hand and cyclists and pedestrian on the other hand are common phenomena in traffic since the cyclists often have to share the space with cars and pedestrians due to lack of special bicycle paths. Paschalidis et al. (2016) investigated cyclists’ attributions of the guilt in conflict situation with pedestrians and car drivers. Interestingly, the degree of blame put on the other party depended on the role of the other party, one’s own conflict and cycling history and one’s own behaviour. In addition to its value as description of the attribution mechanisms, Paschalidis et al.’s study is also is an important contribution describing how the cyclist-pedestrian and cyclist-car driver conflicts and, finally, accident may occur. Billot-Grasset et al. (2016) had a great opportunity to use hospital database for contacting cyclists who had been injured in a cycling accident. Based on postal survey answers, Billot-Grasset et al. created a typology of 17 configurations of cycling collisions and single bicycle accidents and used this typology for analysing the contributing factors such as weather, time of the day, infrastructure and driving under influence of alcohol. Lovelace et al. (2016) approached cycling injuries by using a geo-referenced dataset on road traffic incidents in UK. The dataset included attributes of each incident, casualties from these incidents and information of the vehicles involved. By using this vast data, Lovelace et al. were able to show how the crash risk varies spatially and temporally and discuss the negative health effects of promoting bicycling among vulnerable groups in dangerous areas. These studies provide valuable information for understanding the consequences of the increasing cycling rates if they are not accompanied with safety promotion and improvements in cycling infrastructure. Cycling is an important means for commuting and recreation especially among those road user groups who do not have access to a private vehicle and whose mileage is mostly composed of short local trips in which public transport is not feasible. These groups include, for example, children and adolescents. In his study, Lajunen (2016) investigated investigates barriers and facilitators of helmet use among primary and secondary school pupils and their parents. Helmet wearing rates seem to be lower especially among adolescents compared to children. Since modern bicycle helmets are highly effective at reducing the risk for severe brain injury in head impacts characteristic of bicycle crashes, it is important to promote helmet use among cyclists and especially among children and adolescents (Cripton, Dressler, Stuart, Dennison, & Richards, 2014). Lajunen’s study indicates that barriers to helmet use are different for children than for adults. Last but not least, de Waard et al. (2016) present an article about alcohol use among cyclists. While drunk driving has attracted lots of attention among traffic researchers and enforcement authorities, much less attention has been paid on cyclists riding under influence of alcohol. De Waard et al.’s study addresses this significant deficiency in literature. De Waard et al.’s study underlines the fact that drunk riding is a largely ignored but significant public health problem, which should be addressed. References Ahlstrom, C., Kircher, K., Thorslund, B., & Adell, E. (2016). Bicyclists’ visual strategies when conducting self-paced vs. system-paced smartphone tasks in traffic. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 204–216. http://dx.doi.org/10.1016/j.trf.2015.01.010. Andersen, L., Schnohr, P., Schroll, M., & Hein, H. (2000). ALl-cause mortality associated with physical activity during leisure time, work, sports, and cycling to work. Archives of Internal Medicine, 160(11), 1621–1628. http://dx.doi.org/10.1001/archinte.160.11.1621. Billot-Grasset, A., Amoros, E., & Hours, M. (2016). How cyclist behavior affects bicycle accident configurations? Transportation Research Part F: Traffic Psychology and Behaviour, 41, 261–276. http://dx.doi.org/10.1016/j.trf.2015.10.007. Cripton, P. A., Dressler, D. M., Stuart, C. A., Dennison, C. R., & Richards, D. (2014). Bicycle helmets are highly effective at preventing head injury during head impact: Head-form accelerations and injury criteria for helmeted and unhelmeted impacts. Accident Analysis and Prevention, 70, 1–7. de Hartog, J. J., Boogaard, H., Nijland, H., & Hoek, G. (2010). Do the health benefits of cycling outweigh the risks? Environmental Health Perspectives, 118 (8), 1109–1116. http://dx.doi.org/10.1289/ehp.0901747. de Waard, D., Houwing, S., Lewis-Evans, B., Twisk, D., & Brookhuis, K. (2016). Bicycling under the influence of alcohol. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 302–306. http://dx.doi.org/10.1016/j.trf.2015.03.003. Dozza, M., Bianchi Piccinini, G. F., & Werneke, J. (2016). Using naturalistic data to assess e-cyclist behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 217–226. http://dx.doi.org/10.1016/j.trf.2015.04.003. European Commission; Directorate-General for Mobility Transport (2015). Road safety in the European Union trends, statistics and main challenges, March 2015. Brussels: European Commission. Götschi, T., Garrard, J., & Giles-Corti, B. (2016). Cycling as a part of daily life: A review of health perspectives. Transport Reviews, 36(1), 45–71. http://dx. doi.org/10.1080/01441647.2015.1057877. Lajunen, T. (2016). Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 294–301. http://dx.doi.org/10.1016/j.trf.2015.03.005. Lehtonen, E., Havia, V., Kovanen, A., Leminen, M., & Saure, E. (2016). Evaluating bicyclists’ risk perception using video clips: Comparison of frequent and infrequent city cyclists. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 195–203. http://dx.doi.org/10.1016/j.trf.2015.04.006. Lindsay, G., Macmillan, A., & Woodward, A. (2011). Moving urban trips from cars to bicycles: Impact on health and emissions. Australian and New Zealand Journal of Public Health, 35(1), 54–60. Lovelace, R., Roberts, H., & Kellar, I. (2016). Who, where, when: The demographic and geographic distribution of bicycle crashes in West Yorkshire. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 227–293. http://dx.doi.org/10.1016/j.trf.2015.02.010. Paschalidis, E., Basbas, S., Politis, I., & Prodromou, M. (2016). ‘‘Put the blame on. . .others!”: The battle of cyclists against pedestrians and car drivers at the urban environment. A cyclists’ perception study. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 243–260. http://dx.doi.org/ 10.1016/j.trf.2015.07.021. Pucher, J., Buehler, R., & Seinen, M. (2011). Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies. Transportation Research Part A: Policy and Practice, 45(6), 451–475. http://dx.doi.org/10.1016/j.tra.2011.03.001. Shaw, C., Hales, S., Howden-Chapman, P., & Edwards, R. (2014). Health co-benefits of climate change mitigation policies in the transport sector. Nature Climate Change, 4(6), 427–433.
Editorial / Transportation Research Part F 41 (2016) 179–181
181
Stelling-Kon´czak, A., Hagenzieker, M., Commandeur, J. J. F., Agterberg, M. J. H., & Wee, B. V. (2016). Auditory localisation of conventional and electric cars: Laboratory results and implications for cycling safety. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 227–242. Vansteenkiste, P., Zeuwts, L., Cardon, G., & Lenoir, M. (2016). A hazard-perception test for cycling children: An exploratory study. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 182–194.
⇑
Timo Lajunen Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway ⇑ Corresponding author. E-mail address: [email protected] Türker Özkan Middle East Technical University (METU), Ankara, Turkey Bryan E. Porter Old Dominion University, Norfolk, VA, USA
Contents lists available at ScienceDirect
Transportation Research Part F journal homepage: www.elsevier.com/locate/trf
Editorial
Bicycle safety 1. Background Bicycling is a healthy and environmentally friendly alternative to automobile use or public transport as well as a popular recreational activity. While cycling has clear benefits for an individual and the public health, cycling also reduces the negative effects of road transportation on environment and well-being (Lindsay, Macmillan, & Woodward, 2011; Shaw, Hales, Howden-Chapman, & Edwards, 2014). Because of the clear societal benefits of bicycle use, many countries promote cycling by various means (Andersen, Schnohr, Schroll, & Hein, 2000; de Hartog, Boogaard, Nijland, & Hoek, 2010) and, consequently, bicycling rates have increased in Europe (European Commission; Directorate-General for Mobility Transport, 2015) and well as in USA and Canada (Pucher, Buehler, & Seinen, 2011). Unfortunately, cycling can be considered also as a risky activity: 8% of all road fatalities are cyclists in EU the highest fatality proportion (24%) being in the Netherlands. In addition, the number of cyclist fatalities in EU has decreased by only 3% from 2010 to 2013 which is lower than the total fatality decrease of 18% (European Commission; Directorate-General for Mobility Transport, 2015). This modest improvement in cycling safety is partly due to increase in popularity of cycling. If the popularity of cycling continues to increase as expected, we can also expect an increase in injury rate among cyclists. Therefore, safety improvements should go hand in hand with promotion of cycling to minimize the number of bicycle injuries while increasing the popularity of cycling (Götschi, Garrard, & Giles-Corti, 2016). 2. Contributions This special issue is composed of ten articles which represent different methodological approaches and themes within bicycling safety. The methodological richness of bicycle studies is clearly presented in the selected articles: three articles report laboratory studies (Lehtonen, Havia, Kovanen, Leminen, & Saure, 2016; Stelling-Kon´czak, Hagenzieker, & Wee, 2016; Zeuwts, Vansteenkiste, Cardon, & Lenoir, 2016); three articles use surveys (Billot-Grasset, Amoros, & Hours, 2016; Lajunen, 2016; Paschalidis, Basbas, Politis, & Prodromou, 2016); two studies were conducted in naturalistic settings using an instrumented bicycle (Ahlstrom, Kircher, Thorslund, & Adell, 2016; Dozza, Bianchi Piccinini, & Werneke, 2016); one study was based on road side breath testing for alcohol (de Waard, Houwing, Lewis-Evans, Twisk, & Brookhuis, 2016); and finally one study was based on analysis of accident records (Lovelace, Roberts, & Kellar, 2016). The same richness as in methods can be seen also in topics. Three of the articles investigate different aspects of risk perception while riding. Zeuwts et al. (2016) report a study in which a hazard perception test for bicyclists was developed and differences between adults and children were studied. Lehtonen et al. (2016) had a slightly different approach: infrequent and frequent bicyclists were asked to evaluate how much caution different cycling situations needed by using video clips and continuous evaluation. These two studies show how different methods and instructions can be used in hazard perception tests. While the above mentioned studies were conducted in laboratory, Ahlstrom et al. (2016) studied bicyclists’ visual strategies when using a smartphone for listening to music, calls, text messages and internet searches while riding. Ahlstrom’s study shows how riders divide their attention according to the task. E-bicycles and e-cars pose new challenges and opportunities for the traffic system. While e-bikes and e-cars no doubt can reduce the environmental burden of road traffic, they bring new challenges for road users. E-bikes may increase the popularity of cycling but at the same time reduce the related health benefits. Dozza et al. (2016) compared the e-bike use to the use of ordinary non-powered bikes. Their results show how e-bike changes the cycling behaviour, which may result as new types of risks and crash characteristics. E-cars as rather quiet vehicles pose a new potential risk for pedestrians and cyclists. Stelling-Kon´czak et al. (2016) investigated the effects of ordinary car with combustion engine and e-car on perception of location and motion of the vehicle. Since the sense of hearing can decline with age, the sample included young, middle aged http://dx.doi.org/10.1016/j.trf.2016.07.013 1369-8478/Ó 2016 Published by Elsevier Ltd.
180
Editorial / Transportation Research Part F 41 (2016) 179–181
and elderly participants. These two studies provide essential information about the possible effects of e-cars and e-bikes on safety. Conflicts between cyclists and vehicles on one hand and cyclists and pedestrian on the other hand are common phenomena in traffic since the cyclists often have to share the space with cars and pedestrians due to lack of special bicycle paths. Paschalidis et al. (2016) investigated cyclists’ attributions of the guilt in conflict situation with pedestrians and car drivers. Interestingly, the degree of blame put on the other party depended on the role of the other party, one’s own conflict and cycling history and one’s own behaviour. In addition to its value as description of the attribution mechanisms, Paschalidis et al.’s study is also is an important contribution describing how the cyclist-pedestrian and cyclist-car driver conflicts and, finally, accident may occur. Billot-Grasset et al. (2016) had a great opportunity to use hospital database for contacting cyclists who had been injured in a cycling accident. Based on postal survey answers, Billot-Grasset et al. created a typology of 17 configurations of cycling collisions and single bicycle accidents and used this typology for analysing the contributing factors such as weather, time of the day, infrastructure and driving under influence of alcohol. Lovelace et al. (2016) approached cycling injuries by using a geo-referenced dataset on road traffic incidents in UK. The dataset included attributes of each incident, casualties from these incidents and information of the vehicles involved. By using this vast data, Lovelace et al. were able to show how the crash risk varies spatially and temporally and discuss the negative health effects of promoting bicycling among vulnerable groups in dangerous areas. These studies provide valuable information for understanding the consequences of the increasing cycling rates if they are not accompanied with safety promotion and improvements in cycling infrastructure. Cycling is an important means for commuting and recreation especially among those road user groups who do not have access to a private vehicle and whose mileage is mostly composed of short local trips in which public transport is not feasible. These groups include, for example, children and adolescents. In his study, Lajunen (2016) investigated investigates barriers and facilitators of helmet use among primary and secondary school pupils and their parents. Helmet wearing rates seem to be lower especially among adolescents compared to children. Since modern bicycle helmets are highly effective at reducing the risk for severe brain injury in head impacts characteristic of bicycle crashes, it is important to promote helmet use among cyclists and especially among children and adolescents (Cripton, Dressler, Stuart, Dennison, & Richards, 2014). Lajunen’s study indicates that barriers to helmet use are different for children than for adults. Last but not least, de Waard et al. (2016) present an article about alcohol use among cyclists. While drunk driving has attracted lots of attention among traffic researchers and enforcement authorities, much less attention has been paid on cyclists riding under influence of alcohol. De Waard et al.’s study addresses this significant deficiency in literature. De Waard et al.’s study underlines the fact that drunk riding is a largely ignored but significant public health problem, which should be addressed. References Ahlstrom, C., Kircher, K., Thorslund, B., & Adell, E. (2016). Bicyclists’ visual strategies when conducting self-paced vs. system-paced smartphone tasks in traffic. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 204–216. http://dx.doi.org/10.1016/j.trf.2015.01.010. Andersen, L., Schnohr, P., Schroll, M., & Hein, H. (2000). ALl-cause mortality associated with physical activity during leisure time, work, sports, and cycling to work. Archives of Internal Medicine, 160(11), 1621–1628. http://dx.doi.org/10.1001/archinte.160.11.1621. Billot-Grasset, A., Amoros, E., & Hours, M. (2016). How cyclist behavior affects bicycle accident configurations? Transportation Research Part F: Traffic Psychology and Behaviour, 41, 261–276. http://dx.doi.org/10.1016/j.trf.2015.10.007. Cripton, P. A., Dressler, D. M., Stuart, C. A., Dennison, C. R., & Richards, D. (2014). Bicycle helmets are highly effective at preventing head injury during head impact: Head-form accelerations and injury criteria for helmeted and unhelmeted impacts. Accident Analysis and Prevention, 70, 1–7. de Hartog, J. J., Boogaard, H., Nijland, H., & Hoek, G. (2010). Do the health benefits of cycling outweigh the risks? Environmental Health Perspectives, 118 (8), 1109–1116. http://dx.doi.org/10.1289/ehp.0901747. de Waard, D., Houwing, S., Lewis-Evans, B., Twisk, D., & Brookhuis, K. (2016). Bicycling under the influence of alcohol. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 302–306. http://dx.doi.org/10.1016/j.trf.2015.03.003. Dozza, M., Bianchi Piccinini, G. F., & Werneke, J. (2016). Using naturalistic data to assess e-cyclist behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 217–226. http://dx.doi.org/10.1016/j.trf.2015.04.003. European Commission; Directorate-General for Mobility Transport (2015). Road safety in the European Union trends, statistics and main challenges, March 2015. Brussels: European Commission. Götschi, T., Garrard, J., & Giles-Corti, B. (2016). Cycling as a part of daily life: A review of health perspectives. Transport Reviews, 36(1), 45–71. http://dx. doi.org/10.1080/01441647.2015.1057877. Lajunen, T. (2016). Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 294–301. http://dx.doi.org/10.1016/j.trf.2015.03.005. Lehtonen, E., Havia, V., Kovanen, A., Leminen, M., & Saure, E. (2016). Evaluating bicyclists’ risk perception using video clips: Comparison of frequent and infrequent city cyclists. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 195–203. http://dx.doi.org/10.1016/j.trf.2015.04.006. Lindsay, G., Macmillan, A., & Woodward, A. (2011). Moving urban trips from cars to bicycles: Impact on health and emissions. Australian and New Zealand Journal of Public Health, 35(1), 54–60. Lovelace, R., Roberts, H., & Kellar, I. (2016). Who, where, when: The demographic and geographic distribution of bicycle crashes in West Yorkshire. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 227–293. http://dx.doi.org/10.1016/j.trf.2015.02.010. Paschalidis, E., Basbas, S., Politis, I., & Prodromou, M. (2016). ‘‘Put the blame on. . .others!”: The battle of cyclists against pedestrians and car drivers at the urban environment. A cyclists’ perception study. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 243–260. http://dx.doi.org/ 10.1016/j.trf.2015.07.021. Pucher, J., Buehler, R., & Seinen, M. (2011). Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies. Transportation Research Part A: Policy and Practice, 45(6), 451–475. http://dx.doi.org/10.1016/j.tra.2011.03.001. Shaw, C., Hales, S., Howden-Chapman, P., & Edwards, R. (2014). Health co-benefits of climate change mitigation policies in the transport sector. Nature Climate Change, 4(6), 427–433.
Editorial / Transportation Research Part F 41 (2016) 179–181
181
Stelling-Kon´czak, A., Hagenzieker, M., Commandeur, J. J. F., Agterberg, M. J. H., & Wee, B. V. (2016). Auditory localisation of conventional and electric cars: Laboratory results and implications for cycling safety. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 227–242. Vansteenkiste, P., Zeuwts, L., Cardon, G., & Lenoir, M. (2016). A hazard-perception test for cycling children: An exploratory study. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 182–194.
⇑
Timo Lajunen Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway ⇑ Corresponding author. E-mail address: [email protected] Türker Özkan Middle East Technical University (METU), Ankara, Turkey Bryan E. Porter Old Dominion University, Norfolk, VA, USA