Road Safety Trends at National Level in Europe: A Review of Time-series Analysis Performed during the Period 2000–12

References

• Amoros, E., Martin, J. L., & Laumon, B. (2006). Under-reporting of road crash casualties in France. Accident Analysis & Prevention, 38(4), 627–635. doi: 10.1016/j.aap.2005.11.006
   PubMed Web of Science ®Google Scholar
• Antoniou, C., & Yannis, G. (2013). State-space based analysis and forecasting of macroscopic road safety trends in Greece. Accident Analysis & Prevention, 60, 268–276. doi: 10.1016/j.aap.2013.02.039
   PubMed Web of Science ®Google Scholar
• Bergel, R., Carnis, L., Lassarre, S., Le Breton, P., Le Tertre, A., Page, Y., … Uhry, Z. (2002). Amnistie présidentielle et sécurité routière (Presidential amnesty and road safety). Rapport d'un groupe d'experts appartenant à l'Inrets, à l'Invs, au Setra, au Lab, et à l'Université de Reims Champagne-Ardenne (in French).
   Google Scholar
• Bergel, R., & Cherfi, M. (2007). ARMA-type models. Chapter 3.4 in Dupont, E., Martensen, H. (2007), 248–289. http://erso.swov.nl/safetynet/fixed/WP7/D7_4/D7.4.pdf
   Google Scholar
• Bergel, R., & Depire, A. (2004a). Recherche d'une forme fonctionnelle d'un modèle agrégé de risque routier [Functional form for an aggregate monthly model for road risk]. Actes Inrets n 90 du groupe de travail 2001 du Séminaire Modélisation du Trafic, Arcueil (in French).
   Google Scholar
• Bergel, R., & Depire, A. (2004b, July). Climate, road traffic and road risk: An aggregate approach. Proceedings of the WCTR'04, Istanbul.
   Google Scholar
• Bergel, R., Girard, B., Lassarre, S., & Le Breton, P. (1995, September). A model of seasonally corrected indicators of road safety. Proceedings of the conference road safety and strategic highway research program (SHRP) and traffic safety on two continents, Prague.
   Google Scholar
• Bergel-Hayat, R. (2008). The use of explanatory variables in time series modelling: Applications to transport demand and road risk (Ph.D. thesis). University Paris-Est, Marne-la-Vallée.
   Google Scholar
• Bergel-Hayat, R. (2012). Time-series models of aggregate road risk and their applications to European countries. Transport Reviews: A Transnational Transdisciplinary Journal, 32(5), 653–670. doi: 10.1080/01441647.2012.695407
   Web of Science ®Google Scholar
• Bergel-Hayat, R., Christoforou, Z., & Ferriere, S. (2013). The impact of the economic crisis on road mortality: An exploratory approach for some countries in Europe. Proceedings of the ETC conference, Frankfurt, 30 September–2 October 2013.
   Google Scholar
• Bergel-Hayat, R., Debbarh, M., Antoniou, C., & Yannis, G. (2013). Explaining the road accident risk: Weather effects. Accident Analysis & Prevention, 60, 456–465. doi: 10.1016/j.aap.2013.03.006
   PubMed Web of Science ®Google Scholar
• Bergel-Hayat, R., & Zukowska, J. (2014). Structural time series modelling of the number of road fatalities in Poland in relation with economic factors. TRA 5th conference, Paris, 14–17 April 2014.
   Google Scholar
• Bergel-Hayat, R., & Zukowska, J. (2015a). Time series analysis of road safety trends aggregated at national level in Europe for the period 2000–2010. Gdansk: Gdansk University of Technology.
   Google Scholar
• Bergel-Hayat, R., & Zukowska, J. (2015b). Analyse des tendances de sécurité routière agrégées au niveau national en Europe, 2000-2012. Rapport de synthèse. UPE-IFSTTAR, Champs sur Marne.
   Google Scholar
• Bijleveld, F., Commandeur, J., Koopman, S. J., & van Montfort, K. (2010). Multivariate non-linear time series modelling of exposure and risk in road safety research. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(1), 145–161. doi: 10.1111/j.1467-9876.2009.00690.x
   Web of Science ®Google Scholar
• Bijleveld, F. D. (2005). The covariance between the number of accidents and the number of victims in multivariate analysis of accident related outcomes. Accident Analysis & Prevention, 37, 591–600. doi: 10.1016/j.aap.2005.01.004
   PubMed Web of Science ®Google Scholar
• Bijleveld, F. D. (2008). Time series analysis in road safety research using state space methods (Ph.D. thesis). Vrije Universiteit, Amsterdam.
   Google Scholar
• Bijleveld, F. D., Commandeur, J. J. F., Gould, P., & Koopman, S. J. (2008). Model-based measurement of latent risk in time series with applications. Journal of the Royal Statistical Society: Series A (Statistics in Society), 171(1), 265–277. doi: 10.1111/j.1467-985X.2007.00496.x
   Web of Science ®Google Scholar
• Brandstaetter, Ch., & Gatscha, M. (2007). Classical linear regression models. Chapter 3.2.1 in Dupont, E., Martensen, H. (2007), 177–196. http://erso.swov.nl/safetynet/fixed/WP7/D7_4/D7.4.pdf
   Google Scholar
• Brijs, T., Karlis, D., & Wets, G. (2008). Studying the effect of weather conditions on daily crash counts using a discrete time-series model. Accident Analysis & Prevention, 40(3), 1180–1190. doi: 10.1016/j.aap.2008.01.001
   PubMed Web of Science ®Google Scholar
• Broughton, J. (1991). Forecasting road accident casualties in Great Britain. Accident Analysis & Prevention, 23(5), 353–362. doi: 10.1016/0001-4575(91)90056-B
   PubMed Web of Science ®Google Scholar
• Broughton, J., Keigan, M., Yannis, G., Evgenikos, P., Chaziris, A., Papadimitriou, E., … Tecl, J. (2010). Estimation of the real number of road casualties in Europe. Safety Science, 48(3), 365–371. doi: 10.1016/j.ssci.2009.09.012
   Web of Science ®Google Scholar
• Broughton, J., & Knowles, J. (2010). Providing the numerical context for British casualty reduction targets. Safety Science, 48(9), 1134–1141. doi: 10.1016/j.ssci.2010.01.008
   Web of Science ®Google Scholar
• Cameron, M., & Delaney, A. (2008). Speed enforcement — effects, mechanisms, intensity and economic benefits of each mode of operation. Proceedings of the national conference on high risk road users, Australasian College of Road Safety and the Travelsafe Committee of the Queensland Parliament, Brisbane.
   Google Scholar
• Cameron, M., Newstead, S., Diamantopoulou, K., & Oxley, P. (2003). The interaction between speed camera enforcement and speed-related mass media publicity in Victoria, Australia. Proceedings of the 47th Annual scientific conference, association for the advancement of automotive medicine, Lisbon, Portugal.
   Google Scholar
• Cardoso, J. L. (2005). The use of international data on fuel sales and vehicle fleet for the estimation of yearly national traffic volume. Accident Analysis & Prevention, 37(1), 207–215. doi: 10.1016/j.aap.2003.12.005
   PubMed Web of Science ®Google Scholar
• Christens, P. F. (2003). Statistical modelling of traffic safety development (Ph. D. thesis). Technical University of Denmark, Kongens Lyngby, Denmark.
   Google Scholar
• Christens, P. F., & Thyregod, P. (2003). New methods for assessing the impact of traffic safety countermeasures, Aalborg, Denmark: Trafikdagepå Aalborg Universitet.
   Google Scholar
• Commandeur, J., Bjleveld, F., & Bergel, R. (2007). A multivariate time series analysis applied to SafetyNet data. SafetyNet Deliverable D7.7 of the EU FP6 project SafetyNet. Retrieved January 15, 2014 from http://erso.swov.nl
   Google Scholar
• Commandeur, J., & de Blois, Ch. (2007). State space models. Chapter 3.6 in Dupont, E., Martensen, H. (2007), 295–336. Retrieved from http://erso.swov.nl/safetynet/fixed/WP7/D7_4/D7.4.pdf
   Google Scholar
• Commandeur, J. J. F., Bijleveld, F., Bergel-Hayat, R., Antoniou, C., Yannis, G., & Papadimitriou, E. (2013). On statistical inference in time series analysis of the evolution of road safety. Accident Analysis & Prevention, 60(2013), 424–434. doi: 10.1016/j.aap.2012.11.006
   PubMed Web of Science ®Google Scholar
• Commandeur, J. J. F., & Koopman, S. J. (2007). An introduction to state space time series analysis. Oxford: Oxford University Press.
   Google Scholar
• COST 329. (2004). Models for traffic and safety development and interventions. European Commission, Directorate General for Transport, Brussels, final report of the Action.
   Google Scholar
• Diamantopoulou, K., & Cameron, M. (2001). Development of an index to measure police traffic enforcement effectiveness. Proceedings, road safety research, policing and education conference, Melbourne.
   Google Scholar
• Dupont, E., Commandeur, J. J. F., Lassarre, S., Bijleveld, F., Martensen, H., Antoniou, C., … Giustiniani, G. (2014). Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries. Accident Analysis & Prevention, 71(C), 327–336. doi: 10.1016/j.aap.2014.06.009
   PubMed Web of Science ®Google Scholar
• Dupont, E., & Martensen, H. (Ed.). (2007). Multilevel modelling and time series analysis in traffic safety research — methodology and manual. Deliverables D7.4 and D7.5 of the EU FP6 project SafetyNet. Retrieved January 15, 2014, from http://www.erso.svow.nl
   Google Scholar
• Gaudry, M. (1984). DRAG, un modèle de la Demande Routière, des Accidents et de leur Gravité, appliqué au Québec de 1956 à 1982, Publication 359, Centre de Recherche sur les Transports, Université de Montréal.
   Google Scholar
• Gaudry, M., & Lassarre, S. (Eds.). (2000). Structural road accident models — the international DRAG family. Oxford: Elsevier Science Publishers.
   Google Scholar
• Gould, P. G. (2005). Econometric modelling of road crashes (PhD thesis). Monash University, Australia.
   Google Scholar
• Hakim, S., Hakkert, S., Hochermann, I., & Shefert, D. (1991). A critical review of macro models for road accidents. Accident Analysis & Prevention, 23(5), 379–400. doi: 10.1016/0001-4575(91)90058-D
   PubMed Web of Science ®Google Scholar
• Harvey, A. C. (1989). Forecasting structural time series and the Kalman filter. Cambridge: Cambridge University Press.
   Google Scholar
• Harvey, A. C., & Durbin, J. (1986). The effects of seat belt legislation on British road casualties: A case study in structural time series modelling. Journal of the Royal Statistical Society, 149(part 3), 187–227. doi: 10.2307/2981553
   Google Scholar
• Hermans, E., Wets, G., & Van den Bossche, F. (2006a). The frequency and severity of road traffic accidents studied by state space methods. Journal of Transportation and Statistics, 9(1), 63–76.
   Google Scholar
• Hermans, E., Wets, G., & Van den Bossche, F. (2006b). Describing the evolution in the number of highway deaths by a decomposition in exposure, accident risk and fatality risk. Transportation Research Record - Journal of the Transportation Research Board, 1950, 1–8. doi: 10.3141/1950-01
   Web of Science ®Google Scholar
• Holló, P., Eksler, V., & Zukowska, J. (2010). Road safety performance indicators and their explanatory value: A critical view based on the experience of Central European countries. Safety Science 2010, 48, 1142–1150.
   Google Scholar
• Jaeger, L., & Lassarre, S. (1999). TAG, un modèle économétrique pour un suivi de l'insécurité routière. Revue RTS, 65, 3–20 (in French). doi: 10.1016/S0761-8980(00)88842-1
   Google Scholar
• Krystek, R., & Zukowska, J. (2003). Falling accident risk in Poland. KONBiN'03, The 3-rd safety and reliability international conference, Poland.
   Google Scholar
• Lassarre, S. (2001). Analysis of progress in road safety in ten European countries. Accident Analysis & Prevention, 33, 743–751. doi: 10.1016/S0001-4575(00)00088-9
   PubMed Web of Science ®Google Scholar
• Martensen, H., & Dupont, E. (Eds.). (2012). Final report Work Package 4. Deliverable 4.10 of the EC FP7 project DaCoTA. Retrieved January 15, 2014, from http://www.dacota-project.eu
   Google Scholar
• Muhlrad, N., & Dupont, E. (Eds.). (2010). Consultation of a panel of experts on the needs for data and technical tools in road safety policy-making. Deliverable 1.1/4.1 of the EC FP7 project DaCoTA. Retrieved January 15, 2014, from http://www.dacota-project.eu
   Google Scholar
• Newstead, S., Delaney, A., Watson, L., & Cameron, M. (2004). A model for considering the ‘total safety’ of the light passenger vehicle fleet. Proceedings, 2004 Road Safety Research, Policing and Education Conference, Perth.
   Google Scholar
• OECD. (1970). Proceedings of the symposium on the use of statistical methods in the analysis of road accidents, Crowthorne, April 1969. OECD, Paris.
   Google Scholar
• OECD. (2008). Towards zero: Ambitious road safety targets and the safety system approach. Paris: OECD.
   Google Scholar
• OECD. (2011). Reporting on serious road traffic casualties: Combining and using different data sources to improve understanding of non-fatal road traffic crashes. Paris: OECD/ITF.
   Google Scholar
• ONISR. (2012). La sécurité routière en France : bilan de l'année 2011. Analyse conjoncturelle (pp. 111–121). La Défense: Ministère de l'Interieur. (in French)
   Google Scholar
• Oppe, S. (1989). Macroscopic models for traffic and traffic safety. Accident Analysis & Prevention, 21, 225–232. doi: 10.1016/0001-4575(89)90013-4
   PubMed Web of Science ®Google Scholar
• Oppe, S. (1991). The development of traffic and traffic safety in six developed counties. Accident Analysis & Prevention, 23(5), 401–412. doi: 10.1016/0001-4575(91)90059-E
   PubMed Web of Science ®Google Scholar
• Oppe, S., & Bijleveld, F. D. (2003). Reanalysis of traffic enforcement data from Victoria. SWOV report D-2003-6. Leidschendam: SWOV.
   Google Scholar
• Oppe, S., & Koornstra, M. J. (1990). A mathematical model for related long term developments of road traffic and safety. In M. Koshi (Ed.), Transportation and traffic theory (pp. 113–133). New York: Elsevier.
   Google Scholar
• Oxley, P., Cameron, M., & Newstead, S. (2003). Estimation of the safety benefits of a vehicle replacement programme in Victoria. Proceedings, 2003 road safety research, policing and education conference, Sydney.
   Google Scholar
• Papadimitriou, E., Yannis, G., Bijveled, F., & Cardoso, Jao (2013). Exposure data and risk indicators for safety performance assessment in Europe. Accident Analysis and Prevention, 60, 371–383. doi: 10.1016/j.aap.2013.04.040
   PubMed Web of Science ®Google Scholar
• Stipdonk, H., Bijleveld, F., Van Norden, Y., & Commandeur, J. (2012). Analysing the development of road safety using demographic data. Accident Analysis & Prevention, 60, 435–444. doi: 10.1016/j.aap.2012.08.005
   PubMed Web of Science ®Google Scholar
• Van den Bossche, F. (2006). Road safety, risk and exposure in Belgium (Ph.D. thesis). Universitet Hasselt.
   Google Scholar
• Van den Bossche, F., & Wets, G. (2003). A structural road accident model for Belgium. (RA-2003-21) Technical report, Policy research Centre for Traffic Safety, Diepenbeek, Belgium.
   Google Scholar
• Van den Bossche, F., Wets, G., & Brijs, T. (2004). Role of exposure in analysis of road accidents: A Belgian case study. Transportation Research Record - Journal of the Transportation Research Board, 1908, 96–103. doi: 10.3141/1908-12
   Google Scholar
• Van den Bossche, F., Wets, G., & Brijs, T. (2006). Predicting road crashes using calendar data. Electronic proceedings of the 85th annual meeting of the transportation research board.
   Google Scholar
• Van den Bossche, F., Wets, G., & Brijs, T. (2007). Analysis of road risk per age and gender category: A time series approach. Electronic proceedings of the 86th annual transportation research board meeting, 21–25 January, Washington DC, USA.
   Google Scholar
• Wesemann, P., Van Norden, Y., & Stipdonk, H. (2010). An outlook on Dutch road safety in 2020: Future developments of exposure, crashes and policy. Safety Science, 48, 1098–1105. doi: 10.1016/j.ssci.2010.05.003
   Web of Science ®Google Scholar
• Yannis, G., Antoniou, C., & Papadimitriou, E. (2007). Road casualties and enforcement: Distributional assumptions of serially correlated count data. Traffic Injury and Prevention, 8(3), 300–308. doi: 10.1080/15389580701369241
   PubMedGoogle Scholar
• Yannis, G., Antoniou, C., & Papadimitriou, E. (2011). Autoregressive non-linear time-series modelling of traffic fatalities in Europe. European Transport Research Review, 3, 113–127. doi: 10.1007/s12544-011-0055-4
   Google Scholar
• Yannis, G., Antoniou, C., Papadimitriou, E., & Katsochis, D. (2011). When may road fatalities start to decrease? Journal of Safety Research 2011, 42(1), 17–25.
   PubMed Web of Science ®Google Scholar
• Yannis, G., Papadimitriou, E., & Folla, K. (2014). Effect of GDP changes on road traffic fatalities. Safety Science, 63, 42–49. doi:10.1016/j.ssci.2013.10.017
   Web of Science ®Google Scholar
• Yannis, G., Papadimitriou, E., Lejeune, Ph., Treny, V., Hemdorff, S., Bergel, R., … Bjornskau, T. (2005). State of the art report on risk and exposure data. SafetyNet Deliverable 2.1. Retrieved on January 15, 2015, from http://www.erso.swov.nl
   Google Scholar
• Zukowska, J. (2003). Traffic risk modelling using time-series (Ph.D. thesis). Gdansk University of Technology, Poland.
   Google Scholar
• Zukowska, J. (2004, June 17–19). Traffic fatalities modelling using time-series. International workshop on rehabilitation of existing urban building stock. Gdansk University of Technology, Poland.
   Google Scholar
• Zukowska, J. (2012). Road safety analysis in Poland using time-series modelling techniques. Journal of Polish Safety and Reliability Association Summer Safety and Reliability Seminars, 3(1), 109–112.
   Google Scholar