The Typical Traffic Accident in Lithuania In Comparison with Sweden

Rasa Ušpalytė-Vitkūnienė, Aliaksei Laureshyn

Abstract


Every day we strive to improve the environment and make it as comfortable as possible, creating new products and new technologies that are literally changing people’s lives. Transport is one of the most important engines of development in the world and, unfortunately, it is one of the most painful taking into account how many people’s lives we are losing in it. Ensuring safe traffic, stabilizing a number of accidents, reducing accidents on motor roads and streets are the most important tasks in the field of transport in Lithuania and the EU today. Lithuania could not be left behind when the EU countries pursued an important goal of halving the number of fatalities by the end of 2010 compared to 2001. Substantial road accident rates are recorded in cities with the highest concentration of road users. The aim of this article is to identify the typical accidents for Lithuanian cities and to compare them with the case of Sweden, which is one of the leading countries in the field of traffic safety. The five largest cities in Lithuania been selected for the analysis, where typical traffic accidents are identified. The analysis will help develop recommendations for changes in traffic infrastructure to ensure safe traffic.

Keywords:

pedestrians’ safety; traffic safety; typical accident

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References


Ab Malek, I., Salim, N. N. M., Alias, S. N., Zaki, N. A. M., & Ab Malek, H. (2019). Road Fatalities Using Logistic Regression. In Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017) (pp. 405–411). Singapore: Springer. https://doi.org/10.1007/978-981-13- 7279-7_50

Ahmed, A., Sadullah, A. F. M., & Yahya, A. S. (2019). Errors in Accident Data, Its Types, Causes and Methods of Rectification-Analysis of the Literature. Accident Analysis & Prevention, 130, 3–21. https://doi.org/10.1016/j. aap.2017.07.018

Durant, R. F., & Legge, J. S. (1993). Policy Design, Social Regulation, and Theory Building: Lessons From the Traffic Safety Policy Arena. Political Research Quarterly, 46(3), 641–656. https://doi.org/10.1177/106591299304600310

Elvik, R. (1995). An Analysis of Official Economic Valuations of Traffic Accident Fatalities in 20 Motorized Countries. Accident analysis & prevention, 27(2), 237–247. https://doi.org/10.1016/0001-4575(94)00060-Y

EU Commision. (2018). Road Safety: Data Show Improvements in 2017 but Renewed Efforts Are Needed for Further Substantial Progress. Retrieved from https://ec.europa.eu/commission/presscorner/detail/en/IP_18_2761 [Accessed on 10 December 2019].

EU Commission. (n. d.). Mobility and Transport. Road Safety. Retrieved from https://ec.europa.eu/transport/road_safety/home_en [ Accessed on 15 December 2019].

Feldstein, I., Dietrich, A., Milinkovic, S., & Bengler, K. (2016). A Pedestrian Simulator for Urban Crossing Scenarios. FAC-PapersOnLine, 49(19), 239–244. https://doi.org/10.1016/j.ifacol.2016.10.531

George, Y., Athanasios, T., & George, P. (2017). Investigation of Road Accident Severity per Vehicle Type. Transportation research procedia, 25, 2076–2083. https://doi.org/10.1016/j.trpro.2017.05.401

Kristianssen, A. C., Andersson, R., Belin, M. Å., & Nilsen, P. (2018). Swedish Vision Zero policies for Safety – A Comparative Policy Content Analysis. Safety science, 103, 260–269. https://doi.org/10.1016/j.ssci.2017.11.005

Lithuanian Road administration. (n. d.). Traffic accident statistic. Retrieved from http://lakd.lrv.lt/ [Accessed on 20 March 2019]. [In Lithuanian].

Russo, F., Biancardo, S. A., & Dell’Acqua, G. (2014). Consistent Approach to Predictive Modeling and Countermeasure Determination by Crash Type for Low-Volume Roads. Baltic Journal of Road & Bridge Engineering, 9(2), 77–87. https://doi.org/10.3846/bjrbe.2014.10

STRADA – Swedish Traffic Accident Data Acquisition’. (n. d.). Retrieved from https://www.transportstyrelsen.se/STRADA [ Accessed on 20 March 2019]. [In Swedish].

Su, J., Chen, J., Wang, H., Chen, W., & Wang, K. (2017). Establishment and Analysis on Typical Road Traffic Near-Crash Scenarios Related to Pedestrian in China. Traffic and Transportation, 209–214.

Subramanian, L. D., O’Neal, E. E., Mallaro, S., Williams, B., Sherony, R., Plumert, J. M., & Kearney, J. K. (2018). Pedestrian Road Crossing in Nighttime Lighting Conditions Using an Immersive Simulator (No. 18-01218). In Transportation Research Board 97th Annual Meeting.

Theofilatos, A., Graham, D., & Yannis, G. (2012). Factors Affecting Accident Severity Inside and Outside Urban Areas in Greece. Traffic injury prevention, 13(5), 458–467. https://doi.org/10.1080/15389588.2012.661110

Wachnicka, J., Budzyński, M., Kustra, W., & Gobis, A. (2019). The Effects of Selected Factors on Regional Road Fatalities – Analysis of the Łódź Region. In MATEC Web of Conferences (vol. 262, pp. 5–16). EDP Sciences. https://doi. org/10.1051/matecconf/201926205016

Woodman, R., Lu, K., Higgins, M. D., Brewerton, S., Jennings, P. A., & Birrell, S. (2019). Gap Acceptance Study of Pedestrians Crossing Between Platooning Autonomous Vehicles in a Virtual Environment. Transportation research part F: traffic psychology and behaviour, 67, 1–14. https://doi.org/10.1016/j. trf.2019.09.017

Yannis, G., Thomas, P., Papadimitriou, E., Talbot, R., & Martensen, H. (2016). 80 Developing the European Road Safety Decision Support System. Injury Prevention, 22(Suppl 2), A30.3–A31. https://doi.org/10.1136/injuryprev- 2016-042156.80




DOI: 10.7250/bjrbe.2020-15.484

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