Volume List  / Volume 3 (1)

Article

INTEGRATING GIS AND SPATIAL ANALYTICAL TECHNIQUES IN AN ANALYSIS OF ROAD TRAFFIC ACCIDENTS IN SERBIA

DOI: 10.7708/ijtte.2013.3(1).01


3 / 1 / 1-15 Pages

Author(s)

Liljana Çela - South East Europe Transport Observatory, Omladinskih Brigada 1, Belgrade, Serbia -

Shino Shiode - Department of Geography, Environment & Development Studies, Birkbeck, University of London, Malet Street, London WC1E 7HX -

Krsto Lipovac - The Faculty of Criminal Justice and Police Academy, 11080 Zemun, Cara Dusana 196, Belgrade, Serbia -


Abstract

Road safety issue is drawing major attention of local Serbian authorities who seeks the reduction of the volume of Road Traffic Accidents. The study starts with a summative review of the problem with a focus on the situation in the European Union member countries and the Western Balkan (WB) countries: Albania, Bosnia and Herzegovina, Croatia, Montenegro, the former Yugoslav Republic of Macedonia, Kosovo and Serbia. It then interprets traffic accident data using network K-function and Network Kernel Density Estimation. Unlike the conventional planar methods, the network methods analyze the spatial patterns of accident locations within the network space and are therefore not affected by the configuration of the street network or its distance. The Network K-function helped authors to investigate the presence of clusters, whereas the Network Kernel Density method helped identify the actual cluster locations. Multiple linear regression analysis was also used to find the most significant variables related to the road conditions, time and the main cause which have likely contributed to high rates of accidents. The empirical analysis was carried out using traffic data from the City of Belgrade. Implications for further research were discussed, suggesting that the findings can be used for more in-depth studies aimed at identifying the most significant cause of road accidents in any given area and that they could be extended and applied in other countries of the region.


Download Article

Number of downloads: 2176


Acknowledgements:

The authors would like to express their gratitude to Criminology Police Academy who provided them with Road Traffic Accidents data for 2007 in Serbia, and South East Europe Transport Observatory (SEETO) who provided them with annual statistical data of road safety and polygon features of the Western Balkan countries. Authors are also grateful to the Republic Geodetic Authority of Serbia for providing them with features of a major road network of Serbia.


References:

Aeron-Thomas, A. 2000. Under-reporting of road traffic casualties in low income countries. TRL Report PR/INT/199/00. TRL Ltd., Crowthorne: CSIS Discussion.

 

CARE database - reports and graphics. Available from Internet: http://ec.europa.eu/transport/road_safety/specialist/statistics/index_en.htm.

 

Council Decision 93/704/EC. 1993. Oj No L329. 63-65.

 

Dai, D. 2012. Identifying clusters and risk factors of injuries in pedestrian–vehicle crashes in a GIS environment, Journal of Transport Geography. DOI: http://dx.doi.org/10.1016/j.jtrangeo.2012.02.005, 24(2012): 206-214.

 

Elvik, R.; Christensen, P.; Amundsen, A. 2004. Speed and road accidents: an evaluation of the Power Model. TOI report 740. Oslo: The Institute of Transport Economics.

 

European Transport Safety Council - Estimating Crash Cost. Available from Internet: http://www.grsproadsafety.org/themes/default/pdfs/Estimating%20crash%20costs.pdf.

 

European Transport Safety Council - Social and economic consequences of road traffic injury. Available from Internet: http://www.etsc.eu/documents/Social%20and%20economic%20consequences%20of%20road%20traffic%20injury%20in%20Europe.pdf.

 

Global Status Report on Road Safety 2009 - World Health Organization. Available from Internet: http://www.who.int/violence_injury_prevention/road_safety_status/key_data/kd_ai.pdf.

 

Jacobs, G.; Aeron-Thomas, A.; Astrop, A. 2000. Estimating global road fatalities. TLR Report 445, Transport Research Laboratory.

 

Okabe, A.; Yomono, H.; Kitamura, M. 1995. Statistical Analysis of the Distribution of Points on a Network, Geographical Analysis. DOI: http://dx.doi.org/10.1111/j.1538-4632.1995.tb00341.x, 27(2): 152-175.

 

Okabe, A.; Okunuki, K.; Shiode, S. 2006. SANET: A toolbox for spatial analysis on a network, Geographical Analysis, 38(1): 57-66.

 

Okabe, A.; Satoh, T.; Sugihara, K. 2009. A kernel density estimation method for networks, its computational method and a GIS-based tool, International Journal of Geographical Information Science. DOI: http://dx.doi.org/10.1080/13658810802475491, 23(1): 7-32.

 

South East Europe Transport Observatory - MAP. 2011. Available from Internet: http://www.seetoint.org/index.php?option=com_content&view=article&id=372&Itemid=104.

 

Yamada, I.; Thill, J.C. 2002. Empirical Comparisons of Planar and Network K-functions in Traffic Accident Analysis. In Transportation Research Board 82nd Annual Meeting, Washington, D.C.