Improving the Method of Conflict Situations

Denis Kapski, Lina Bertulienė


The paper presents the results of research to develop methodology for a rapid assessment of the effect of measures used to improve road safety. The research includes the improvement of the method of determining traffic conflict situations and the development of accident prediction in conflict situations. A method of conflict situations is one of the most advanced and effective methods for predicting accidents at conflict sites since this method is based on the dependency of the number of accidents on the number of conflict situations. Having determined at the study site the number of conflict situations it is possible to calculate a predictable annual number of accidents at that site. The research implemented gave a possibility to increase the accuracy of accident prediction according to the method of conflict situations making it suitable to be used in practice for assessing the quality of road safety measures at the conflict sites – signalized intersections and pedestrian crossings, in the zone of which the artificial speed humps have been installed, such as a “sleeping policeman”.


road traffic; traffic conflicts; road accidents; accident prediction; forecasting methods

Full Text:



Archer, J. 2001. Traffic Conflict Technique: Historical to Current State-of-the-Art. Institutionen för Infrastruktur KTH, Stockholm, 2001 [cited 12 July 2012]. Available from Internet:

Autey, J.; Sayed, T.; Zaki, M. 2012. Safety Evaluation of Right-Turn Smart Channels Using Automated Traffic Conflict Analysis, Accident Analysis and Prevention 45: 120–130.

Coelingh, E.; Jakobsson, L.; Lind, H.; Lindman, M. 2007. Collision Warning with Auto Brake – a Reallife Safety Perspective, in Proc. of 20th Enhanced Safety of Vehicle Conference. June 18‒21, 2007, Lyon, France. 9 p.

El-Basyounya, K.; Sayed, T. 2013. Safety Performance Functions Using Traffic Conflicts, Safety Science 51(1): 160–164.

Eremin, V. M.; Korolev, P. N. 2007. Kompjuternye jeksperimenty s modeljami transportnyh potokov dlja ocenki stepeni opasnosti dvizhenija na dvuhpolosnyh nereguliruemyh peresechenijah, Transport: Nauka, Tehnika, Upravlenie: Nauch. inform. sb. VINITI RAN. 2007(3): 33–35.

Eresov, V. І.; Rjabec, J.V. 2001. Konflіktnі situacіi ta bezpeka ruhu pіshohodіv, Bezpeka dorozhnogo ruhu Ukraini 2(10): 24–30.

Fakhfakh, N.; Khoudour, L.; El-Koursi, E. M.; Jacot, J.; Dufaux, A. 2010. A Video-Based Object Detection System for Improving Safety at Level Crossings, Open Transportation Journal 5: 45–59.

Hatakenaka, H.; Hirasawa, T.; Mizutani, H.; Munehiro, Y. 2003. Traffic Safety Measures with Image Processing Sensors and Analysis of Vehicle Behaviors [cited 20 September 2013]. Available from Internet:

Hyden, C. 1983. The Development of a Method for Traffic Safety Evaluation: the Swedish Traffic-Conflicts Technique. University of Lund, Lund Institute of Technplogy, Department of Trafic Planning and Engineering, Lund.

Ismail, K.; Sayed, T.; Saunier, N. 2009. Automated Pedestrian Safety Analysis Using Video Data in the Context of Scramble Phase Intersections, in Annual Conference of the Transportation Association of Canada. October 18–21, 2009, Vancouver, British Columbia [cited 20 Mach 2010]. Available from Internet: stock/ismail09automated-tac.pdf.

Kapski, D. 2008. Prognozirovanie avarijnosti v dorozhnom dvizhenii. Minsk: BNTU. 243 p.

Kot, E. N. 2006. Povyshenie jeffektivnosti i bezopasnosti dvizhenija peshehodnyh i transportnyh potokov na perekrestkah sovershenstvovaniem sredstv i rezhimov svetofornogo regulirovanija. Dis. kand. tehn. Nauk. Minsk. 172 p.

Kot, E. N. 2005. Issledovanie vzaimodejstvija peshehodnyh i povorotnyh transportnyh potokov metodom konfliktnyh situacij, Bezpeka Dorozhnogo Ruhu Ukraini 3–4(21): 16–24.

Klunder, G.; Abdoelbasier, A.; Immers, B. 2006. Development of a Micro-Simulation Model to Predict Road Traffic Safety At Intersections. TNO Report, TNO Built environment and Geosciences [cited 22 October 2007]. Available from Internet:

Laureshyn, A. 2010. Application of Automated Video Analysis to Road User Behaviour. PhD thesis. Lund, Sveden. 202 p.

Malkhamah, S.; Tight, M.; Montgomery, F. 2005. The Development of Automatic Method of Safety Monitoring at Pelican Crossing, Accident Analysis and Prevention 37(5): 938–946.

Uno, N.; Iida, Y.; Itsubo, S.; Yasuhara, S. 2010. A Microscopic Analysis of Traffic Conflict Caused by Lane-Changing Vehicle at Weaving Section. Dept of Civil Engineering, Kyoto University [cited 20 Mach 2010]. Available from Internet: ewgt/13conference/25_uno.pdf.

Vrubel, J. A.; Kapski, D.; Kot, E. N. 2006. Opredelenie poter v dorozhnom dvizhenii. Minsk: BNTU. 240 p.

DOI: 10.3846/bjrbe.2014.38


  • There are currently no refbacks.

Copyright (c) 2014 Vilnius Gediminas Technical University (VGTU) Press Technika