A Literature review on the conflict analysis of vehicle-pedestrian interactions


  • Ahmad Kizawi Széchenyi István University, Department of Transport Infrastructure and Water Resources Engineering, Egyetem tér 1, 9026 Győr, Hungary
  • Attila Borsos Széchenyi István University, Department of Transport Infrastructure and Water Resources Engineering, Egyetem tér 1, 9026 Győr, Hungary




traffic conflict, Surrogate Measures of Safety (SMoS), road safety, pedestrian


An alternative to traffic safety analysis based on historical crash data the use of non-crash events is becoming more popular thanks to the rapid improvement in video-based vehicle trajectory processing. By means of Surrogate Measures of Safety (SMoS) in traffic conflict studies, the most critical elements on the road network can be identified and the probability of accidents can be proactively determined. This paper aims to summarize the state-of-the-art research regarding the analysis of pedestrian-vehicle interactions at unsignalized crossings, to synthetize the previous studies using Surrogate Measures of Safety (SMoS), and to identify the research gaps.


Download data is not yet available.


T. Fülep, J. Óberling, Traffic Safety based on Accident Statistics Concerning Road Vehicles and Infrastructure, Acta Technica Jaurinensis 5 (3) (2012) pp. 197–205. rdoi: https://doi.org/10.14513/actatechjaur.v12.n1.489

P. Songchitruksa, A. P. Tarko., The extreme value theory approach to safety estimation, Accident Analysis & Prevention 38 (4) (2006) pp. 811–822. doi: https://doi.org/10.1016/j.aap.2006.02.003

D. Ceunynck, Defining and applying surrogate safety measures and behavioural indicators through site-based observations Ph.D. thesis, Lund University (2017). [cited 2021-03-05] URL https://portal.research.lu.se/portal/files/30184385/170823Dissertation_TimDeCeunynck_final_inclcover.pdf

Laureshyn A., Svensson Å., Hydén, C., Evaluation of traffic safety, based on micro-level behavioral data: Theoretical framework and first implementation. Accident Analysis & Prevention 42 (6) (2010) pp. 1637–1646. doi: https://doi.org/10.1016/j.aap.2010.03.021

A. Kumar, M. Paul, I. Ghosh, Analysis of pedestrian conflict with right turning vehicles at signalized intersections in India, Proactive safety assessment and improvements at intersections, Journal of Transportation Engineering Part (A) Systems 145 (6) (2018) pp. pp. 04019018-01–04019018-12. doi: https://doi.org/10.1061/JTEPBS.0000239

H. Amado, S. Ferreira et al., Pedestrian-vehicle interaction at unsignalized crosswalks, A systematic review. Sustainability 12 (7) (2020) pp. 1–23. doi: https://doi.org/10.3390/su12072805

D. Dey, J. Terken, Pedestrian interaction with vehicles, Roles of explicit and implicit communication, in: Automotive UI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings, Association for Computing Machinery, Oldenburg, 2017, pp. 109–113. doi: https://doi.org/10.1145/3122986.3123009

R. S. Perkins, J. I. Harris, Traffic conflict characteristics-Accident potential at intersections, Highway Research Record 225 (1968) pp. 35–43.

C. Johnsson, A. Laureshyn, T. De Ceunynck, In search of surrogate safety indicators for vulnerable road users, a review of surrogate safety indicators, Transport Reviews 38 (6) (2018) pp. 765–785. doi: https://doi.org/10.1080/01441647.2018.1442888

H. C. Chin, S. T. Quek, Measurement of traffic conflicts, Safety Science 26 (3) (1997) pp. 169–185.

C. Hydén, The development of a method for traffic safety evaluation, the Swedish traffic conflict technique, Doctoral thesis, Lund University, Department of Traffic Planning and Engineering (1987).

A. Laureshyn, T. De Ceunynck et al., In search of the severity dimension of traffic events, Extended Delta-V as a traffic conflict indicator, Accident Analysis & Prevention 98 (2017) pp. 46–56. doi: https://doi.org/10.1016/j.aap.2016.09.026

L. Zheng, K. Ismail, X. Meng, Traffic conflict techniques for road safety analysis, Open questions and some insights, Canadian Journal of Civil Engineering 41 (7) (2014) pp. 633–641. doi: https://doi.org/10.1139/cjce-2013-0558

P. Chen, W. Zeng et al., Surrogate Safety Analysis of Pedestrian-Vehicle Conflict at Intersections Using Unmanned Aerial Vehicle Videos. Journal of Advanced Transportation, (2017). doi: https://doi.org/10.1155/2017/5202150

J. C. Hayward, Near-miss determination through use of a scale of danger, Highway Research Record 384 (1972) pp. 24-34.

X. Jiang, Intercultural Analyses of Time-to Collision in Vehicle Pedestrian Conflict on an Urban Midblock Crosswalk, IEEE transactions on intelligent transportation systems 16 (2) (2015) pp. 1–6. doi: https://doi.org/10.1109/tits.2014.2345555

B. L. Allen, B. T. Shin, D. J. Cooper, Analysis of traffic conflicts and collision, Transportation Research Record 667(1978) pp. 67–74.

P. J. Cooper, Experience with traffic conflicts in Canada with emphasis on “post encroachment time” techniques, In Proceedings of the NATO Advanced Research Workshop on International Calibration Study of Traffic Conflict Technique (1983).

D. Gettman, L. Head, Surrogate Safety Measures from Traffic Simulation Models, Final Report, Publication No. FHWARD-03-050, Federal Highway Administration, Washington, DC, USA. (2003).

D. Gettman, L. Sayed et al., Surrogate Safety Assessment Model and Validation,” FHWA Report, Publication No.: FHWA-HRT-08-051, Federal Highway Administration, Washington, DC, USA. (2008).

K. Campbell, H. C. Joksch, P. E. Green, A bridging analysis for estimating the benefis of active safety technologies, UMTRI-96-18, Final Report. University of Michigan, Transportation Research Institute (1996).

A. P. Tarko, Use of crash surrogates and exceedance statistics to estimate road safety, Accident Analysis & Prevention 45 (2012) pp. 230–240. doi: https://doi.org/10.1016/j.aap.2011.07.008

H. Farah, C. L. Azevdo, Safety analysis of passing maneuvers using extreme value theory, IATSS Research 41 (1) (2017) pp. 12–21. doi: https://doi.org/10.1016/j.iatssr.2016.07.001

T. J. Gordon, A Multivariate Analysis of Crash and Naturalistic Driving Data in Relation to Highway Factors Report No. S2-S01C-RW-1. Transportation Research Board, Washington, DC (2013).

S. Zhang, M. Abdel-Aty et al., Modeling pedestrians’ near-accident events at signalized intersections using gated recurrent unit (GRU), Accident Analysis & Prevention 148 (2020) 105844. doi: https://doi.org/10.1016/j.aap.2020.105844

P. Holló, Road Safety Situation of Hungary Reflected by National and International Objectives, Acta Technica Jaurinensis 4 (2) (2011) pp. 2–7.

P. Songchitruksa, A. P. Tarko, The extreme value theory approach to safety estimation. Accident Analysis and Prevention (2006), 38:811–822.

S. Coles, An Introduction to Statistical Modeling of Extreme Values, (2001)

A. Tarko, G. Davis, N. Saunier, T. Sayed, S. Washington, White Paper SURROGATE MEASURES OF SAFETY ANB20(3) Subcommittee on Surrogate Measures of Safety ANB20 Committee on Safety Data Evaluation and Analysis (2009)




How to Cite

Kizawi, A., & Borsos, A. (2021). A Literature review on the conflict analysis of vehicle-pedestrian interactions. Acta Technica Jaurinensis. https://doi.org/10.14513/actatechjaur.00601