A spatial decision support system for traffic accident prevention in different weather conditions

  • Danijel Ivajnšič University of Maribor, Faculty of Arts, Maribor, Slovenia; University of Maribor, Faculty of Natural Sciences and Mathematics, Maribor, Slovenia https://orcid.org/0000-0003-4419-5295
  • David Pintarič University of Maribor, Faculty of arts, Maribor, Slovenia https://orcid.org/0000-0002-6021-9851
  • Veno Jaša Grujić University of Maribor, Faculty of Education, Maribor, Slovenia; University of Maribor, Faculty of Natural Sciences and Mathematics, Maribor, Slovenia
  • Igor Žiberna University of Maribor, Faculty of Arts, Maribor, Slovenia
Keywords: GIS, mobile application, spatial database, spatial patterns, traffic safety


Natural conditions play an important role as determinants and cocreators of the spatiotemporal road traffic accident Hot Spot footprint; however, none of the modern commercial, or open-source, navigation systems currently provides it for the driver. Our findings, based on a spatiotemporal database recording 11 years of traffic accidents in Slovenia, proved that different weather conditions yield distinct spatial patterns of dangerous road segments. All potentially dangerous road segments were identified and incorporated into a mobile spatial decision support system (SLOCrashInfo), which raises awareness among drivers who are entering or leaving the predefined danger zones on the street network. It is expected that such systems could potentially increase road traffic safety in the future.


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Aguero-Valverde, J., Jovanis, P. P. 2006: Spatial analysis of fatal and injury crashes in Pennsylvania. Accident Analysis & Prevention 38-3. DOI: https://doi.org/10.1016/j.aap.2005.12.006

Anderson, T. K. 2009: Kernel density estimation and K-means clustering to profile road accident hotspots. Accident Analysis Prevention 41-3. DOI: https://doi.org/10.1016/j.aap.2008.12.014

Bailey, T. C., Gatrell, A. C. 1995: Interactive Spatial Data Analysis. England.

Bergel-Hayat, R., Debbarh, M., Antoniou, C., Yannis, G. 2013: Explaining the road accident risk: Weather effects. Accident Analysis and Prevention 60. DOI: https://doi.org/10.1016/j.aap.2013.03.006

Black, W. R. 1991: Highway accidents: A spatial and temporal analysis. Transportation Research Record 1318.

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 and Prevention 40-3. DOI: https://doi.org/10.1016/j.aap.2008.01.001

Brodsky, H., Hakkert, A. S. 1988: Risk of road accident in rainy weather. Accident Analysis and Prevention 20-3. DOI: https://doi.org/10.1016/0001-4575(88)90001-2

Castillo-Manzano, J. I., Castro-Nuño, M., Fageda, X. 2016: Exploring the relationship between truck load capacity and traffic accidents in the European Union. Transportation Research Part E: Logistics and Transportation Review 88. DOI: https://doi.org/10.1016/j.tre.2016.02.003

Colino-Rabanal, V. J., Peris, S. J. 2016: Wildlife road kills: improving knowledge about ungulate distributions? Hystrix – the Italian Journal of Mammology 27-2. DOI: https://doi.org/10.4404/hystrix-27.2-11279

Delmelle, E. C., Thill, J. C. 2008: Urban bicyclists: A spatial analysis of adult and youth traffic hazard intensity. Transportation Research Record: Journal of the Transportation Research Board 2074-1. DOI: https://doi.org/10.3141/2074-04

Eisenberg, D. 2004: The mixed effects of precipitation on traffic crashes. Accident Analysis and Prevention 36-4. DOI: https://doi.org/10.1016/S0001-4575(03)00085-X

El-Said, M. Z. M., Soon, J. T., Eng Hie, A. T., Nurul Amirah 'Atiqah Binti, M. 'A. P., Yok Hoe. Y., Abdul Rahman, E. K. 2019: Spatial analysis of road traffic accident hotspots: evaluation and validation of recent approaches using road safety audit. Journal of Transportation Safety & Security. DOI: https://doi.org/10.1080/19439962.2019.1658673

Erdogan, S., Yilmaz, I., Baybura, T., Gullu, M. 2008: Geographical information systems aided traffic accident analysis system case study: city of Afyonkarahisar. Accident Analysis and Prevention 40-1. DOI: https://doi.org/10.1016/j.aap.2007.05.004

Etehad, H., Yousefzadeh-Chabok, S., Davoudi-Kiakalaye, A., Moghadam Dehnaadi, A., Hemati, H., Mohtasham-Amiri, Z. 2015: Impact of road traffic accidents on the elderly. Archives of Gerontology and Geriatrics 61-3. DOI: http://doi. org/10.1016/j.archger.2015.08.008

Fridström, L., Ifver, J., Ingebrigtsen, S., Kulmala, R., Thomsen, L. K. 1995: Measuring the contribution of randomness, exposure, weather, and daylight to the variation in road accident counts. Accident Analysis and Prevention 27-1. DOI: https://doi.org/10.1016/0001-4575(94)E0023-E

Global status report on road safety 2018. Geneva. Internet: https://www.who.int/publications/i/item/9789241565684 (2. 4. 2021).

Goniewicz, K., Goniewicz, M., Pawłowski, W., Fiedor, P. 2016: Road accident rates: strategies and programmes for improving road traffic safety. European Journal of Trauma and Emergency Surgery 42. DOI: https://doi.org/10.1007/s00068-015-0544-6

Grande, Z., Castillo, E., Mora, E., Lo, H. K. 2017: Highway and road probabilistic safety assessment based on Bayesian network models. Computer‐Aided Civil and Infrastructure Engineering 32-5. DOI: https://doi.org/10.1111/mice.12248

Hermans, E., Wets, G., Van Den Bossche, F. 2006: Frequency and severity of Belgian road traffic accidents studied by state-space methods. Joural of Transportation and Statistics 9-1. Internet: https://www.bts.gov/archive/publications/journal_of_transportation_and_statistics/volume_09_number_01/paper_06/index (2. 4. 2021).

Internet 1: www.dacota-project.eu (10. 12. 2020).

Internet 2: https://egp.gu.gov.si/egp/ (10. 12. 2020).

Internet 3: https://www.policija.si/o-slovenski-policiji/statistika/prometna-varnost (10. 12. 2020).

Internet 4: https://podatki.gov.si/dataset/pldp-karte-prometnih-obremenitev (10. 12. 2020).

Krisp, J. M., Durot, S. 2007: Segmentation of lines based on point densities – An optimisation of wildlife warning sign placement in southern Finland. Accident Analysis and Prevention 39-1. DOI: https://doi.org/10.1016/j.aap.2006.06.002

Nagata, T., Uno, H., Perry, M. J. 2010: Clinical consequences of road traffic injuries among the elderly in Japan. BMC Public Health 10-1. DOI: https://doi.org/10.1186/1471-2458-10-375

O’Sullivan, D., Unwin, D. J. 2002: Geographic Information Analysis. Hoboken.

Okabe, A., Okunuki, K-I., Shoiode, S. 2006: The SaNET toolbox: New Methods for Network Spatial analysis. Transactions in GIS 10-4. DOI: https://doi.org/10.1111/j.1467-9671.2006.01011.x

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

Perrels, A., Votsis, A., Nurmi, V., Pilli-Sihvoa, K. 2015: Weather Conditions, Weather Information and Car Crashes. ISPRS International Journal of Geo-Information 4-4. DOI: https://doi.org/10.3390/ijgi4042681

Pulugurtha, S. S., Krishnakumar, V. K., Nambisan, S. S. 2007: New methods to identify and rank high pedestrian crash zones: An illustration. Accident Analysis and Prevention 39-4. DOI: https://doi.org/10.1016/j.aap.2006.12.001

Romano, B., Jiang, Z. 2017: Visualizing traffic accident hotspots based on spatial-temporal network kernel density estimation. Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Los Angeles. DOI: https://doi.org/10.1145/3139958.3139981

Savaş Durduran S. 2010: A decision making system to automatic recognize of traffic accidents on the basis of a GIS platform. Expert Systems with Applications 37-12. DOI: https://doi.org/10.1016/j.eswa.2010.04.068

Uchida, N., Takeuchi, S., Ishida, T., Shibata, Y. 2017: Mobile Traffic Accident Prevention System Based on Chronological Changes of Wireless Signals and Sensors. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 8-3. DOI: https://doi.org/10.22667/JOWUA.2017.09.30.057

Xie, Z., Yan, J. 2008: Kernel Density Estimation of traffic accidents in a network space. Computers, Environment and Urban Systems 32-5. DOI: https://doi.org/10.1016/j.compenvurbsys.2008.05.001

Yannis, G., Karlaftis, M. G. 2010: Weather Effects on Daily Traffic Accidents and Fatalities: Time Series Count Data approach. Proceedings of the Transportation Research Board 89th annual Meeting. Washington.

How to Cite
IvajnšičD, PintaričD, Grujić VJ, ŽibernaI. A spatial decision support system for traffic accident prevention in different weather conditions. AGS [Internet]. 2021Jul.28 [cited 2021Sep.24];61(1):75–92. Available from: https://ojs.zrc-sazu.si/ags/article/view/9415