Prostorski sistem za podporo odločanju pri preprečevanje prometnih nesreč v različnih vremenskih razmerah
DOI:
https://doi.org/10.3986/AGS.9415Ključne besede:
GIS, mobilna aplikacija, prostorske podatkovne baze, prostorski vzorci, prometna varnostPovzetek
Vremenske razmere so pomemben dejavnik in soustvarjalec prostorsko-časovnih vzorcev prometnih nesreč. Kljub veliki uporabni vrednosti podatki o prostorskem odtisu prometnih nesreč niso del programske podpore voznikov v sodobnih komercialnih ali odprtokodnih navigacijskih sistemih. Na podlagi baze 11-letnih podatkov o prometnih nesrečah v Sloveniji smo ugotovili, da različne vremenske razmere oblikujejo različne prostorske vzorce nevarnih cestnih odsekov. Potencialno nevarne cestne odseke smo vključili v mobilni prostorski sistem za podporo odločanju (SLOCrashInfo), ki voznike opozori, ko vstopajo ali zapuščajo nevarna območja cestnega omrežja. Pričakujemo, da se bo s tem sistemom povečala varnost v cestnem prometu.
Prenosi
Literatura
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.
Prenosi
Objavljeno
Kako citirati
Številka
Rubrike
Licenca
Avtorske pravice (c) 2021 Danijel Ivajnšič, David Pintarič, Veno Jaša Grujić, Igor Žiberna
![Creative Commons licenca](http://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png)
To delo je licencirano pod Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 mednarodno licenco.