Use of big data for actualization of approaches to road accident analysis
Creators
- 1. tate Agency of Roads of Ukraine (Ukravtodor)
- 2. State Enterprise «M. P. Shulgin State Road Research Institute»
Description
The death and injuries of road users is one of the biggest problems that negatively affect the development of society and socio-economic progress. The price of human life is too high to neglect the least opportunity to save it. Therefore, the object of research is the huge amounts of information that modern society generates and which are known under the general concept of Big data. Regarding highways and streets, Big Data means arrays of information about a network of highways and streets, design decisions applied to them, operational status, traffic conditions, interaction of pedestrian and traffic flows and the like.
The study used Big Data from road owners, suppliers of cartographic and navigation systems, intelligent transportation systems and law enforcement. For each of the Big Data sources, the methods of collection and processing, the scope, degree of selectivity, and accuracy of the measurements are evaluated.
The results confirm the fact that the main indicator characterizing the influence of road conditions, the technical condition of the car and psycho-physiological factors on the driver is the speed of both individual vehicles and traffic flows over a certain period of time and on a selected section of the road. The proposed approach is based on the fact that speeds with a high degree of reliability can be established using the Big Data in a form suitable for machine processing. Big data is not just a source of information, it allows to track trends, assess risks and make forecasts.
The obtained results indicate that Big data can and should be used to describe traffic conditions and analyze the behavior of road users, including in order to better understand the interaction of factors in the occurrence of road traffic accidents (RTAs). And also, as far as possible, to prevent emergencies and/or reduce the severity of the consequences of the traffic accident. Thus, Big Data can be used to update the current approaches to determining the concentration of traffic accidents and the existing methods for assessing the impact of road conditions on road safety.
Files
Use of big data for actualization of approaches to road accident analysis.pdf
Files
(2.5 MB)
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Additional details
References
- Save LIVES – A road safety technical package (2017). World Health Organization. Available at: https://apps.who.int/iris/bitstream/handle/10665/255199/9789241511704-eng.pdf?sequence=1&isAllowed=y
- Road safety annual report 2019 (2019). OECD/ITF. Available at: https://www.itf-oecd.org/sites/default/files/docs/irtad-road-safety-annual-report-2019.pdf
- Road traffic injuries: the facts (2019). ASIRT, World Health Organization. Available at: https://www.asirt.org/wp-content/uploads/2020/03/road-traffic-injuries-the-facts-infographicen.pdf
- Monitorynh dorozhno-transportnykh pryhod na avtomobilnykh dorohakh zahalnoho korystuvannia derzhavnoho znachennia Ukrainy za 2019 rik (2020). DP «DerzhdorNDI», 73.
- Annual safety report 2018 (2018). Available at: https://ec.europa.eu/transport/road_safety/sites/roadsafety/files/pdf/statistics/dacota/asr2018.pdf
- Iarmolinskii, A. I., Pugachev, I. N., Sheshera, N. G. (2016). Sovershenstvovanie metodiki ocenki avariinosti avtomobilnykh dorog po stepeni obespecheniia bezopasnosti dvizheniia v gorodskikh usloviiakh. Vestnik TOGU, 3 (42), 33–42.
- Drew, D. R. (1968). Traffic Flow Theory and Control. McGraw Hill, 467.
- Lanovyi, O. T. (2016). Teoretychni osnovy ta praktychni metody zabezpechennia umov bezperervnoho, bezpechnoho ta zruchnoho rukhu transportnykh potokiv merezheiu avtomobilnykh dorih. Kyiv, 399. Available at: http://diser.ntu.edu.ua/Lanovuy_dis.pdf
- Eboli, L., Guido, G., Mazzulla, G., Pungillo, G., Pungillo, R. (2017). Investigating Car Users' Driving Behaviour through Speed Analysis. PROMET – Traffic&Transportation, 29 (2), 193–202. doi: http://doi.org/10.7307/ptt.v29i2.2117
- Tay, R., Champness, P., Watson, B. (2003). Personality and speeding. IATSS Research, 27 (1), 68–74. doi: http://doi.org/10.1016/s0386-1112(14)60060-1
- Road safety audit guidelines for safety checks on new road projects (2011). PIARC Technical committee C3.1 Road safety, 385.
- Kaskiv, V., Vozniuk, A., Nahrebelna, L. (2020). Towards road safety audit on road network of ukraine. Avtoshliakhovyk Ukrayiny, 1 (261), 32–39. doi: http://doi.org/10.33868/0365-8392-2020-1-261-32-39
- Why do road traffic accidents happen? Danish road traffic accident investigation board (AIB) (2014). Available at: http://www.hvu.dk/SiteCollectionDocuments/HVUdec14_UK_HvorforSkerUlykkerne.pdf
- Dingus, T. A., Guo, F., Lee, S., Antin, J. F., Perez, M., Buchanan-King, M., Hankey, J. (2016). Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proceedings of the National Academy of Sciences, 113 (10), 2636–2641. doi: http://doi.org/10.1073/pnas.1513271113
- Fisher D. L., Rizzo, M., Caird, J., Lee, J. D. (Eds.) (2011). Handbook of Driving Simulation for Engineering, Medicine, and Psychology. CRC Press, 752. doi: http://doi.org/10.1201/b10836
- Wachnicka, J. (2018). Mathematical models as practical tool for road fatalities forecasts on road network in regions. MATEC Web of Conferences, 231, 01018. doi: http://doi.org/10.1051/matecconf/201823101018