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Tytuł artykułu

Estimated assessment of the potential impact of driverassistance systems used in automated vehicles on the level of road safety in Poland

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Strengthening road safety in the face of the enormous development of the automotive in recent decades is crucial. The safety benefits of automated vehicles are paramount. Automated vehicles have the potential to remove human error in road traffic, which will help protect drivers and passengers, as well as pedestrians and bicyclists. The carried-out forecasts are pioneering for Polish road traffic conditions. In England, studies have been carried out to determine the estimated impact of autonomous vehicles on road safety in simulated traffic conditions on the motorway. In Poland, preliminary forecasts of the reduction in the number of road accidents were made; however, they were based on other assumptions. Therefore, estimating the impact of using autonomous vehicles in order to increase the level of road safety is an innovative activity for Polish road conditions. For the purposes of this article, available statistical data on vehicles registered in Poland, their equipment with advanced driver-assistance systems as well as accident data and their causes were analyzed. A diagnosis of Road Safety in Poland in 2018 (base year for further estimations) was made, taking into account the trend of recent years together with an indication of the most common causes of road accidents. These data were compiled with statistical data from other countries about the influence of driversupport systems on traffic safety. Possible potential for increasing Road Safety in Poland by the year 2030 was estimated. The analyses were prepared assuming different types of processes related to traffic, road safety, and the recent development of the passenger car fleet in Poland. Presented results show four scenarios of road safety change, where the number of accidents is reduced with statistical average of 5000 reduction in the year 2030. These expectations are based on various predictable factors connected with upgrade of car fleet quality and take into account changes in road safety observed in recent years. Based on the current trend of driving automation and rapid development of driver-support systems, the provided estimations were found reliable and likely. The conducted research shows the benefits and the need for the use of driver-assistance systems in vehicles as they can measurably affect the level of road safety.
Czasopismo
Rocznik
Strony
325--338
Opis fizyczny
Bibliogr. 26 poz.
Twórcy
  • Motor Transport Institute, Jagiellońska 80, 03-301 Warsaw, Poland
autor
  • Motor Transport Institute, Jagiellońska 80, 03-301 Warsaw, Poland
  • Motor Transport Institute, Jagiellońska 80, 03-301 Warsaw, Poland
  • University of Leeds, Institute for Transport Studies, 34-40 University Rd, LS2 9JT Leeds, UK
Bibliografia
  • 1. Bačkalić, S. & Jovanović, D. & Bačkalić, T. & et al. The application of reiability reallocation model in traffic safety analysis on rural roads. Transport Problems. 2019. Vol. 14. Issue 1. DOI: 10.21307/tp.2019.14.1.11.
  • 2. Budzyński, M. & Romanowska, A. & Żukowska, J. & Kustra, W. Experiences and Challenges in Fatality Reduction on Polish Roads. Sustainability. 2019. Vol. 11(4).
  • 3. Papadoulis, A. & Quddus, M. & Imprialou, M. Evaluating the safety impact of connected and autonomous vehicles on motorways. Accident Analysis & Prevention. 2019. Vol. 124.P. 12-22.
  • 4. Bagloee, S.A. & Tavana, M. & Asadi, M. & Oliver, T. Autonomous vehicles: challenges, opportunities, and future implications for transportation policies. Journal of Modern Transportation. 2016. Vol. 24. P. 284-303.
  • 5. Rossi, F. & Zhang, R. & Hindy, Y. & Pavone, M. Routing autonomous vehicles in congested transportation networks: structural properties and coordination algorithms. Autonomous Robots. 2018. Vol. 42. P. 1427-1442.
  • 6. Stanton, N.A. & Salmon, P.M. Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems. Safety Science. 2009. Vol. 47(2). P. 227-237.
  • 7. Theeuwes, J. Self-Explaining Roads and Traffic System. In Designing Safe Road Systems. CRC Press. P. 11-26. https://doi.org/10.1201/9781315576732-2.
  • 8. Endsley, M.R. Situation Awareness in Future Autonomous Vehicles: Beware of the Unexpected. In: Congress of the International Ergonomics Association IEA 2018: Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). 2018. P. 303-309. Conference paper.
  • 9. Hulse, L.M. & Xie, H. & Galea, E.R. Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age. Safety Science. 2018. Vol. 102. P. 1-13.
  • 10. Automated vehicles for safety. National Highway Traffic Safety Administration. 2018. Available at: https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety.
  • 11. Wypadki drogowe w Polsce w 2018 roku. Komenda Główna Policji, Biuro Ruchu Drogowego. 2019. [In Polish: Road accidents in Poland in 2018. National Police Headquarters, Road Prevention and Traffic Office, Road Traffic Department. 2019].
  • 12. Pei, X. & Wong, S.C. & Sze, N.N. The roles of exposure and speed in road safety analysis. Accident analysis & prevention. 2012. Vol. 48. P. 464-471.
  • 13. Sommer, S. Nowoczesne systemy bezpieczeństwa w pojazdach samochodowych. Logistyka. 2015. Vol. 3. P. 4552-4556. Available at: https://www.czasopismologistyka.pl/artykulynaukowe/send/333-artykuly-na-plycie-cd-1/8055-sommer-nowoczesne-systemy [In Polish: Modern safety systems in motor vehicles].
  • 14. Martwe pole pod nadzorem. [In Polish: Blind spot under surveillance]. Available at: https://www.autoexpert.pl/technika-i-serwis/Martwe-pole-pod-nadzorem. 15. Seat Leon (2020) owner’s manual. Electronic version. Available at: https://www.seat.pl/datamanual-manual/leon/my21_w30/pl-pl/LEON_07_20_PL.pdf.
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  • 18. Skoda Octavia (2020) owner’s manual. Electronic version. Available at: https://ws.skodaauto.com/OwnersManualService/Data/pl/Octavia_NX/01-
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  • 19. Automotive Industry Report 2019/2020. Polish Automotive Industry Association. 2019. Available at: https://www.pzpm.org.pl/en/Automotive-market/Reports.
  • 20. The 2017 Strategy & Digital Auto Report, Fast and furious: Why making money in the „roboconomy” is getting harder. PwC. 2017.
  • 21. Burnewicz, J. Prognozy popytu na transport w Polsce do roku 2020 i 2030. Rok bazowy 2010, załącznik nr 2 do Strategii rozwoju transportu. Ministerstwo Infrastruktury. 2012. [In Polish: Forecasts of demand for transport in Poland until 2020 and 2030. Base year 2010. 2nd Annex to the Transport Development Strategy].
  • 22. State of the Road Safety and activities implemented in this field in 2018. National Road Safety Council. 2019. P. 44.
  • 23. Insurance Institute for Highway Safety, Highway Loss Data Institute, 501 (c) (3) organizations. 2019. Available at: https://iihs.org.
  • 24. European Commission. Available at: https://ec.europa.eu/commission/presscorner/detail/en/IP_18_3708.
  • 25. Commission Communication to the European Parliament. 2018. Available at: https://ec.europa.eu/transparency/regdoc/rep/1/2018/PL/COM-2018-283-F1-PL-MAIN-PART-1.PDF.
  • 26. Gietelink, O. & Ploeg, J. & De Schutter, B. & Verhaegen, M. Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations. Vehicle System Dynamics. 2006. Vol. 44. No. 7. P. 569-590.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d86ab4a3-f225-4d3a-bfb8-767931eb2ea9
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