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Tytuł artykułu

Estimating the potential of a warning system preventing road accidents at pedestrian crossings

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Background: The safety of pedestrians is one of the main traffic safety issues today and despite measures being applied, the number of pedestrian deaths in traffic is not changing. According to the Pareto Rule, 80% of consequences come from 20% of the causes and here the question arises whether we have already used these 20% of the most efficient measures. Today the European Union (EU) puts big hopes are on contemporary technologies, such as Advanced Emergency Braking Systems (AEB) and cooperative intelligent transport systems (C-ITS). This decade, we can expect smarter vehicles with automatic brakes, and smarter infrastructure which can communicate with vehicles. Along this other profits technological development provides new opportunities for improving pedestrian safety. One of the most promising solutions is deployment of C-ITS systems at uncontrolled crossings. It would monitor the situation and warn the road users of potential dangers as well as make the vehicles brake automatically. However, before making large investments into this field, one has to be sure that this approach will work. The aim of this paper is to describe typical vehicle-pedestrian crash scenarios and to estimate whether a C-ITS warning system is able to prevent them. Research estimates the potential of this system and provides insights to its must-have features. Methods: To understand the situations in which the warning system should function, researchers carried out traffic conflict studies at uncontrolled crossings with traffic filmed in both winter and summer. They determined and described serious conflicts and, based on their scenarios, classified them into three types. Then, researchers selected the most critical conflict of each type and analysed whether warning signals can be provided to the vehicle and the driver early enough to prevent collisions. For these purposes, researchers used a modelling software for traffic accident investigation. To access the efficiency of the C-ITS warning system, researchers estimated the probability of preventing collisions and used the efficiency parameters of classical traffic calming measures. Results: The C-ITS warning system has good potential in preventing vehicle-pedestrian collisions at uncontrolled pedestrian crossings. It is remarkable and very promising that it would be able to prevent all types of conflicts analysed in the scope of this study by warning AEB-equipped vehicles. Warning the driver would be also effective, but the system work will largely depend on the quality of warning signals. An effective C-ITS warning system should be capable of predicting the trajectories and acceleration of road users as well as calculating the stopping distance of vehicles based on the coefficient of static friction. Study showed that in some cases, the system will have to give false positive alarms, but the fewer such alarms will be given, the more efficient the system will be. A disturbing or annoying C-ITS warning system cannot be considered effective. Conclusions: Road accident statistics contain general data about vehicle-pedestrian collisions at uncontrolled crossing, but there is few information about behavioral patterns leading to accidents. Based on large-scaled traffic studies, researchers were able to determine these patterns and described how road users act when being involved in a dangerous situation. This knowledge helped to model typical vehicle-pedestrian collisions as well as their possible scenarios. Researchers used the conflict models totest the C-ITS warning system and to understand its efficiency. The study results were implementedin a prototype that has been developed in Estonia and is being tested it in real traffic conditions of a smart city in the scope of the Finnish-Estonian project “FinEst Twins”. The next steps are to analyze the test results and to conduct research to understand how to warn drivers (and pedestrians) most effectively.
Czasopismo
Rocznik
Strony
441--452
Opis fizyczny
Bibliogr. 24 poz., fot., rys., tab., wykr.
Twórcy
autor
  • School of Engineering, Tallinn University of Technology, Noorkuu 8-9, Tallinn 13516, Estonia
autor
  • Lettore LLC, Pikk tn 7, 10123, Tallinn, Estonia
autor
  • Department of Mechanical and Industrial Engineering, School of Engineering, Tallinn University of Technology, Ehitajate tee 5, 19086, Tallinn, Estonia
Bibliografia
  • 1. Astarita V., Giofré V. P., 2019. From traffic conflict simulation to traffic crash simulation: Introducing traffic safety indicators based on the explicit simulation of potential driver errors, Simulation Modelling Practice and Theory. http://doi.org/10.1016/j.simpat.2019.03.003
  • 2. Bercman Technologies webpage. Available on the Internet: https://www.bercman.com/spc (27/05/2021).
  • 3. Bosch automotive engineering, 2007, 7th ed., Robert Bosch GmbH: 435, 438.
  • 4. Bulla-Cruz L.A., Laureshyn A., Lyons L., 2020. Event-based road safety assessment: A novel approach towards risk microsimulation in roundabouts, Measurement. http://doi.org/10.1016/j.measurement.2020.108192
  • 5. Elvik R., Vaa T., Hoye A., Sorensen M., 2009. The Handbook of Road Safety Measures (2nd ed.), Emerald Group Publishing.
  • 6. Ess J., Antov D, 2016. Unified methodology for estimating efficiency of traffic calming measures - example of Estonia, The Baltic Journal of Road and Bridge Engineering 11(4): 259-265. http://doi.org/10.3846/bjrbe.2016.30.
  • 7. Ess J., Antov D., 2017. Estonian traffic behaviour monitoring studies 2001-2016: overview and results, The Baltic Journal of Road and Bridge Engineering 12(3): 167-173. http://doi.org/10.3846/bjrbe.2017.20.
  • 8. European Commission, 2016. Saving Lives: Boosting Car Safety in the EU Reporting on the monitoring and assessment of advanced vehicle safety features, their cost effectiveness and feasibility for the review of the regulations on general vehicle safety and on the protection of pedestrians and other vulnerable road users. Available on the Internet: https://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=CELEX:52016 DC0787&from=EN (14/04/2021).
  • 9. European Commission, 2018. Annual Accident Report. Available on the Internet: https://ec.europa.eu/transport/road_safety/sites/roadsafety/files/pdf/statistics/dacota/asr2018.pdf (14/04/2021).
  • 10. European Commission, 2019a. EU Road Safety Policy Framework 2021-2030 - Next steps towards "Vision Zero". Available on the Internet: https://ec.europa.eu/transport/sites/transport /files/legislation/swd20190283-roadsafetyvision-zero.pdf (14/04/2021).
  • 11. European Commission, 2019b. Supplementing Directive 2010/40/EU of the European Parliament and of the Council with regard to the deployment and operational use of cooperative intelligent transport systems. Available on the Internet: https://ec.europa.eu/transport/sites/transport/files/legislation/c20191789.pdf (14/04/2021).
  • 12. European New Car Assessment Programme. 2017. Test Protocol – AEB VRU systems. Available on the Internet: https://cdn.euroncap.com/media/26997/euro-ncap-aeb-vru-test-protocol-v20.pdf (14/04/2021).
  • 13. FinEst webpage. Available on the Internet: http://www.finesttwins.eu/projects (27/05/2021).
  • 14. Johnsson C., Laureshyn A., De Ceunynck T., 2018. In search of surrogate safety indicators for vulnerable road users: a review of surrogate safety indicators, Transport Reviews 38(6): 765-785. http://doi.org/10.1080/01441647.2018.1442888.
  • 15. Hupfer, C., 1997. Deceleration to Safety Time (DST) - a useful figure to evaluate traffic safety? 10th ICTCT Workshop, Lund.
  • 16. Laureshyn A., Jonsson C., De Ceunynck T., Svensson Å., de Goede M., Saunier N., Włodarek P., van der Horst R., Daniels S., 2016. Review of current study methods for VRU safety - part 4, Project No. 635895 In-Depth understanding of accident causation for Vulnerable road users, Warsaw University of Technology. Available on the Internet: https://portal.research.lu.se/portal/files/3956 2440/InDeV_D2_1_Appx_4_Naturalistic_driving.pdf (14/04/2021).
  • 17. Laureshyn A., De Ceunynckac T., Karlsson C., Svensson Å., Daniels S., 2017. In search of the severity dimension of traffic events: Extended Delta-V as a traffic conflict indicator, Accident Analysis & Prevention. http://doi.org/10.1016/j.aap.2016.09.026
  • 18. Madsen T. K. O., Lahrmann H. S., 2017. Comparison of five bicycle facility designs in signalized intersections using traffic conflict studies, Transportation Research. Part F: Traffic Psychology and Behaviour 46(B): 438-450. http://doi.org/10.1016/j.trf.2016.05.008.
  • 19. Polders, E., Brijs, T., 2018. How to analyse accident causation? A handbook with focus on vulnerable road users, Deliverable 6.3. Horizon 2020 EC Project, InDeV. Hasselt, Belgium, Hasselt University. Available on the Internet: http://www.intrasl.net/downloads/publicaciones/Handbook-InDeV.pdf (14/04/2021).
  • 20. Regulation (EU) 2018/858 of the European Parliament and of the Council of 30 May 2018 on the approval and market surveillance of motor vehicles and their trailers, and of systems, components and separate technical units intended for such vehicles, amending Regulations (EC) No 715/2007 and (EC) No 595/2009 and repealing Directive 2007/46/EC. Available on the Internet: https://eurlex.europa.eu/eli/reg/2018/858/oj (14/04/2021).
  • 21. Roséna E., Stigsonb H., Sandera U., 2011. Literature review of pedestrian fatality risk as a function of car impact speed, Accident Analysis and Prevention 43: 25-33. http://doi.org/10.1016/j.aap.2010.04.003
  • 22. Svensson, Å., 1998. A Method for Analysing the Traffic Process in a Safety Perspective, Bulletin 166. Dept. of Traffic Planning and Engineering, Lund University, Lund, Sweden.
  • 23. Tarko P. A., 2012. Use of crash surrogates and exceedance statistics to estimate road safety, Accident Analysis and Prevention 45: 230-240. http://doi.org/10.1016/j.aap.2011.07.008
  • 24. The city of Tallinn webpage. Available on the Internet: https://www.tallinn.ee/eng/tallinnovation/Intelligent-traffic-signs (27/05/2021).
Uwagi
PL
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-d8962e5b-1f7b-4cec-b9ba-888f4f5f75e2
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